Cerebral blood flow, oxygen metabolism, and lactate during hypoxia in patients with obstructive sleep apnea

Cerebral blood flow, oxygen metabolism, and lactate during hypoxia in patients with obstructive... Abstract Study Objectives Obstructive sleep apnea (OSA) is associated with increased risk of stroke but the underlying mechanism is poorly understood. We suspect that the normal cerebrovascular response to hypoxia is disturbed in patients with OSA. Methods Global cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2), and lactate concentration during hypoxia were measured in patients with OSA and matched controls. Twenty-eight patients (82.1% males, mean age 52.3 ± 10.0 years) with moderate-to-severe OSA assessed by partial polysomnography were examined and compared with 19 controls (73.7% males, mean age 51.8 ± 10.1 years). Patients and controls underwent magnetic resonance imaging (MRI) during 35 min of normoxia followed by 35 min inhaling hypoxic air (10%–12% O2). After 3 months of continuous positive airway pressure (CPAP) treatment, 22 patients were rescanned. Results During hypoxia, CBF significantly increased with decreasing arterial blood oxygen concentration (4.53 mL (blood)/100 g/min per -1 mmol(O2)/L, p < 0.001) in the control group, but was unchanged (0.89 mL (blood)/100 g/min per -1 mmol(O2)/L, p = 0.289) in the patient group before CPAP treatment. The CBF response to hypoxia was significantly weaker in patients than in controls (p = 0.003). After 3 months of CPAP treatment the CBF response normalized, showing a significant increase during hypoxia (5.15 mL (blood)/100 g/min per -1 mmol(O2)/L, p < 0.001). There was no difference in CMRO2 or cerebral lactate concentration between patients and controls, and no effect of CPAP treatment. Conclusions Patients with OSA exhibit reduced CBF in response to hypoxia. CPAP treatment normalized these patterns. obstructive sleep apnea, cerebral blood flow, hypoxemia, cerebral metabolic rate of oxygen, cerebral lactate Statement of Significance Obstructive sleep apnea (OSA) is a strong predictor of the development of cerebral infarctions, but the underlying mechanisms are poorly understood. This study uses highly specific magnetic resonance imaging (MRI) techniques to establish how hypoxia as an isolated characteristic affects cerebral blood flow, cerebral metabolic rate of oxygen, and cerebral metabolites in OSA patients compared with controls. These measures showed an attenuated response to hypoxia, suggesting that the oxygen supply is aggravated not only by the hypoxia, but also by hemodynamic changes and abnormal vascular reactivity. Continuous positive airway pressure (CPAP) treatment normalizes these abnormalities. These findings are of importance to our understanding of the development of ischemic episodes during apnea and of their prevention. Introduction Obstructive sleep apnea (OSA) is a highly prevalent disease [1, 2] associated with significant comorbidities, especially cardiovascular and cerebrovascular diseases [3–6], but the pathophysiological mechanisms underlying its association with stroke are not fully understood. Patients with OSA experience sleep-related repetitive collapses of the upper airway, leading to sleep fragmentation, hypoxemia, hypercapnia, increased sympathetic and reduced parasympathetic activity, hemodynamic and cerebrovascular changes [7–11]. The intermittent hypoxic episodes during sleep, combined with significant hemodynamic change during the apneas, are considered to be a central part of the pathophysiology of the development of ischemic brain lesions [12, 13]. There is considerable focus on the regulation of cerebral blood flow (CBF), the cerebrovascular reserve capacity (CVR) in OSA, and the possible improvement of CBF after continuous positive air pressure (CPAP) therapy. CBF is controlled by several autoregulatory mechanisms, including chemical, metabolic, and neurogenic regulation, whereby changes in carbon dioxide and, to a lesser extent, oxygen are the most powerful stimuli leading to changes in cerebrovascular flow. Acute hypoxia stimulates cerebral vasodilation, increasing CBF as a compensatory mechanism. Kety and Schmidt [14] noted a 35% increase in global CBF during inhalation of air with a 10% fraction of O2 in healthy participants, but found no significant change in the global cerebral metabolic rate of oxygen (CMRO2), as also noted in more recent studies [15–17]. Other researchers have reported small but significant increases in CMRO2 after inhalation of hypoxic air or breath-holds in young healthy controls [18–20]. Cerebral lactate is also known to increase during hypoxic events in healthy controls [15, 16, 18, 21]. It is currently not known how CBF, CMRO2, and cerebral lactate concentrations change in patients with OSA, and it is not clear how CPAP treatment affects brain oxygen metabolism and CBF. CPAP has a tendency to reduce the risk of cardiovascular events and to yield a lower score on the Epworth Sleepiness Scale (ESS) and lower blood pressure [22]. It also improves cerebral blood velocity in the middle cerebral artery in patients with OSA in response to hypoxia [23, 24]. The aim of this study was to examine CMRO2, CBF, and lactate during hypoxia in patients with OSA and to compare them with controls. We evaluated the effects on these characteristics after 3 months of CPAP treatment. Materials and Methods Twenty-eight patients diagnosed with moderate-to-severe OSA (apnea–hypopnea index, AHI > 15 events/h) and 19 healthy controls (AHI < 5 events/h) were consecutively recruited from the Danish Center for Sleep Medicine, Glostrup Hospital, and through an Internet advertisement placed between September 2015 and May 2016. Exclusion criteria were: presence of severe heart, lung, or kidney disease; body mass index (BMI) > 40 kg/m2; pregnancy or breastfeeding; any clinical sign of previous stroke or transient ischemic attack; malignant disease within the previous 3 years; insulin-treated diabetes; use of antidepressants, hypnotics, morphine, or other respiratory-depressant medication; and weekly alcohol consumption greater than 14 units per week. Eleven patients and four controls suffered from hypertension, while three patients and one control suffered from type 2 diabetes. Subjects were well treated with antihypertensive medication or oral hypoglycemic medication. None of the patients with OSA had received CPAP treatment before the study. Six OSA patients were smokers and 12 were former smokers, while three controls were smokers and four were former smokers (Table 1). The study protocol was reviewed and approved by the regional Ethics Committee and the Danish Data Protection Agency. The study was carried out in accordance with the Declaration of Helsinki of the World Medical Association. All participants gave their written, informed consent to take part in the study. Table 1. Baseline characteristics, comorbidities, OSA severity, and CPAP compliance of patients and controls Parameter  OSA patients (n = 28)  Controls (n = 19)  OSA vs. controls (P-value)  Male, sex (%)  82.1  73.7  0.740  BMI (kg/m2)  29.38 ± 3.8  27.03 ± 3.0  0.029  Age (years)  52.3 ± 10.0  51.8 ± 10.1  0.803  Hypertention (%)  39.3  21.1  0.188  DM type 2 (%)  10.7  5.3  0.901  Smoker (%)  21.4  15.8  0.917  AHI  40.91 ± 16.1  2.37 ± 1.6  <0.001  ESS  8.1 ± 4.5  5.5 ± 3.5  0.043  ODI  40.9 ± 15.5  5.8 ± 4.1  <0.001  CPAP > 4 h/night (%)  73.1 (95% CI: 60.1, 86.0)  —  —  Parameter  OSA patients (n = 28)  Controls (n = 19)  OSA vs. controls (P-value)  Male, sex (%)  82.1  73.7  0.740  BMI (kg/m2)  29.38 ± 3.8  27.03 ± 3.0  0.029  Age (years)  52.3 ± 10.0  51.8 ± 10.1  0.803  Hypertention (%)  39.3  21.1  0.188  DM type 2 (%)  10.7  5.3  0.901  Smoker (%)  21.4  15.8  0.917  AHI  40.91 ± 16.1  2.37 ± 1.6  <0.001  ESS  8.1 ± 4.5  5.5 ± 3.5  0.043  ODI  40.9 ± 15.5  5.8 ± 4.1  <0.001  CPAP > 4 h/night (%)  73.1 (95% CI: 60.1, 86.0)  —  —  Data are reported as the mean and SD. Groups are compared with the chi-squared test and the paired Student’s t-test. Statistical significant difference are highlighted with bold (P < 0.05). ODI = oxygen desaturation index. View Large Participants were assessed in accordance with the criteria of the American Academy of Sleep Medicine in 2012 [25]. Healthy controls were excluded if their AHI exceeded 5 events/h. All OSA patients were offered CPAP treatment. Patients who were treated with CPAP were rescanned after 3 months. Their compliance was defined as the number of days using CPAP for more than 4 h/night, expressed as a percentage. Participants were scanned on a Philips 3T Achieva MRI scanner (Philips Medical Systems, Best, Netherlands). Hypoxia was induced with an AltiTrainer System (SMTEC, Nyon, Switzerland), which mixes atmospheric air with 99.99% nitrogen from a gas cylinder. The participants were awake and wore a full-face mask connected to the AltiTrainer by a one-way valve tube. The fraction of inhaled oxygen was regulated to correspond to approximately 10% of oxygen, inducing hypoxemia in the participants. The system delivered normoxia for 35 min followed by 35 min inhalation of hypoxic air. CO2 was not controlled; instead, it fluctuated in conjunction with respiration. Before and after the scan, a blood sample was taken from the participants to measure hemoglobin, hematocrit, and blood lactate concentration. Participants were monitored with electrocardiography (ECG), blood pressure, end-tidal CO2 tension monitoring, and pulse oximetry (Veris Monitor, Medrad). The pulse oximetry was calibrated by measurements from a previous study using simultaneously drawn arterial blood samples and pulse oximetry from 23 subjects during normoxia and hypoxia [18]. Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) techniques were used to estimate global CBF, global CMRO2, and cerebral metabolite concentrations. Figure 1 depicts the timeline for acquisition of the parameters and the hypoxic challenge. Figure 1. View largeDownload slide Timeline of MRI acquisitions. Blood samples were taken before and after the MRI scan. After 35 min the participants inhaled a 10% fraction of hypoxic air. After 15 min of hypoxic exposure the MRI measurements were repeated. Figure 1. View largeDownload slide Timeline of MRI acquisitions. Blood samples were taken before and after the MRI scan. After 35 min the participants inhaled a 10% fraction of hypoxic air. After 15 min of hypoxic exposure the MRI measurements were repeated. Cerebral blood flow Global CBF was measured by phase-contrast mapping (PCM) MRI of the blood flow in the internal carotid arteries and the basilar artery. Specifically, it was calculated as the sum of the flows in the internal carotid arteries and the basilar artery, assuming a phase–velocity relationship [26] (one slice, field of view = 240 × 240 mm2, voxel size = 0.75 × 0.75 × 8 mm3, echo time = 7.51 ms, repetition time = 12.4 ms, flip angle = 10°, 10 repeated measures, non-gated, velocity encoding = 100 cm/s, total duration = 1 min 42 s). The imaging slices were placed perpendicular to the carotid or basilar arteries (Figure 2a). Flow was calculated in each vessel as the product of the cross-sectional area and the mean blood velocity (Figure 2b). Data were processed using Matlab (Mathworks, Natick, MA) scripts written in-house. The total blood flow was normalized with respect to whole-brain tissue weight to obtain quantitative values in mL/100 g/min. The cerebral delivery of O2 (CDO2) was calculated by multiplying CBF by the arterial oxygen concentration. Figure 2. View largeDownload slide (a) Sagittal and coronal view of angiography highlighting the internal carotid arteries with the imaging plane visualized. (b) Phase-difference map showing the velocity (cm/s) in the internal carotids used to measure CBF. (c) Sagittal view of angiography highlighting the sagittal sinus and the transverse plane of the brain covering the sagittal sinus used for calculating SvO2. (d) Phase-difference map showing the sagittal sinus and surrounding tissue. Figure 2. View largeDownload slide (a) Sagittal and coronal view of angiography highlighting the internal carotid arteries with the imaging plane visualized. (b) Phase-difference map showing the velocity (cm/s) in the internal carotids used to measure CBF. (c) Sagittal view of angiography highlighting the sagittal sinus and the transverse plane of the brain covering the sagittal sinus used for calculating SvO2. (d) Phase-difference map showing the sagittal sinus and surrounding tissue. Cerebral metabolic rate of oxygen CMRO2 was calculated using the Fick principle equation (1):  CMRO2=[Hgb]⋅(CBFSS)⋅(SaO2-SvO2) (1) where CBFss is the blood flow in the sagittal sinus in mL/min scaled to global CBF, SaO2 and SvO2 are the arterial and venous oxygen saturation levels, respectively, and [Hgb] is the oxygen-carrying hemoglobin concentration (mmol/L) at full saturation. SaO2 was measured by digital pulse oximeter. SvO2 and blood flow in the sagittal sinus were measured simultaneously using an MRI sequence combining susceptibility-based oximetry (SBO) for acquisition of saturation and PCM for acquisition of blood flow [27]. Examples of MRI images from PCM and SBO are illustrated in Figure 2a–d. SBO exploits the relative paramagnetic difference between deoxygenated and oxygenated hemoglobin by measuring the susceptibility of blood relative to surrounding tissue. By modeling the large vessels of interest as a long paramagnetic cylinder and taking into account field cancellation due to the Lorentz sphere phenomenon, it is possible to quantify the difference in susceptibility between blood and the surrounding tissue. The relationship of the susceptibility to venous oxygen saturation is expressed by equation (2) [19, 28]:  SvO2=[1-2|Δφ|γΔχdoB0ΔTE(cos2θ-13)Hct+ΔχoxyΔχdo]⋅100 (2) where ∆ϕ is the difference in phase values between intravascular blood in the sagittal sinus and the surrounding reference tissue; γ is the proton gyromagnetic ratio; ∆χdo = 4π ∙ 0.27 ppm is the difference in volume susceptibility between fully deoxygenated and oxygenated erythrocytes; and ∆χoxy = 4π(−0.008) ppm, the volume susceptibility difference between fully oxygenated erythrocytes and water [29]. θ is the tilt angle of the sagittal sinus relative to the main magnetic field (B0); ∆TE is the difference in echo time; and Hct is the hematocrit level. Susceptibility-weighted maps (ϕ) were created with a dual-echo gradient-echo sequence (one slice, field of view = 220 × 190 mm2, voxel size = 0.5 × 0.5 × 8 mm3, echo time 1 = 10.89 ms, echo time 2 = 24.16 ms, flip angle = 30°, five repeated measures, total duration = 1 min 30 s, SENSE-factor = 2) and modulus, real and imaginary values from both echoes were saved. The maps were computed by subtracting phase-value maps corresponding to the two images generated with the short and long echo times. Unwrapping of the aliased phase was performed manually. The difference in susceptibility between venous blood and tissue was calculated by drawing a region of interest (ROI) in the sagittal sinus and surrounding tissue. The ROIs were established from five repeated measures along a section of the sagittal sinus and the mean of the phase values of all the voxels inside the ROI was calculated to determine the difference in susceptibility and thereby the SvO2. Acquisition of each frame was repeated with phase-contrast velocity encoding for simultaneous measurement of blood flow in the sagittal sinus. The blood flow in the sagittal sinus was acquired by drawing an ROI covering the sagittal sinus. The mean velocity and cross-sectional area from the ROI were multiplied to calculate flow, similar to the post-processing used to calculate global CBF described earlier. Blood flow in the sagittal sinus was scaled to global CBF measured at baseline in each participant to normalize CMRO2 with respect to individual global brain values [30]. CMRO2 calculated from measurements with SBO has been validated theoretically [31] and by anatomical phantom models [32]. All processing was performed using Matlab scripts developed in-house. The data analyst was blinded with respect to oxygen status and subject. Magnetic resonance spectroscopy The cerebral concentration of lactate, total creatine (tCr), N-acetylaspartate (NAA), and combined glutamate+glutamine (Glx), was measured by MRS. A water-suppressed point-resolved spectroscopy (PRESS) pulse sequence was used (repetition time = 3,000 ms, echo time = 36.5 ms, voxel size = 30 × 35 × 30 mm3, sampling frequency = 2000 Hz, spectral resolution = 1.95 Hz, 64 acquisitions, total duration 6 min 34 s). The water signal was also measured and used as an internal standard for quantification [33]. The voxel was located in the visual cortex covering the calcarine fissure inside the brain tissue to avoid contamination with subcutaneous fat. Fourier transformation of the signal produced a spectrum of resonance frequencies, with the area under the spectral peaks proportional to metabolite concentrations. Absolute concentrations of metabolites were estimated using the unsuppressed water signal as the reference signal using LCModel (Version 6.3-1F; Toronto, Canada). Anatomical scan High-resolution anatomical scans were obtained with a 3D T1-weighted turbo field echo sequence (150 slices, field of view = 241 × 180 × 165 mm3, voxel size = 1.09 × 0.81 × 1.1 mm3, echo time = 2.78 ms, repetition time = 6.9 ms, flip angle = 9°). Individual brain volumes were estimated from the anatomical scans using FSL BET and FAST software (FMRIB Software Library, University of Oxford, Oxford, United Kingdom). Brain weight was calculated by assuming a brain density of 1.05 g/mL [34]. Statistics The chi-squared test and the two-sample Student’s t-test, with statistical significance concluded for values of p < 0.05, were used to compare the demographic and clinical variables of controls and OSA subjects (Table 1). The significance of the effect of hypoxia on the measured parameters was calculated using a paired Student’s t-test (Table 2). To test the effect of the degree of hypoxia on the measured parameters their correlation with arterial oxygen concentration (CaO2) was examined (Figure 3) using a mixed linear regression model of the form expressed in equation (3): Table 2. Summary of clinical results Parameter  OSA patients (n = 28)  Patients after CPAP (n = 22)  Controls (n = 19)  Difference of Δ values between groups (P-value)  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  OSA vs. controls  OSA vs. CPAP  CPAP vs. controls  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Blood content   CaO2 (mmol/L)  9.1 ± 0.8  8.1 ± 1.1  <0.001  9.0 ± 0.7  7.6 ± 1.0  <0.001  8.8 ± 0.7  7.1 ± 0.8  <0.001  0.016  0.107  0.354   SaO2 (%)  96.1 ± 1.3  84.0 ± 8.5  <0.001  95.8 ± 1.5  81.6 ± 9.1  <0.001  96.0 ± 1.1  77.1 ± 7.2  0.001  0.002  0.308  0.047   SvO2 (%)  64.2 ± 0.06  59.9 ± 0.06  0.001  65.0 ± 0.06  57.8 ± 0.08  <0.001  66.9 ± 0.07  60.2 ± 0.07  <0.001  0.063  0.572  0.298   PaCO2 (kPa)  4.73 ± 0.46  4.45 ± 0.52  <0.001  4.81 ± 0.45  4.38 ± 0.48  <0.001  4.70 ± 0.61  4.04 ± 0.62  <0.001  0.015  0.154  0.236   Hgb (mmol/L)  9.5 ± 0.8  9.4 ± 0.8  0.013  9.4 ± 0.7  9.1 ± 0.7  <0.001  9.2 ± 0.7  8.9 ± 0.7  <0.001  0.642  0.306  0.512  Hemodynamics   MAP BP (mmHg)  110.9 ± 14.5  113.0 ± 11.6  0.141  101.5 ± 8.6  105.4 ± 12.0  0.045  99.8 ± 12.3  99.3 ± 12.1  0.863  0.306  0.719  0.187   Heart rate (bpm)  67.4 ± 11.4  69.8 ± 9.9  0.040  68.4 ± 10.8  71.5 ± 11.9  0.039  65.6 ± 9.5  73.2 ± 11.5  <0.001  0.005  0.707  0.025  Cerebral metabolism   CDO2 (µmol/100 g/min)  390.2 ± 72.6  332.8 ± 59.1  <0.001  401.7 ± 52.0  357.8 ± 54.6  0.010  390.1 ± 59.8  346.6 ± 69.4  0.003  0.125  0.480  0.663   CBF (mL/100 g/min)  42.91 ± 7.5  42.14 ± 9.3  0.530  45.35 ± 7.0  48.86 ± 10.2  0.086  44.43 ± 6.9  49.77 ± 11.5  0.025  0.011  0.056  0.532   A-V O2 (%)  32.2 ± 5.9  26.4 ± 9.9  0.002  30.0 ± 6.0  25.1 ± 8.8  0.007  29.2 ± 7.0  18.9 ± 11.0  <0.001  0.064  0.361  0.118   CMRO2 (µmol/100 g/min)  131.2 ± 16.1  125.1 ± 29.7  0.205  130.4 ± 20.3  117.4 ± 26.3  0.014  124.4 ± 22.4  106.2 ± 30.7  <0.001  0.081  0.254  0.586   Cerebral lactate (mmol/L)  0.54 ± 0.38  0.78 ± 0.54  0.012  0.62 ± 0.43  0.77 ± 0.57  0.286  0.58 ± 0.47  0.91 ± 0.60  0.002  0.492  0.593  0.288   tCr (mmol/L)  5.4 ± 0.4  5.3 ± 0.5  0.150  5.3 ± 0.5  5.1 ± 0.7  0.050  5.6 ± 0.4  5.5 ± 0.4  0.141  0.750  0.301  0.185   Glutamate (mmol/L)  6.4 ± 1.4  6.2 ± 1.5  0.203  6.5 ± 1.4  6.1 ± 1.6  0.244  7.1 ± 1.5  7.3 ± 1.2  0.181  0.088  0.759  0.086  Parameter  OSA patients (n = 28)  Patients after CPAP (n = 22)  Controls (n = 19)  Difference of Δ values between groups (P-value)  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  OSA vs. controls  OSA vs. CPAP  CPAP vs. controls  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Blood content   CaO2 (mmol/L)  9.1 ± 0.8  8.1 ± 1.1  <0.001  9.0 ± 0.7  7.6 ± 1.0  <0.001  8.8 ± 0.7  7.1 ± 0.8  <0.001  0.016  0.107  0.354   SaO2 (%)  96.1 ± 1.3  84.0 ± 8.5  <0.001  95.8 ± 1.5  81.6 ± 9.1  <0.001  96.0 ± 1.1  77.1 ± 7.2  0.001  0.002  0.308  0.047   SvO2 (%)  64.2 ± 0.06  59.9 ± 0.06  0.001  65.0 ± 0.06  57.8 ± 0.08  <0.001  66.9 ± 0.07  60.2 ± 0.07  <0.001  0.063  0.572  0.298   PaCO2 (kPa)  4.73 ± 0.46  4.45 ± 0.52  <0.001  4.81 ± 0.45  4.38 ± 0.48  <0.001  4.70 ± 0.61  4.04 ± 0.62  <0.001  0.015  0.154  0.236   Hgb (mmol/L)  9.5 ± 0.8  9.4 ± 0.8  0.013  9.4 ± 0.7  9.1 ± 0.7  <0.001  9.2 ± 0.7  8.9 ± 0.7  <0.001  0.642  0.306  0.512  Hemodynamics   MAP BP (mmHg)  110.9 ± 14.5  113.0 ± 11.6  0.141  101.5 ± 8.6  105.4 ± 12.0  0.045  99.8 ± 12.3  99.3 ± 12.1  0.863  0.306  0.719  0.187   Heart rate (bpm)  67.4 ± 11.4  69.8 ± 9.9  0.040  68.4 ± 10.8  71.5 ± 11.9  0.039  65.6 ± 9.5  73.2 ± 11.5  <0.001  0.005  0.707  0.025  Cerebral metabolism   CDO2 (µmol/100 g/min)  390.2 ± 72.6  332.8 ± 59.1  <0.001  401.7 ± 52.0  357.8 ± 54.6  0.010  390.1 ± 59.8  346.6 ± 69.4  0.003  0.125  0.480  0.663   CBF (mL/100 g/min)  42.91 ± 7.5  42.14 ± 9.3  0.530  45.35 ± 7.0  48.86 ± 10.2  0.086  44.43 ± 6.9  49.77 ± 11.5  0.025  0.011  0.056  0.532   A-V O2 (%)  32.2 ± 5.9  26.4 ± 9.9  0.002  30.0 ± 6.0  25.1 ± 8.8  0.007  29.2 ± 7.0  18.9 ± 11.0  <0.001  0.064  0.361  0.118   CMRO2 (µmol/100 g/min)  131.2 ± 16.1  125.1 ± 29.7  0.205  130.4 ± 20.3  117.4 ± 26.3  0.014  124.4 ± 22.4  106.2 ± 30.7  <0.001  0.081  0.254  0.586   Cerebral lactate (mmol/L)  0.54 ± 0.38  0.78 ± 0.54  0.012  0.62 ± 0.43  0.77 ± 0.57  0.286  0.58 ± 0.47  0.91 ± 0.60  0.002  0.492  0.593  0.288   tCr (mmol/L)  5.4 ± 0.4  5.3 ± 0.5  0.150  5.3 ± 0.5  5.1 ± 0.7  0.050  5.6 ± 0.4  5.5 ± 0.4  0.141  0.750  0.301  0.185   Glutamate (mmol/L)  6.4 ± 1.4  6.2 ± 1.5  0.203  6.5 ± 1.4  6.1 ± 1.6  0.244  7.1 ± 1.5  7.3 ± 1.2  0.181  0.088  0.759  0.086  Data are reported as the mean and SD. Groups are compared with paired and unpaired t-tests. CaO2 = arterial O2 concentration; PaO2 = arterial O2 pressure; SaO2 = arterial saturation; SvO2 = venous saturation; PaCO2 = arterial CO2 pressure, Hgb = hemoglobin concentration; MAP BP = mean arterial blood pressure; A-V O2 = arteriovenous O2 saturation difference; NAA = N-acetylaspartate; tCr = creatine and phosphocreatine. View Large Figure 3. View largeDownload slide Linear mixed model (equation 3) of arterial oxygen concentration (CaO2) during normoxia (red dots) and hypoxia (blue dots) and (a) CBF, (b) CDO2, (c) CMRO2, (d) lactate. Results from controls, OSA patients, and patients after 3 months of CPAP are demonstrated. The significance (p) of the regression and the coefficient of the slope (β1) of the relationship with CaO2 are shown in each panel. Figure 3. View largeDownload slide Linear mixed model (equation 3) of arterial oxygen concentration (CaO2) during normoxia (red dots) and hypoxia (blue dots) and (a) CBF, (b) CDO2, (c) CMRO2, (d) lactate. Results from controls, OSA patients, and patients after 3 months of CPAP are demonstrated. The significance (p) of the regression and the coefficient of the slope (β1) of the relationship with CaO2 are shown in each panel.  Y=β0+β1⋅CaO2+u+ɛ (3) The measured parameter was modeled as the response variable (Y). CaO2 was modeled as an independent variable. Subjects (μ) were modeled as random effects to account for between-subject variability, and ε is the residual error term. The result of the regression and the β1 coefficient and related probability are shown in Figure 2. To test for differences in responses to the hypoxic challenge between the OSA patient and control groups, the grouping and interaction between grouping and CaO2 were added to the model as fixed-variable terms (equation 4):  Y=β0+β1⋅CaO2+β2⋅group+β3⋅group⋅CaO2+u+ɛ (4) A difference in response to hypoxia between the two groups will produce a significant interaction coefficient (β3) [35], which is shown in Table 3 with its corresponding probability. Statistical analyses were performed using the Matlab statistics toolbox. Table 3. Summary statistics of the linear mixed model (equation 4) testing for differences in responses to the hypoxic challenge between the OSA patient group and the control group by including group and its interaction with CaO2 as fixed-variable terms   OSA vs. control  OSA vs. CPAP  CPAP vs. control  Interaction coefficient  P-value  Interaction coefficient  P-value  Interaction coefficient  P-value  CBF (mL/100 g/min)  −1.77  0.0029  −3.70  0.0022  0.33  0.7985  CDO2 (µmol/100 g/min)  −10.87  0.0295  −21.00  0.0529  −2.76  0.8081  CMRO2 (µmol/min)  0.40  0.8078  −8.01  0.0451  2.02  0.5430  Lactate (mmol/L)  −0.044  0.2591  −0.13  0.1957  −0.053  0.5703    OSA vs. control  OSA vs. CPAP  CPAP vs. control  Interaction coefficient  P-value  Interaction coefficient  P-value  Interaction coefficient  P-value  CBF (mL/100 g/min)  −1.77  0.0029  −3.70  0.0022  0.33  0.7985  CDO2 (µmol/100 g/min)  −10.87  0.0295  −21.00  0.0529  −2.76  0.8081  CMRO2 (µmol/min)  0.40  0.8078  −8.01  0.0451  2.02  0.5430  Lactate (mmol/L)  −0.044  0.2591  −0.13  0.1957  −0.053  0.5703  The interaction coefficients (β3) and their significance (p) are shown. Statistical significant difference are highlighted with bold (P < 0.05). CaO2 = arterial O2 concentration; OSA = patients with obstructive sleep apnea at baseline; CPAP = patients after CPAP treatment. View Large Results Twenty-eight of 37 patients were included in the study (eight patients dropped out because of claustrophobia related to MRI scans, and one was excluded because of the malfunction of the oxygen mask). Twenty-two patients were rescanned after treatment with CPAP (dropouts occurred due to noncompliance with MRI or with CPAP, or withdrawal of consent). CBF measurement failed in one of the patients after CPAP treatment. Pulse oximetry failed in two patients at baseline and in three patients after CPAP treatment. Blood samples after hypoxia failed in three patients at baseline and in one patient after CPAP treatment. The acquisition of MRS failed in five of the patients after CPAP treatment. We enrolled 24 controls, but excluded five participants due to undiagnosed OSA, leaving 19 controls. Baseline characteristics of the two groups are shown in Table 1. The patients and controls were similar with respect to gender and age, although the BMI was higher in the OSA patient group. The patients rescanned after CPAP treatment had almost normalized levels of AHI (2.4 ± 1.6) and ESS scores (5.5 ± 3.5). Compliance with CPAP treatment involving more than 4 h use per night over 3 months was 73.1% (95% CI: 60.1, 86.0). SaO2 decreased significantly in both groups during hypoxia. SaO2 decreased significantly more in the control group than in patients after exposure to the same level of hypoxia. Heart rate increased significantly in all groups after exposure to hypoxia, although the increase was significantly greater in the controls than in the patients, before and after CPAP treatment. The arteriovenous O2 saturation difference (A-V O2) decreased from normoxia to hypoxia, with a greater reduction in the control group than in patients at baseline and after CPAP treatment (Table 2). The smaller A-V O2 difference of oxygen seen in controls may in part be caused by the increased heart rate and the increased CBF in controls, which reduces the diffusion time of oxygen from blood to the cerebral tissue. The smaller oxygen tension in the blood also reduces gas exchange to the tissue because of the lower gradient during hypoxia in both groups. During hypoxia CBF increased significantly in the control group (p = 0.025), but was unchanged in the OSA patients (p = 0.53) (Table 2). The unchanged CBF caused a significantly greater decrease in CDO2 during hypoxia in patients compared with the control group (Table 3). Patients had increased CBF during hypoxia after treatment with CPAP, similar to what was observed in the control group, while their CDO2 was similar to that of the control group (Table 3 and Figure 3). CMRO2 decreased during hypoxia and was significantly correlated with CaO2 for all groups in the mixed model (Figure 3c) and there was a difference between patients before and after CPAP (Table 3). However, the t-tests identified significant decreases only in the control group and in patients after CPAP treatment (Table 2). Cerebral lactate increased significantly in controls (p < 0.001) during hypoxia but not in patients (p = 0.87) (Table 2). The difference between controls and patients was not significant (Table 3), probably because three patients demonstrated a pronounced increase in cerebral lactate during hypoxia as opposed to the remaining patients (Figure 3d). When these patients were excluded we found a significant difference between the patient and control groups in the mixed model. NAA, Glx, and tCr showed no significant change between normoxia and hypoxia or any effect from CPAP treatment. Discussion To our knowledge, this is the first study to evaluate the effect of hypoxemia on CBF, CMRO2, and cerebral metabolites in patients with moderate-to-severe OSA identified by PCM MRI, SBO, and spectroscopy determined by MRI. The main findings of this study are that: (1) hypoxia increased CBF in controls but not in OSA patients, and (2) after 3 months of CPAP, patients regained the capacity for CBF to increase after exposure to hypoxia, similar to controls. OSA is known to be associated with a significant risk of ischemic stroke [36], but the detailed mechanism underlying this link is not known. We believe that part of the mechanism involved in stroke [37] includes the changes in CBF after exposure to hypoxia. In the presence of normal autoregulation, hypocapnia, as seen in the control group and in patients who hyperventilate, causes cerebrovascular arterial vasoconstriction [38], while hypoxia opposes this mechanism and dilates the cerebral vessels, leading to increased CBF. Hypoxia also raises the heart rate in both groups and, potentially, increases cardiac output, which may contribute to the increased CBF. However, patients with OSA present another response. Patients generally experience smaller decreases in end-tidal CO2, and SaO2, while CBF is unchanged in response to hypoxia. A possible hyperventilation induced by hypoxia in the patient group was ruled out by the end-tidal CO2 measurements. The patient group showed higher end-tidal CO2 compared with the control group during hypoxia. Thus, hyperventilation cannot explain the lower level of desaturation or the lack of CBF increase in patients than in controls during the hypoxic challenge. Patients after CPAP treatment had the ability restored for their CBF to increase after exposure to hypoxia. There was a positive effect of CPAP treatment after 3 months. Earlier studies using transcranial Doppler and related methods (autonomic challenges, autoregulatory index, and response to hypoxia) support our findings, revealing a weaker response with respect to cerebral blood velocity than in the control groups [23, 24, 39]. We found a reduction in CMRO2 in all the groups during hypoxic challenge and a significant difference between the patients before and after CPAP. An earlier study by Smith et al. [40] suggested that hypocapnia was the reason for increased CMRO2 during poikilocapnic hypoxia. This is in contrast to the decrease in CMRO2 we observed, even though the participants reacted with hypocapnia in the study. These authors examined a group of young participants, and this age difference may explain the different responses. In the study by Vestergaard et al. [18], who used the same MRI study protocol as in the present study, the young and healthy controls showed a small but significant increase in CMRO2 during hypoxia. Our study showed reduced CMRO2 during hypoxia, which could be explained by the differences in the clinical characteristics of the controls, especially those associated with age. The global baseline CMRO2 measured in this study was consistent with values obtained by various techniques [21, 41–43]. Previous studies have shown lower CVR and CMRO2 in patients with OSA during 30-s breath-holding than in controls [30, 44]. The CVR during short breath-holding is mainly driven by a hypercapnic response since short breath-holding causes only slight desaturation (≈90% SaO2). We extend these studies by showing that CVR also decreases during long-lasting hypoxia, in which CVR is driven by the arterial desaturation rather than hypercapnia. Despite the long-standing interest in brain metabolism, no studies have so far evaluated cerebral lactate metabolism in patients with OSA [45]. The lactate concentration in our study increased in response to hypoxia in the control group, but was unchanged in response to hypoxia in patients before and after CPAP treatment. There was no difference between patients and controls, although three patients had a pronounced increase in lactate concentration. Excluding these subjects from the analysis, the controls exhibited a significantly greater increase in lactate concentration than did patients. We observed an increase in cerebral lactate concentration in controls, with a simultaneous drop in CMRO2. OSA patients before and after CPAP treatment showed no increase in cerebral lactate concentration, while CMRO2 was reduced. This could contribute to the insufficient energy supply to the brain when both oxygen consumption and lactate production are compromised during hypoxia in patients with OSA. There was no difference in Glx or tCr concentration before or after hypoxia in any group. Cerebral Glx has previously been reported to be unchanged after exposure to hypoxia in healthy controls [46], consistent with our results. tCr decreases during hypoxia and visual stimulation [18]. Phosphocreatine and ATP were also reduced in a study of hypoxic rodents [47], although we found no difference in our study. Controls underwent greater desaturation than patients during hypoxic exposure, suggesting that OSA patients compensate for hypoxic stimuli. The reason for the lesser desaturation in patients is not known and so requires further examination. Additionally, we observed a fall in hemoglobin concentration in the blood samples from normoxia to hypoxia in all groups. The mechanism responsible is also unknown, although we think it is associated with hypoxia-related vasodilation, causing fluid drainage into the blood and thereby dilution. An overall limitation of the study is our induction of hypoxia, which simulates spontaneous apneas in fully awake patients rather than investigating brain metabolism in apneas during sleep. The mechanisms in the brain during apneas involve complex interactions between cardiovascular and cerebrovascular hemodynamics, O2, CO2, and the autonomic tone. In this study, we focused on one factor, hypoxia, and its influence on cerebrovascular circulation. Further studies should include PaCO2. PaCO2 accumulates by the end of the apnea, leading to hypercapnia, whereas the level of PaCO2 in this study decreased due to the hypoxic response. The PaCO2 level fluctuated in conjunction with the extent of ventilation after exposure to hypoxia, leading to hypocapnia. We cannot distinguish between the effects of hypoxia and those of hypocapnia. Consequently, the low PaCO2 level in our study may have had an opposite cerebral vasoconstrictive effect to that of the hypercapnia-induced vasodilation normally seen in obstructive apneas. There was a higher level of CBF in controls with lower PaCO2, while patients at baseline had a higher level of PaCO2 and an unchanged CBF. Thus, we conclude that the level of PaCO2 did not contribute substantially to the differences between the groups. Measurement of CBF by MR phase mapping entails some potential errors from arterial geometry, resolution of images, and flow pulsation. However, these effects are relatively small when using setups similar to that used in this study [43, 48–51]. The reproducibility for the PCM sequence used in the present study was 6.5% and the intra-subject variability was similar to that of other techniques [52]. The reproducibility of venous saturation measurements with SBO was shown to be reliable, with a 2.3% coefficient of variation [32]. We also point out that we compared subjects between two states in a paired fashion, which mitigates potential biases in the methods. Cardiac and cerebrovascular hemodynamics undergoes pronounced changes during sleep apnea. Our findings from the MRI method provide a valuable tool for objectively determining CBF, CMRO2, and lactate concentration, and have the potential to help us understand the pathophysiological mechanisms operating in OSA. The study highlights the alteration of cerebrovascular reactivity to hypoxia in patients with OSA. The lack of response to hypoxia may imply overall damage to cerebrovascular reactivity and the sympathetic nervous system in patients with OSA. This may further raise the risk of hypoxia during apnea, potentially increasing that of cerebral ischemia. Future research should include the study of cerebrovascular reactivity and cardiac function during spontaneous sleep. In conclusion, CBF is unchanged in patients with OSA in response to hypoxia, whereas this increases in healthy controls during hypoxia. After 3 months of CPAP treatment patients normalize this response by increasing CBF when exposed to hypoxia. The cerebral lactate concentrations in patients were also unchanged in response to hypoxia, while the control group showed an increase in cerebral lactate. These findings may be central to our understanding of the development of ischemic episodes during apnea and of the protective effect of CPAP treatment. Funding The study was supported by a grant from A.P. Møller Fonden and Læge Sofus Carl Emil Friis og Hustru Olga Doris Friis Legat. Notes Conflict of interest statement. None declared. Acknowledgments MLF Jensen: study design, protocol development, data acquisition and processing, statistical analysis and interpretation, drafting, and revision of the manuscript. HBW Larsson: study design, development of the MRI method and study protocol, data processing, analysis and interpretation, and revision of the manuscript. MB Vestergaard: development of the MRI method and study protocol, data processing, statistical analysis and interpretation, and manuscript revision. P Tønnesen: study design, interpretation of data, and manuscript revision. PJ Jennum: supervision of all parts of the study including its design, creation and initiation, and revision of the manuscript. All authors have given their approval to the final version of the manuscript. References 1. Heinzer Ret al.   Prevalence of sleep-disordered breathing in the general population: the HypnoLaus study. Lancet Respir Med  2015; 3( 4): 310– 318. Google Scholar CrossRef Search ADS   2. Young Tet al.   The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med  1993; 328( 17): 1230– 1235. Google Scholar CrossRef Search ADS   3. Yaggi HKet al.   Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med  2005; 353( 19): 2034– 2041. Google Scholar CrossRef Search ADS   4. Lamberts Met al.   Cardiovascular risk in patients with sleep apnoea with or without continuous positive airway pressure therapy: follow-up of 4.5 million Danish adults. J Intern Med  2014; 276( 6): 659– 666. Google Scholar CrossRef Search ADS   5. Chang CCet al.   High incidence of stroke in young women with sleep apnea syndrome. Sleep Med  2014; 15( 4): 410– 414. Google Scholar CrossRef Search ADS   6. Arzt Met al.   Association of sleep-disordered breathing and the occurrence of stroke. Am J Respir Crit Care Med  2005; 172( 11): 1447– 1451. Google Scholar CrossRef Search ADS   7. Jennum Pet al.   Blood pressure, catecholamines, and pancreatic polypeptide in obstructive sleep apnea with and without nasal Continuous Positive Airway Pressure (nCPAP) treatment. Am J Hypertens  1989; 2( 11 Pt 1): 847– 852. Google Scholar CrossRef Search ADS   8. Jennum Pet al.   Intracranial pressure and obstructive sleep apnea. Chest  1989; 95( 2): 279– 283. Google Scholar CrossRef Search ADS   9. Alex Ret al.   Effect of apnea duration on apnea induced variations in cerebral blood flow velocity and arterial blood pressure. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual Conference  2014; 2014: 270– 273. 10. Macey PMet al.   Global brain blood-oxygen level responses to autonomic challenges in obstructive sleep apnea. PLoS One  2014; 9( 8): e105261. Google Scholar CrossRef Search ADS   11. Somers VKet al.   Sympathetic activation by hypoxia and hypercapnia–implications for sleep apnea. Clin Exp Hypertens A  1988; 10( Suppl 1): 413– 422. 12. Winklewski PJet al.   Cerebral blood flow, sympathetic nerve activity and stroke risk in obstructive sleep apnoea. Is there a direct link? Blood Press  2013; 22( 1): 27– 33. Google Scholar CrossRef Search ADS   13. Pizza Fet al.   Cerebral hemodynamic changes in stroke during sleep-disordered breathing. Stroke  2012; 43( 7): 1951– 1953. Google Scholar CrossRef Search ADS   14. Kety SSet al.   The effects of altered arterial tensions of carbon dioxide and oxygen on cerebral blood flow and cerebral oxygen consumption of normal young men. J Clin Invest  1948; 27( 4): 484– 492. Google Scholar CrossRef Search ADS   15. Ainslie PNet al.   Stability of cerebral metabolism and substrate availability in humans during hypoxia and hyperoxia. Clin Sci (Lond)  2014; 126( 9): 661– 670. Google Scholar CrossRef Search ADS   16. Overgaard Met al.   Hypoxia and exercise provoke both lactate release and lactate oxidation by the human brain. FASEB J  2012; 26( 7): 3012– 3020. Google Scholar CrossRef Search ADS   17. Bailey DMet al.   Increased cerebral output of free radicals during hypoxia: implications for acute mountain sickness? Am J Physiol Regul Integr Comp Physiol  2009; 297( 5): R1283– R1292. Google Scholar CrossRef Search ADS   18. Vestergaard MBet al.   Acute hypoxia increases the cerebral metabolic rate - a magnetic resonance imaging study. J Cereb Blood Flow Metab  2016; 36( 6): 1046– 1058. Google Scholar CrossRef Search ADS   19. Rodgers ZBet al.   High temporal resolution MRI quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge. J Cereb Blood Flow Metab  2013; 33( 10): 1514– 1522. Google Scholar CrossRef Search ADS   20. Xu Fet al.   Effect of hypoxia and hyperoxia on cerebral blood flow, blood oxygenation, and oxidative metabolism. J Cereb Blood Flow Metab  2012; 32( 10): 1909– 1918. Google Scholar CrossRef Search ADS   21. Cohen PJet al.   Effects of hypoxia and normocarbia on cerebral blood flow and metabolism in conscious man. J Appl Physiol  1967; 23( 2): 183– 189. Google Scholar CrossRef Search ADS   22. Guo Jet al.   Effect of CPAP therapy on cardiovascular events and mortality in patients with obstructive sleep apnea: a meta-analysis. Sleep Breath  2016; 20( 3): 965– 974. Google Scholar CrossRef Search ADS   23. Foster GEet al.   Effects of continuous positive airway pressure on cerebral vascular response to hypoxia in patients with obstructive sleep apnea. Am J Respir Crit Care Med  2007; 175( 7): 720– 725. Google Scholar CrossRef Search ADS   24. Reichmuth KJet al.   Impaired vascular regulation in patients with obstructive sleep apnea: effects of continuous positive airway pressure treatment. Am J Respir Crit Care Med  2009; 180( 11): 1143– 1150. Google Scholar CrossRef Search ADS   25. Berry RBet al.  ; American Academy of Sleep Medicine. Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events. Deliberations of the sleep apnea definitions task force of the American Academy of Sleep Medicine. J Clin Sleep Med  2012; 8( 5): 597– 619. 26. Evans AJet al.   Magnetic resonance imaging of blood flow with a phase subtraction technique. In vitro and in vivo validation. Invest Radiol  1993; 28( 2): 109– 115. Google Scholar CrossRef Search ADS   27. Rodgers ZBet al.   MRI-based methods for quantification of the cerebral metabolic rate of oxygen. J Cereb Blood Flow Metab  2016; 36( 7): 1165– 1185. Google Scholar CrossRef Search ADS   28. Rodgers ZBet al.   Rapid T2- and susceptometry-based CMRO2 quantification with interleaved TRUST (iTRUST). Neuroimage  2015; 106: 441– 450. Google Scholar CrossRef Search ADS   29. Jain Vet al.   Investigating the magnetic susceptibility properties of fresh human blood for noninvasive oxygen saturation quantification. Magn Reson Med  2012; 68( 3): 863– 867. Google Scholar CrossRef Search ADS   30. Rodgers ZBet al.   Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge. J Cereb Blood Flow Metab  2016; 36( 4): 755– 767. Google Scholar CrossRef Search ADS   31. Li Cet al.   Accuracy of the cylinder approximation for susceptometric measurement of intravascular oxygen saturation. Magn Reson Med  2012; 67( 3): 808– 813. Google Scholar CrossRef Search ADS   32. Jain Vet al.   MRI estimation of global brain oxygen consumption rate. J Cereb Blood Flow Metab  2010; 30( 9): 1598– 1607. Google Scholar CrossRef Search ADS   33. Christiansen Pet al.   In vivo quantification of brain metabolites by 1H-MRS using water as an internal standard. Magn Reson Imaging  1993; 11( 1): 107– 118. Google Scholar CrossRef Search ADS   34. Torack RMet al.   Correlative assay of computerized cranial tomography CCT, water content and specific gravity in normal and pathological postmortem brain. J Neuropathol Exp Neurol  1976; 35( 4): 385– 392. Google Scholar CrossRef Search ADS   35. Gujarati D. Use of dummy variables in testing for equality between sets of coefficients in linear regressions: a note. Am Stat  1970; 24( 5): 18– 22. 36. Cereda CWet al.   Sleep-disordered breathing in acute ischemic stroke and transient ischemic attack: effects on short- and long-term outcome and efficacy of treatment with continuous positive airways pressure–rationale and design of the SAS CARE study. Int J Stroke  2012; 7( 7): 597– 603. Google Scholar CrossRef Search ADS   37. Siebenmann Cet al.   Regulation of cardiac output in hypoxia. Scand J Med Sci Sports  2015; 25( Suppl 4): 53– 59. Google Scholar CrossRef Search ADS   38. Duelli Ret al.   Changes in brain capillary diameter during hypocapnia and hypercapnia. J Cereb Blood Flow Metab  1993; 13( 6): 1025– 1028. Google Scholar CrossRef Search ADS   39. Nasr Net al.   Cerebral autoregulation in patients with obstructive sleep apnea syndrome during wakefulness. Eur J Neurol  2009; 16( 3): 386– 391. Google Scholar CrossRef Search ADS   40. Smith ZMet al.   Sustained high-altitude hypoxia increases cerebral oxygen metabolism. J Appl Physiol (1985)  2013; 114( 1): 11– 18. Google Scholar CrossRef Search ADS   41. Mintun MAet al.   Brain oxygen utilization measured with O-15 radiotracers and positron emission tomography. J Nucl Med  1984; 25( 2): 177– 187. 42. Jain Vet al.   Rapid magnetic resonance measurement of global cerebral metabolic rate of oxygen consumption in humans during rest and hypercapnia. J Cereb Blood Flow Metab  2011; 31( 7): 1504– 1512. Google Scholar CrossRef Search ADS   43. Xu Fet al.   Noninvasive quantification of whole-brain cerebral metabolic rate of oxygen (CMRO2) by MRI. Magn Reson Med  2009; 62( 1): 141– 148. Google Scholar CrossRef Search ADS   44. Prilipko Oet al.   An fMRI study of cerebrovascular reactivity and perfusion in obstructive sleep apnea patients before and after CPAP treatment. Sleep Med  2014; 15( 8): 892– 898. Google Scholar CrossRef Search ADS   45. Xia Yet al.   Changes in cerebral metabolites in obstructive sleep apnea: a systemic review and meta-analysis. Sci Rep  2016; 6: 28712. Google Scholar CrossRef Search ADS   46. Arngrim Net al.   Migraine induced by hypoxia: an MRI spectroscopy and angiography study. Brain  2016; 139( Pt 3): 723– 737. Google Scholar CrossRef Search ADS   47. Tsuji Met al.   Phosphocreatine and ATP regulation in the hypoxic developing rat brain. Brain Res Dev Brain Res  1995; 85( 2): 192– 200. Google Scholar CrossRef Search ADS   48. Bakker CJet al.   Accuracy and precision of time-averaged flow as measured by nontriggered 2D phase-contrast MR angiography, a phantom evaluation. Magn Reson Imaging  1995; 13( 7): 959– 965. Google Scholar CrossRef Search ADS   49. Bakker CJet al.   Measuring blood flow by nontriggered 2D phase-contrast MR angiography. Magn Reson Imaging  1996; 14( 6): 609– 614. Google Scholar CrossRef Search ADS   50. Vestergaard MBet al.   Comparison of global cerebral blood flow measured by phase-contrast mapping MRI with 15 O-H2 O positron emission tomography. J Magn Reson Imaging  2017; 45( 3): 692– 699. Google Scholar CrossRef Search ADS   © Sleep Research Society 2018. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png SLEEP Oxford University Press

Cerebral blood flow, oxygen metabolism, and lactate during hypoxia in patients with obstructive sleep apnea

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Abstract

Abstract Study Objectives Obstructive sleep apnea (OSA) is associated with increased risk of stroke but the underlying mechanism is poorly understood. We suspect that the normal cerebrovascular response to hypoxia is disturbed in patients with OSA. Methods Global cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2), and lactate concentration during hypoxia were measured in patients with OSA and matched controls. Twenty-eight patients (82.1% males, mean age 52.3 ± 10.0 years) with moderate-to-severe OSA assessed by partial polysomnography were examined and compared with 19 controls (73.7% males, mean age 51.8 ± 10.1 years). Patients and controls underwent magnetic resonance imaging (MRI) during 35 min of normoxia followed by 35 min inhaling hypoxic air (10%–12% O2). After 3 months of continuous positive airway pressure (CPAP) treatment, 22 patients were rescanned. Results During hypoxia, CBF significantly increased with decreasing arterial blood oxygen concentration (4.53 mL (blood)/100 g/min per -1 mmol(O2)/L, p < 0.001) in the control group, but was unchanged (0.89 mL (blood)/100 g/min per -1 mmol(O2)/L, p = 0.289) in the patient group before CPAP treatment. The CBF response to hypoxia was significantly weaker in patients than in controls (p = 0.003). After 3 months of CPAP treatment the CBF response normalized, showing a significant increase during hypoxia (5.15 mL (blood)/100 g/min per -1 mmol(O2)/L, p < 0.001). There was no difference in CMRO2 or cerebral lactate concentration between patients and controls, and no effect of CPAP treatment. Conclusions Patients with OSA exhibit reduced CBF in response to hypoxia. CPAP treatment normalized these patterns. obstructive sleep apnea, cerebral blood flow, hypoxemia, cerebral metabolic rate of oxygen, cerebral lactate Statement of Significance Obstructive sleep apnea (OSA) is a strong predictor of the development of cerebral infarctions, but the underlying mechanisms are poorly understood. This study uses highly specific magnetic resonance imaging (MRI) techniques to establish how hypoxia as an isolated characteristic affects cerebral blood flow, cerebral metabolic rate of oxygen, and cerebral metabolites in OSA patients compared with controls. These measures showed an attenuated response to hypoxia, suggesting that the oxygen supply is aggravated not only by the hypoxia, but also by hemodynamic changes and abnormal vascular reactivity. Continuous positive airway pressure (CPAP) treatment normalizes these abnormalities. These findings are of importance to our understanding of the development of ischemic episodes during apnea and of their prevention. Introduction Obstructive sleep apnea (OSA) is a highly prevalent disease [1, 2] associated with significant comorbidities, especially cardiovascular and cerebrovascular diseases [3–6], but the pathophysiological mechanisms underlying its association with stroke are not fully understood. Patients with OSA experience sleep-related repetitive collapses of the upper airway, leading to sleep fragmentation, hypoxemia, hypercapnia, increased sympathetic and reduced parasympathetic activity, hemodynamic and cerebrovascular changes [7–11]. The intermittent hypoxic episodes during sleep, combined with significant hemodynamic change during the apneas, are considered to be a central part of the pathophysiology of the development of ischemic brain lesions [12, 13]. There is considerable focus on the regulation of cerebral blood flow (CBF), the cerebrovascular reserve capacity (CVR) in OSA, and the possible improvement of CBF after continuous positive air pressure (CPAP) therapy. CBF is controlled by several autoregulatory mechanisms, including chemical, metabolic, and neurogenic regulation, whereby changes in carbon dioxide and, to a lesser extent, oxygen are the most powerful stimuli leading to changes in cerebrovascular flow. Acute hypoxia stimulates cerebral vasodilation, increasing CBF as a compensatory mechanism. Kety and Schmidt [14] noted a 35% increase in global CBF during inhalation of air with a 10% fraction of O2 in healthy participants, but found no significant change in the global cerebral metabolic rate of oxygen (CMRO2), as also noted in more recent studies [15–17]. Other researchers have reported small but significant increases in CMRO2 after inhalation of hypoxic air or breath-holds in young healthy controls [18–20]. Cerebral lactate is also known to increase during hypoxic events in healthy controls [15, 16, 18, 21]. It is currently not known how CBF, CMRO2, and cerebral lactate concentrations change in patients with OSA, and it is not clear how CPAP treatment affects brain oxygen metabolism and CBF. CPAP has a tendency to reduce the risk of cardiovascular events and to yield a lower score on the Epworth Sleepiness Scale (ESS) and lower blood pressure [22]. It also improves cerebral blood velocity in the middle cerebral artery in patients with OSA in response to hypoxia [23, 24]. The aim of this study was to examine CMRO2, CBF, and lactate during hypoxia in patients with OSA and to compare them with controls. We evaluated the effects on these characteristics after 3 months of CPAP treatment. Materials and Methods Twenty-eight patients diagnosed with moderate-to-severe OSA (apnea–hypopnea index, AHI > 15 events/h) and 19 healthy controls (AHI < 5 events/h) were consecutively recruited from the Danish Center for Sleep Medicine, Glostrup Hospital, and through an Internet advertisement placed between September 2015 and May 2016. Exclusion criteria were: presence of severe heart, lung, or kidney disease; body mass index (BMI) > 40 kg/m2; pregnancy or breastfeeding; any clinical sign of previous stroke or transient ischemic attack; malignant disease within the previous 3 years; insulin-treated diabetes; use of antidepressants, hypnotics, morphine, or other respiratory-depressant medication; and weekly alcohol consumption greater than 14 units per week. Eleven patients and four controls suffered from hypertension, while three patients and one control suffered from type 2 diabetes. Subjects were well treated with antihypertensive medication or oral hypoglycemic medication. None of the patients with OSA had received CPAP treatment before the study. Six OSA patients were smokers and 12 were former smokers, while three controls were smokers and four were former smokers (Table 1). The study protocol was reviewed and approved by the regional Ethics Committee and the Danish Data Protection Agency. The study was carried out in accordance with the Declaration of Helsinki of the World Medical Association. All participants gave their written, informed consent to take part in the study. Table 1. Baseline characteristics, comorbidities, OSA severity, and CPAP compliance of patients and controls Parameter  OSA patients (n = 28)  Controls (n = 19)  OSA vs. controls (P-value)  Male, sex (%)  82.1  73.7  0.740  BMI (kg/m2)  29.38 ± 3.8  27.03 ± 3.0  0.029  Age (years)  52.3 ± 10.0  51.8 ± 10.1  0.803  Hypertention (%)  39.3  21.1  0.188  DM type 2 (%)  10.7  5.3  0.901  Smoker (%)  21.4  15.8  0.917  AHI  40.91 ± 16.1  2.37 ± 1.6  <0.001  ESS  8.1 ± 4.5  5.5 ± 3.5  0.043  ODI  40.9 ± 15.5  5.8 ± 4.1  <0.001  CPAP > 4 h/night (%)  73.1 (95% CI: 60.1, 86.0)  —  —  Parameter  OSA patients (n = 28)  Controls (n = 19)  OSA vs. controls (P-value)  Male, sex (%)  82.1  73.7  0.740  BMI (kg/m2)  29.38 ± 3.8  27.03 ± 3.0  0.029  Age (years)  52.3 ± 10.0  51.8 ± 10.1  0.803  Hypertention (%)  39.3  21.1  0.188  DM type 2 (%)  10.7  5.3  0.901  Smoker (%)  21.4  15.8  0.917  AHI  40.91 ± 16.1  2.37 ± 1.6  <0.001  ESS  8.1 ± 4.5  5.5 ± 3.5  0.043  ODI  40.9 ± 15.5  5.8 ± 4.1  <0.001  CPAP > 4 h/night (%)  73.1 (95% CI: 60.1, 86.0)  —  —  Data are reported as the mean and SD. Groups are compared with the chi-squared test and the paired Student’s t-test. Statistical significant difference are highlighted with bold (P < 0.05). ODI = oxygen desaturation index. View Large Participants were assessed in accordance with the criteria of the American Academy of Sleep Medicine in 2012 [25]. Healthy controls were excluded if their AHI exceeded 5 events/h. All OSA patients were offered CPAP treatment. Patients who were treated with CPAP were rescanned after 3 months. Their compliance was defined as the number of days using CPAP for more than 4 h/night, expressed as a percentage. Participants were scanned on a Philips 3T Achieva MRI scanner (Philips Medical Systems, Best, Netherlands). Hypoxia was induced with an AltiTrainer System (SMTEC, Nyon, Switzerland), which mixes atmospheric air with 99.99% nitrogen from a gas cylinder. The participants were awake and wore a full-face mask connected to the AltiTrainer by a one-way valve tube. The fraction of inhaled oxygen was regulated to correspond to approximately 10% of oxygen, inducing hypoxemia in the participants. The system delivered normoxia for 35 min followed by 35 min inhalation of hypoxic air. CO2 was not controlled; instead, it fluctuated in conjunction with respiration. Before and after the scan, a blood sample was taken from the participants to measure hemoglobin, hematocrit, and blood lactate concentration. Participants were monitored with electrocardiography (ECG), blood pressure, end-tidal CO2 tension monitoring, and pulse oximetry (Veris Monitor, Medrad). The pulse oximetry was calibrated by measurements from a previous study using simultaneously drawn arterial blood samples and pulse oximetry from 23 subjects during normoxia and hypoxia [18]. Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) techniques were used to estimate global CBF, global CMRO2, and cerebral metabolite concentrations. Figure 1 depicts the timeline for acquisition of the parameters and the hypoxic challenge. Figure 1. View largeDownload slide Timeline of MRI acquisitions. Blood samples were taken before and after the MRI scan. After 35 min the participants inhaled a 10% fraction of hypoxic air. After 15 min of hypoxic exposure the MRI measurements were repeated. Figure 1. View largeDownload slide Timeline of MRI acquisitions. Blood samples were taken before and after the MRI scan. After 35 min the participants inhaled a 10% fraction of hypoxic air. After 15 min of hypoxic exposure the MRI measurements were repeated. Cerebral blood flow Global CBF was measured by phase-contrast mapping (PCM) MRI of the blood flow in the internal carotid arteries and the basilar artery. Specifically, it was calculated as the sum of the flows in the internal carotid arteries and the basilar artery, assuming a phase–velocity relationship [26] (one slice, field of view = 240 × 240 mm2, voxel size = 0.75 × 0.75 × 8 mm3, echo time = 7.51 ms, repetition time = 12.4 ms, flip angle = 10°, 10 repeated measures, non-gated, velocity encoding = 100 cm/s, total duration = 1 min 42 s). The imaging slices were placed perpendicular to the carotid or basilar arteries (Figure 2a). Flow was calculated in each vessel as the product of the cross-sectional area and the mean blood velocity (Figure 2b). Data were processed using Matlab (Mathworks, Natick, MA) scripts written in-house. The total blood flow was normalized with respect to whole-brain tissue weight to obtain quantitative values in mL/100 g/min. The cerebral delivery of O2 (CDO2) was calculated by multiplying CBF by the arterial oxygen concentration. Figure 2. View largeDownload slide (a) Sagittal and coronal view of angiography highlighting the internal carotid arteries with the imaging plane visualized. (b) Phase-difference map showing the velocity (cm/s) in the internal carotids used to measure CBF. (c) Sagittal view of angiography highlighting the sagittal sinus and the transverse plane of the brain covering the sagittal sinus used for calculating SvO2. (d) Phase-difference map showing the sagittal sinus and surrounding tissue. Figure 2. View largeDownload slide (a) Sagittal and coronal view of angiography highlighting the internal carotid arteries with the imaging plane visualized. (b) Phase-difference map showing the velocity (cm/s) in the internal carotids used to measure CBF. (c) Sagittal view of angiography highlighting the sagittal sinus and the transverse plane of the brain covering the sagittal sinus used for calculating SvO2. (d) Phase-difference map showing the sagittal sinus and surrounding tissue. Cerebral metabolic rate of oxygen CMRO2 was calculated using the Fick principle equation (1):  CMRO2=[Hgb]⋅(CBFSS)⋅(SaO2-SvO2) (1) where CBFss is the blood flow in the sagittal sinus in mL/min scaled to global CBF, SaO2 and SvO2 are the arterial and venous oxygen saturation levels, respectively, and [Hgb] is the oxygen-carrying hemoglobin concentration (mmol/L) at full saturation. SaO2 was measured by digital pulse oximeter. SvO2 and blood flow in the sagittal sinus were measured simultaneously using an MRI sequence combining susceptibility-based oximetry (SBO) for acquisition of saturation and PCM for acquisition of blood flow [27]. Examples of MRI images from PCM and SBO are illustrated in Figure 2a–d. SBO exploits the relative paramagnetic difference between deoxygenated and oxygenated hemoglobin by measuring the susceptibility of blood relative to surrounding tissue. By modeling the large vessels of interest as a long paramagnetic cylinder and taking into account field cancellation due to the Lorentz sphere phenomenon, it is possible to quantify the difference in susceptibility between blood and the surrounding tissue. The relationship of the susceptibility to venous oxygen saturation is expressed by equation (2) [19, 28]:  SvO2=[1-2|Δφ|γΔχdoB0ΔTE(cos2θ-13)Hct+ΔχoxyΔχdo]⋅100 (2) where ∆ϕ is the difference in phase values between intravascular blood in the sagittal sinus and the surrounding reference tissue; γ is the proton gyromagnetic ratio; ∆χdo = 4π ∙ 0.27 ppm is the difference in volume susceptibility between fully deoxygenated and oxygenated erythrocytes; and ∆χoxy = 4π(−0.008) ppm, the volume susceptibility difference between fully oxygenated erythrocytes and water [29]. θ is the tilt angle of the sagittal sinus relative to the main magnetic field (B0); ∆TE is the difference in echo time; and Hct is the hematocrit level. Susceptibility-weighted maps (ϕ) were created with a dual-echo gradient-echo sequence (one slice, field of view = 220 × 190 mm2, voxel size = 0.5 × 0.5 × 8 mm3, echo time 1 = 10.89 ms, echo time 2 = 24.16 ms, flip angle = 30°, five repeated measures, total duration = 1 min 30 s, SENSE-factor = 2) and modulus, real and imaginary values from both echoes were saved. The maps were computed by subtracting phase-value maps corresponding to the two images generated with the short and long echo times. Unwrapping of the aliased phase was performed manually. The difference in susceptibility between venous blood and tissue was calculated by drawing a region of interest (ROI) in the sagittal sinus and surrounding tissue. The ROIs were established from five repeated measures along a section of the sagittal sinus and the mean of the phase values of all the voxels inside the ROI was calculated to determine the difference in susceptibility and thereby the SvO2. Acquisition of each frame was repeated with phase-contrast velocity encoding for simultaneous measurement of blood flow in the sagittal sinus. The blood flow in the sagittal sinus was acquired by drawing an ROI covering the sagittal sinus. The mean velocity and cross-sectional area from the ROI were multiplied to calculate flow, similar to the post-processing used to calculate global CBF described earlier. Blood flow in the sagittal sinus was scaled to global CBF measured at baseline in each participant to normalize CMRO2 with respect to individual global brain values [30]. CMRO2 calculated from measurements with SBO has been validated theoretically [31] and by anatomical phantom models [32]. All processing was performed using Matlab scripts developed in-house. The data analyst was blinded with respect to oxygen status and subject. Magnetic resonance spectroscopy The cerebral concentration of lactate, total creatine (tCr), N-acetylaspartate (NAA), and combined glutamate+glutamine (Glx), was measured by MRS. A water-suppressed point-resolved spectroscopy (PRESS) pulse sequence was used (repetition time = 3,000 ms, echo time = 36.5 ms, voxel size = 30 × 35 × 30 mm3, sampling frequency = 2000 Hz, spectral resolution = 1.95 Hz, 64 acquisitions, total duration 6 min 34 s). The water signal was also measured and used as an internal standard for quantification [33]. The voxel was located in the visual cortex covering the calcarine fissure inside the brain tissue to avoid contamination with subcutaneous fat. Fourier transformation of the signal produced a spectrum of resonance frequencies, with the area under the spectral peaks proportional to metabolite concentrations. Absolute concentrations of metabolites were estimated using the unsuppressed water signal as the reference signal using LCModel (Version 6.3-1F; Toronto, Canada). Anatomical scan High-resolution anatomical scans were obtained with a 3D T1-weighted turbo field echo sequence (150 slices, field of view = 241 × 180 × 165 mm3, voxel size = 1.09 × 0.81 × 1.1 mm3, echo time = 2.78 ms, repetition time = 6.9 ms, flip angle = 9°). Individual brain volumes were estimated from the anatomical scans using FSL BET and FAST software (FMRIB Software Library, University of Oxford, Oxford, United Kingdom). Brain weight was calculated by assuming a brain density of 1.05 g/mL [34]. Statistics The chi-squared test and the two-sample Student’s t-test, with statistical significance concluded for values of p < 0.05, were used to compare the demographic and clinical variables of controls and OSA subjects (Table 1). The significance of the effect of hypoxia on the measured parameters was calculated using a paired Student’s t-test (Table 2). To test the effect of the degree of hypoxia on the measured parameters their correlation with arterial oxygen concentration (CaO2) was examined (Figure 3) using a mixed linear regression model of the form expressed in equation (3): Table 2. Summary of clinical results Parameter  OSA patients (n = 28)  Patients after CPAP (n = 22)  Controls (n = 19)  Difference of Δ values between groups (P-value)  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  OSA vs. controls  OSA vs. CPAP  CPAP vs. controls  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Blood content   CaO2 (mmol/L)  9.1 ± 0.8  8.1 ± 1.1  <0.001  9.0 ± 0.7  7.6 ± 1.0  <0.001  8.8 ± 0.7  7.1 ± 0.8  <0.001  0.016  0.107  0.354   SaO2 (%)  96.1 ± 1.3  84.0 ± 8.5  <0.001  95.8 ± 1.5  81.6 ± 9.1  <0.001  96.0 ± 1.1  77.1 ± 7.2  0.001  0.002  0.308  0.047   SvO2 (%)  64.2 ± 0.06  59.9 ± 0.06  0.001  65.0 ± 0.06  57.8 ± 0.08  <0.001  66.9 ± 0.07  60.2 ± 0.07  <0.001  0.063  0.572  0.298   PaCO2 (kPa)  4.73 ± 0.46  4.45 ± 0.52  <0.001  4.81 ± 0.45  4.38 ± 0.48  <0.001  4.70 ± 0.61  4.04 ± 0.62  <0.001  0.015  0.154  0.236   Hgb (mmol/L)  9.5 ± 0.8  9.4 ± 0.8  0.013  9.4 ± 0.7  9.1 ± 0.7  <0.001  9.2 ± 0.7  8.9 ± 0.7  <0.001  0.642  0.306  0.512  Hemodynamics   MAP BP (mmHg)  110.9 ± 14.5  113.0 ± 11.6  0.141  101.5 ± 8.6  105.4 ± 12.0  0.045  99.8 ± 12.3  99.3 ± 12.1  0.863  0.306  0.719  0.187   Heart rate (bpm)  67.4 ± 11.4  69.8 ± 9.9  0.040  68.4 ± 10.8  71.5 ± 11.9  0.039  65.6 ± 9.5  73.2 ± 11.5  <0.001  0.005  0.707  0.025  Cerebral metabolism   CDO2 (µmol/100 g/min)  390.2 ± 72.6  332.8 ± 59.1  <0.001  401.7 ± 52.0  357.8 ± 54.6  0.010  390.1 ± 59.8  346.6 ± 69.4  0.003  0.125  0.480  0.663   CBF (mL/100 g/min)  42.91 ± 7.5  42.14 ± 9.3  0.530  45.35 ± 7.0  48.86 ± 10.2  0.086  44.43 ± 6.9  49.77 ± 11.5  0.025  0.011  0.056  0.532   A-V O2 (%)  32.2 ± 5.9  26.4 ± 9.9  0.002  30.0 ± 6.0  25.1 ± 8.8  0.007  29.2 ± 7.0  18.9 ± 11.0  <0.001  0.064  0.361  0.118   CMRO2 (µmol/100 g/min)  131.2 ± 16.1  125.1 ± 29.7  0.205  130.4 ± 20.3  117.4 ± 26.3  0.014  124.4 ± 22.4  106.2 ± 30.7  <0.001  0.081  0.254  0.586   Cerebral lactate (mmol/L)  0.54 ± 0.38  0.78 ± 0.54  0.012  0.62 ± 0.43  0.77 ± 0.57  0.286  0.58 ± 0.47  0.91 ± 0.60  0.002  0.492  0.593  0.288   tCr (mmol/L)  5.4 ± 0.4  5.3 ± 0.5  0.150  5.3 ± 0.5  5.1 ± 0.7  0.050  5.6 ± 0.4  5.5 ± 0.4  0.141  0.750  0.301  0.185   Glutamate (mmol/L)  6.4 ± 1.4  6.2 ± 1.5  0.203  6.5 ± 1.4  6.1 ± 1.6  0.244  7.1 ± 1.5  7.3 ± 1.2  0.181  0.088  0.759  0.086  Parameter  OSA patients (n = 28)  Patients after CPAP (n = 22)  Controls (n = 19)  Difference of Δ values between groups (P-value)  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  Normoxia  Hypoxia  P-value  OSA vs. controls  OSA vs. CPAP  CPAP vs. controls  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Mean ± SD  Blood content   CaO2 (mmol/L)  9.1 ± 0.8  8.1 ± 1.1  <0.001  9.0 ± 0.7  7.6 ± 1.0  <0.001  8.8 ± 0.7  7.1 ± 0.8  <0.001  0.016  0.107  0.354   SaO2 (%)  96.1 ± 1.3  84.0 ± 8.5  <0.001  95.8 ± 1.5  81.6 ± 9.1  <0.001  96.0 ± 1.1  77.1 ± 7.2  0.001  0.002  0.308  0.047   SvO2 (%)  64.2 ± 0.06  59.9 ± 0.06  0.001  65.0 ± 0.06  57.8 ± 0.08  <0.001  66.9 ± 0.07  60.2 ± 0.07  <0.001  0.063  0.572  0.298   PaCO2 (kPa)  4.73 ± 0.46  4.45 ± 0.52  <0.001  4.81 ± 0.45  4.38 ± 0.48  <0.001  4.70 ± 0.61  4.04 ± 0.62  <0.001  0.015  0.154  0.236   Hgb (mmol/L)  9.5 ± 0.8  9.4 ± 0.8  0.013  9.4 ± 0.7  9.1 ± 0.7  <0.001  9.2 ± 0.7  8.9 ± 0.7  <0.001  0.642  0.306  0.512  Hemodynamics   MAP BP (mmHg)  110.9 ± 14.5  113.0 ± 11.6  0.141  101.5 ± 8.6  105.4 ± 12.0  0.045  99.8 ± 12.3  99.3 ± 12.1  0.863  0.306  0.719  0.187   Heart rate (bpm)  67.4 ± 11.4  69.8 ± 9.9  0.040  68.4 ± 10.8  71.5 ± 11.9  0.039  65.6 ± 9.5  73.2 ± 11.5  <0.001  0.005  0.707  0.025  Cerebral metabolism   CDO2 (µmol/100 g/min)  390.2 ± 72.6  332.8 ± 59.1  <0.001  401.7 ± 52.0  357.8 ± 54.6  0.010  390.1 ± 59.8  346.6 ± 69.4  0.003  0.125  0.480  0.663   CBF (mL/100 g/min)  42.91 ± 7.5  42.14 ± 9.3  0.530  45.35 ± 7.0  48.86 ± 10.2  0.086  44.43 ± 6.9  49.77 ± 11.5  0.025  0.011  0.056  0.532   A-V O2 (%)  32.2 ± 5.9  26.4 ± 9.9  0.002  30.0 ± 6.0  25.1 ± 8.8  0.007  29.2 ± 7.0  18.9 ± 11.0  <0.001  0.064  0.361  0.118   CMRO2 (µmol/100 g/min)  131.2 ± 16.1  125.1 ± 29.7  0.205  130.4 ± 20.3  117.4 ± 26.3  0.014  124.4 ± 22.4  106.2 ± 30.7  <0.001  0.081  0.254  0.586   Cerebral lactate (mmol/L)  0.54 ± 0.38  0.78 ± 0.54  0.012  0.62 ± 0.43  0.77 ± 0.57  0.286  0.58 ± 0.47  0.91 ± 0.60  0.002  0.492  0.593  0.288   tCr (mmol/L)  5.4 ± 0.4  5.3 ± 0.5  0.150  5.3 ± 0.5  5.1 ± 0.7  0.050  5.6 ± 0.4  5.5 ± 0.4  0.141  0.750  0.301  0.185   Glutamate (mmol/L)  6.4 ± 1.4  6.2 ± 1.5  0.203  6.5 ± 1.4  6.1 ± 1.6  0.244  7.1 ± 1.5  7.3 ± 1.2  0.181  0.088  0.759  0.086  Data are reported as the mean and SD. Groups are compared with paired and unpaired t-tests. CaO2 = arterial O2 concentration; PaO2 = arterial O2 pressure; SaO2 = arterial saturation; SvO2 = venous saturation; PaCO2 = arterial CO2 pressure, Hgb = hemoglobin concentration; MAP BP = mean arterial blood pressure; A-V O2 = arteriovenous O2 saturation difference; NAA = N-acetylaspartate; tCr = creatine and phosphocreatine. View Large Figure 3. View largeDownload slide Linear mixed model (equation 3) of arterial oxygen concentration (CaO2) during normoxia (red dots) and hypoxia (blue dots) and (a) CBF, (b) CDO2, (c) CMRO2, (d) lactate. Results from controls, OSA patients, and patients after 3 months of CPAP are demonstrated. The significance (p) of the regression and the coefficient of the slope (β1) of the relationship with CaO2 are shown in each panel. Figure 3. View largeDownload slide Linear mixed model (equation 3) of arterial oxygen concentration (CaO2) during normoxia (red dots) and hypoxia (blue dots) and (a) CBF, (b) CDO2, (c) CMRO2, (d) lactate. Results from controls, OSA patients, and patients after 3 months of CPAP are demonstrated. The significance (p) of the regression and the coefficient of the slope (β1) of the relationship with CaO2 are shown in each panel.  Y=β0+β1⋅CaO2+u+ɛ (3) The measured parameter was modeled as the response variable (Y). CaO2 was modeled as an independent variable. Subjects (μ) were modeled as random effects to account for between-subject variability, and ε is the residual error term. The result of the regression and the β1 coefficient and related probability are shown in Figure 2. To test for differences in responses to the hypoxic challenge between the OSA patient and control groups, the grouping and interaction between grouping and CaO2 were added to the model as fixed-variable terms (equation 4):  Y=β0+β1⋅CaO2+β2⋅group+β3⋅group⋅CaO2+u+ɛ (4) A difference in response to hypoxia between the two groups will produce a significant interaction coefficient (β3) [35], which is shown in Table 3 with its corresponding probability. Statistical analyses were performed using the Matlab statistics toolbox. Table 3. Summary statistics of the linear mixed model (equation 4) testing for differences in responses to the hypoxic challenge between the OSA patient group and the control group by including group and its interaction with CaO2 as fixed-variable terms   OSA vs. control  OSA vs. CPAP  CPAP vs. control  Interaction coefficient  P-value  Interaction coefficient  P-value  Interaction coefficient  P-value  CBF (mL/100 g/min)  −1.77  0.0029  −3.70  0.0022  0.33  0.7985  CDO2 (µmol/100 g/min)  −10.87  0.0295  −21.00  0.0529  −2.76  0.8081  CMRO2 (µmol/min)  0.40  0.8078  −8.01  0.0451  2.02  0.5430  Lactate (mmol/L)  −0.044  0.2591  −0.13  0.1957  −0.053  0.5703    OSA vs. control  OSA vs. CPAP  CPAP vs. control  Interaction coefficient  P-value  Interaction coefficient  P-value  Interaction coefficient  P-value  CBF (mL/100 g/min)  −1.77  0.0029  −3.70  0.0022  0.33  0.7985  CDO2 (µmol/100 g/min)  −10.87  0.0295  −21.00  0.0529  −2.76  0.8081  CMRO2 (µmol/min)  0.40  0.8078  −8.01  0.0451  2.02  0.5430  Lactate (mmol/L)  −0.044  0.2591  −0.13  0.1957  −0.053  0.5703  The interaction coefficients (β3) and their significance (p) are shown. Statistical significant difference are highlighted with bold (P < 0.05). CaO2 = arterial O2 concentration; OSA = patients with obstructive sleep apnea at baseline; CPAP = patients after CPAP treatment. View Large Results Twenty-eight of 37 patients were included in the study (eight patients dropped out because of claustrophobia related to MRI scans, and one was excluded because of the malfunction of the oxygen mask). Twenty-two patients were rescanned after treatment with CPAP (dropouts occurred due to noncompliance with MRI or with CPAP, or withdrawal of consent). CBF measurement failed in one of the patients after CPAP treatment. Pulse oximetry failed in two patients at baseline and in three patients after CPAP treatment. Blood samples after hypoxia failed in three patients at baseline and in one patient after CPAP treatment. The acquisition of MRS failed in five of the patients after CPAP treatment. We enrolled 24 controls, but excluded five participants due to undiagnosed OSA, leaving 19 controls. Baseline characteristics of the two groups are shown in Table 1. The patients and controls were similar with respect to gender and age, although the BMI was higher in the OSA patient group. The patients rescanned after CPAP treatment had almost normalized levels of AHI (2.4 ± 1.6) and ESS scores (5.5 ± 3.5). Compliance with CPAP treatment involving more than 4 h use per night over 3 months was 73.1% (95% CI: 60.1, 86.0). SaO2 decreased significantly in both groups during hypoxia. SaO2 decreased significantly more in the control group than in patients after exposure to the same level of hypoxia. Heart rate increased significantly in all groups after exposure to hypoxia, although the increase was significantly greater in the controls than in the patients, before and after CPAP treatment. The arteriovenous O2 saturation difference (A-V O2) decreased from normoxia to hypoxia, with a greater reduction in the control group than in patients at baseline and after CPAP treatment (Table 2). The smaller A-V O2 difference of oxygen seen in controls may in part be caused by the increased heart rate and the increased CBF in controls, which reduces the diffusion time of oxygen from blood to the cerebral tissue. The smaller oxygen tension in the blood also reduces gas exchange to the tissue because of the lower gradient during hypoxia in both groups. During hypoxia CBF increased significantly in the control group (p = 0.025), but was unchanged in the OSA patients (p = 0.53) (Table 2). The unchanged CBF caused a significantly greater decrease in CDO2 during hypoxia in patients compared with the control group (Table 3). Patients had increased CBF during hypoxia after treatment with CPAP, similar to what was observed in the control group, while their CDO2 was similar to that of the control group (Table 3 and Figure 3). CMRO2 decreased during hypoxia and was significantly correlated with CaO2 for all groups in the mixed model (Figure 3c) and there was a difference between patients before and after CPAP (Table 3). However, the t-tests identified significant decreases only in the control group and in patients after CPAP treatment (Table 2). Cerebral lactate increased significantly in controls (p < 0.001) during hypoxia but not in patients (p = 0.87) (Table 2). The difference between controls and patients was not significant (Table 3), probably because three patients demonstrated a pronounced increase in cerebral lactate during hypoxia as opposed to the remaining patients (Figure 3d). When these patients were excluded we found a significant difference between the patient and control groups in the mixed model. NAA, Glx, and tCr showed no significant change between normoxia and hypoxia or any effect from CPAP treatment. Discussion To our knowledge, this is the first study to evaluate the effect of hypoxemia on CBF, CMRO2, and cerebral metabolites in patients with moderate-to-severe OSA identified by PCM MRI, SBO, and spectroscopy determined by MRI. The main findings of this study are that: (1) hypoxia increased CBF in controls but not in OSA patients, and (2) after 3 months of CPAP, patients regained the capacity for CBF to increase after exposure to hypoxia, similar to controls. OSA is known to be associated with a significant risk of ischemic stroke [36], but the detailed mechanism underlying this link is not known. We believe that part of the mechanism involved in stroke [37] includes the changes in CBF after exposure to hypoxia. In the presence of normal autoregulation, hypocapnia, as seen in the control group and in patients who hyperventilate, causes cerebrovascular arterial vasoconstriction [38], while hypoxia opposes this mechanism and dilates the cerebral vessels, leading to increased CBF. Hypoxia also raises the heart rate in both groups and, potentially, increases cardiac output, which may contribute to the increased CBF. However, patients with OSA present another response. Patients generally experience smaller decreases in end-tidal CO2, and SaO2, while CBF is unchanged in response to hypoxia. A possible hyperventilation induced by hypoxia in the patient group was ruled out by the end-tidal CO2 measurements. The patient group showed higher end-tidal CO2 compared with the control group during hypoxia. Thus, hyperventilation cannot explain the lower level of desaturation or the lack of CBF increase in patients than in controls during the hypoxic challenge. Patients after CPAP treatment had the ability restored for their CBF to increase after exposure to hypoxia. There was a positive effect of CPAP treatment after 3 months. Earlier studies using transcranial Doppler and related methods (autonomic challenges, autoregulatory index, and response to hypoxia) support our findings, revealing a weaker response with respect to cerebral blood velocity than in the control groups [23, 24, 39]. We found a reduction in CMRO2 in all the groups during hypoxic challenge and a significant difference between the patients before and after CPAP. An earlier study by Smith et al. [40] suggested that hypocapnia was the reason for increased CMRO2 during poikilocapnic hypoxia. This is in contrast to the decrease in CMRO2 we observed, even though the participants reacted with hypocapnia in the study. These authors examined a group of young participants, and this age difference may explain the different responses. In the study by Vestergaard et al. [18], who used the same MRI study protocol as in the present study, the young and healthy controls showed a small but significant increase in CMRO2 during hypoxia. Our study showed reduced CMRO2 during hypoxia, which could be explained by the differences in the clinical characteristics of the controls, especially those associated with age. The global baseline CMRO2 measured in this study was consistent with values obtained by various techniques [21, 41–43]. Previous studies have shown lower CVR and CMRO2 in patients with OSA during 30-s breath-holding than in controls [30, 44]. The CVR during short breath-holding is mainly driven by a hypercapnic response since short breath-holding causes only slight desaturation (≈90% SaO2). We extend these studies by showing that CVR also decreases during long-lasting hypoxia, in which CVR is driven by the arterial desaturation rather than hypercapnia. Despite the long-standing interest in brain metabolism, no studies have so far evaluated cerebral lactate metabolism in patients with OSA [45]. The lactate concentration in our study increased in response to hypoxia in the control group, but was unchanged in response to hypoxia in patients before and after CPAP treatment. There was no difference between patients and controls, although three patients had a pronounced increase in lactate concentration. Excluding these subjects from the analysis, the controls exhibited a significantly greater increase in lactate concentration than did patients. We observed an increase in cerebral lactate concentration in controls, with a simultaneous drop in CMRO2. OSA patients before and after CPAP treatment showed no increase in cerebral lactate concentration, while CMRO2 was reduced. This could contribute to the insufficient energy supply to the brain when both oxygen consumption and lactate production are compromised during hypoxia in patients with OSA. There was no difference in Glx or tCr concentration before or after hypoxia in any group. Cerebral Glx has previously been reported to be unchanged after exposure to hypoxia in healthy controls [46], consistent with our results. tCr decreases during hypoxia and visual stimulation [18]. Phosphocreatine and ATP were also reduced in a study of hypoxic rodents [47], although we found no difference in our study. Controls underwent greater desaturation than patients during hypoxic exposure, suggesting that OSA patients compensate for hypoxic stimuli. The reason for the lesser desaturation in patients is not known and so requires further examination. Additionally, we observed a fall in hemoglobin concentration in the blood samples from normoxia to hypoxia in all groups. The mechanism responsible is also unknown, although we think it is associated with hypoxia-related vasodilation, causing fluid drainage into the blood and thereby dilution. An overall limitation of the study is our induction of hypoxia, which simulates spontaneous apneas in fully awake patients rather than investigating brain metabolism in apneas during sleep. The mechanisms in the brain during apneas involve complex interactions between cardiovascular and cerebrovascular hemodynamics, O2, CO2, and the autonomic tone. In this study, we focused on one factor, hypoxia, and its influence on cerebrovascular circulation. Further studies should include PaCO2. PaCO2 accumulates by the end of the apnea, leading to hypercapnia, whereas the level of PaCO2 in this study decreased due to the hypoxic response. The PaCO2 level fluctuated in conjunction with the extent of ventilation after exposure to hypoxia, leading to hypocapnia. We cannot distinguish between the effects of hypoxia and those of hypocapnia. Consequently, the low PaCO2 level in our study may have had an opposite cerebral vasoconstrictive effect to that of the hypercapnia-induced vasodilation normally seen in obstructive apneas. There was a higher level of CBF in controls with lower PaCO2, while patients at baseline had a higher level of PaCO2 and an unchanged CBF. Thus, we conclude that the level of PaCO2 did not contribute substantially to the differences between the groups. Measurement of CBF by MR phase mapping entails some potential errors from arterial geometry, resolution of images, and flow pulsation. However, these effects are relatively small when using setups similar to that used in this study [43, 48–51]. The reproducibility for the PCM sequence used in the present study was 6.5% and the intra-subject variability was similar to that of other techniques [52]. The reproducibility of venous saturation measurements with SBO was shown to be reliable, with a 2.3% coefficient of variation [32]. We also point out that we compared subjects between two states in a paired fashion, which mitigates potential biases in the methods. Cardiac and cerebrovascular hemodynamics undergoes pronounced changes during sleep apnea. Our findings from the MRI method provide a valuable tool for objectively determining CBF, CMRO2, and lactate concentration, and have the potential to help us understand the pathophysiological mechanisms operating in OSA. The study highlights the alteration of cerebrovascular reactivity to hypoxia in patients with OSA. The lack of response to hypoxia may imply overall damage to cerebrovascular reactivity and the sympathetic nervous system in patients with OSA. This may further raise the risk of hypoxia during apnea, potentially increasing that of cerebral ischemia. Future research should include the study of cerebrovascular reactivity and cardiac function during spontaneous sleep. In conclusion, CBF is unchanged in patients with OSA in response to hypoxia, whereas this increases in healthy controls during hypoxia. After 3 months of CPAP treatment patients normalize this response by increasing CBF when exposed to hypoxia. The cerebral lactate concentrations in patients were also unchanged in response to hypoxia, while the control group showed an increase in cerebral lactate. These findings may be central to our understanding of the development of ischemic episodes during apnea and of the protective effect of CPAP treatment. Funding The study was supported by a grant from A.P. Møller Fonden and Læge Sofus Carl Emil Friis og Hustru Olga Doris Friis Legat. Notes Conflict of interest statement. None declared. Acknowledgments MLF Jensen: study design, protocol development, data acquisition and processing, statistical analysis and interpretation, drafting, and revision of the manuscript. HBW Larsson: study design, development of the MRI method and study protocol, data processing, analysis and interpretation, and revision of the manuscript. MB Vestergaard: development of the MRI method and study protocol, data processing, statistical analysis and interpretation, and manuscript revision. P Tønnesen: study design, interpretation of data, and manuscript revision. PJ Jennum: supervision of all parts of the study including its design, creation and initiation, and revision of the manuscript. All authors have given their approval to the final version of the manuscript. References 1. Heinzer Ret al.   Prevalence of sleep-disordered breathing in the general population: the HypnoLaus study. Lancet Respir Med  2015; 3( 4): 310– 318. Google Scholar CrossRef Search ADS   2. Young Tet al.   The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med  1993; 328( 17): 1230– 1235. Google Scholar CrossRef Search ADS   3. Yaggi HKet al.   Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med  2005; 353( 19): 2034– 2041. Google Scholar CrossRef Search ADS   4. Lamberts Met al.   Cardiovascular risk in patients with sleep apnoea with or without continuous positive airway pressure therapy: follow-up of 4.5 million Danish adults. J Intern Med  2014; 276( 6): 659– 666. Google Scholar CrossRef Search ADS   5. Chang CCet al.   High incidence of stroke in young women with sleep apnea syndrome. Sleep Med  2014; 15( 4): 410– 414. Google Scholar CrossRef Search ADS   6. Arzt Met al.   Association of sleep-disordered breathing and the occurrence of stroke. Am J Respir Crit Care Med  2005; 172( 11): 1447– 1451. Google Scholar CrossRef Search ADS   7. Jennum Pet al.   Blood pressure, catecholamines, and pancreatic polypeptide in obstructive sleep apnea with and without nasal Continuous Positive Airway Pressure (nCPAP) treatment. Am J Hypertens  1989; 2( 11 Pt 1): 847– 852. Google Scholar CrossRef Search ADS   8. Jennum Pet al.   Intracranial pressure and obstructive sleep apnea. Chest  1989; 95( 2): 279– 283. Google Scholar CrossRef Search ADS   9. Alex Ret al.   Effect of apnea duration on apnea induced variations in cerebral blood flow velocity and arterial blood pressure. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual Conference  2014; 2014: 270– 273. 10. Macey PMet al.   Global brain blood-oxygen level responses to autonomic challenges in obstructive sleep apnea. PLoS One  2014; 9( 8): e105261. Google Scholar CrossRef Search ADS   11. Somers VKet al.   Sympathetic activation by hypoxia and hypercapnia–implications for sleep apnea. Clin Exp Hypertens A  1988; 10( Suppl 1): 413– 422. 12. Winklewski PJet al.   Cerebral blood flow, sympathetic nerve activity and stroke risk in obstructive sleep apnoea. Is there a direct link? Blood Press  2013; 22( 1): 27– 33. Google Scholar CrossRef Search ADS   13. Pizza Fet al.   Cerebral hemodynamic changes in stroke during sleep-disordered breathing. Stroke  2012; 43( 7): 1951– 1953. Google Scholar CrossRef Search ADS   14. Kety SSet al.   The effects of altered arterial tensions of carbon dioxide and oxygen on cerebral blood flow and cerebral oxygen consumption of normal young men. J Clin Invest  1948; 27( 4): 484– 492. Google Scholar CrossRef Search ADS   15. Ainslie PNet al.   Stability of cerebral metabolism and substrate availability in humans during hypoxia and hyperoxia. Clin Sci (Lond)  2014; 126( 9): 661– 670. Google Scholar CrossRef Search ADS   16. Overgaard Met al.   Hypoxia and exercise provoke both lactate release and lactate oxidation by the human brain. FASEB J  2012; 26( 7): 3012– 3020. Google Scholar CrossRef Search ADS   17. Bailey DMet al.   Increased cerebral output of free radicals during hypoxia: implications for acute mountain sickness? Am J Physiol Regul Integr Comp Physiol  2009; 297( 5): R1283– R1292. Google Scholar CrossRef Search ADS   18. Vestergaard MBet al.   Acute hypoxia increases the cerebral metabolic rate - a magnetic resonance imaging study. J Cereb Blood Flow Metab  2016; 36( 6): 1046– 1058. Google Scholar CrossRef Search ADS   19. Rodgers ZBet al.   High temporal resolution MRI quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge. J Cereb Blood Flow Metab  2013; 33( 10): 1514– 1522. Google Scholar CrossRef Search ADS   20. Xu Fet al.   Effect of hypoxia and hyperoxia on cerebral blood flow, blood oxygenation, and oxidative metabolism. J Cereb Blood Flow Metab  2012; 32( 10): 1909– 1918. Google Scholar CrossRef Search ADS   21. Cohen PJet al.   Effects of hypoxia and normocarbia on cerebral blood flow and metabolism in conscious man. J Appl Physiol  1967; 23( 2): 183– 189. Google Scholar CrossRef Search ADS   22. Guo Jet al.   Effect of CPAP therapy on cardiovascular events and mortality in patients with obstructive sleep apnea: a meta-analysis. Sleep Breath  2016; 20( 3): 965– 974. Google Scholar CrossRef Search ADS   23. Foster GEet al.   Effects of continuous positive airway pressure on cerebral vascular response to hypoxia in patients with obstructive sleep apnea. Am J Respir Crit Care Med  2007; 175( 7): 720– 725. Google Scholar CrossRef Search ADS   24. Reichmuth KJet al.   Impaired vascular regulation in patients with obstructive sleep apnea: effects of continuous positive airway pressure treatment. Am J Respir Crit Care Med  2009; 180( 11): 1143– 1150. Google Scholar CrossRef Search ADS   25. Berry RBet al.  ; American Academy of Sleep Medicine. Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events. Deliberations of the sleep apnea definitions task force of the American Academy of Sleep Medicine. J Clin Sleep Med  2012; 8( 5): 597– 619. 26. Evans AJet al.   Magnetic resonance imaging of blood flow with a phase subtraction technique. In vitro and in vivo validation. Invest Radiol  1993; 28( 2): 109– 115. Google Scholar CrossRef Search ADS   27. Rodgers ZBet al.   MRI-based methods for quantification of the cerebral metabolic rate of oxygen. J Cereb Blood Flow Metab  2016; 36( 7): 1165– 1185. Google Scholar CrossRef Search ADS   28. Rodgers ZBet al.   Rapid T2- and susceptometry-based CMRO2 quantification with interleaved TRUST (iTRUST). Neuroimage  2015; 106: 441– 450. Google Scholar CrossRef Search ADS   29. Jain Vet al.   Investigating the magnetic susceptibility properties of fresh human blood for noninvasive oxygen saturation quantification. Magn Reson Med  2012; 68( 3): 863– 867. Google Scholar CrossRef Search ADS   30. Rodgers ZBet al.   Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge. J Cereb Blood Flow Metab  2016; 36( 4): 755– 767. Google Scholar CrossRef Search ADS   31. Li Cet al.   Accuracy of the cylinder approximation for susceptometric measurement of intravascular oxygen saturation. Magn Reson Med  2012; 67( 3): 808– 813. Google Scholar CrossRef Search ADS   32. Jain Vet al.   MRI estimation of global brain oxygen consumption rate. J Cereb Blood Flow Metab  2010; 30( 9): 1598– 1607. Google Scholar CrossRef Search ADS   33. Christiansen Pet al.   In vivo quantification of brain metabolites by 1H-MRS using water as an internal standard. Magn Reson Imaging  1993; 11( 1): 107– 118. Google Scholar CrossRef Search ADS   34. Torack RMet al.   Correlative assay of computerized cranial tomography CCT, water content and specific gravity in normal and pathological postmortem brain. J Neuropathol Exp Neurol  1976; 35( 4): 385– 392. Google Scholar CrossRef Search ADS   35. Gujarati D. Use of dummy variables in testing for equality between sets of coefficients in linear regressions: a note. Am Stat  1970; 24( 5): 18– 22. 36. Cereda CWet al.   Sleep-disordered breathing in acute ischemic stroke and transient ischemic attack: effects on short- and long-term outcome and efficacy of treatment with continuous positive airways pressure–rationale and design of the SAS CARE study. Int J Stroke  2012; 7( 7): 597– 603. Google Scholar CrossRef Search ADS   37. Siebenmann Cet al.   Regulation of cardiac output in hypoxia. Scand J Med Sci Sports  2015; 25( Suppl 4): 53– 59. Google Scholar CrossRef Search ADS   38. Duelli Ret al.   Changes in brain capillary diameter during hypocapnia and hypercapnia. J Cereb Blood Flow Metab  1993; 13( 6): 1025– 1028. Google Scholar CrossRef Search ADS   39. Nasr Net al.   Cerebral autoregulation in patients with obstructive sleep apnea syndrome during wakefulness. Eur J Neurol  2009; 16( 3): 386– 391. Google Scholar CrossRef Search ADS   40. Smith ZMet al.   Sustained high-altitude hypoxia increases cerebral oxygen metabolism. J Appl Physiol (1985)  2013; 114( 1): 11– 18. Google Scholar CrossRef Search ADS   41. Mintun MAet al.   Brain oxygen utilization measured with O-15 radiotracers and positron emission tomography. J Nucl Med  1984; 25( 2): 177– 187. 42. Jain Vet al.   Rapid magnetic resonance measurement of global cerebral metabolic rate of oxygen consumption in humans during rest and hypercapnia. J Cereb Blood Flow Metab  2011; 31( 7): 1504– 1512. Google Scholar CrossRef Search ADS   43. Xu Fet al.   Noninvasive quantification of whole-brain cerebral metabolic rate of oxygen (CMRO2) by MRI. Magn Reson Med  2009; 62( 1): 141– 148. Google Scholar CrossRef Search ADS   44. Prilipko Oet al.   An fMRI study of cerebrovascular reactivity and perfusion in obstructive sleep apnea patients before and after CPAP treatment. Sleep Med  2014; 15( 8): 892– 898. Google Scholar CrossRef Search ADS   45. Xia Yet al.   Changes in cerebral metabolites in obstructive sleep apnea: a systemic review and meta-analysis. Sci Rep  2016; 6: 28712. Google Scholar CrossRef Search ADS   46. Arngrim Net al.   Migraine induced by hypoxia: an MRI spectroscopy and angiography study. Brain  2016; 139( Pt 3): 723– 737. Google Scholar CrossRef Search ADS   47. Tsuji Met al.   Phosphocreatine and ATP regulation in the hypoxic developing rat brain. Brain Res Dev Brain Res  1995; 85( 2): 192– 200. Google Scholar CrossRef Search ADS   48. Bakker CJet al.   Accuracy and precision of time-averaged flow as measured by nontriggered 2D phase-contrast MR angiography, a phantom evaluation. Magn Reson Imaging  1995; 13( 7): 959– 965. Google Scholar CrossRef Search ADS   49. Bakker CJet al.   Measuring blood flow by nontriggered 2D phase-contrast MR angiography. Magn Reson Imaging  1996; 14( 6): 609– 614. Google Scholar CrossRef Search ADS   50. Vestergaard MBet al.   Comparison of global cerebral blood flow measured by phase-contrast mapping MRI with 15 O-H2 O positron emission tomography. J Magn Reson Imaging  2017; 45( 3): 692– 699. Google Scholar CrossRef Search ADS   © Sleep Research Society 2018. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

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