Utilization of Quantitative Susceptibility Mapping for Direct Targeting of the Subthalamic Nucleus During Deep Brain Stimulation Surgery

Utilization of Quantitative Susceptibility Mapping for Direct Targeting of the Subthalamic... Abstract BACKGROUND Deep brain stimulation of the subthalamic nucleus (STN) has demonstrated efficacy in improving motor disability in Parkinson's disease. The recently developed quantitative susceptibility mapping (QSM) technique, which can accurately map iron deposits in deep brain nuclei, promises precise targeting of the STN. OBJECTIVE To demonstrate the use of QSM to target STN effectively by correlating with classical physiological-based targeting measures in a prospective study. METHODS The precision and accuracy of direct targeting with QSM was examined in a total of 25 Parkinson's disease patients between 2013 and 2015 at our institution. QSM was utilized as the primary magnetic resonance imaging (MRI) method to perform direct STN targeting on a stereotactic planning station utilizing computed tomography/MR fusion. Intraoperative microelectrode recordings (MER) were obtained to confirm appropriate trajectory through the sensorimotor STN. RESULTS Estimations of STN thickness between the MER and QSM methods appeared to be correlated. Mean STN thickness was 5.3 mm. Kinesthetic responsive cells were found in > 90% of electrode runs. The mean radial error (±SEM) was 0.54 ± 0.1 mm. Satisfactory clinical response as determined by Unified Parkinson's Disease Rating Scale (UPDRS III) was seen at 12 mo after surgery. CONCLUSION Direct targeting of the sensorimotor STN using QSM demonstrates MER correlation and can be safely used for deep brain stimulation lead placement with satisfactory clinical response. These results imply that targeting based on QSM signaling alone is sufficient to obtain reliable and reproducible outcomes in the absence of physiological recordings. DBS, Deep brain stimulation, Parkinson disease, Quantitative susceptibility mapping, QSM ABBREVIATIONS ABBREVIATIONS 3-D 3-dimensional CI confidence interval CT computed tomography DBS deep brain stimulation FLAIR fluid-attenuated inversion recovery GPi globus pallidus pars interna GRE gradient echo MER microelectrode recordings MRI magnetic resonance imaging PD Parkinson disease QSM quantitative susceptibility mapping SD standard deviation STN subthalamic nucleus SWI susceptibility-weighted phase imaging T2WI T2-weighted imaging UPDRS Unified Parkinson's Disease Rating Scale Parkinson disease (PD) is a progressive neurodegenerative disorder associated with the death of dopamine-producing cells in the substantia nigra. Despite significant advances in the pharmacologic management of PD, a substantial number of these patients are considered refractory to standard medical therapies. In these cases, the current treatment of choice is the implantation of deep brain stimulation (DBS) electrodes into the subthalamic nucleus (STN) or globus pallidus pars interna (GPi).1,2 Chronic stimulation of the STN has been demonstrated to effectively treat a spectrum of motor symptoms of advanced PD symptoms, namely: tremor, rigidity, bradykinesia, motor fluctuations, and drug-induced dyskinesias.1,3 Historically, targeting of the STN was performed indirectly based on coordinates obtained from brain atlases, because imaging available at the time could not adequately characterize basal ganglia targets. Novel high-resolution magnetic resonance imaging (MRI) techniques have allowed for the direct targeting of the STN, thus beginning to create a paradigm shift in DBS. In practice, DBS surgeons perform most direct targeting through the utilization of conventional T2-weighted imaging (T2WI) with field strengths ranging between 1.5 and 3 T. Accurate targeting of the sensorimotor STN has been shown to improve quality of life and motor disability in Parkinson patients.2,4 Precise targeting of the STN is essential for maximizing the therapeutic benefits and minimizing potential deleterious side effects of DBS therapy. Despite advances in the spatial resolution of MRI, direct targeting of the STN remains a challenge primarily due to variations in STN anatomy and limitations inherent in conventional MRI.5 In order to overcome these challenges, investigators have described the use of other MRI techniques such as spoiled gradient-recalled echo,6 fluid-attenuated inversion recovery (FLAIR),7 and susceptibility-weighted phase imaging (SWI).8 Although these techniques or sequences provide better delineation of STN borders compared to T2WI, DBS surgeons have been slow to adopt these sequences into regular practice, primarily because these sequences can be difficult to interpret and their accuracy in characterizing STN borders has been questioned.5,8 Recently, there has been renewed interest in utilizing FLAIR and SWI-MRI sequences for STN targeting.5,8 Glutamatergic neurons in the STN contain high levels of iron relative to the surrounding thalamic neurons, which allows better visualization on iron-sensitive MRI sequences.9 However, the accuracy of these sequences in characterizing STN borders has been called into doubt, primarily because they rely on iron paramagnetic susceptibility artifacts which can affect spatial anatomy.5,10 Quantitative susceptibility mapping (QSM) is a novel MRI technique that accurately depicts brain iron by removing the magnetic susceptibility artifacts in MRI and revealing the magnetic susceptibility source5,11,12 (Figure 1). Since deep brain nuclei contain high concentrations of iron associated with their dopamine and glutamate metabolism, there has been growing interest in utilizing QSM for STN targeting in DBS surgery.5,11 For visualizing the STN where the principal type of neurons is glutamatergic and iron-containing, QSM provides the benefits of accurate iron/neuron maps and susceptibility artifact removal, compared to other MRI techniques such as SWI5,11,12 (Figure 2). In this manuscript, we describe the precise and accurate targeting of the STN using QSM. We have found that QSM accurately depicts the sensorimotor STN, strongly correlates with traditional STN microelectrode recordings (MER), and can be safely and easily used for DBS lead placement with satisfactory clinical response. FIGURE 1. View largeDownload slide Example of STN visualization with conventional T2 A, SWI B, and QSM C in the coronal plane (3 T MRI). FIGURE 1. View largeDownload slide Example of STN visualization with conventional T2 A, SWI B, and QSM C in the coronal plane (3 T MRI). FIGURE 2. View largeDownload slide The STN and surrounding anatomic structures as seen on QSM A axial B coronal C sagittal images at 3 T. Final target coordinates (red dot) are selected based on dedicated axial and coronal QSM images. FIGURE 2. View largeDownload slide The STN and surrounding anatomic structures as seen on QSM A axial B coronal C sagittal images at 3 T. Final target coordinates (red dot) are selected based on dedicated axial and coronal QSM images. METHODS Between the years 2013 and 2015, a total of 122 patients with medically refractory, idiopathic PD underwent staged QSM-guided STN-DBS implantations by the senior author. From this pool of patients, a smaller cohort of 25 patients was then randomly selected from a list containing only the medical record numbers for each patient for the purposes of this study. The patients that were selected were kept blinded to the senior author. A sample size of 25 patients (50 STNs in total) was selected to have 80% power to detect a difference of 0.5 mm (half of voxel size in QSM acquisition matrix) between MER- and QSM-based measurements of STN thickness using a paired t-test with a 0.05 2-tailed significance level. Population standard deviation (SD) of STN thickness was assumed to be 1 mm according to previously reported studies.13,14 Patients were deemed appropriate candidates for STN-DBS surgery if they fulfilled the following criteria: diagnosis of medically refractory, idiopathic PD (UK PD Society Brain Bank Criteria) with >30% improvement on the Unified Parkinson's Disease Rating Scale (UPDRS): motor subscale (UPDRS III) during ON/OFF testing with levodopa, satisfactory neuropsychiatric evaluation, absence of significant vascular or structural abnormalities on brain MRI, and no significant medical comorbidities. Indications for STN-DBS surgery included refractory motor fluctuations, medically refractory tremor, and drug-induced dyskinesias. Exclusion criteria were patients with poor response to levodopa challenge, PD < 5 yr, patients with pre-existing DBS electrodes who presented for revision, or abnormal neuropsychiatric evaluation. Neuropsychological evaluation consisted of a 1-h, personalized assessment performed by a licensed neuropsychologist at our institution. A total of 50 DBS electrodes and 57 MERs were included in analysis. ON/OFF motor testing was performed under the supervision of a movement disorder neurologist prior to surgery. All patients included in this study consented to utilize their patient-specific information as approved by our Institutional Review Board. MRI Protocol and Imaging Reconstruction MR scans were acquired several weeks prior to the day of surgery and performed under general anesthesia in a 3 T MRI scanner (Discovery MR750 3T Narrow Bore, GE Healthcare, Milwaukee, Wisconsin). We believe this reduces the possibility of movement artifact and provides the highest fidelity images for preoperative target selection. The sequences for each patient were as follows: (a) 3-dimensional (3-D) T2WI fast spin echo, (b) axial, and (c) coronal-plane T2* weighted spoiled multi-echo gradient echo (GRE) sequence, (d) postcontrast 3-D T1WI fast spoiled GRE. Imaging parameters for each sequence can be seen in Table. QSM was reconstructed from the data acquired with the GRE sequence by using the morphology-enabled dipole inversion method.12,15,16 After all sequences were acquired and reconstructed, the images were uploaded to a stereotactic planning station (StealthStation S7, Medtronic, Dublin, Ireland). QSM was utilized as the primary MR sequence to perform direct STN targeting on this station. TABLE. Parameters Utilized For Axial, Coronal QSM and Axial T2 MRI Sequences   AX QSM  COR QSM  AX T2  Time repetition  43.8  43.8  7000  No. of echoes  12  12  1  First echo time  Min  Min  102  Flip angle  15  15  111  Bandwidth  62.5  62.5  25  Field of view  25  25  24  Matrix  256 × 256  256 × 256  384 × 256  Slice thickness (mm)  1  1  2    AX QSM  COR QSM  AX T2  Time repetition  43.8  43.8  7000  No. of echoes  12  12  1  First echo time  Min  Min  102  Flip angle  15  15  111  Bandwidth  62.5  62.5  25  Field of view  25  25  24  Matrix  256 × 256  256 × 256  384 × 256  Slice thickness (mm)  1  1  2  QSM = quantitative susceptibility mapping, AX = axial, COR = coronal View Large Stereotactic computed tomography (CT) was obtained with the headframe secured in the CT Table Fixation (Elekta; Stockholm, Sweden) at a high resolution (1 mm slice thickness, zero skip, no gantry tilt) intraoperatively. The images obtained were subsequently merged on the stereotactic planning station with the patient's preoperative MR scans. Image Analysis We utilized the sagittal T1 postcontrast images to define the anterior commissure-posterior commissure plane and electrode trajectory. We rely on the axial QSM images to adjust the x- and y-coordinates and the coronal QSM images to adjust the x- and z-coordinates and minimize the inherent inaccuracy of choosing coordinates that are coplanar to the acquisition slice. The STN was directly identified on the QSM images as an almond-shaped hyperintensity located superior to the substantial nigra at an oblique angle of approximately 50° to the midline at the coronal plane. A target point was selected such that the final position of the DBS electrode would traverse the superolateral STN and rest 2 to 2.5 mm medial to its lateral border and 2 to 2.5 mm posterior to its anterior border. The mean target coordinates (±SD) were 11.5 mm lateral (±1.2 mm), 2.9 mm posterior (±1.1 mm), and 4.5 mm inferior (±0.85) to the midcommissural point. Once the target point was selected, the trajectory of approach was carefully chosen with the 3-D contrast-enhanced T1WI to avoid traversing sulci, dural venous lakes, or intrasulcal vessels. All surgical planning was performed with the StealthStation FramelinkTM software platform (Medtronic). Intraoperative Technique After informed consent was obtained, the Leksell Coordinate Frame G (Elekta) was placed under local anesthesia in the preoperative holding area. After obtaining a high-resolution, stereotactic CT scan with the fiducial box in place, the patients were placed supine in beach chair position and moved inside the gantry of the O-arm® Surgical Imaging System (Medtronic). The Leksell coordinates were set as determined by the software-based trajectory planning and the entry point was marked on the skin. The patient was then prepped and draped in usual fashion.17 Local anesthetic (1:1 mixture of 0.25% bupivacaine and 1% lidocaine) was infiltrated into the scalp and a skin incision was made with a 10-blade scalpel. Sedation was performed using dexmedetomidine, which is rapidly reversible. A 14-mm bur hole was created with a self-arresting perforating drill. At this point, sedation was held in anticipation of the MER. We utilized a +182 mm cannula with 15 mm offset so the MER began approximately 15 mm above target. A single microelectrode was setup through the center Ben Gun hole. An intraoperative CT scan was obtained prior to the MER to project the microelectrode trajectory down to target. If electrode position had more than 1 mm radial error, we elected to make adjustments at this stage prior to the MER. The intraoperative MER was performed under the supervision of an attending movement disorder neurologist. A “satisfactory” MER run was predefined as greater than 4 mm of STN and the presence of kinesthetic responsive cells. In cases with a satisfactory MER, an intraoperative CT scan was obtained with the tip of the microelectrode at target. This scan was merged with the patient's preoperative QSM utilizing the StealthStation FramelinkTM software (Medtronic) to visualize microelectrode's position in the STN, depth, trajectory, and relationship with regional anatomic structures. In cases where the MER demonstrated less than 4-mm STN thickness or if kinesthetic-responsive units were not encountered, we also obtained an intraoperative CT scan with the tip of the microelectrode at target and would make adjustments as needed. We routinely use DBS lead model 3389 (Medtronic) for our STN-DBS cases for the greatest potential contact position within the STN. Once the DBS electrode was placed in a satisfactory position (confirmed with intraoperative CT and QSM merge), test macrostimulation and neurological exam were performed by the attending neurosurgeon and movement disorder neurologist to determine degree of therapeutic effect and map stimulation-induced side-effects. A hand-held pulse generator was utilized with starting parameters of 130 Hz frequency, 90 microsecond pulse duration with contacts 0- and 3 + through varying intensities. Test stimulation was considered satisfactory with reduction in symptomatology (tremor, rigidity) and an absence of side effects below 5 V. If the test stimulation results were satisfactory, we implanted the DBS lead at position and the lead was secured in place with Stimloc lead anchoring device (Medtronic) followed by a standard closure. DBS leads were staged 1 mo apart. All patients underwent bilateral Activa SC placement (Medtronic) 1 wk after second lead placement. Lead Placement Accuracy Lead placement accuracy was evaluated by calculating the mean radial error similar to other investigators.18 This value was defined as the intended and final lead coordinates, measured in the axial plane used for anatomical targeting. STN Thickness The thickness of STN was measured, recorded, and compared utilizing 2 techniques. The first technique was determined through standard intraoperative MER (MER method). STN thickness was derived by calculating the difference between the superior and inferior STN boundaries as determined by the intraoperative MER. The second technique utilized CT/QSM fusion on the StealthStation (Medtronic; QSM method). After the MER was completed, an intraoperative CT was obtained with the tip of the microelectrode at target and the span of the electrode on QSM imaging that was coaxial within the STN was measured and recorded. Therapeutic Evaluation The patients were followed at 3, 6, and 12 mo after the surgery. Postoperative clinical motor scores (UPDRS III) were assessed by a dedicated movement disorder neurologist at our institution. The degrees of postoperative medication reduction and programming parameters at 12 mo were obtained. Repeat neuropsychologic assessment was routinely performed at 1 yr after surgery. Statistical Analysis For all collected data, mean values along with SDs and 95% intervals were calculated utilizing MATLAB software (MathWorks Inc, Natick, Massachusetts). The required size of the patient cohort was estimated using the following relation: $$N\ = \frac{{{\sigma ^2}}}{{{D^2}}}\ {( {{Z_{\frac{\alpha }{2}}} + {Z_\beta }} )^2}$$. Here, σ is SD of within-pair difference of measurements, Zα/2 and Zβ are z-scores for type I and type II error rates, correspondingly (Zα/2 = 1.96 for 0.05 2-tailed significance level, Zβ = 0.84 for 0.8 statistical test power), and D is meaningful difference of measurements looked for in the current study. MER- and QSM-based measurements of the STN thickness were compared utilizing paired 2-tailed Student's t-test. Intraclass correlation coefficient and its 95% confidence interval (CI) were calculated to test consistency of 2 measurements. To assess agreement between 2 methods, Bland–Altman test was performed on z-score normalized data, z = (d − μ)/σ, where d is the estimation of the STN thickness, and μ and σ are the mean and SD of all measurements for a particular method (Figure 3). Transformation was necessary due to the differences in SDs of results obtained with MER and QSM. Paired 2-tailed Student's t-test was further used to determine statistical significance of differences between pre- and postsurgical levodopa dose equivalence (LEDD), as well as UPDRS III scores for (a) preoperative state OFF medication and postoperative state OFF medication/ON stimulation and (b) preoperative state ON medication and postoperative state OFF/ON stimulation medication. In all cases, a result was regarded as statistically significant if the P value was less than .05. The normality of data distribution was assessed using Kolmogorov-Smirnov test with 5% significance level and quantile–quantile plots. FIGURE 3. View largeDownload slide Bland–Altman plot of z-score for STN thickness as measured by the MER and QSM methods. The limits of agreement are denoted by dashed lines representing the mean ± 1.96 SD of the differences in scores. FIGURE 3. View largeDownload slide Bland–Altman plot of z-score for STN thickness as measured by the MER and QSM methods. The limits of agreement are denoted by dashed lines representing the mean ± 1.96 SD of the differences in scores. RESULTS The demographics of our patient population were as follows: mean age (±SD): 68 yr ± 7 (95% CI [65, 71]), median: 67, range: 51-78) and 72% were male. The mean preoperative UPDRS III score (±SD) in the OFF medication state was 42.66 ± 14.43 (95% CI [36.7, 48.6], range: 28-85). The mean UPDRS III score (±SD) in the ON medication state was 19.40 ± 12.50 (95% CI [14.2, 24.6] range: 2-43). The mean (±SD) preoperative LEDD was 1522 mg ± 715 (95% CI [1226.86, 1817.30]). As expected, paired 2-tailed t-test revealed the difference between the mean OFF and ON medication UPDRS III scores were statistically significant (P < .001); mean = 23.3, SD = 1.6, 95% CI [18.9, 27.6]. Final Target Coordinates/Mean Radial Error The mean final target coordinates of the implanted DBS lead tips (±SD) relative to the mid-commissural point were 11.4 mm lateral (±1.3 mm), 3.1 mm posterior (±1.1 mm), and 4.5 mm inferior (±1.0). The mean radial error (±SEM) was 0.54 mm ± 0.1. STN Thickness Mean STN thickness (±SD) measured with MER was 5. 3 mm ± 0.9, 95% CI [5.02, 5.50]. During intraoperative MER testing, kinesthetic responsive cells were present in 92% of patients. Eighty-six percent of patients required only 1 MER run. Similarly, the mean STN thickness (±SD) measured with QSM was 5.1 mm ± 0.4, 95% CI [4.95, 5.18]. Utilizing a paired, 2-tailed t-test, the mean thickness of STN measured between the 2 methods was not statistically significant (P = 0.125), mean difference = 0.19 mm ± 0.88, 95% CI [–0.06, 0.44], intraclass correlation coefficient (ICC) = 0.12, 95% CI [–0.16, 0.39]. Bland–Altman plot of z-scores revealed high agreement and absence of systematic bias between 2 methods (Figure 3). Clinical Outcomes (12-mo Follow-up) Patient clinical response was also determined by comparing preoperative and postoperative UPDRS III scores and quantifying the amount of Parkinson medication reduction with the LEDD score. In our patient population, the mean (±SD) ON medication/ON stimulation UPDRS III score at 12 mo was 14 ± 11, median: 14, range: 5 to 51, mean (±SD) OFF medication/ON stimulation UPDRS III score at 1 yr was 18.8 ± 12, median: 13, range: 4 to 53. Paired t-test demonstrated a statistically significant mean difference (±SD) 23.9 ± 11.4 between the preoperative OFF medication and postoperative OFF medication/ON stimulation UPDRS III scores (P < .001), 95% CI [19.2, 28.6]. There was no statistical difference between the preoperative ON and postoperative OFF medication/ON stimulation UPDRS III scores (P = .765), 95% CI [–3.62, 4.86]. L-Dopa-equivalent Daily Dosage Mean (±SD) postoperative LEDD was 891 mg ± 566, 95% CI [13.9, 23.7]. When compared to the preoperative LEDD, paired 2-tailed t-test demonstrated a statistically significant average LEDD reduction of 58% (P < .001), mean difference (±SD): 630 mg ± 620, 95% CI [374, 887]). Programming Settings The mean programming settings were as follows: left electrode (mean therapeutic amplitude = 2.71V (range = 1.0-4.1 V), mean pulse width = 67.5 μs (range = 60-150 μs), mean frequency = 139 Hz (range = 60-185); right electrode (mean therapeutic amplitude = 2.78 V [range = 1.0-4.0 V]), mean pulse width = 67.2 μs (range = 60-90 μs), mean frequency = 136 Hz (range = 60-180 Hz). In terms of electrode stimulation configuration settings: 86% were monopolar, 10% bipolar, and 4% interleaved at follow-up. Complications There were no intraoperative complications noted in this patient series. Postoperatively, 1 patient developed a symptomatic delayed unilateral chronic subdural hematoma which was treated conservatively with a 6-wk oral dexamethasone taper and serial imaging. At a 6-mo follow-up CT scan, the hematoma had resolved. Two patients developed mild erythema and tenderness of the parietal connector incisions which were treated with a 1-wk course of doxycycline and topical silver sulfadiazine for a presumed mild superficial infection. These symptoms resolved without incident. DISCUSSION This study demonstrated excellent MER concordance rates when utilizing QSM at 3 T as the primary targeting MR sequence for STN-DBS surgery. In addition to its accurate depiction of STN borders, we found QSM to be an easy-to-use MR sequence during DBS surgery. With the progressive evolution to a more image-guided approach to DBS surgery, the QSM sequence offers several unique advantages. First, we obtained a satisfactory MER run utilizing 1 electrode-1 pass in >85% of our cases utilizing the middle Ben Gun hole. This alone provides significant benefits in terms of reducing length of surgery time, degree of acquired pneumocephalus and brain shift, potential for intracerebral hemorrhage, and patient comfort. Second, this also lends support to the ongoing debate of in favor of image-guided DBS surgery. With the high MER concordance rates we achieved with QSM targeting, we anticipate this will open further avenues into performing DBS surgery under general anesthesia. Our conclusions mirror that of Polanski et al,8 in that we agree that the need for MER will likely fade as DBS surgery continues to evolve. QSM overcomes image quality issues of defining STN on traditional T2WI and SWI. On T2WI, which is traditionally used for direct targeting, the STN appears as hypointense structure (due to its high iron content) and can be difficult to distinguish from the substantia nigra and zona incerta.5,11,12 On SWI, the STN also appears as a hypointense structure, however, its spatial resolution compared to surrounding anatomic structures is better delineated (Figure 1). Clinically, SWI has been shown to perform better compared to T2WI for the purposes of STN targeting, given its improved contrast-to-noise ratio.5 However, there are disadvantages inherent to SWI that distort the borders of STN and cause it to appear larger.5,9 Compared to conventional T2WI and SWI, QSM depicts the STN as a heterogeneous, hyperintense structure relative to surrounding anatomical structures (Figures 1 and 2). The STN has varying areas of intensity depicted on QSM, which may correspond to its 3 functionally different areas: limbic, associative, and sensorimotor (tripartite model).19 QSM addresses the disadvantages of SWI by reducing blooming artifacts and providing direct quantifications of tissue iron content.5,11,20 For example, the medial and inferior STN borders appear uniformly hyperintense, while the posterior and lateral STN borders have areas of mixed intensity. Hollander et al21 proposed these areas of varying intensity in the STN on QSM are secondary to heterogeneous iron concentrations in these regions. The highest area of iron deposition may possibly correspond to the limbic STN circuit, while the lowest concentration (hypointense areas) could correspond to the sensorimotor area.21,22 We typically utilize this transition area defined by QSM (hyperintense to hypointense) as our STN target point (Figure 2), which may correspond with the anatomical sensorimotor region. A recent study by Polanski and colleagues8 examined and compared the accuracies of T2, FLAIR, and SWI imaging at 3 T for STN targeting. In this study, the degree of intraoperative MER concordance was compared in 21 patients who underwent bilateral STN-DBS electrode placement. Of note, the authors performed 182 MERs, which means the average patient underwent approximately 8 MERs. The results of their study demonstrated the highest rate of MER concordance using SWI for direct STN targeting (86% positive predictive value vs T2 [65.5%] and FLAIR [77.6%]). In addition, the center Ben Gun hole demonstrated a 39.4% positive MER concordance. As the risk of intraoperative hemorrhage is directly proportional to the number of MER passes, purely image-guided DBS has become a topic of great interest among functional neurosurgeons.23 Although other investigators have published excellent clinical results utilizing various different MR sequences, we believe QSM’s inherent ability to depict the STN in a manner that is both accurate and easy to interpret, could potentially minimize the total number of MER passes that are required. In our study, we performed a total of 57 MER passes (50 electrodes) for a >85% concordance rate with the center Ben Gun hole. This observed concordance rate is generally within the range of other investigators8,24,25; however, we believe a combination of synergistic intraoperative factors including headframe application error, brain shift due to pneumocephalus, and small imaging distortions on CT/MR fusion led to the few instances of suboptimal MER. As mentioned previously, in cases where we observed a suboptimal MER, an intraoperative CT was obtained and merged with the patient's preoperative QSM. What we found was that in all of cases of a suboptimal MER, the tip of the microelectrode was not in an ideal location (>1 mm from target). Adjustments to the lead position were made as necessary until a satisfactory MER was observed. At this point, an additional intraoperative CT scan was obtained to evaluate microelectrode tip position. In every case where we obtained a satisfactory MER after an adjustment, the CT/QSM merge demonstrated a satisfactory tip position in the STN. This finding is worth noting because it suggests that direct targeting with QSM alone (rather than in tandem with MER) may be sufficient for DBS lead placement. This movement towards purely image-guided DBS surgery has been enhanced with promising studies demonstrating the successful use of intraoperative MRI and electrode placement under general anesthesia.18,24,25 However, given the significant economic challenges brought forth with MR-guided DBS surgery, a reasonable and attractive option is the utilization of intraoperative CT/MR fusion. However, both approaches require an MR sequence that is both reliable and easy-to-use. With our experience utilizing the QSM sequence for direct targeting, we have found that it accurately represents STN and has correlation with MER. The mean final coordinates were within acceptable range to our predetermined target coordinates. In addition, our mean radial error fell within the acceptable range as shown by other investigators.18,26 We attribute discrepancies in these values due to several factors: intraoperative brain shift from pneumocephalus, technical errors inherent to head frame placement and construction, and inaccuracies intrinsic to CT/MR merging for direct targeting. These factors are always present to some degree and generally unavoidable in any type of DBS surgery. Of particular note, our results validate those seen by other authors in that subcortical brain shift from pneumocephalus, although present to varying degrees, did not appear to adversely affect our clinical outcomes and therefore, did not appear to be clinically significant.27 Limitations There are a number of limitations to this study that should be addressed. This was a single-center study with all surgeries performed by 1 surgeon with experience utilizing QSM. It is unclear if the accuracy of electrode placement would be different if used by a different surgeon. For centers that perform an MRI the morning of surgery once the stereotactic headframe is placed, there is additional time that is required for running and postprocessing the QSM sequence. Our comparison of STN thickness between the QSM and MER methods is also subject to observer bias, as we were not blinded to the results of the measurements. We believe, however, that even with this bias present, our satisfactory clinical results demonstrate the effectiveness of QSM-guided DBS. Therefore, small discrepancies between the actual values of these measurements may not be clinically relevant. In addition, as there was no control group (T2WI), we cannot definitively state if QSM more accurate than T2WI. We believe that further analysis and later studies with more patients at other institutions will be able to address these shortcomings. CONCLUSION Direct targeting of the sensorimotor STN with QSM shows that MER correlation can be safely and easily used for DBS lead placement with satisfactory clinical response. These results imply that targeting based on QSM signaling alone is sufficient to obtain reliable and reproducible outcomes in the absence of physiological recordings. Further studies with other potential PD targets such as GPi and caudal zona incerta are warranted and merit further investigation. Disclosure The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article. Notes Portions of the methodology and results of this manuscript were presented in electronic poster format by our study investigators at the 19th Annual North American Neuromodulation Society Meeting on December 12, 2015 in Las Vegas, Nevada. REFERENCES 1. Benabid AL, Krack PP, Benazzouz A, Limousin P, Koudsie A, Pollak P. 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An assessment of current brain targets for deep brain stimulation surgery with susceptibility-weighted imaging at 7 tesla. Neurosurgery . 2010; 67( 6): 1745- 1756; discussion 1756. Google Scholar CrossRef Search ADS PubMed  11. Liu T, Eskreis-Winkler S, Schweitzer AD et al.   Improved subthalamic nucleus depiction with quantitative susceptibility mapping. Radiology . 2013; 269( 1): 216- 223. Google Scholar CrossRef Search ADS PubMed  12. Wang Y, Liu T. Quantitative suceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker. Magn Reson Med . 2015; 73( 1): 82- 101. Google Scholar CrossRef Search ADS PubMed  13. Patil PG, Conrad EC, Aldridge JW, Chenevert TL, Chou KL. The anatomical and electrophysiological subthalamic nucleus visualized by 3-T magnetic resonance imaging. Neurosurgery . 2012; 71( 6): 1089- 1095 Google Scholar CrossRef Search ADS PubMed  14. Zonenshayn M, Rezai AR, Mogilner AY, Beric A, Sterio D, Kelly PJ. Comparison of anatomic and neurophysiological methods for subthalamic nucleus targeting. Neurosurgery . 2000; 47( 2): 282- 292 Google Scholar CrossRef Search ADS PubMed  15. Liu J, Liu T, de Rochefort L et al.   Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map. Neuroimage . 2012; 59( 3): 2560- 2568. Google Scholar CrossRef Search ADS PubMed  16. de Rochefort L, Liu T, Kressler B et al.   Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: validation and application to brain imaging. Magn Reson Med . 2010; 63( 1): 194- 206. Google Scholar PubMed  17. Machado A, Rezai AR, Kopell BH, Gross RE, Sharan AD, Benabid AL. Deep brain stimulation for Parkinson's disease: surgical technique and perioperative management. Mov Disord . 2006; 21( suppl 14): S247- S258. Google Scholar CrossRef Search ADS PubMed  18. Starr PA, Markun LC, Larson PS et al.   Interventional MRI-guided deep brain stimulation in pediatric dystonia: first experience with the ClearPoint system. J Neurosurg Pediatr . 2014; 14( 4): 400- 408. Google Scholar CrossRef Search ADS PubMed  19. Alexander GE, Crutcher MD. Functional architecture of basal ganglia circuits: neural substrates of parallel processing. Trends Neurosci . 1990; 13( 7): 266- 271. Google Scholar CrossRef Search ADS PubMed  20. Brunenberg EJ, Platel B, Hofman PA, Ter Haar Romeny BM, Visser-Vandewalle V. Magnetic resonance imaging techniques for visualization of the subthalamic nucleus. J Neurosurg . 2011; 115( 5): 971- 984. Google Scholar CrossRef Search ADS PubMed  21. de Hollander G, Keuken MC, Bazin PL et al.   A gradual increase of iron toward the medial-inferior tip of the subthalamic nucleus. Hum Brain Mapp . 2014; 35( 9): 4440- 4449. Google Scholar CrossRef Search ADS PubMed  22. Dormont D, Ricciardi KG, Tande D et al.   Is the subthalamic nucleus hypointense on T2-weighted images? A correlation study using MR imaging and stereotactic atlas data. AJNR . 2004; 25( 9): 1516- 1523. Google Scholar PubMed  23. Zrinzo L, Foltynie T, Limousin P, Hariz MI. Reducing hemorrhagic complications in functional neurosurgery: a large case series and systematic literature review. J Neurosurg . 2012; 116( 1): 84- 94. Google Scholar CrossRef Search ADS PubMed  24. Harries AM, Kausar J, Robterts SA et al.   Deep brain stimulation of the subthalamic nucleus for advanced Parkinson disease using general anesthesia: long-term results. J Neurosurg . 2012; 116: 107- 113. Google Scholar CrossRef Search ADS PubMed  25. Burchiel KJ, McCartney S, Lee A, Raslan AM. Accuracy of deep brain stimulation electrode placement using intraoperative computed tomography without microelectrode recording. J Neurosurg . 2013; 119( 2): 301- 306 Google Scholar CrossRef Search ADS PubMed  26. Larson PS, Starr PA, Bates G, Tansey L, Richardson RM, Martin AJ. An optimized system for interventional magnetic resonance imaging-guided stereotactic surgery: preliminary evaluation of targeting accuracy. Neurosurgery . 2012. 70( 1 Suppl Operative): 95- 103. Google Scholar PubMed  27. Petersen EA, Holl EM, Martinez-Torres I et al.   Minimizing brain shift in stereotactic functional neurosurgery. Neurosurgery . 2010; 67( 3 Suppl Operative): 213- 221. Acknowledgment The authors would like to thank Hannah Silk for her technical help and support in the writing of this manuscript. Copyright © 2017 by the Congress of Neurological Surgeons http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Operative Neurosurgery Oxford University Press

Utilization of Quantitative Susceptibility Mapping for Direct Targeting of the Subthalamic Nucleus During Deep Brain Stimulation Surgery

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Copyright © 2017 by the Congress of Neurological Surgeons
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2332-4252
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2332-4260
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10.1093/ons/opx131
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Abstract

Abstract BACKGROUND Deep brain stimulation of the subthalamic nucleus (STN) has demonstrated efficacy in improving motor disability in Parkinson's disease. The recently developed quantitative susceptibility mapping (QSM) technique, which can accurately map iron deposits in deep brain nuclei, promises precise targeting of the STN. OBJECTIVE To demonstrate the use of QSM to target STN effectively by correlating with classical physiological-based targeting measures in a prospective study. METHODS The precision and accuracy of direct targeting with QSM was examined in a total of 25 Parkinson's disease patients between 2013 and 2015 at our institution. QSM was utilized as the primary magnetic resonance imaging (MRI) method to perform direct STN targeting on a stereotactic planning station utilizing computed tomography/MR fusion. Intraoperative microelectrode recordings (MER) were obtained to confirm appropriate trajectory through the sensorimotor STN. RESULTS Estimations of STN thickness between the MER and QSM methods appeared to be correlated. Mean STN thickness was 5.3 mm. Kinesthetic responsive cells were found in > 90% of electrode runs. The mean radial error (±SEM) was 0.54 ± 0.1 mm. Satisfactory clinical response as determined by Unified Parkinson's Disease Rating Scale (UPDRS III) was seen at 12 mo after surgery. CONCLUSION Direct targeting of the sensorimotor STN using QSM demonstrates MER correlation and can be safely used for deep brain stimulation lead placement with satisfactory clinical response. These results imply that targeting based on QSM signaling alone is sufficient to obtain reliable and reproducible outcomes in the absence of physiological recordings. DBS, Deep brain stimulation, Parkinson disease, Quantitative susceptibility mapping, QSM ABBREVIATIONS ABBREVIATIONS 3-D 3-dimensional CI confidence interval CT computed tomography DBS deep brain stimulation FLAIR fluid-attenuated inversion recovery GPi globus pallidus pars interna GRE gradient echo MER microelectrode recordings MRI magnetic resonance imaging PD Parkinson disease QSM quantitative susceptibility mapping SD standard deviation STN subthalamic nucleus SWI susceptibility-weighted phase imaging T2WI T2-weighted imaging UPDRS Unified Parkinson's Disease Rating Scale Parkinson disease (PD) is a progressive neurodegenerative disorder associated with the death of dopamine-producing cells in the substantia nigra. Despite significant advances in the pharmacologic management of PD, a substantial number of these patients are considered refractory to standard medical therapies. In these cases, the current treatment of choice is the implantation of deep brain stimulation (DBS) electrodes into the subthalamic nucleus (STN) or globus pallidus pars interna (GPi).1,2 Chronic stimulation of the STN has been demonstrated to effectively treat a spectrum of motor symptoms of advanced PD symptoms, namely: tremor, rigidity, bradykinesia, motor fluctuations, and drug-induced dyskinesias.1,3 Historically, targeting of the STN was performed indirectly based on coordinates obtained from brain atlases, because imaging available at the time could not adequately characterize basal ganglia targets. Novel high-resolution magnetic resonance imaging (MRI) techniques have allowed for the direct targeting of the STN, thus beginning to create a paradigm shift in DBS. In practice, DBS surgeons perform most direct targeting through the utilization of conventional T2-weighted imaging (T2WI) with field strengths ranging between 1.5 and 3 T. Accurate targeting of the sensorimotor STN has been shown to improve quality of life and motor disability in Parkinson patients.2,4 Precise targeting of the STN is essential for maximizing the therapeutic benefits and minimizing potential deleterious side effects of DBS therapy. Despite advances in the spatial resolution of MRI, direct targeting of the STN remains a challenge primarily due to variations in STN anatomy and limitations inherent in conventional MRI.5 In order to overcome these challenges, investigators have described the use of other MRI techniques such as spoiled gradient-recalled echo,6 fluid-attenuated inversion recovery (FLAIR),7 and susceptibility-weighted phase imaging (SWI).8 Although these techniques or sequences provide better delineation of STN borders compared to T2WI, DBS surgeons have been slow to adopt these sequences into regular practice, primarily because these sequences can be difficult to interpret and their accuracy in characterizing STN borders has been questioned.5,8 Recently, there has been renewed interest in utilizing FLAIR and SWI-MRI sequences for STN targeting.5,8 Glutamatergic neurons in the STN contain high levels of iron relative to the surrounding thalamic neurons, which allows better visualization on iron-sensitive MRI sequences.9 However, the accuracy of these sequences in characterizing STN borders has been called into doubt, primarily because they rely on iron paramagnetic susceptibility artifacts which can affect spatial anatomy.5,10 Quantitative susceptibility mapping (QSM) is a novel MRI technique that accurately depicts brain iron by removing the magnetic susceptibility artifacts in MRI and revealing the magnetic susceptibility source5,11,12 (Figure 1). Since deep brain nuclei contain high concentrations of iron associated with their dopamine and glutamate metabolism, there has been growing interest in utilizing QSM for STN targeting in DBS surgery.5,11 For visualizing the STN where the principal type of neurons is glutamatergic and iron-containing, QSM provides the benefits of accurate iron/neuron maps and susceptibility artifact removal, compared to other MRI techniques such as SWI5,11,12 (Figure 2). In this manuscript, we describe the precise and accurate targeting of the STN using QSM. We have found that QSM accurately depicts the sensorimotor STN, strongly correlates with traditional STN microelectrode recordings (MER), and can be safely and easily used for DBS lead placement with satisfactory clinical response. FIGURE 1. View largeDownload slide Example of STN visualization with conventional T2 A, SWI B, and QSM C in the coronal plane (3 T MRI). FIGURE 1. View largeDownload slide Example of STN visualization with conventional T2 A, SWI B, and QSM C in the coronal plane (3 T MRI). FIGURE 2. View largeDownload slide The STN and surrounding anatomic structures as seen on QSM A axial B coronal C sagittal images at 3 T. Final target coordinates (red dot) are selected based on dedicated axial and coronal QSM images. FIGURE 2. View largeDownload slide The STN and surrounding anatomic structures as seen on QSM A axial B coronal C sagittal images at 3 T. Final target coordinates (red dot) are selected based on dedicated axial and coronal QSM images. METHODS Between the years 2013 and 2015, a total of 122 patients with medically refractory, idiopathic PD underwent staged QSM-guided STN-DBS implantations by the senior author. From this pool of patients, a smaller cohort of 25 patients was then randomly selected from a list containing only the medical record numbers for each patient for the purposes of this study. The patients that were selected were kept blinded to the senior author. A sample size of 25 patients (50 STNs in total) was selected to have 80% power to detect a difference of 0.5 mm (half of voxel size in QSM acquisition matrix) between MER- and QSM-based measurements of STN thickness using a paired t-test with a 0.05 2-tailed significance level. Population standard deviation (SD) of STN thickness was assumed to be 1 mm according to previously reported studies.13,14 Patients were deemed appropriate candidates for STN-DBS surgery if they fulfilled the following criteria: diagnosis of medically refractory, idiopathic PD (UK PD Society Brain Bank Criteria) with >30% improvement on the Unified Parkinson's Disease Rating Scale (UPDRS): motor subscale (UPDRS III) during ON/OFF testing with levodopa, satisfactory neuropsychiatric evaluation, absence of significant vascular or structural abnormalities on brain MRI, and no significant medical comorbidities. Indications for STN-DBS surgery included refractory motor fluctuations, medically refractory tremor, and drug-induced dyskinesias. Exclusion criteria were patients with poor response to levodopa challenge, PD < 5 yr, patients with pre-existing DBS electrodes who presented for revision, or abnormal neuropsychiatric evaluation. Neuropsychological evaluation consisted of a 1-h, personalized assessment performed by a licensed neuropsychologist at our institution. A total of 50 DBS electrodes and 57 MERs were included in analysis. ON/OFF motor testing was performed under the supervision of a movement disorder neurologist prior to surgery. All patients included in this study consented to utilize their patient-specific information as approved by our Institutional Review Board. MRI Protocol and Imaging Reconstruction MR scans were acquired several weeks prior to the day of surgery and performed under general anesthesia in a 3 T MRI scanner (Discovery MR750 3T Narrow Bore, GE Healthcare, Milwaukee, Wisconsin). We believe this reduces the possibility of movement artifact and provides the highest fidelity images for preoperative target selection. The sequences for each patient were as follows: (a) 3-dimensional (3-D) T2WI fast spin echo, (b) axial, and (c) coronal-plane T2* weighted spoiled multi-echo gradient echo (GRE) sequence, (d) postcontrast 3-D T1WI fast spoiled GRE. Imaging parameters for each sequence can be seen in Table. QSM was reconstructed from the data acquired with the GRE sequence by using the morphology-enabled dipole inversion method.12,15,16 After all sequences were acquired and reconstructed, the images were uploaded to a stereotactic planning station (StealthStation S7, Medtronic, Dublin, Ireland). QSM was utilized as the primary MR sequence to perform direct STN targeting on this station. TABLE. Parameters Utilized For Axial, Coronal QSM and Axial T2 MRI Sequences   AX QSM  COR QSM  AX T2  Time repetition  43.8  43.8  7000  No. of echoes  12  12  1  First echo time  Min  Min  102  Flip angle  15  15  111  Bandwidth  62.5  62.5  25  Field of view  25  25  24  Matrix  256 × 256  256 × 256  384 × 256  Slice thickness (mm)  1  1  2    AX QSM  COR QSM  AX T2  Time repetition  43.8  43.8  7000  No. of echoes  12  12  1  First echo time  Min  Min  102  Flip angle  15  15  111  Bandwidth  62.5  62.5  25  Field of view  25  25  24  Matrix  256 × 256  256 × 256  384 × 256  Slice thickness (mm)  1  1  2  QSM = quantitative susceptibility mapping, AX = axial, COR = coronal View Large Stereotactic computed tomography (CT) was obtained with the headframe secured in the CT Table Fixation (Elekta; Stockholm, Sweden) at a high resolution (1 mm slice thickness, zero skip, no gantry tilt) intraoperatively. The images obtained were subsequently merged on the stereotactic planning station with the patient's preoperative MR scans. Image Analysis We utilized the sagittal T1 postcontrast images to define the anterior commissure-posterior commissure plane and electrode trajectory. We rely on the axial QSM images to adjust the x- and y-coordinates and the coronal QSM images to adjust the x- and z-coordinates and minimize the inherent inaccuracy of choosing coordinates that are coplanar to the acquisition slice. The STN was directly identified on the QSM images as an almond-shaped hyperintensity located superior to the substantial nigra at an oblique angle of approximately 50° to the midline at the coronal plane. A target point was selected such that the final position of the DBS electrode would traverse the superolateral STN and rest 2 to 2.5 mm medial to its lateral border and 2 to 2.5 mm posterior to its anterior border. The mean target coordinates (±SD) were 11.5 mm lateral (±1.2 mm), 2.9 mm posterior (±1.1 mm), and 4.5 mm inferior (±0.85) to the midcommissural point. Once the target point was selected, the trajectory of approach was carefully chosen with the 3-D contrast-enhanced T1WI to avoid traversing sulci, dural venous lakes, or intrasulcal vessels. All surgical planning was performed with the StealthStation FramelinkTM software platform (Medtronic). Intraoperative Technique After informed consent was obtained, the Leksell Coordinate Frame G (Elekta) was placed under local anesthesia in the preoperative holding area. After obtaining a high-resolution, stereotactic CT scan with the fiducial box in place, the patients were placed supine in beach chair position and moved inside the gantry of the O-arm® Surgical Imaging System (Medtronic). The Leksell coordinates were set as determined by the software-based trajectory planning and the entry point was marked on the skin. The patient was then prepped and draped in usual fashion.17 Local anesthetic (1:1 mixture of 0.25% bupivacaine and 1% lidocaine) was infiltrated into the scalp and a skin incision was made with a 10-blade scalpel. Sedation was performed using dexmedetomidine, which is rapidly reversible. A 14-mm bur hole was created with a self-arresting perforating drill. At this point, sedation was held in anticipation of the MER. We utilized a +182 mm cannula with 15 mm offset so the MER began approximately 15 mm above target. A single microelectrode was setup through the center Ben Gun hole. An intraoperative CT scan was obtained prior to the MER to project the microelectrode trajectory down to target. If electrode position had more than 1 mm radial error, we elected to make adjustments at this stage prior to the MER. The intraoperative MER was performed under the supervision of an attending movement disorder neurologist. A “satisfactory” MER run was predefined as greater than 4 mm of STN and the presence of kinesthetic responsive cells. In cases with a satisfactory MER, an intraoperative CT scan was obtained with the tip of the microelectrode at target. This scan was merged with the patient's preoperative QSM utilizing the StealthStation FramelinkTM software (Medtronic) to visualize microelectrode's position in the STN, depth, trajectory, and relationship with regional anatomic structures. In cases where the MER demonstrated less than 4-mm STN thickness or if kinesthetic-responsive units were not encountered, we also obtained an intraoperative CT scan with the tip of the microelectrode at target and would make adjustments as needed. We routinely use DBS lead model 3389 (Medtronic) for our STN-DBS cases for the greatest potential contact position within the STN. Once the DBS electrode was placed in a satisfactory position (confirmed with intraoperative CT and QSM merge), test macrostimulation and neurological exam were performed by the attending neurosurgeon and movement disorder neurologist to determine degree of therapeutic effect and map stimulation-induced side-effects. A hand-held pulse generator was utilized with starting parameters of 130 Hz frequency, 90 microsecond pulse duration with contacts 0- and 3 + through varying intensities. Test stimulation was considered satisfactory with reduction in symptomatology (tremor, rigidity) and an absence of side effects below 5 V. If the test stimulation results were satisfactory, we implanted the DBS lead at position and the lead was secured in place with Stimloc lead anchoring device (Medtronic) followed by a standard closure. DBS leads were staged 1 mo apart. All patients underwent bilateral Activa SC placement (Medtronic) 1 wk after second lead placement. Lead Placement Accuracy Lead placement accuracy was evaluated by calculating the mean radial error similar to other investigators.18 This value was defined as the intended and final lead coordinates, measured in the axial plane used for anatomical targeting. STN Thickness The thickness of STN was measured, recorded, and compared utilizing 2 techniques. The first technique was determined through standard intraoperative MER (MER method). STN thickness was derived by calculating the difference between the superior and inferior STN boundaries as determined by the intraoperative MER. The second technique utilized CT/QSM fusion on the StealthStation (Medtronic; QSM method). After the MER was completed, an intraoperative CT was obtained with the tip of the microelectrode at target and the span of the electrode on QSM imaging that was coaxial within the STN was measured and recorded. Therapeutic Evaluation The patients were followed at 3, 6, and 12 mo after the surgery. Postoperative clinical motor scores (UPDRS III) were assessed by a dedicated movement disorder neurologist at our institution. The degrees of postoperative medication reduction and programming parameters at 12 mo were obtained. Repeat neuropsychologic assessment was routinely performed at 1 yr after surgery. Statistical Analysis For all collected data, mean values along with SDs and 95% intervals were calculated utilizing MATLAB software (MathWorks Inc, Natick, Massachusetts). The required size of the patient cohort was estimated using the following relation: $$N\ = \frac{{{\sigma ^2}}}{{{D^2}}}\ {( {{Z_{\frac{\alpha }{2}}} + {Z_\beta }} )^2}$$. Here, σ is SD of within-pair difference of measurements, Zα/2 and Zβ are z-scores for type I and type II error rates, correspondingly (Zα/2 = 1.96 for 0.05 2-tailed significance level, Zβ = 0.84 for 0.8 statistical test power), and D is meaningful difference of measurements looked for in the current study. MER- and QSM-based measurements of the STN thickness were compared utilizing paired 2-tailed Student's t-test. Intraclass correlation coefficient and its 95% confidence interval (CI) were calculated to test consistency of 2 measurements. To assess agreement between 2 methods, Bland–Altman test was performed on z-score normalized data, z = (d − μ)/σ, where d is the estimation of the STN thickness, and μ and σ are the mean and SD of all measurements for a particular method (Figure 3). Transformation was necessary due to the differences in SDs of results obtained with MER and QSM. Paired 2-tailed Student's t-test was further used to determine statistical significance of differences between pre- and postsurgical levodopa dose equivalence (LEDD), as well as UPDRS III scores for (a) preoperative state OFF medication and postoperative state OFF medication/ON stimulation and (b) preoperative state ON medication and postoperative state OFF/ON stimulation medication. In all cases, a result was regarded as statistically significant if the P value was less than .05. The normality of data distribution was assessed using Kolmogorov-Smirnov test with 5% significance level and quantile–quantile plots. FIGURE 3. View largeDownload slide Bland–Altman plot of z-score for STN thickness as measured by the MER and QSM methods. The limits of agreement are denoted by dashed lines representing the mean ± 1.96 SD of the differences in scores. FIGURE 3. View largeDownload slide Bland–Altman plot of z-score for STN thickness as measured by the MER and QSM methods. The limits of agreement are denoted by dashed lines representing the mean ± 1.96 SD of the differences in scores. RESULTS The demographics of our patient population were as follows: mean age (±SD): 68 yr ± 7 (95% CI [65, 71]), median: 67, range: 51-78) and 72% were male. The mean preoperative UPDRS III score (±SD) in the OFF medication state was 42.66 ± 14.43 (95% CI [36.7, 48.6], range: 28-85). The mean UPDRS III score (±SD) in the ON medication state was 19.40 ± 12.50 (95% CI [14.2, 24.6] range: 2-43). The mean (±SD) preoperative LEDD was 1522 mg ± 715 (95% CI [1226.86, 1817.30]). As expected, paired 2-tailed t-test revealed the difference between the mean OFF and ON medication UPDRS III scores were statistically significant (P < .001); mean = 23.3, SD = 1.6, 95% CI [18.9, 27.6]. Final Target Coordinates/Mean Radial Error The mean final target coordinates of the implanted DBS lead tips (±SD) relative to the mid-commissural point were 11.4 mm lateral (±1.3 mm), 3.1 mm posterior (±1.1 mm), and 4.5 mm inferior (±1.0). The mean radial error (±SEM) was 0.54 mm ± 0.1. STN Thickness Mean STN thickness (±SD) measured with MER was 5. 3 mm ± 0.9, 95% CI [5.02, 5.50]. During intraoperative MER testing, kinesthetic responsive cells were present in 92% of patients. Eighty-six percent of patients required only 1 MER run. Similarly, the mean STN thickness (±SD) measured with QSM was 5.1 mm ± 0.4, 95% CI [4.95, 5.18]. Utilizing a paired, 2-tailed t-test, the mean thickness of STN measured between the 2 methods was not statistically significant (P = 0.125), mean difference = 0.19 mm ± 0.88, 95% CI [–0.06, 0.44], intraclass correlation coefficient (ICC) = 0.12, 95% CI [–0.16, 0.39]. Bland–Altman plot of z-scores revealed high agreement and absence of systematic bias between 2 methods (Figure 3). Clinical Outcomes (12-mo Follow-up) Patient clinical response was also determined by comparing preoperative and postoperative UPDRS III scores and quantifying the amount of Parkinson medication reduction with the LEDD score. In our patient population, the mean (±SD) ON medication/ON stimulation UPDRS III score at 12 mo was 14 ± 11, median: 14, range: 5 to 51, mean (±SD) OFF medication/ON stimulation UPDRS III score at 1 yr was 18.8 ± 12, median: 13, range: 4 to 53. Paired t-test demonstrated a statistically significant mean difference (±SD) 23.9 ± 11.4 between the preoperative OFF medication and postoperative OFF medication/ON stimulation UPDRS III scores (P < .001), 95% CI [19.2, 28.6]. There was no statistical difference between the preoperative ON and postoperative OFF medication/ON stimulation UPDRS III scores (P = .765), 95% CI [–3.62, 4.86]. L-Dopa-equivalent Daily Dosage Mean (±SD) postoperative LEDD was 891 mg ± 566, 95% CI [13.9, 23.7]. When compared to the preoperative LEDD, paired 2-tailed t-test demonstrated a statistically significant average LEDD reduction of 58% (P < .001), mean difference (±SD): 630 mg ± 620, 95% CI [374, 887]). Programming Settings The mean programming settings were as follows: left electrode (mean therapeutic amplitude = 2.71V (range = 1.0-4.1 V), mean pulse width = 67.5 μs (range = 60-150 μs), mean frequency = 139 Hz (range = 60-185); right electrode (mean therapeutic amplitude = 2.78 V [range = 1.0-4.0 V]), mean pulse width = 67.2 μs (range = 60-90 μs), mean frequency = 136 Hz (range = 60-180 Hz). In terms of electrode stimulation configuration settings: 86% were monopolar, 10% bipolar, and 4% interleaved at follow-up. Complications There were no intraoperative complications noted in this patient series. Postoperatively, 1 patient developed a symptomatic delayed unilateral chronic subdural hematoma which was treated conservatively with a 6-wk oral dexamethasone taper and serial imaging. At a 6-mo follow-up CT scan, the hematoma had resolved. Two patients developed mild erythema and tenderness of the parietal connector incisions which were treated with a 1-wk course of doxycycline and topical silver sulfadiazine for a presumed mild superficial infection. These symptoms resolved without incident. DISCUSSION This study demonstrated excellent MER concordance rates when utilizing QSM at 3 T as the primary targeting MR sequence for STN-DBS surgery. In addition to its accurate depiction of STN borders, we found QSM to be an easy-to-use MR sequence during DBS surgery. With the progressive evolution to a more image-guided approach to DBS surgery, the QSM sequence offers several unique advantages. First, we obtained a satisfactory MER run utilizing 1 electrode-1 pass in >85% of our cases utilizing the middle Ben Gun hole. This alone provides significant benefits in terms of reducing length of surgery time, degree of acquired pneumocephalus and brain shift, potential for intracerebral hemorrhage, and patient comfort. Second, this also lends support to the ongoing debate of in favor of image-guided DBS surgery. With the high MER concordance rates we achieved with QSM targeting, we anticipate this will open further avenues into performing DBS surgery under general anesthesia. Our conclusions mirror that of Polanski et al,8 in that we agree that the need for MER will likely fade as DBS surgery continues to evolve. QSM overcomes image quality issues of defining STN on traditional T2WI and SWI. On T2WI, which is traditionally used for direct targeting, the STN appears as hypointense structure (due to its high iron content) and can be difficult to distinguish from the substantia nigra and zona incerta.5,11,12 On SWI, the STN also appears as a hypointense structure, however, its spatial resolution compared to surrounding anatomic structures is better delineated (Figure 1). Clinically, SWI has been shown to perform better compared to T2WI for the purposes of STN targeting, given its improved contrast-to-noise ratio.5 However, there are disadvantages inherent to SWI that distort the borders of STN and cause it to appear larger.5,9 Compared to conventional T2WI and SWI, QSM depicts the STN as a heterogeneous, hyperintense structure relative to surrounding anatomical structures (Figures 1 and 2). The STN has varying areas of intensity depicted on QSM, which may correspond to its 3 functionally different areas: limbic, associative, and sensorimotor (tripartite model).19 QSM addresses the disadvantages of SWI by reducing blooming artifacts and providing direct quantifications of tissue iron content.5,11,20 For example, the medial and inferior STN borders appear uniformly hyperintense, while the posterior and lateral STN borders have areas of mixed intensity. Hollander et al21 proposed these areas of varying intensity in the STN on QSM are secondary to heterogeneous iron concentrations in these regions. The highest area of iron deposition may possibly correspond to the limbic STN circuit, while the lowest concentration (hypointense areas) could correspond to the sensorimotor area.21,22 We typically utilize this transition area defined by QSM (hyperintense to hypointense) as our STN target point (Figure 2), which may correspond with the anatomical sensorimotor region. A recent study by Polanski and colleagues8 examined and compared the accuracies of T2, FLAIR, and SWI imaging at 3 T for STN targeting. In this study, the degree of intraoperative MER concordance was compared in 21 patients who underwent bilateral STN-DBS electrode placement. Of note, the authors performed 182 MERs, which means the average patient underwent approximately 8 MERs. The results of their study demonstrated the highest rate of MER concordance using SWI for direct STN targeting (86% positive predictive value vs T2 [65.5%] and FLAIR [77.6%]). In addition, the center Ben Gun hole demonstrated a 39.4% positive MER concordance. As the risk of intraoperative hemorrhage is directly proportional to the number of MER passes, purely image-guided DBS has become a topic of great interest among functional neurosurgeons.23 Although other investigators have published excellent clinical results utilizing various different MR sequences, we believe QSM’s inherent ability to depict the STN in a manner that is both accurate and easy to interpret, could potentially minimize the total number of MER passes that are required. In our study, we performed a total of 57 MER passes (50 electrodes) for a >85% concordance rate with the center Ben Gun hole. This observed concordance rate is generally within the range of other investigators8,24,25; however, we believe a combination of synergistic intraoperative factors including headframe application error, brain shift due to pneumocephalus, and small imaging distortions on CT/MR fusion led to the few instances of suboptimal MER. As mentioned previously, in cases where we observed a suboptimal MER, an intraoperative CT was obtained and merged with the patient's preoperative QSM. What we found was that in all of cases of a suboptimal MER, the tip of the microelectrode was not in an ideal location (>1 mm from target). Adjustments to the lead position were made as necessary until a satisfactory MER was observed. At this point, an additional intraoperative CT scan was obtained to evaluate microelectrode tip position. In every case where we obtained a satisfactory MER after an adjustment, the CT/QSM merge demonstrated a satisfactory tip position in the STN. This finding is worth noting because it suggests that direct targeting with QSM alone (rather than in tandem with MER) may be sufficient for DBS lead placement. This movement towards purely image-guided DBS surgery has been enhanced with promising studies demonstrating the successful use of intraoperative MRI and electrode placement under general anesthesia.18,24,25 However, given the significant economic challenges brought forth with MR-guided DBS surgery, a reasonable and attractive option is the utilization of intraoperative CT/MR fusion. However, both approaches require an MR sequence that is both reliable and easy-to-use. With our experience utilizing the QSM sequence for direct targeting, we have found that it accurately represents STN and has correlation with MER. The mean final coordinates were within acceptable range to our predetermined target coordinates. In addition, our mean radial error fell within the acceptable range as shown by other investigators.18,26 We attribute discrepancies in these values due to several factors: intraoperative brain shift from pneumocephalus, technical errors inherent to head frame placement and construction, and inaccuracies intrinsic to CT/MR merging for direct targeting. These factors are always present to some degree and generally unavoidable in any type of DBS surgery. Of particular note, our results validate those seen by other authors in that subcortical brain shift from pneumocephalus, although present to varying degrees, did not appear to adversely affect our clinical outcomes and therefore, did not appear to be clinically significant.27 Limitations There are a number of limitations to this study that should be addressed. This was a single-center study with all surgeries performed by 1 surgeon with experience utilizing QSM. It is unclear if the accuracy of electrode placement would be different if used by a different surgeon. For centers that perform an MRI the morning of surgery once the stereotactic headframe is placed, there is additional time that is required for running and postprocessing the QSM sequence. Our comparison of STN thickness between the QSM and MER methods is also subject to observer bias, as we were not blinded to the results of the measurements. We believe, however, that even with this bias present, our satisfactory clinical results demonstrate the effectiveness of QSM-guided DBS. Therefore, small discrepancies between the actual values of these measurements may not be clinically relevant. In addition, as there was no control group (T2WI), we cannot definitively state if QSM more accurate than T2WI. We believe that further analysis and later studies with more patients at other institutions will be able to address these shortcomings. CONCLUSION Direct targeting of the sensorimotor STN with QSM shows that MER correlation can be safely and easily used for DBS lead placement with satisfactory clinical response. These results imply that targeting based on QSM signaling alone is sufficient to obtain reliable and reproducible outcomes in the absence of physiological recordings. Further studies with other potential PD targets such as GPi and caudal zona incerta are warranted and merit further investigation. Disclosure The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article. Notes Portions of the methodology and results of this manuscript were presented in electronic poster format by our study investigators at the 19th Annual North American Neuromodulation Society Meeting on December 12, 2015 in Las Vegas, Nevada. REFERENCES 1. Benabid AL, Krack PP, Benazzouz A, Limousin P, Koudsie A, Pollak P. 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Larson PS, Starr PA, Bates G, Tansey L, Richardson RM, Martin AJ. An optimized system for interventional magnetic resonance imaging-guided stereotactic surgery: preliminary evaluation of targeting accuracy. Neurosurgery . 2012. 70( 1 Suppl Operative): 95- 103. Google Scholar PubMed  27. Petersen EA, Holl EM, Martinez-Torres I et al.   Minimizing brain shift in stereotactic functional neurosurgery. Neurosurgery . 2010; 67( 3 Suppl Operative): 213- 221. Acknowledgment The authors would like to thank Hannah Silk for her technical help and support in the writing of this manuscript. Copyright © 2017 by the Congress of Neurological Surgeons

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Operative NeurosurgeryOxford University Press

Published: Apr 1, 2018

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