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Denby, C. E.; Chatterjee, K.; Pullicino, R.; Lane, S.; Radon, M. R.; Das, K. V.
doi: 10.1007/s00234-019-02349-zpmid: 31901972
PurposeTo determine whether the sensitivity and specificity of four-dimensional CTA (4D-CTA) are equivalent to digital subtraction angiography (DSA) in the detection of underlying vascular abnormalities in patients with intracerebral haemorrhage (ICH).MethodsA systematic review of studies comparing 4D-CTA with DSA in the detection of the underlying structural causes of ICH was performed on the literature published between 1998 and 2019.ResultsWe identified a total of 237 articles from PubMed, SCOPUS and Web of Science using the following Medical Subject Headings (MeSH) terms: primary intracerebral haemorrhage, 4D-CTA, DSA, cerebral haemorrhage, angiography, digital subtraction, arteriovenous malformations, 4D, CTA, dynamic-CTA and time-resolved CTA. Following the removal of duplicate publications and articles failing to meet our inclusion criteria, there were four articles potentially viable for analysis. Therefore, there were not sufficient studies to provide a statistically meaningful meta-analysis.ConclusionThe review of current literature has demonstrated that there are few published studies comparing 4D-CTA with DSA in spontaneous ICH, with only four suitable studies identified for potential analysis. However, due to the restricted number of patients and high sensitivity and specificity of 3 studies (100%), performing a meta-analysis was not meaningful. Qualitative analysis of the data concluded that 4D-CTA has the diagnostic potential to replace invasive DSA in certain cases with vascular abnormalities. However, further research studies directly comparing 4D-CTA with DSA using larger prospective patient cohorts are required to strengthen the evidence base.
Bot, Joseph C.J.; Mazzai, Linda; Hagenbeek, Rogier E.; Ingala, Silvia; van Oosten, Bob; Sanchez-Aliaga, Esther; Barkhof, Frederik
doi: 10.1007/s00234-019-02335-5pmid: 31925469
PurposeMiliary enhancement refers to the presence of multiple small, monomorphic, enhancing foci on T1-weighted post-contrast MRI images. In the absence of a clear clinical presentation, a broad differential diagnosis may result in invasive procedures and possibly brain biopsy for diagnostic purposes.MethodsAn extensive review of the literature is provided for diseases that may present with miliary enhancement on T1-weighted brain MR images. Additional disease-specific findings, both clinical and radiological, are summarized and categorized by the presence or absence of perivascular space involvement.ResultsMiliary pattern of enhancement may be due to a variety of underlying causes, including inflammatory, infectious, nutritional or neoplastic processes. The recognition of disease spread along the perivascular spaces in addition to the detection or exclusion of disease-specific features on MRI images, such as leptomeningeal enhancement, presence of haemorrhagic lesions, spinal cord involvement and specific localisation or systemic involvement, allows to narrow the potential differential diagnoses.ConclusionA systematic approach to disease-specific findings from both clinical and radiological perspectives might facilitate diagnostic work-up, and recognition of disease spread along the perivascular spaces may help narrowing down differential diagnoses and may help to minimize the use of invasive diagnostic procedures.
Gensicke, Henrik; Evans, James W; Al Ajlan, Fahad S.; Dowlatshahi, Dar; Najm, Mohamed; Calleja, Ana L.; Puig, Josep; Sohn, Sung-lI; Ahn, Seong H.; Poppe, Alexandre Y.; Mikulik, Robert; Asdaghi, Negar; Field, Thalia S.; Jin, Albert; Asil, Talip;
Park, Chae Jung; Choi, Yoon Seong; Park, Yae Won; Ahn, Sung Soo; Kang, Seok-Gu; Chang, Jong-Hee; Kim, Se Hoon; Lee, Seung-Koo
doi: 10.1007/s00234-019-02312-ypmid: 31820065
PurposeTo evaluate whether diffusion tensor imaging (DTI) radiomics with machine learning improves the prediction of isocitrate dehydrogenase (IDH) mutation status of lower-grade gliomas beyond radiomic features from conventional MRI and DTI histogram parameters.MethodsA total of 168 patients with pathologically confirmed lower-grade gliomas were retrospectively enrolled. A total of 158 and 253 radiomic features were extracted from DTI (DTI radiomics) and conventional MRI (T1-weighted image with contrast enhancement, T2-weighted image, and FLAIR [conventional radiomics]), respectively. The random forest models for predicting IDH status were trained with variable combinations as follows: (1) DTI radiomics, (2) conventional radiomics, (3) conventional radiomics + DTI radiomics, and (4) conventional radiomics + DTI histogram. The models were validated with nested cross-validation. The predictive performances of those models were compared by using area under the curve (AUC) from receiver operating characteristic analysis, and 95% confidence interval (CI) was calculated.ResultsAdding DTI radiomics to conventional radiomics significantly improved the accuracy of IDH status subtyping (AUC, 0.900 [95% CI, 0.855–0.945], p = 0.006), whereas adding DTI histogram parameters yielded nonsignificant trend toward improvement (0.869 [95% CI, 0.816–0.922], p = 0.150) compared with the model with conventional radiomics alone (0.835 [95% CI, 0.773–0.896]). The performance of the model consisting of both DTI and conventional radiomics was significantly superior than that of model consisting of both DTI histogram parameters and conventional radiomics (0.900 vs 0.869, p = 0.040).ConclusionDTI radiomics with machine learning can help improve the subtyping of IDH status beyond conventional radiomics and DTI histogram parameters in patients with lower-grade gliomas.
Li, Ming-ge; Liu, Tie-fang; Zhang, Tian-hao; Chen, Zhi-ye; Nie, Bin-bin; Lou, Xin; Wang, Zhen-fu; Ma, Lin
doi: 10.1007/s00234-019-02333-7pmid: 31822931
PurposeMild cognitive impairment (MCI) is commonly observed in Parkinson’s disease (PD), even in the early stages. However, the neural substrates of cognitive impairment in PD remain unclear. The aim of the current study was to investigate the change of local brain function in PD patients with MCI.MethodsFifty patients with PD, including 25 PD patients with MCI (PD-MCI) and 25 PD patients with normal cognition (PD-NC), and 25 age- and sex-matched healthy controls (HC) were enrolled. Conventional magnetic resonance imaging (MRI), 3D structural images, and resting state-functional MRI (rs-fMRI) were performed in all subjects. Regional homogeneity (ReHo) was measured based on the rs-fMRI images to investigate the altered local brain functions.ResultsBrain regions with decreased ReHo were located in the left posterior cerebellar lobe in PD sub-groups compared to the HC group, and the brain regions with increased ReHo were located in the limbic lobe (right precuneus/bilateral middle cingulate cortex) in PD-MCI compared with HC group. PD-MCI presented with increased ReHo in the bilateral precuneus/left superior parietal lobe and decreased ReHo in the left insula compared to PD-NC. ReHo values for the left precuneus were negatively related to neuropsychological scores, and ReHo values for the left insula were positively related to neuropsychological scores in PD subjects.ConclusionThe present study demonstrated abnormal spontaneous synchrony in the left insula and left precuneus in patients with PD-MCI compared to PD-NC, which might provide a novel insight into the diagnosis and clinical treatment of cognitive impairment in PD.
doi: 10.1007/s00234-019-02330-wpmid: 31828361
PurposeTo analyze the implementation of deep learning software for the detection and worklist prioritization of acute intracranial hemorrhage on non-contrast head CT (NCCT) in various clinical settings at an academic medical center.MethodsUrgent NCCT scans were reviewed by the Aidoc (Tel Aviv, Israel) neural network software. All cases flagged by the software as positive for acute intracranial hemorrhage on the neuroradiology worklist were prospectively included in this assessment. The scans were classified regarding presence and type of hemorrhage, whether these were initial or follow-up scans, and patient visit location, including trauma/emergency, inpatient, and outpatient departments.ResultsDuring the 2 months of enrollment, 373 NCCT scans were flagged by the Aidoc software for possible intracranial hemorrhage out of 2011 scans analyzed (18.5%). Among the flagged cases, 275 (72.4%) were positive; 290 (77.7%) were inpatient cases, 75 (20.1%) were trauma/emergency cases, and eight (2.1%) were outpatient cases, and 229 of 373 (62.5%) were follow-up cases, of which 219 (95.6%) inpatient cases. Among the 144 new cases flagged for hemorrhage, 66 (44.4%) were positive, of which 39 (58.2%) were trauma/emergency cases. The overall sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 88.7%, 94.2% and 73.7%, 97.7%, and 93.4%, respectively. The accuracy of the intracranial hemorrhage detection was significantly higher for emergency cases than for inpatient cases (96.5% versus 89.4%).ConclusionThis study reveals that the performance of the deep learning software for acute intracranial hemorrhage detection varies depending upon the patient visit location. Furthermore, a substantial portion of flagged cases were follow-up exams, the majority of which were inpatient exams. These findings can help optimize the artificial intelligence-driven clincical workflow.
Nunninger, Maximilian; Braun, Victor Paul Bela; Ziegert, Marco; Schwarz, Felix Benjamin; Hamm, Bernd; Scheel, Michael; Jahnke, Paul
doi: 10.1007/s00234-019-02339-1pmid: 31838562
PurposeTo develop and evaluate a technical approach for CT-guided periradicular infiltration using quantitative needle access and guidance parameters extracted from CT scout images.MethodsFive 3D-printed phantoms of the abdomen mimicking different patients were used to develop a technical approach for scout-guided periradicular infiltration. The needle access point, puncture depth, and needle angulation were calculated using measurements extracted from anterior-posterior and lateral CT scout images. Fifty needle placements were performed with the technique thus developed. Dose exposure and number of image acquisitions were compared with ten procedures performed using a conventional free-hand technique. Data were analyzed with the Mann-Whitney U test.ResultsParameters derived solely from scout images provided adequate guidance for successful and reliable needle placement. Needle guidance was performed with the same equipment as the standard periradicular infiltration. Two scout images and 3.5 ± 2.3 (mean ± SD) single-shot images for needle positioning were acquired. Mean DLP ± SD was 3.8 ± 2.5 mGy cm. The number of single-shot acquisitions was reduced by 68% and the overall dose was reduced by 84% in comparison with the conventional free-hand technique (p < 0.0001).ConclusionScout-guided needle placement for periradicular infiltration is feasible and reduces radiation exposure significantly.
Showing 1 to 10 of 18 Articles
doi: 10.1007/s00234-019-02320-ypmid: 31713667
PurposeTo compare the association of different measures of intracranial thrombus permeability on non-contrast computerized tomography (NCCT) and computed tomography angiography (CTA) with recanalization with or without intravenous alteplase.MethodsPatients with anterior circulation occlusion from the INTERRSeCT study were included. Thrombus permeability was measured on non-contrast CT and CTA using the following methods: [1] automated method, mean attenuation increase on co-registered thin (< 2.5 mm) CTA/NCCT; [2] semi-automated method, maximum attenuation increase on non-registered CTA/NCCT (ΔHUmax); [3] manual method, maximum attenuation on CTA (HUmax); and [4] visual method, residual flow grade. Primary outcome was recanalization with intravenous alteplase on the revised AOL scale (2b/3). Regression models were compared using C-statistic, Akaike (AIC), and Bayesian information criterion (BIC).ResultsFour hundred eighty patients were included in this analysis. Statistical models using methods 2, 3, and 4 were similar in their ability to discriminate recanalizers from non-recanalizers (C-statistic 0.667, 0.683, and 0.634, respectively); method 3 had the least information loss (AIC = 483.8; BIC = 492.2). A HUmax ≥ 89 measured with method 3 provided optimal sensitivity and specificity in discriminating recanalizers from non-recanalizers [recanalization 55.4% (95%CI 46.2–64.6) when HUmax > 89 vs. 16.8% (95%CI 13.0–20.6) when HUmax ≤ 89]. In sensitivity analyses restricted to patients with co-registered CTA/NCCT (n = 88), methods 1–4 predicted recanalization similarly (C-statistic 0.641, 0.688, 0.640, 0.648, respectively) with Method 2 having the least information loss (AIC 104.8, BIC 109.8).ConclusionSimple methods that measure thrombus permeability are as reliable as complex image processing methods in discriminating recanalizers from non-recanalizers.
PurposeMyxoma-related intracranial diseases were rarely documented in history. The main purpose of our study is to provide a more comprehensive and detailed understanding of the pathogenesis, imaging features, surgical procedures and pathology of such patients through long-term follow-up.MethodsFrom March 2012 to July 2018, baseline information that included neuroimaging and neuropathology data from 12 cardiac myxoma patients with neurological symptoms were retrospectively analysed, and the treatment options were discussed. Nine patients underwent long-term postoperative follow-up.ResultsTwelve cardiac myxoma patients with neurological symptoms were identified, and among them, 10 patients were postoperative patients who had undergone excision of cardiac myxoma, 5 patients had received craniotomy, and the others had received conservative treatment. Positive neuroimaging findings were found in all patients, including cerebral infarction (12/12, 100%), multiple intracranial aneurysms (8/12, 67%), and extravascular metastasis (6/12, 50%). After a long-term average follow-up of 27 months, an increased number of metastatic lesions or an enlargement of the intracranial aneurysms was found in 4 patients.ConclusionsNeuroimaging findings of myxoma-related intracranial lesions were diversed and usually presented as multiple cerebral infarction, aneurysm formation, focal intracranial haemorrhage and space-occupying lesions. Progress is over a long period of time after primary tumour resection. It is necessary for patients to be regularly examined within 2 years after cardiac myxoma resection using MRI+CTA/MRA/DSA in order to be ruled out. Stable and effective chemotherapy drugs are urgently needed.