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As swelling occurs, CSF is preferentially displaced from the ischemic hemisphere. The ratio of CSF volume in the stroke-affected hemisphere to that in the contralateral hemisphere may quantify the progression of cerebral edema. We automatically segmented CSF from 1,875 routine CTs performed within 96 hours of stroke onset in 924 participants of a stroke cohort study. In 737 subjects with follow-up imaging beyond 24-hours, edema severity was classified as affecting less than one-third of the hemisphere (CED-1), large hemispheric infarction (LHI, over one-third the hemisphere), without midline shift (CED-2) or with midline shift (CED-3). Malignant edema was LHI resulting in deterioration, requiring osmotic therapy, surgery, or resulting in death. Hemispheric CSF ratio was lower on baseline CT in those with LHI (0.91 vs. 0.97, p < 0.0001) and decreased more rapidly in those with LHI who developed midline shift (0.01 per hour for CED-3 vs. 0.004/hour CED-2). The ratio at 24-hours was lower in those with midline shift (0.41, IQR 0.30-0.57 vs. 0.66, 0.56-0.81 for CED-2). A ratio below 0.50 provided 90% sensitivity, 82% specificity for predicting malignant edema among those with LHI (AUC 0.91, 0.85-0.96). This suggests that the hemispheric CSF ratio may provide an accessible early biomarker of edema severity.

Stroke is one of the leading causes of death and disability worldwide. Reducing this disease burden through drug discovery and evaluation of stroke patient outcomes requires broader characterization of stroke pathophysiology, yet the underlying biologic and genetic factors contributing to outcomes are largely unknown. Remedying this critical knowledge gap requires deeper phenotyping, including large-scale integration of demographic, clinical, genomic, and imaging features. Such big data approaches will be facilitated by developing and running processing pipelines to extract stroke-related phenotypes at large scale. Millions of stroke patients undergo routine brain imaging each year, capturing a rich set of data on stroke-related injury and outcomes. The Stroke Neuroimaging Phenotype Repository (SNIPR) was developed as a multi-center centralized imaging repository of clinical computed tomography (CT) and magnetic resonance imaging (MRI) scans from stroke patients worldwide, based on the open source XNAT imaging informatics platform. The aims of this repository are to: (i) store, manage, process, and facilitate sharing of high-value stroke imaging data sets, (ii) implement containerized automated computational methods to extract image characteristics and disease-specific features from contributed images, (iii) facilitate integration of imaging, genomic, and clinical data to perform large-scale analysis of complications after stroke; and (iv) develop SNIPR as a collaborative platform aimed at both data scientists and clinical investigators. Currently, SNIPR hosts research projects encompassing ischemic and hemorrhagic stroke, with data from 2,246 subjects, and 6,149 imaging sessions from Washington University's clinical image archive as well as contributions from collaborators in different countries, including Finland, Poland, and Spain. Moreover, we have extended the XNAT data model to include relevant clinical features, including subject demographics, stroke severity (NIH Stroke Scale), stroke subtype (using TOAST classification), and outcome [modified Rankin Scale (mRS)]. Image processing pipelines are deployed on SNIPR using containerized modules, which facilitate replicability at a large scale. The first such pipeline identifies axial brain CT scans from DICOM header data and image data using a meta deep learning scan classifier, registers serial scans to an atlas, segments tissue compartments, and calculates CSF volume. The resulting volume can be used to quantify the progression of cerebral edema after ischemic stroke. SNIPR thus enables the development and validation of pipelines to automatically extract imaging phenotypes and couple them with clinical data with the overarching aim of enabling a broad understanding of stroke progression and outcomes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Mohammadian Foroushani, Dhar, Chen, Gurney, Hamzehloo, Lee and Marcus.)

Introduction: Malignant cerebral edema develops in a small subset of patients with hemispheric strokes, precipitating deterioration and death if decompressive hemicraniectomy (DHC) is not performed in a timely manner. Predicting which stroke patients will develop malignant edema is imprecise based on clinical data alone. Head computed tomography (CT) imaging is often performed at baseline and 24-h. We determined the incremental value of incorporating imaging-derived features from serial CTs to enhance prediction of malignant edema., Methods: We identified hemispheric stroke patients at three sites with NIHSS ≥ 7 who had baseline as well as 24-h clinical and CT imaging data. We extracted quantitative imaging features from baseline and follow-up CTs, including CSF volume, intracranial reserve (CSF/cranial volume), as well as midline shift (MLS) and infarct-related hypodensity volume. Potentially lethal malignant edema was defined as requiring DHC or dying with MLS over 5-mm. We built machine-learning models using logistic regression first with baseline data and then adding 24-h data including reduction in CSF volume (ΔCSF). Model performance was evaluated with cross-validation using metrics of recall (sensitivity), precision (predictive value), as well as area under receiver-operating-characteristic and precision-recall curves (AUROC, AUPRC)., Results: Twenty of 361 patients (6%) died or underwent DHC. Baseline clinical variables alone had recall of 60% with low precision (7%), AUROC 0.59, AUPRC 0.15. Adding baseline intracranial reserve improved recall to 80% and AUROC to 0.82 but precision remained only 16% (AUPRC 0.28). Incorporating ΔCSF improved AUPRC to 0.53 (AUROC 0.91) while all imaging features further improved prediction (recall 90%, precision 38%, AUROC 0.96, AUPRC 0.66)., Conclusion: Incorporating quantitative CT-based imaging features from baseline and 24-h CT enhances identification of patients with malignant edema needing DHC. Further refinements and external validation of such imaging-based machine-learning models are required.

Background and Purpose- Volumes of hemorrhage and perihematomal edema (PHE) are well-established biomarkers of primary and secondary injury, respectively, in spontaneous intracerebral hemorrhage. An automated imaging pipeline capable of accurately and rapidly quantifying these biomarkers would facilitate large cohort studies evaluating underlying mechanisms of injury. Methods- Regions of hemorrhage and PHE were manually delineated on computed tomography scans of patients enrolled in 2 intracerebral hemorrhage studies. Manual ground-truth masks from the first cohort were used to train a fully convolutional neural network to segment images into hemorrhage and PHE. The primary outcome was automated-versus-human concordance in hemorrhage and PHE volumes. The secondary outcome was voxel-by-voxel overlap of segmentations, quantified by the Dice similarity coefficient (DSC). Algorithm performance was validated on 84 scans from the second study. Results- Two hundred twenty-four scans from 124 patients with supratentorial intracerebral hemorrhage were used for algorithm derivation. Median volumes were 18 mL (interquartile range, 8-43) for hemorrhage and 12 mL (interquartile range, 5-30) for PHE. Concordance was excellent (0.96) for automated quantification of hemorrhage and good (0.81) for PHE, with DSC of 0.90 (interquartile range, 0.85-0.93) and 0.54 (0.39-0.65), respectively. External validation confirmed algorithm accuracy for hemorrhage (concordance 0.98, DSC 0.90) and PHE (concordance 0.90, DSC 0.55). This was comparable with the consistency observed between 2 human raters (DSC 0.90 for hemorrhage, 0.57 for PHE). Conclusions- We have developed a deep learning-based imaging algorithm capable of accurately measuring hemorrhage and PHE volumes. Rapid and consistent automated biomarker quantification may accelerate powerful and precise studies of disease biology in large cohorts of intracerebral hemorrhage patients.

Background and Purpose- Cerebral edema (CED) develops in the hours to days after stroke; the resulting increase in brain volume may lead to midline shift (MLS) and neurological deterioration. The time course and implications of edema formation are not well characterized across the spectrum of stroke. We analyzed displacement of cerebrospinal fluid (ΔCSF) as a dynamic quantitative imaging biomarker of edema formation. Methods- We selected subjects enrolled in a stroke cohort study who presented within 6 hours of onset and had baseline and ≥1 follow-up brain computed tomography scans available. We applied a neural network-based algorithm to quantify hemispheric CSF volume at each imaging time point and modeled CSF trajectory over time (using a piecewise linear mixed-effects model). We evaluated ΔCSF within the first 24 hours as an early biomarker of CED (defined as developing MLS on computed tomography beyond 24 hours) and poor outcome (modified Rankin Scale score, 3-6). Results- We had serial imaging in 738 subjects with stroke, of whom 91 (13%) developed CED with MLS. Age did not differ (69 versus 70 years), but baseline National Institutes of Health Stroke Scale was higher (16 versus 7) and baseline CSF volume lower (132 versus 161 mL, both P <0.001) in those with CED. ΔCSF was faster in those developing MLS, with the majority seen by 24 hours (36% versus 11% or 2.4 versus 0.8 mL/h; P <0.0001). Risk of CED almost doubled for every 10% ΔCSF within 24 hours (odds ratio, 1.76 [95% CI, 1.46-2.14]), adjusting for age, glucose, and National Institutes of Health Stroke Scale. Risk of neurological deterioration (1.6-point increase in National Institutes of Health Stroke Scale at 24 hours) and poor outcome (adjusted odds ratio, 1.34 [95% CI, 1.15-1.56]) was also greater for every 10% increase in ΔCSF. Conclusions- CSF volumetrics provides quantitative evaluation of early edema formation. ΔCSF from baseline to 24-hour computed tomography is a promising early biomarker for the development of MLS and worse neurological outcome.

Down syndrome (DS) is one of the most common survivable chromosomal disorders, and is well known to be associated with multiple autoimmune diseases. Multiple sclerosis (MS) is a chronic inflammatory autoimmune demyelinating disease of the central nervous system. An association of DS and other autoimmune disease has been previously reported, and we report one case of DS in coexistence with MS, diabetes mellitus, and thyroid diseases. We suggest that MS, such as other autoimmune diseases, is prevalent in DS patients.

Background: Multiple sclerosis is a leading cause of disability in young adults. Mitoxantrone has recently been shown to be effective in ameliorating multiple sclerosis activity and reducing the relapse rate. This study aimed to assess the efficacy of mitoxantrone on disease activity and decreasing relapse rate in patients with multiple sclerosis in Iran., Methods: This was a clinical trial on patients who received intravenous mitoxantrone, 12 mg/m2 every 3 months. The study was performed at Isfahan Multiple Sclerosis Clinics, affiliated to Isfahan University of Medical Sciences. This clinical trial was conducted from October 2003 through April 2005. One hundred and forty-seven patients with worsening relapsing-remitting and secondary progressive multiple sclerosis received mitoxantrone, 12 mg/m(2) every 3 months. Clinical assessment was made every 3 months for one year., Results: Of the 147 patients, 129 (93 females and 36 males) could successfully complete the course of our study. A significant therapeutic effect (P < 0.0001) was detected for the attack rate before and after treatment. The Mean attack rate 12 months before treatment was 1.10 (SD = 0.95), which reduced to 0.09 (SD = 0.29) during treatment. The Mean expanded disability status scale at the beginning of the treatment was 4.32, which declined to 3.62 (P < 0.0001) after one year., Conclusion: Mitoxantrone was generally well tolerated and reduced progression of disability and clinical exacerbation in our patients. Physicians must be careful about the complications of mitoxantrone especially cardiotoxicity.

Objective: To assess contrast transcranial Doppler (TCD) for detection of right-to-left shunt (RLSh)., Methods: We studied 30 patients aged between 25-45 years admitted to Al-Zahra Hospital, affiliated to Isfahan University of Medical Sciences, between May 2003 and May 2005. All patients underwent transesophageal echocardiography (TEE) with contrast and contrast TCD., Results: Eleven (36.6%) patients had RLSh detected by TEE with contrast, and 19 (63.3%) patients had no shunt by TEE. Eighteen patients (60%) patients had no RLSh by contrast TCD, and 12 (40%) patients had RLSh by contrast TCD. Ten (33.3%) patients had RLSh by contrast TCD and TEE with contrast procedures. One patient had RLSh by TEE, and it was negative on TCD test, and 2 patients were positive on TCD test and negative in TEE. With contrast TEE as the gold standard, the sensitivity of contrast TCD was 90.9% and specificity was 89.4%, with an accuracy of 90%. Meanwhile, the positive predictive value of contrast TCD was 83.3% and the negative predictive value was 94.4%., Conclusion: In our study, the negative predictive value of contrast TCD was excellent. Therefore, this examination is able to exclude RLSh with a high level of confidence.

Background: There are few treatment options for patients with secondary progressive and worsening relapsing-remitting multiple sclerosis. Mitoxantrone is an antineoplastic drug, recently approved for treatment of multiple sclerosis. Mitoxantrone is, however, associated with dose-related cardiotoxicity, which limits its use., Objective: To investigate the possible cardiotoxicity of mitoxantrone in multiple sclerosis., Methods: We studied 96 patients with worsening relapsing-remitting or secondary progressive multiple sclerosis, to evaluate cardiotoxicity within one year of mitoxantrone therapy. This study was performed in the Multiple Sclerosis Clinic of Isfahan University of Medical Sciences from October 2003 through October 2004. Analysis of mitoxantrone therapy (12 mg/m2), in terms of cardiac toxicity, was conducted on patients who received at least 4 doses. Cardiac assessment was carried out every 6 months with electrocardiogram, as well as a spectral and color-flow Doppler echocardiographic examination at the time of enrollment and 6 and 12 months later., Results: Ninety-six patients were assessed over 12 months. There was no evidence of clinically-significant cardiac dysfunction. Three patients had a left ventricular ejection fraction of <10% of the base-line value and three had <50%., Conclusion: Mitoxantrone (12 mg/m2) is effective and generally well tolerated by patients with worsening relapsing-remitting and secondary progressive multiple sclerosis. Our findings suggest that the risk for developing cardiotoxicity is low in patients with multiple sclerosis within one year of the treatment with mitoxantrone.