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Dive into the research topics where Sheena L. Dupuy is active.

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Featured researches published by Sheena L. Dupuy.


Journal of Neuroimaging | 2015

Quantification of global cerebral atrophy in multiple sclerosis from 3T MRI using SPM: the role of misclassification errors.

Elisa Dell’Oglio; Antonia Ceccarelli; Bonnie I. Glanz; Brian C. Healy; Shahamat Tauhid; Ashish Arora; Nikila Saravanan; Matthew J. Bruha; Alexander V. Vartanian; Sheena L. Dupuy; Ralph H. B. Benedict; Rohit Bakshi; Mohit Neema

We tested the validity of a freely available segmentation pipeline to measure compartmental brain volumes from 3T MRI in patients with multiple sclerosis (MS). Our primary focus was methodological to explore the effect of segmentation corrections on the clinical relevance of the output metrics.


Journal of Neuroimaging | 2016

The Effect of Fingolimod on Conversion of Acute Gadolinium-Enhancing Lesions to Chronic T1 Hypointensities in Multiple Sclerosis

Vinit V. Oommen; Shahamat Tauhid; Brian C. Healy; Alicia S. Chua; Muhammad Taimur Malik; Camilo Diaz-Cruz; Sheena L. Dupuy; Howard L. Weiner; Tanuja Chitnis; Rohit Bakshi

Brain lesions converting to chronic T1 hypointensities (“chronic black holes” [CBH]), indicate severe tissue destruction (axonal loss and irreversible demyelination) in multiple sclerosis (MS). Two mechanisms by which fingolimod could limit MS lesion evolution include sequestration of lymphocytes in the periphery or direct neuroprotective effects. We investigated the effect of fingolimod on the evolution of acute gadolinium‐enhancing (Gd+) brain lesions to CBH in patients with MS.


JAMA Neurology | 2017

Association Between Serum MicroRNAs and Magnetic Resonance Imaging Measures of Multiple Sclerosis Severity

Keren Regev; Brian C. Healy; Fariha Khalid; Anu Paul; Renxin Chu; Shahamat Tauhid; Subhash Tummala; Camilo Diaz-Cruz; Radhika Raheja; Maria Antonietta Mazzola; Felipe von Glehn; Pia Kivisäkk; Sheena L. Dupuy; Gloria Kim; Tanuja Chitnis; Howard L. Weiner; Roopali Gandhi; Rohit Bakshi

Importance MicroRNAs (miRNAs) are promising multiple sclerosis (MS) biomarkers. Establishing the association between miRNAs and magnetic resonance imaging (MRI) measures of disease severity will help define their significance and potential impact. Objective To correlate circulating miRNAs in the serum of patients with MS to brain and spinal MRI. Design, Setting, and Participants A cross-sectional study comparing serum miRNA samples with MRI metrics was conducted at a tertiary MS referral center. Two independent cohorts (41 and 79 patients) were retrospectively identified from the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Womens Hospital. Expression of miRNA was determined by locked nucleic acid–based quantitative real-time polymerase chain reaction. Spearman correlation coefficients were used to test the association between miRNA and brain lesions (T2 hyperintense lesion volume [T2LV]), the ratio of T1 hypointense lesion volume [T1LV] to T2LV [T1:T2]), brain atrophy (whole brain and gray matter), and cervical spinal cord lesions (T2LV) and atrophy. The study was conducted from December 2013 to April 2016. Main Outcomes and Measures miRNA expression. Results Of the 120 patients included in the study, cohort 1 included 41 participants (7 [17.1%] men), with mean (SD) age of 47.7 (9.5) years; cohort 2 had 79 participants (26 [32.9%] men) with a mean (SD) age of 43.0 (7.5) years. Associations between miRNAs and MRIs were both protective and pathogenic. Regarding miRNA signatures, a topographic specificity differed for the brain vs the spinal cord, and the signature differed between T2LV and atrophy/destructive measures. Four miRNAs showed similar significant protective correlations with T1:T2 in both cohorts, with the highest for hsa.miR.143.3p (cohort 1: Spearman correlation coefficient rs = −0.452, P = .003; cohort 2: rs = −0.225, P = .046); the others included hsa.miR.142.5p (cohort 1: rs = −0.424, P = .006; cohort 2: rs = −0.226, P = .045), hsa.miR.181c.3p (cohort 1: rs = −0.383, P = .01; cohort 2: rs = −0.222, P = .049), and hsa.miR.181c.5p (cohort 1: rs = −0.433, P = .005; cohort 2: rs = −0.231, P = .04). In the 2 cohorts, hsa.miR.486.5p (cohort 1: rs = 0.348, P = .03; cohort 2: rs = 0.254, P = .02) and hsa.miR.92a.3p (cohort 1: rs = 0.392, P = .01; cohort 2: rs = 0.222, P = .049) showed similar significant pathogenic correlations with T1:T2; hsa.miR.375 (cohort 1: rs = −0.345, P = .03; cohort 2: rs = −0.257, P = .022) and hsa.miR.629.5p (cohort 1: rs = −0.350, P = .03; cohort 2: rs = −0.269, P = .02) showed significant pathogenic correlations with brain atrophy. Although we found several miRNAs associated with MRI outcomes, none of these associations remained significant when correcting for multiple comparisons, suggesting that further validation of our findings is needed. Conclusions and Relevance Serum miRNAs may serve as MS biomarkers for monitoring disease progression and act as surrogate markers to identify underlying disease processes.


European Journal of Radiology | 2015

MRI detection of hypointense brain lesions in patients with multiple sclerosis: T1 spin-echo vs. gradient-echo

Sheena L. Dupuy; Shahamat Tauhid; Gloria Kim; Renxin Chu; Subhash Tummala; Shelley Hurwitz; Rohit Bakshi

OBJECTIVE Compare T1 spin-echo (T1SE) and T1 gradient-echo (T1GE) sequences in detecting hypointense brain lesions in multiple sclerosis (MS). BACKGROUND Chronic hypointense lesions on T1SE MRI scans are a surrogate of severe demyelination and axonal loss in MS. The role of T1GE images in the detection of such lesions has not been clarified. DESIGN/METHODS In 45 patients with MS [Expanded Disability Status Scale (EDSS) score (mean±SD) 3.5±2.0; 37 relapsing-remitting (RR); 8 secondary progressive (SP)], cerebral T1SE, T1GE, and T2-weighted fluid-attenuated inversion-recovery (FLAIR) images were acquired on a 1.5T MRI scanner. Images were re-sampled to axial 5mm slices before directly comparing lesion detectability using Jim (v.7, Xinapse Systems). Statistical methods included Wilcoxon signed rank tests to compare sequences and Spearman correlations to test associations. RESULTS Considering the entire cohort, T1GE detected a higher lesion volume (5.90±6.21 vs. 4.17±4.84ml, p<0.0001) and higher lesion number (27.82±20.66 vs. 25.20±20.43, p<0.05) than T1SE. Lesion volume differences persisted when considering RR and SP patients separately (both p<0.01). A higher lesion number by T1GE was seen only in the RR group (p<0.05). When comparing correlations between lesion volume and overall neurologic disability (EDSS score), T1SE correlated with EDSS (Spearman r=0.29, p<0.05) while T1GE (r=0.23, p=0.13) and FLAIR (r=0.24, p=0.12) did not. CONCLUSION Our data suggest that hypointense lesions on T1SE and T1GE are not interchangeable in patients with MS. Based on these results, we hypothesize that T1GE shows more sensitivity to lesions at the expense of less pathologic specificity for tissue destruction than T1SE.


Journal of the Neurological Sciences | 2017

A two-year study using cerebral gray matter volume to assess the response to fingolimod therapy in multiple sclerosis

Fawad Yousuf; Sheena L. Dupuy; Shahamat Tauhid; Renxin Chu; Gloria Kim; Subhash Tummala; Fariha Khalid; Howard L. Weiner; Tanuja Chitnis; Brian C. Healy; Rohit Bakshi

BACKGROUND Cerebral gray matter (GM) atrophy has clinical relevance in multiple sclerosis (MS). Fingolimod has known efficacy on clinical and conventional MRI findings in MS; the effect on GM is unknown. OBJECTIVE To explore fingolimods treatment effect on cerebral GM atrophy over two years in patients with relapsing forms of MS. DESIGN/METHODS Patients starting fingolimod [n=24, age (mean±SD) 41.2±11.6years, Expanded Disability Status Scale (EDSS) score 1.1±1.4; 58% women] were compared to untreated patients [n=29, age 45.7±8.4years, EDSS 1.0±1.2; 93% women]. Baseline, one and two year MRI was applied to an SPM12 pipeline to assess brain parenchymal fraction (BPF) and cortical GM fraction (cGMF). T2 lesion volume (T2LV) and gadolinium-enhancing lesions were assessed. Change was modeled using a mixed effects linear regression with a random intercept and fixed effects for time, group, and the time-by-group interaction. The group slope difference was assessed using the interaction term. RESULTS Over two years, cGMF remained stable in the fingolimod group (p>0.05), but decreased in the untreated group (p<0.001) (group difference p<0.001). BPF change did not differ between groups (all time-points p>0.05). T2LV increased over two years in the untreated group (p<0.001) but not in the fingolimod group (p≥0.44) (group difference p<0.001). CONCLUSION These results suggest a treatment effect of fingolimod on cerebral GM atrophy in the first two years. GM atrophy is more sensitive to such effects than whole brain atrophy. However, due to the non-randomized, retrospective design, heterogeneous between-group characteristics, and small sample size, these results require confirmation in future studies.


Neurology and Therapy | 2016

The Effect of Dimethyl Fumarate on Cerebral Gray Matter Atrophy in Multiple Sclerosis

Sheena L. Dupuy; Shahamat Tauhid; Shelley Hurwitz; Renxin Chu; Fawad Yousuf; Rohit Bakshi


Journal of Neurology | 2016

An MRI-defined measure of cerebral lesion severity to assess therapeutic effects in multiple sclerosis

Gloria Kim; Shahamat Tauhid; Sheena L. Dupuy; Subhash Tummala; Fariha Khalid; Brian C. Healy; Rohit Bakshi


BMC Medical Imaging | 2016

The effect of intramuscular interferon beta-1a on spinal cord volume in relapsing-remitting multiple sclerosis.

Sheena L. Dupuy; Fariha Khalid; Brian C. Healy; Sonya Bakshi; Mohit Neema; Shahamat Tauhid; Rohit Bakshi


Journal of the Neurological Sciences | 2018

Quantitative MRI analysis of cerebral lesions and atrophy in post-partum patients with multiple sclerosis

Fariha Khalid; Brian C. Healy; Sheena L. Dupuy; Renxin Chu; Tanuja Chitnis; Rohit Bakshi; Maria K. Houtchens


Neurology | 2016

Cortical Thickness Measurements from 1.5T vs. 3T MRI in Healthy Subjects and Patients with Multiple Sclerosis (P4.179)

Subhash Tummala; Renxin Chu; Fariha Khalid; Sheena L. Dupuy; Shahamat Tauhid; Brian C. Healy; Rohit Bakshi

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Rohit Bakshi

Brigham and Women's Hospital

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Shahamat Tauhid

Brigham and Women's Hospital

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Brian C. Healy

Brigham and Women's Hospital

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Fariha Khalid

Brigham and Women's Hospital

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Renxin Chu

Brigham and Women's Hospital

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Gloria Kim

Brigham and Women's Hospital

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Subhash Tummala

Brigham and Women's Hospital

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Howard L. Weiner

Brigham and Women's Hospital

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Tanuja Chitnis

Brigham and Women's Hospital

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Shelley Hurwitz

Brigham and Women's Hospital

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