About

Adil Javed, MD, PhD, is a Professor of Neurology at the University of Chicago. His expertise lies in autoimmune diseases of the brain and spine, including multiple sclerosis, lupus, Sjögren's disease, and related connective tissue diseases. He has particular clinical and research interests in neuromyelitis optica (NMO), also known as Devic's disease, and specializes in nervous system complications of infectious and post-infectious diseases. Dr. Javed is a principal investigator in several multiple sclerosis trials and his translational research focuses on analyzing brain pathology using new and unconventional magnetic resonance imaging (MRI) techniques.

Research topics

• Medicine
• Internal medicine
• Immunology
• Radiology
• Gastroenterology
• Psychiatry
• Neuroscience
• Biology
• Psychology
• Pediatrics
• Physical therapy
• Pathology

Selected publications

• Cervical Internal Carotid Artery Plaque Composition and Chronic White Matter Disease in Patients with Noncardioembolic Stroke: A Multicenter Analysis

  Stroke Vascular and Interventional Neurology · 2025-10-30

  articleOpen access

  BACKGROUND Cerebral white matter disease (WMD) may result from the accumulation of silent embolic brain infarcts in the setting of subclinical, nonstenotic cervical carotid atherosclerosis. The contribution of cervical plaque to the burden of WMD is not well established. METHODS A multicenter, retrospective cohort of consecutive adult patients with stroke due to cervical carotid atherostenosis (>50% luminal stenosis), small vessel disease, or cryptogenic mechanism with unilateral hemispheric stroke was queried. Maximum cervical carotid plaque thickness was used to predict higher grade WMD (Fazekas grade 2–3 versus 0–1) in unadjusted logistic regression, stratified by quartile of interside plaque (mean total plaque in axial dimension of the left and right cervical carotid arteries), and adjusted for age, stroke mechanism, atherosclerotic risk factors, and clustering by site. RESULTS Of the 375 included patients, the median age was 66 years (interquartile range 58–74), 170 (45.3%) were female, and the median interside cervical internal carotid artery plaque thickness was 1.8 mm (interquartile range 0.2‐3.2). Compared with patients in the lowest quartile of interside plaque (<0.2 mm), those in higher quartiles had higher grade WMD (Q3 adjusted odds ratio [aOR] 1.44, 95% CI, 1.09–1.89; Q4 aOR 1.85, 95% CI, 1.37–2.50). The association with higher grade WMD persisted in a sensitivity analysis considering interside plaque thickness as a continuous variable (adjusted incidence rate ratio/1 mm plaque 1.09, 95% CI, 1.02–1.17). The effect was preserved across stroke mechanisms, sex, and infarct pattern (cortical versus subcortical); however, younger patients had a stronger association between plaque thickness and WMD, whereas the eldest patients had no association ( P interaction <0.01). CONCLUSIONS In this cohort of patients with noncardioembolic stroke, greater interside cervical carotid plaque thickness was strongly associated with greater WMD. This association supports a potential role of subclinical cervical carotid artery atherosclerosis as a contributor to WMD, which may represent the accumulation of silent brain infarcts.

  PublisherDOI

• Treatment Options for NMOSD in Children: Effectiveness and Safety of Subcutaneous Tocilizumab (P12-8.009)

  Neurology · 2025-04-07 · 2 citations

  articleSenior author

  NA

  PublisherDOI

• Reconstructability of LAPC the nice target beyond the circumferential vascular involvement degree

  HPB · 2025-01-01

  article
  PublisherDOI

• Validation of retroactively derived T1 relaxation values from 3D T1-weighted images with clinical and MRI measures of disability in multiple sclerosis

  PLoS ONE · 2025-05-19 · 1 citations

  articleOpen accessSenior author

  BACKGROUND: Quantitative T1 mapping is a valuable technique for assessing tissue injury in multiple sclerosis (MS) lesions. We previously introduced a novel methodology for converting high-resolution anatomical 3D T1-weighted (T1W) images into parametric T1 relaxometry maps. Herein, we correlate MS lesion pathology as quantified by retroactive T1 mapping with clinical and MRI metrics of disability and with magnetization transfer ratio (MTR). METHODS: 38 subjects with relapsing-remitting MS (RRMS) were examined, contributing to 587 unique lesions for analysis. T1 and MTR values were compared using correlation statistics. Univariate correlations between lesional T1 or MTR and Expanded Disability Status Scale (EDSS) were examined using Spearman's rho (ρ), and for disease duration and brain parenchymal fraction (BPF), Pearson's r. Mean T1 values of lesions were compared across different categories of EDSS severity using Kruskal-Wallis test. Ordinal regression model was used to assess the association between EDSS and T1 values of select brain regions. RESULTS: The mean T1 of lesions showed a high correlation with - MTR, r = 0.68. T2 lesion volumes stratified based on different T1 thresholds showed a significant correlation with MS disease metrics: lesion volume threshold at 700 < T1 < 900 was correlated with disease duration (r = 0.34, p = 0.04) and BPF (r = -0.47, p = 0.003); lesion volume threshold at 900 < T1 < 1100 was correlated with EDSS (ρ = 0.42, p = 0.01), disease duration (r = 0.45, p = 0.01), and BPF (r = -0.56, p < 0.001); lesion volume threshold at T1 > 1100 was correlated with EDSS (ρ = 0.41, p = 0.01), disease duration (r = 0.45, p = 0.001), and BPF (r = -0.51, p < 0.001). T1 values at the 25th, 50th, and 75th percentiles significantly correlated with BPF (r = -0.41, p = 0.01; r = -0.41, p = 0.01; r = -0.38, p = 0.02). MTR showed a significant correlation with EDSS but not with disease duration or BPF. Mean T1 values in the NAWM showed a significant association with EDSS (coefficient = 0.03, pseudo R2 = 0.07, p = 0.03). CONCLUSIONS: We provide clinical validation of retroactive T1 mapping as a complementary post-processing technique for monitoring disease activity and disability progression in MS.

  PublisherDOI

• Neuromyeltis Optica Spectrum Disorder Disease Activity in the Nonagenarians: Recalcitrant Autoimmunity Unabated by Aging (P12-8.011)

  Neurology · 2025-04-07

  articleSenior author

  NA

  PublisherDOI

• Prediction of active Multiple Sclerosis lesions through use of logistic regression classifier and first-order features

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2024-08-14

  article

  Multiple Sclerosis is a neuroinflammatory disease in which the immune system attacks nerve fibers and myelin sheaths, leading to the formation of lesions through white matter. Gadolinium-enhanced MRI is used to diagnose and track the progression of MS. Active MS lesions enhance with gadolinium, but there is an interest in prediction of lesion enhancement based on lesion features. In this study, we examined first-order features derived from T1w pre-contrast MS lesions acquired on multiple 3T imagers at a single center to train a logistic regression classifier to classify lesions as active or inactive.

  PublisherDOI

• T1 mapping from routine 3D T1-weighted inversion recovery sequences in clinical practice: comparison against reference inversion recovery fast field echo T1 scans and feasibility in multiple sclerosis

  Neuroradiology · 2024-06-17 · 1 citations

  articleSenior authorCorresponding
  PublisherDOI

• Commentary: T1 Mapping from routine 3D T1-weighted inversion recovery sequences in clinical practice: comparison against reference inversion recovery fast field echo T1 scans and feasibility in multiple sclerosis

  Journal of Neurology and Neuromedicine · 2024-11-04

  articleOpen access

  MRI has long been a critical tool for diagnosing and monitoring Multiple Sclerosis (MS). Conventional MRI employed in clinical practice is non-parametric, which disallows quantitative measures of tissue damage. This creates an unmet need to develop a post-acquisition image processing algorithm that can convert a qualitative image into a corresponding quantitative map. We present a methodology that can convert a clinically routine T1-weighted MPRAGE image into a parametric T1 map with high accuracy and precision in relation to a commonly used T1 mapping reference standard. We evaluate the methodology’s performance in Multiple Sclerosis for the purpose of quantifying tissue damage primarily in lesions and secondarily in white matter and gray matter regions.

  PublisherOA PDFDOI

• Laparoscopic radical cholecystectomy with CBD excision in gallbladder cancer patients with biliary obstruction

  HPB · 2024-01-01

  articleOpen access
  PublisherOA PDFDOI

• Sampling Time Considerations for T1 map acquisition on the 64mT Hyperfine Swoop system: A Phantom Evaluation Study

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2024-08-14

  article

  T1 maps provide quantitative relaxometric measures of tissue responses that may carry correlative indices of specific disease indications. On the recently commercialized 64mT system (Hyperfine Inc.), little has been reported regarding both clinical T1 relaxometric normal values in presence of Gadolinium-based contrast and relevant acquisition schemes with Gd contrast enhancement. In this study, we examine an array of Gadolinium-doped vials that represent 10-5000 fold dilution in the vasculature using an Inversion-Recovery FSE acquisition to gain key insights on: a) anticipated normal values in presence of Gd, b) conventional fitting algorithm performance, and c) potential inferences on inversion timing selection.

  PublisherDOI

Frequent coauthors

• Anthony Traboulsee

  Vancouver Biotech (Canada)

  69 shared

• Gaëlle Klingelschmitt

  Roche (Switzerland)

  64 shared

• Daniela Stokmaier

  Roche (Switzerland)

  64 shared

• Ingo Kleiter

  64 shared

• Jeffrey L. Bennett

  University of Colorado Denver

  64 shared

• Jacqueline Palace

  John Radcliffe Hospital

  64 shared

• Kazuo Fujihara

  64 shared

• Hans‐Christian von Büdingen

  Roche (Switzerland)

  64 shared

Labs

• Adil Javed LabPI

Education

• M.D.

  University of Chicago

• Ph.D.

  University of Chicago