Author Of 4 Presentations
P0063 - Development of a Custom Multivariate Proteomic Serum Based Assay for Association with Radiographic and Clinical Endpoints in MS (ID 833)
Multiple Sclerosis (MS) is a complex and heterogeneous disease. Investigating the biological pathways and cell types involved in MS pathophysiology as represented by protein biomarker expression can help inform the development of tools to monitor disease activity, disease progression, identify early evidence of relapse, and monitor treatment response.
To develop a blood based multiplex proteomic assay that associates with clinical and radiographic endpoints in patients with MS. These endpoints include the presence of gadolinium-enhanced (Gd+) lesions, Annualized Relapse Rate (ARR) and clinically defined relapse status (active versus stable).
Serum samples (n=690 in total) from multiple deeply-phenotyped cohorts (ACP, CLIMB and EPIC) were tested in immunoassays for the measurement of 1196 proteins using Proximity Extension Assays (PEA) from OlinkTM and for 215 proteins using xMAPTM immunoassays from Myriad RBM, Inc. (RBM). Associated radiographic and clinical endpoints at the time of the blood draw were correlated with the protein levels. Twenty-one proteins were selected for inclusion in a custom assay based on their performance in univariate and multivariate statistical models, and replication across independent cohorts. Biological pathway modeling and network analysis were performed to ensure comprehensive representation of MS neurophysiology. Area under the curve (AUC) was selected as the key metric for model performance evaluation.
Multivariate statistical ensembles restricted to the expression levels of the biomarkers selected for the custom assay achieved AUC performance of 0.827 for classification of the presence of Gd+ lesions, 0.802 for classification of clinically defined relapse status, and 0.930 for the classification of patients with Low ARR (≤0.2 relapses) vs High ARR (≥1.0 relapses). A multivariate model utilizing shifts in biomarker expression in longitudinally paired samples achieved the highest observed performance of 0.950 for classification of Gd+ lesion presence. In each case, the multivariate models significantly outperformed (p-value <0.05) the AUC of the highest performing univariate biomarker.
Multivariate models restricted to the 21 selected proteins effectively classified several radiographic and clinical endpoints with stronger performance than any single biomarker. A 21-plex custom assay panel is being developed for further investigation and validation using additional cohorts.
P0083 - Gadolinium improves detection of central vein lesions in MS using 3T FLAIR*. (ID 1404)
The central vein sign (CVS) is a proposed MRI diagnostic biomarker for multiple sclerosis (MS). Use of gadolinium (Gd) in the CVS literature has been inconsistent, and it is unknown whether Gd improves detection of CVS when using FLAIR*.
To determine if, and to what extent, gadolinium injection improves detection of CVS lesions when using FLAIR* imaging.
A cross-sectional multicenter study recruited adults clinically and/or radiologically suspected of having MS. High-isotropic-resolution, T2*-weighted segmented echo-planar imaging (T2*-EPI) was acquired pre- and post-injection of Gd-based contrast agent at 3T; pre-Gd 3D FLAIR images were also acquired. T2*-EPI and FLAIR images were processed on the QMENTA platform to generate FLAIR* images. FLAIR* pre-Gd and post-Gd scans from this substudy of 30 patients at 5 sites were analyzed. FLAIR images were used to create T2 lesion masks. Subsequently, FLAIR* images were evaluated in a random order. Lesions were categorized as CVS+, CVS-, or excluded based on the North American Imaging in MS (NAIMS) Criteria by two trained raters blinded to clinical data and Gd use. The proportion of CVS+ lesions was calculated for each scan, and differences in CVS detection based on Gd use were assessed by a Wilcoxon rank-sum test. Diagnostic performance was compared against McDonald 2017 Criteria.
The mean participant age was 45 years (SD: 12); 23 (77%) were women. 14 (47%) met McDonald 2017 Criteria for MS, while 16 (53%) did not (“non-MS”). A total of 487 CVS+ lesions and 976 CVS- lesions were evaluated. The percentage of CVS+ lesions post-Gd in the MS group (median 67% [IQR 30%]) was higher than pre-Gd (41% [47%], p<0.001). There was no apparent difference in percentage of CVS+ lesion in the non-MS group (post-Gd: 10% [23%]; pre-Gd: 5% [29%]; p=0.1). In the MS group, 12/14 (86%) had ≥40% CVS+ lesions on post-Gd imaging, whereas only 8/14 (57%) exceeded that threshold on pre-Gd imaging. When evaluating CVS performance using the 40% CVS+ threshold, the sensitivity and specificity of the CVS post-Gd for MS were 86% and 81%, respectively, compared to 54% and 86% pre-Gd.
The detection of the CVS using FLAIR* at 3T is improved when Gd is used. Based on these results, a multicenter prospective CVS diagnostic study, sponsored by NINDS and NAIMS, will use Gd in the study protocol. Future clinical use of the CVS should balance the increased costs and potential risks of Gd use with the risks of misdiagnosis due to missing CVS on non-contrast imaging.
P0542 - Assessment of central vein sign conspicuity in multicenter 3T FLAIR* imaging (ID 985)
- Q. Cao
- M. Martin
- B. Renner
- L. Daboul
- C. O'Donnell
- D. Moreno-Dominguez
- P. Rodrigues
- J. Derbyshire
- C. Azevedo
- A. Bar-Or
- E. Caverzasi
- P. Calabresi
- B. Cree
- L. Freeman
- R. Henry
- E. Longbrake
- J. Oh
- N. Papinutto
- R. Samudralwar
- M. Schindler
- E. Sotirchos
- N. Sicotte
- A. Solomon
- R. Shinohara
- D. Reich
- D. Ontaneda
- P. Sati
The central vein sign (CVS) is a proposed diagnostic biomarker for MS that can be identified using FLAIR*. The robustness of 3T FLAIR*, with and without the injection of gadolinium contrast agent (Gd), for imaging the CVS in a multicenter setting has not yet been demonstrated.
To assess the conspicuity of the CVS on 3T FLAIR* imaging acquired across different sites with and without the injection of Gd.
A cross-sectional multicenter study recruited adults with a clinical and/or radiological suspicion of having MS from 10 sites within the North American Imaging in MS (NAIMS) Cooperative. High-isotropic-resolution T2*-weighted segmented echo-planar imaging (T2*-EPI) was acquired at 3T, pre- and post-injection of Gd, along with 3D FLAIR on different scanner brands and models. T2*-EPI and FLAIR images were processed on an online imaging platform (QMENTA) to generate FLAIR* images. To objectively assess the conspicuity of the CVS inside MS lesions, lesions and veins were segmented automatically and used to compute lesion-to-vein contrast-to-noise ratio (CNR) measures. ANOVA was used to compare CNR values across sites with post-hoc Tukey Honest Significant Difference testing. Multiple testing between sites was considered by controlling the false discovery rate. One-sided paired t-testing was used to compare the overall lesion-to-vein CNR values between pre- and post-Gd FLAIR*.
Seventy-eight patients from nine sites were included in the analysis; one site was excluded due to low enrollment. The overall mean(coefficient of variation, CV) lesion-to-vein CNR values across the nine sites were 0.35(14%) and 0.37(12%) for pre- and post-Gd FLAIR*, respectively. Excluding an additional site that used an unharmonized FLAIR acquisition, the resulting mean(CV) CNR values were 0.36(12%) for pre-Gd and 0.37(11%) for post-Gd FLAIR*. Across most sites, there was a significant improvement in lesion-to-vein CNR measures for post-Gd compared to pre-Gd FLAIR* [mean difference = 0.011, p < 0.001, 95% CI: (0.008,0.015)].
Lesion-to-vein CNR measures across sites are in line with values first published for 3T FLAIR* and demonstrate the robustness of 3T FLAIR* for imaging the CVS in a multicenter setting. Moreover, there was an increase in vein conspicuity with improvement in CNR on post-Gd FLAIR*. Based on these results, a prospective multicenter NAIMS CVS diagnostic study, sponsored by NINDS, will use 3T FLAIR* imaging with Gd in the study protocol.
P0856 - Collecting real world MRI in MS: preliminary results from FlywheelMS (ID 1226)
Real-world evidence can be used to better characterize the course of multiple sclerosis (MS), care provision and outcomes in clinical practice. Magnetic resonance imaging (MRI) that occurs in the context of usual care is an important source of information that can inform clinical decision-making. Guidelines exist to enhance the clinical impact of routine MRI in MS, but it is unclear whether MRIs acquired as part of routine care in the United States adhere to these guidelines.
To describe the clinical routine brain MRIs from patients with MS across different US imaging sites.
FlywheelMS is a novel patient-centered study that aims to extract and digitize health information not readily available in existing electronic health records of patients with MS. Up to 5,000 consenting adults with a confirmed MS diagnosis will be enrolled. Brain MRI data were retrieved, and summary statistics were computed to describe the sessions, imaging sites, scanner field strengths and slice thickness of T1-weighted and FLAIR (fluid-attenuated inversion recovery) images. Longitudinal acquisition consistency (i.e. MRIs acquired from the same center with the same scanner) was also assessed.
Out of 2,389 patients enrolled, 1555 brain MRI data were retrieved from the first 492 patients (female, 81%; mean age at consent, 49±11 years). The mean number of MRI sessions per patient was 3.2±2.4, and data were captured between 1999 and 2018. Sessions were acquired at 598 different imaging sites, using mainly 1.5T scanners (61.3%), followed by 3T (32.7%) and lower field-strength magnets (3.4%; not available, 2.6%). The mean slice thickness of T1-weighted (3.1±1.7 mm) and FLAIR images (3.1±1.3 mm) was similar. Of the 352 patients (72%) that had more than one MRI session, 85 (24.1%) had consistent acquisition (i.e. same site/scanner), 153 (43.5%) had one site or scanner change, and 114 (32.4%) had more than one site and/or scanner change.
The novel, patient-centered approach of FlywheelMS can successfully extract imaging data from medical records of patients with MS across US imaging sites. These data will help us in describing the clinical routine MRI, determining the compliance to guidelines and understanding which measure (e.g. lesion volume and/or atrophy) could be potentially extracted from MRI data.