Salient Central Lesion Volume: A Standardized Novel Fully Automated Proxy for Brain FLAIR Lesion Volume in Multiple Sclerosis.
MRI
automated lesion detection
multiple sclerosis
proxy
Journal
Journal of neuroimaging : official journal of the American Society of Neuroimaging
ISSN: 1552-6569
Titre abrégé: J Neuroimaging
Pays: United States
ID NLM: 9102705
Informations de publication
Date de publication:
09 2019
09 2019
Historique:
received:
25
02
2019
revised:
17
06
2019
accepted:
18
06
2019
pubmed:
2
7
2019
medline:
20
6
2020
entrez:
2
7
2019
Statut:
ppublish
Résumé
Quantitative neuroimaging is an important part of multiple sclerosis research and clinical trials, and measures of lesion volume (LV) and brain atrophy are key clinical trial endpoints. However, translation of these endpoints to heterogeneous historical datasets and nonstandardized clinical routine imaging has been difficult. The NeuroSTREAM technique was recently introduced as a robust and broadly applicable surrogate for brain atrophy measurement, but no such surrogate currently exists for conventional T2-LV. Therefore, we sought to develop a fully automated proxy for T2-LV with similar analytic value but increased robustness to common issues arising in clinical routine imaging. We created an algorithm to identify salient central lesion volume (SCLV), comprised of the subset of lesion voxels within a specific distance to the lateral ventricles (centrality) and with intensity at least a quantitatively-derived amount brighter than normal appearing tissue (salience). We evaluated this method on four datasets (clinical, inter-scanner, scan-rescan, and real-world multi-center), including 1.5T, 3T, Philips, Siemens, and GE scanners with heterogeneous protocols, to assess agreement with conventional T2-LV, comparative relationship with disability, reliability across scanners and between scans, and applicability to real-world scans. SCLV correlated strongly with conventional T2-LV in both research-quality (r = .90, P < .001) and real-world (r = 0.87, P < 0.001) datasets. It also showed similar correlations with Expanded Disability Status Scale, as conventional T2-LV (r = 0.48 for T2-LV vs. r = 0.45 for SCLV). Inter-scanner reproducibility (ICC) was 0.86, p < 0.001 for SCLV compared to 0.84, p < 0.001 for conventional T2-LV, whereas scan-rescan ICC was 0.999 for SCLV versus 0.997 for T2-LV. SCLV is a robust, fully-automated proxy for T2-LV in situations where conventional T2-LV is not easily or reliably calculated.
Sections du résumé
BACKGROUND AND PURPOSE
Quantitative neuroimaging is an important part of multiple sclerosis research and clinical trials, and measures of lesion volume (LV) and brain atrophy are key clinical trial endpoints. However, translation of these endpoints to heterogeneous historical datasets and nonstandardized clinical routine imaging has been difficult. The NeuroSTREAM technique was recently introduced as a robust and broadly applicable surrogate for brain atrophy measurement, but no such surrogate currently exists for conventional T2-LV. Therefore, we sought to develop a fully automated proxy for T2-LV with similar analytic value but increased robustness to common issues arising in clinical routine imaging.
METHODS
We created an algorithm to identify salient central lesion volume (SCLV), comprised of the subset of lesion voxels within a specific distance to the lateral ventricles (centrality) and with intensity at least a quantitatively-derived amount brighter than normal appearing tissue (salience). We evaluated this method on four datasets (clinical, inter-scanner, scan-rescan, and real-world multi-center), including 1.5T, 3T, Philips, Siemens, and GE scanners with heterogeneous protocols, to assess agreement with conventional T2-LV, comparative relationship with disability, reliability across scanners and between scans, and applicability to real-world scans.
RESULTS
SCLV correlated strongly with conventional T2-LV in both research-quality (r = .90, P < .001) and real-world (r = 0.87, P < 0.001) datasets. It also showed similar correlations with Expanded Disability Status Scale, as conventional T2-LV (r = 0.48 for T2-LV vs. r = 0.45 for SCLV). Inter-scanner reproducibility (ICC) was 0.86, p < 0.001 for SCLV compared to 0.84, p < 0.001 for conventional T2-LV, whereas scan-rescan ICC was 0.999 for SCLV versus 0.997 for T2-LV.
CONCLUSIONS
SCLV is a robust, fully-automated proxy for T2-LV in situations where conventional T2-LV is not easily or reliably calculated.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
615-623Informations de copyright
© 2019 by the American Society of Neuroimaging.
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