A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients.

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Version: Final published version
License: CC BY-NC 4.0
Serval ID
serval:BIB_FC74FD68A743
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients.
Journal
Journal of magnetic resonance imaging
Author(s)
Todea A.R., Melie-Garcia L., Barakovic M., Cagol A., Rahmanzadeh R., Galbusera R., Lu P.J., Weigel M., Ruberte E., Radue E.W., Schaedelin S., Benkert P., Oezguer Y., Sinnecker T., Müller S., Achtnichts L., Vehoff J., Disanto G., Findling O., Chan A., Salmen A., Pot C., Lalive P., Bridel C., Zecca C., Derfuss T., Remonda L., Wagner F., Vargas M., Du Pasquier R., Pravata E., Weber J., Gobbi C., Leppert D., Wuerfel J., Kober T., Marechal B., Corredor-Jerez R., Psychogios M., Lieb J., Kappos L., Cuadra M.B., Kuhle J., Granziera C.
Working group(s)
Swiss MS Cohort Study
ISSN
1522-2586 (Electronic)
ISSN-L
1053-1807
Publication state
Published
Issued date
09/2023
Peer-reviewed
Oui
Volume
58
Number
3
Pages
864-876
Language
english
Notes
Publication types: Multicenter Study ; Journal Article
Publication Status: ppublish
Abstract
Detecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarged white matter lesions (NELs) in the follow-up of MS patients; however, multicenter validation studies are lacking.
To assess the accuracy of LeMan-PV for the longitudinal detection NEL white-matter MS lesions in a multicenter clinical setting.
Retrospective, longitudinal.
A total of 206 patients with a definitive MS diagnosis and at least two follow-up MRI studies from five centers participating in the Swiss Multiple Sclerosis Cohort study. Mean age at first follow-up = 45.2 years (range: 36.9-52.8 years); 70 males.
Fluid attenuated inversion recovery (FLAIR) and T1-weighted magnetization prepared rapid gradient echo (T1-MPRAGE) sequences at 1.5 T and 3 T.
The study included 313 MRI pairs of datasets. Data were analyzed with LeMan-PV and compared with a manual "reference standard" provided by a neuroradiologist. A second rater (neurologist) performed the same analysis in a subset of MRI pairs to evaluate the rating-accuracy. The Sensitivity (Se), Specificity (Sp), Accuracy (Acc), F1-score, lesion-wise False-Positive-Rate (aFPR), and other measures were used to assess LeMan-PV performance for the detection of NEL at 1.5 T and 3 T. The performance was also evaluated in the subgroup of 123 MRI pairs at 3 T.
Intraclass correlation coefficient (ICC) and Cohen's kappa (CK) were used to evaluate the agreement between readers.
The interreader agreement was high for detecting new lesions (ICC = 0.97, Pvalue < 10 <sup>-20</sup> , CK = 0.82, P value = 0) and good (ICC = 0.75, P value < 10 <sup>-12</sup> , CK = 0.68, P value = 0) for detecting enlarged lesions. Across all centers, scanner field strengths (1.5 T, 3 T), and for NEL, LeMan-PV achieved: Acc = 61%, Se = 65%, Sp = 60%, F1-score = 0.44, aFPR = 1.31. When both follow-ups were acquired at 3 T, LeMan-PV accuracy was higher (Acc = 66%, Se = 66%, Sp = 66%, F1-score = 0.28, aFPR = 3.03).
In this multicenter study using clinical data settings acquired at 1.5 T and 3 T, and variations in MRI protocols, LeMan-PV showed similar sensitivity in detecting NEL with respect to other recent 3 T multicentric studies based on neural networks. While LeMan-PV performance is not optimal, its main advantage is that it provides automated clinical decision support integrated into the radiological-routine flow.
4 TECHNICAL EFFICACY: Stage 2.
Keywords
Male, Humans, Adult, Middle Aged, Multiple Sclerosis/diagnostic imaging, Multiple Sclerosis/pathology, White Matter/diagnostic imaging, White Matter/pathology, Cohort Studies, Retrospective Studies, Magnetic Resonance Imaging/methods, Brain/diagnostic imaging, Brain/pathology, lesion activity, lesion segmentation, longitudinal analysis, longitudinal lesion segmentation, multiple sclerosis, white matter lesions
Pubmed
Web of science
Open Access
Yes
Create date
27/02/2023 12:45
Last modification date
09/02/2024 9:55
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