A Multicenter Longitudinal MRI Study Assessing LeMan‐PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients
Authors: Todea Alexandra Ramona , Melie‐Garcia Lester , Barakovic Muhamed , Cagol Alessandro , Rahmanzadeh Reza , Galbusera Riccardo , Lu Po‐Jui , Weigel Matthias , Ruberte Esther , Radue Ernst‐Wilhelm , Schaedelin Sabine , Benkert Pascal , Oezguer Yaldizli , Sinnecker Tim , Müller Stefanie , Achtnichts Lutz , Vehoff Jochen , Disanto Giulio , Findling Oliver , Chan Andrew , Salmen Anke , Pot Caroline , Lalive Patrice , Bridel Claire , Zecca Chiara , Derfuss Tobias , Remonda Luca , Wagner Franca , Vargas Maria , Du Pasquier Renaud , Pravata Emanuele , Weber Johannes , Gobbi Claudio , Leppert David , Wuerfel Jens , Kober Tobias , Marechal Benedicte , Corredor‐Jerez Ricardo , Psychogios Marios , Lieb Johanna , Kappos Ludwig , Cuadra Meritxell Bach , Kuhle Jens , Granziera Cristina ,   for the Swiss MS Cohort Study
Published: January 2023

Background

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.

Purpose

To assess the accuracy of LeMan‐PV for the longitudinal detection NEL white‐matter MS lesions in a multicenter clinical setting.

Study Type

Retrospective, longitudinal.

Subjects

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.

Field Strength/Sequence

Fluid attenuated inversion recovery (FLAIR) and T1‐weighted magnetization prepared rapid gradient echo (T1‐MPRAGE) sequences at 1.5 T and 3 T.

Assessment

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.

Statistical Tests

Intraclass correlation coefficient (ICC) and Cohen's kappa (CK) were used to evaluate the agreement between readers.

Results

The interreader agreement was high for detecting new lesions (ICC = 0.97, Pvalue < 10−20, CK = 0.82, P value = 0) and good (ICC = 0.75, P value < 10−12, 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).

Data Conclusion

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.

Evidence Level

4

Technical Efficacy

Stage 2