A Clinically-Compatible Workflow for Computer-Aided Assessment of Brain Disease Activity in Multiple Sclerosis Patients

Benoit Combès; Anne Kerbrat; Guillaume Pasquier; Olivier Commowick; Brandon Le Bon; Francesca Galassi; Philippe L'Hostis; Nora El Graoui; Raphael Chouteau; Emmanuel Cordonnier; Gilles Edan; Jean-Christophe Ferré

doi:10.3389/fmed.2021.740248

A Clinically-Compatible Workflow for Computer-Aided Assessment of Brain Disease Activity in Multiple Sclerosis Patients

Front Med (Lausanne). 2021 Nov 3:8:740248. doi: 10.3389/fmed.2021.740248. eCollection 2021.

Authors

Affiliations

¹ Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France.
² Neurology Department, Rennes University Hospital, Rennes, France.
³ IRT bcom, Rennes, France.
⁴ Biotrial, Rennes, France.
⁵ CHU Rennes, Department of Neuroradiology, Rennes, France.

Abstract

Over the last 10 years, the number of approved disease modifying drugs acting on the focal inflammatory process in Multiple Sclerosis (MS) has increased from 3 to 10. This wide choice offers the opportunity of a personalized medicine with the objective of no clinical and radiological activity for each patient. This new paradigm requires the optimization of the detection of new FLAIR lesions on longitudinal MRI. In this paper, we describe a complete workflow-that we developed, implemented, deployed, and evaluated-to facilitate the monitoring of new FLAIR lesions on longitudinal MRI of MS patients. This workflow has been designed to be usable by both hospital and private neurologists and radiologists in France. It consists of three main components: (i) a software component that allows for automated and secured anonymization and transfer of MRI data from the clinical Picture Archive and Communication System (PACS) to a processing server (and vice-versa); (ii) a fully automated segmentation core that enables detection of focal longitudinal changes in patients from T1-weighted, T2-weighted and FLAIR brain MRI scans, and (iii) a dedicated web viewer that provides an intuitive visualization of new lesions to radiologists and neurologists. We first present these different components. Then, we evaluate the workflow on 54 pairs of longitudinal MRI scans that were analyzed by 3 experts (1 neuroradiologist, 1 radiologist, and 1 neurologist) with and without the proposed workflow. We show that our workflow provided a valuable aid to clinicians in detecting new MS lesions both in terms of accuracy (mean number of detected lesions per patient and per expert 1.8 without the workflow vs. 2.3 with the workflow, p = 5.10^-4) and of time dedicated by the experts (mean time difference 2'45″, p = 10^-4). This increase in the number of detected lesions has implications in the classification of MS patients as stable or active, even for the most experienced neuroradiologist (mean sensitivity was 0.74 without the workflow and 0.90 with the workflow, p-value for no difference = 0.003). It therefore has potential consequences on the therapeutic management of MS patients.

Keywords: MRI; Multiple Sclerosis; computer aided diagnosis; lesion activity; radiology.