Multiple Sclerosis: Identification of Temporal Changes in Brain Lesions with Computer-Assisted Detection Software

• Published in: The neuroradiology journal Vol. 26; no. 2; pp. 143 - 150
• Main Authors: Bilello, M., Arkuszewski, M., Nucifora, P., Nasrallah, I., Melhem, E.R., Cirillo, L., Krejza, J.
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.04.2013
• Subjects: Adult; Aged; Area Under Curve; Brain - pathology; Brain - physiopathology; Brain Mapping; Disease Progression; Female; Follow-Up Studies; Humans; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Male; Middle Aged; Multiple Sclerosis - pathology; Sensitivity and Specificity; Software; Young Adult; computer assessment; magnetic resonance; brain lesions; imaging; multiple sclerosis
• ISSN: 1971-4009; 2385-1996
• DOI: 10.1177/197140091302600202

Multiple sclerosis (MS) is a chronic disease with a progressing and evolving course. Serial imaging with MRI is the mainstay in monitoring and managing MS patients. In this work we demonstrate the performance of a locally developed computer-assisted detection (CAD) software used to track temporal changes in brain MS lesions. CAD tracks changes in T2-bright MS lesions between two time points on a 3D high-resolution isotropic FLAIR MR sequence of the brain acquired at 3 Tesla. The program consists of an image-processing pipeline, and displays scrollable difference maps used as an aid to the neuroradiologist for assessing lesional change. To assess the value of the software we have compared diagnostic accuracy and duration of interpretation of the CAD-assisted and routine clinical interpretations in 98 randomly chosen, paired MR examinations from 88 patients (68 women, 20 men, mean age 43.5, age range 21–75) with a diagnosis of definite MS. The ground truth was determined by a three-expert panel. In case-wise analysis, CAD interpretation showed higher sensitivity than a clinical report (87% vs 77%, respectively). Lesion-wise analysis demonstrated improved sensitivity of CAD over a routine clinical interpretation of 40%–48%. Mean software-assisted interpretation time was 2.7 min. Our study demonstrates the potential of including CAD software in the workflow of neuroradiology practice for the detection of MS lesional change. Automated quantification of temporal change in MS lesion load may also be used in clinical research, e.g., in drug trials.