Multiple Sclerosis Disease Evolution Assessment in Brain MRI Lesions Based on Texture and Multi-Scale Amplitude Modulation-Frequency Modulation (AM-FM) Features

• Published in: IEEE access 2023-01, Vol.11, p.1-1
• Main Authors: Loizou, Christos P., Fotso, Kevin, Nicolaou, Antria, Pantzaris, M., Pattichis, Marios S., Pattichis, Constantinos. S.
• Format: Article
• Language: English
• Subjects: AM-FM analysis; Amplitude modulation; Biomedical monitoring; Brain; Classification; Classification analysis; Decision making; Disease evolution; Diseases; EDSS; Evolution; Feature extraction; Frequency modulation; Image registration; Lesions; Magnetic resonance imaging; Medical imaging; MRI; Multiple sclerosis; Texture; Texture analysis; Time measurement; White matter
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3260982

Background : Monitoring disease evolution in Multiple sclerosis (MS) subjects may aid in decision making for personalizing treatment and disease evolution prediction. We investigate the use of disability progression, using clinical features, the expanded disability status scale (EDSS), and their relationship with texture features and Amplitude Modulation-Frequency Modulation (AM-FM) features extracted from MRI MS detectable lesions for the prognosis of future disability on magnetic resonance imaging (MRI). Methods : MS detectable brain lesions from N=38 symptomatic untreated subjects diagnosed with clinically isolated syndrome (CIS), were manually segmented, by an experienced MS neurologist, on transverse T2-weighted (T 2 W) images obtained from serial brain MRI scans at the baseline (Time 0M ) and the repeat (Time 6-12M ) examinations. The subjects were separated into two different groups based on their EDSS: (G 1 : 1≤EDSS 2Y ≤3.5 (N=26) and G 2 : 3.5