Semi-automated image analysis of gel electrophoresis of cerebrospinal fluid for oligoclonal band detection

• Published in: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2016; pp. 744 - 747
• Main Authors: Boudet, S., Peyrodie, L., Wang, Z., Forzy, G.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01-08-2016
• Subjects: Biomembranes; Cerebrospinal Fluid - chemistry; Color; Distortion; DNA; Electrophoresis, Agar Gel; Fluids; Gray-scale; Humans; Image color analysis; Image Processing, Computer-Assisted; Immune system; Multiple Sclerosis - diagnosis; Oligoclonal Bands - chemistry
• ISSN: 1557-170X
• DOI: 10.1109/EMBC.2016.7590809

Detection of oligoclonal electrophoretic bands in cerebrospinal fluid (CSF) is an important diagnostic tool for Multiple Sclerosis (MS). Electrophoretic profiles are difficult to interpret due to low contrast and artefacts. A semi-automated method to ease analysis and to reduce subjectivity is presented. The method sequentially converts color images to grayscale, realigns bands, removes artifacts, then converts 2D images to a signal, before detecting, thresholding and editing peaks to optimize profiles. Such treated profiles (21 positive and 15 negative) are compared to ground truth analysis of an expert biologist. 16 profiles over 21 are well detected positive and 12 profiles over 15 are detected negative, results seem similar to inter-experts variability reported in literature.