Reliability of measuring regional callosal atrophy in neurodegenerative diseases.
The Corpus Callosum (CC) is an important structure connecting the two brain hemispheres. As several neurodegenerative diseases are known to alter its shape, it is an interesting structure to assess as biomarker. Yet, currently, the CC-segmentation is often performed manually and is consequently an error prone and time-demanding procedure. In this paper, we present an accurate and automated method for corpus callosum segmentation based on T1-weighted MRI images. After the initial construction of a CC atlas based on healthy controls, a new image is subjected to a mid-sagittal plane (MSP) detection algorithm and a 3D affine registration in order to initialise the CC within the extracted MSP. Next, an active shape model is run to extract the CC. We calculated the reliability of most popular CC features (area, circularity, corpus callosum index and thickness profile) in healthy controls, Alzheimer's Disease patients and Multiple Sclerosis patients. Importantly, we also provide inter-scanner reliability estimates. We obtained an intra-class correlation coefficient (ICC) of over 0.95 for most features and most datasets. The inter-scanner reliability assessed on the MS patients was remarkably well and ranged from 0.77 to 0.97. In summary, we have constructed an algorithm that reliably detects the CC in 3D T1 images in a fully automated way in healthy controls and different neurodegenerative diseases. Although the CC area and the circularity are the most reliable features (ICC > 0.97); the reliability of the thickness profile (ICC > 0.90; excluding the tip) is sufficient to warrant its inclusion in future clinical studies.
Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Jeroen
J
Van Schependom
Icometrix NV, Kolonel Begaultlaan 1B, 3012 Leuven, Belgium.
Saurabh
S
Jain
Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Melissa
M
Cambron
Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Anne-Marie
AM
Vanbinst
Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Johan
J
De Mey
Icometrix NV, Kolonel Begaultlaan 1B, 3012 Leuven, Belgium.
Dirk
D
Smeets
Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; Faculté de Psychologie et des Sciences de l'Education, Place du Parc 20, 7000 Mons, Belgium; National MS Center Melsbroek, Vanheylenstraat 16, 1820 Melsbroek, Belgium.
Guy
G
Nagels
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001271:Atlases as Topic; D001284:Atrophy; D015415:Biomarkers; D003337:Corpus Callosum / Q000000981:diagnostic imaging / Q000473:pathology*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging / Q000473:pathology; D019636:Neurodegenerative Diseases / Q000000981:diagnostic imaging / Q000473:pathology*; D015203:Reproducibility of Results; D055815:Young Adult
D015415:Biomarkers
Alzheimer's disease; Biomarker; Corpus callosum segmentation; Corpus callosum thickness profile; Multiple sclerosis; Repeatability; Reproducibility