Cortical thickness measurement estimated from high-resolution anatomical MRI scans may serve as a marker of cortical atrophy in clinical research applications. Most of the working algorithms and pipelines are optimized for human in-vivo data analyses that offer robust and reproducible measures. As animal-models are widely utilized in many preclinical phases of clinical trials the need for an optimized automated MRI data analysis to yield reliable data is warranted. We present a processing pipeline optimized for cortical thickness estimation of canine brains in native and template spaces. Preliminary results of 5 healthy and 5 mucopolysaccharidosis (MPS) dogs demonstrate single-canine mean/median cortical thickness in range of 2.69-3.58mm in native space and 3.26-4.15mm in template space. Our MRI generated values exceed previous histological measurements (observed mean about 2mm) in limited literature reports. Randomly selected manual measures corroborated the ranges defined by estimated cortical thickness probability density functions. Geometric transformations between native and template spaces change absolute mean/median cortical thickness values, but do not change the data nature and properties since the Pearson correlation coefficients between different space estimates were 0.84 for mean values and 0.89 for median values. No significant difference in total cortical thickness between MPS and age-and gender-matched dogs was observed.
|Title of host publication
|2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - Jul 2019
|41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
Duration: Jul 23 2019 → Jul 27 2019
|Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
|41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
|7/23/19 → 7/27/19
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© 2019 IEEE.