Development of computerised scoring system for Chiari-like malformation associated pain and syringomyelia.

Lead Research Organisation: University of Surrey
Department Name: Vision Speech and Signal Proc CVSSP

Abstract

The aim of this new study is to build on the our current collaborative work to investigate the specific research question of what, and
what degree of, external conformational features are associated with problematic internal morphology (e.g. deep stop,
short muzzle, domed head, forward facing oelarge? eyes in shallow orbits and low set ears). This will be addressed
via the following objectives: 1.Develop a Machine learning-based regression model for CM and SM in the CKCS.
Previously we used a classifying model on 2D midline sagittal MRI. We will expand this model to a 3D analysis of features
determined from high-resolution three-dimensional (3D) magnetization-prepared rapid acquisition with gradient echo
(MPRAGE) and CT. 2.Develop a ML image assessment model to predict and score risk of CM-P and SM-S from diagnostic
MRI and CT. Use Correlated Correlation Analysis to understand how combinations of correlated breeding-related features
(short muzzle, domed forehead, depth of stop, wide palpebral apertures) externally correlate with problematic internal
morphology. 3.Expand the model to other brachycephalic breeds including the Chihuahua and Griffon Bruxellois.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R513350/1 01/10/2018 30/09/2023
2377477 Studentship EP/R513350/1 01/10/2019 30/09/2022 Jake Cumber