The need for improved brain lesion segmentation techniques for children with cerebral palsy: A review

Pagnozzi, Alex M., Gal, Yaniv, Boydm, Roslyn N., Fiori, Simona, Fripp, Jurgen, Rose, Stephen and Dowson, Nicholas (2015) The need for improved brain lesion segmentation techniques for children with cerebral palsy: A review. International Journal of Developmental Neuroscience, 47 Part B: 229-246. doi:10.1016/j.ijdevneu.2015.08.004

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Author Pagnozzi, Alex M.
Gal, Yaniv
Boydm, Roslyn N.
Fiori, Simona
Fripp, Jurgen
Rose, Stephen
Dowson, Nicholas
Title The need for improved brain lesion segmentation techniques for children with cerebral palsy: A review
Journal name International Journal of Developmental Neuroscience   Check publisher's open access policy
ISSN 1873-474X
Publication date 2015-09-21
Year available 2015
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1016/j.ijdevneu.2015.08.004
Open Access Status File (Author Post-print)
Volume 47
Issue Part B
Start page 229
End page 246
Total pages 18
Place of publication Oxford, United Kingdom
Publisher Pergamon Press
Language eng
Abstract Cerebral palsy (CP) describes a group of permanent disorders of posture and movement caused by disturbances in the developing brain. Accurate diagnosis and prognosis, in terms of motor type and severity, is difficult to obtain due to the heterogeneous appearance of brain injury and large anatomical distortions commonly observed in children with CP. There is a need to optimise treatment strategies for individual patients in order to lead to lifelong improvements in function and capabilities. Magnetic resonance imaging (MRI) is critical to non-invasively visualizing brain lesions, and is currently used to assist the diagnosis and qualitative classification in CP patients. Although such qualitative approaches under-utilise available data, the quantification of MRIs is not automated and therefore not widely performed in clinical assessment. Automated brain lesion segmentation techniques are necessary to provide valid and reproducible quantifications of injury. Such techniques have been used to study other neurological disorders, however the technical challenges unique to CP mean that existing algorithms require modification to be sufficiently reliable, and therefore have not been widely applied to MRIs of children with CP. In this paper, we present a review of a subset of available brain injury segmentation approaches that could be applied to CP, including the detection of cortical malformations, white and grey matter lesions and ventricular enlargement. Following a discussion of strengths and weaknesses, we suggest areas of future research in applying segmentation techniques to the MRI of children with CP. Specifically, we identify atlas-based priors to be ineffective in regions of substantial malformations, instead propose relying on adaptive, spatially consistent algorithms, with fast initialisation mechanisms to provide additional robustness to injury. We also identify several cortical shape parameters that could be used to identify cortical injury, and shape modelling approaches to identify anatomical injury. The benefits of automatic segmentation in CP is important as it has the potential to elucidate the underlying relationship between image derived features and patient outcome, enabling better tailoring of therapy to individual patients.
Keyword Cerebral palsy
Magnetic resonance imaging
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
School of Medicine Publications
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Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
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