Distinctive facial features in idiopathic Moyamoya disease in Caucasians: a first systematic analysis.

PeerJ 2018 27;6:e4740. Epub 2018 Jun 27.

Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Nederlands.

Background: Craniofacial dysmorphic features are morphological changes of the face and skull which are associated with syndromic conditions. Moyamoya angiopathy is a rare cerebral vasculopathy that can be divided into Moyamoya syndrome, which is associated or secondary to other diseases, and into idiopathic Moyamoya disease. Facial dysmorphism has been described in rare genetic syndromes with associated Moyamoya syndrome. However, a direct relationship between idiopathic Moyamoya disease with dysmorphic facial changes is not known yet.

Methods: Landmarks were manually placed on frontal photographs of the face of 45 patients with bilateral Moyamoya disease and 50 matched controls. After procrustes alignment of landmarks a multivariate, penalized logistic regression (elastic-net) was performed on geometric features derived from landmark data to classify patients against controls. Classifiers were visualized in importance plots that colorcode importance of geometric locations for the classification decision.

Results: The classification accuracy for discriminating the total patient group from controls was 82.3% (-value = 6.3×10, binomial test, a-priori chance 50.2%) for an elastic-net classifier. Importance plots show that differences around the eyes and forehead were responsible for the discrimination. Subgroup analysis corrected for body mass index confirmed a similar result.

Discussion: Results suggest that there is a resemblance in faces of Caucasian patients with idiopathic Moyamoya disease and that there is a difference to matched controls. Replication of findings is necessary as it is difficult to control all residual confounding in study designs such as ours. If our results would be replicated in a larger cohort, this would be helpful for pathophysiological interpretation and early detection of the disease.

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http://dx.doi.org/10.7717/peerj.4740DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029584PMC
June 2018
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References

(Supplied by CrossRef)
Pathophysiology and genetic factors in Moyamoya disease
Achrol et al.
Neurosurgical Focus 2009
Automated syndrome detection in a set of clinical facial photographs
Boehringer et al.
American Journal of Medical Genetics Part A 2011
Smith-Magenis syndrome and Moyamoya disease in a patient with del(17)(p11.2p13.1)
Girirajan et al.
American Journal of Medical Genetics Part A 2007
Moyamoya disease and syndromes: from genetics to clinical management
Guey et al.
Application of Clinical Genetics 2015
Reconstruction of images from Gabor graphs with applications in facial image processing
Günther et al.
International Journal of Wavelets, Multiresolution and Information Processing 2015

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