Kraemer Markus, Huynh Quoc Bao, Wieczorek Dagmar, Balliu Brunilda, Mikat Barbara, Boehringer Stefan
Department of Neurology, Alfried Krupp Hospital Essen, Essen, Germany.
Department of Neurology, University Clinic of Duesseldorf, Duesseldorf, Germany.
PeerJ. 2018 Jun 27;6:e4740. doi: 10.7717/peerj.4740. eCollection 2018.
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.
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.
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.
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.
颅面畸形特征是面部和颅骨的形态学改变，与综合征性疾病相关。烟雾病是一种罕见的脑血管病，可分为与其他疾病相关或继发的烟雾综合征，以及特发性烟雾病。面部畸形已在与烟雾综合征相关的罕见遗传综合征中有所描述。然而，特发性烟雾病与面部畸形改变之间的直接关系尚不清楚。
在45例双侧烟雾病患者和50例匹配对照的面部正面照片上手动放置地标点。在地标点进行普氏配准后，对从地标数据导出的几何特征进行多变量惩罚逻辑回归（弹性网络），以对患者与对照进行分类。在重要性图中可视化分类器，该图对分类决策中几何位置的重要性进行颜色编码。
对于弹性网络分类器，将整个患者组与对照区分开的分类准确率为82.3%（P值=6.3×10，二项式检验，先验概率50.2%）。重要性图显示，眼睛和额头周围的差异是区分的原因。校正体重指数后的亚组分析证实了类似结果。
结果表明，患有特发性烟雾病的白种人患者面部存在相似之处，且与匹配对照存在差异。由于在我们这样的研究设计中难以控制所有残余混杂因素，因此有必要重复研究结果。如果我们的结果能在更大的队列中得到重复，这将有助于对该疾病进行病理生理学解释和早期检测。
