计算机面部匹配技术使用二维照片，能够准确地将具有相同综合征形式智力障碍的无关个体的面部整体特征进行匹配。
Computer face-matching technology using two-dimensional photographs accurately matches the facial gestalt of unrelated individuals with the same syndromic form of intellectual disability.
机构信息
Hunter Genetics, Hunter New England Health Service, Newcastle, NSW, Australia.
GrowUpWell, Priority of Research Excellence, The University of Newcastle, Newcastle, NSW, Australia.
出版信息
BMC Biotechnol. 2017 Dec 19;17(1):90. doi: 10.1186/s12896-017-0410-1.
BACKGROUND
Massively parallel genetic sequencing allows rapid testing of known intellectual disability (ID) genes. However, the discovery of novel syndromic ID genes requires molecular confirmation in at least a second or a cluster of individuals with an overlapping phenotype or similar facial gestalt. Using computer face-matching technology we report an automated approach to matching the faces of non-identical individuals with the same genetic syndrome within a database of 3681 images [1600 images of one of 10 genetic syndrome subgroups together with 2081 control images]. Using the leave-one-out method, two research questions were specified: 1) Using two-dimensional (2D) photographs of individuals with one of 10 genetic syndromes within a database of images, did the technology correctly identify more than expected by chance: i) a top match? ii) at least one match within the top five matches? or iii) at least one in the top 10 with an individual from the same syndrome subgroup? 2) Was there concordance between correct technology-based matches and whether two out of three clinical geneticists would have considered the diagnosis based on the image alone?
RESULTS
The computer face-matching technology correctly identifies a top match, at least one correct match in the top five and at least one in the top 10 more than expected by chance (P < 0.00001). There was low agreement between the technology and clinicians, with higher accuracy of the technology when results were discordant (P < 0.01) for all syndromes except Kabuki syndrome.
CONCLUSIONS
Although the accuracy of the computer face-matching technology was tested on images of individuals with known syndromic forms of intellectual disability, the results of this pilot study illustrate the potential utility of face-matching technology within deep phenotyping platforms to facilitate the interpretation of DNA sequencing data for individuals who remain undiagnosed despite testing the known developmental disorder genes.
背景
大规模并行基因测序允许快速测试已知的智力障碍（ID）基因。然而，发现新的综合征 ID 基因需要在至少两个或一群具有重叠表型或相似面部整体特征的个体中进行分子确认。我们使用计算机面部匹配技术报告了一种自动方法，用于在一个 3681 个图像数据库[10 个遗传综合征亚组中的一个的 1600 个图像，以及 2081 个对照图像]中匹配具有相同遗传综合征的非同一个体的面部。使用留一法，指定了两个研究问题：1）使用 10 个遗传综合征亚组之一的个体的二维（2D）照片，该技术是否正确识别了比预期更多的个体：i）最佳匹配？ii）在前五个匹配中至少有一个匹配？或 iii）在前 10 个中有一个与同一综合征亚组的个体？2）基于技术的正确匹配与是否有两位临床遗传学家会仅根据图像考虑诊断之间是否存在一致性？
结果
计算机面部匹配技术正确识别了一个最佳匹配，在前五个中至少有一个正确匹配，在前 10 个中至少有一个匹配，这比随机预期的要多（P<0.00001）。该技术与临床医生之间的一致性较低，当结果不一致时，技术的准确性更高（P<0.01），除了歌舞伎综合征外，对于所有综合征都是如此。
结论
尽管计算机面部匹配技术的准确性是在已知综合征形式的智力障碍个体的图像上进行测试的，但这项初步研究的结果说明了面部匹配技术在深度表型平台中的潜在应用，以促进对尽管测试了已知发育障碍基因但仍未诊断的个体的 DNA 测序数据的解释。
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