Division of Endocrinology, Department of Medicine, University of Kentucky, Lexington, KY 40503, USA.
Clin Endocrinol (Oxf). 2011 Aug;75(2):226-31. doi: 10.1111/j.1365-2265.2011.04020.x.
Early diagnosis of a number of endocrine diseases is theoretically possible by the examination of facial photographs. One of these is acromegaly. If acromegaly were found, early in the course of the disease, morbidity would be lessened and cures more likely. OBJECTIVES, DESIGN, PATIENTS, MEASUREMENTS: Our objective was to develop a computer program which would separate 24 facial photographs, of patients with acromegaly, from those of 25 normal subjects. The key to doing this was to use a previously developed database that consisted of three-dimensional representations of 200 normal person's heads (SIGGRAPH '99 Conference Proceedings, 1999). We transformed our 49, two-dimensional photos into three-dimensional constructs and then, using the computer program, attempted to separate them into those with and without the features of acromegaly. We compared the accuracy of the computer to that of 10 generalist physicians. A second objective was to examine, by a subjective analysis, the features of acromegaly in the normal subjects of our photographic database.
The accuracy of the computer model was 86%; the average of the 10 physicians was 26%. The worst individual physician, 16%, the best, 90%. The faces of 200 normal subjects, the original faces in the database, could be divided into four groups, averaged by computer, from those with fewer to those with more features of acromegaly.
The present computer model can sort photographs of patients with acromegaly from photographs of normal subjects and is much more accurate than the sorting by practicing generalists. Even normal subjects have some of the features of acromegaly. Screening with this approach can be improved with automation of the procedure, software development and the identification of target populations in which the prevalence of acromegaly may be increased over that in the general population.
通过面部照片的检查，理论上可以早期诊断出许多内分泌疾病。其中之一是肢端肥大症。如果在疾病早期发现肢端肥大症，发病率就会降低，治愈的可能性就会增加。
目的、设计、患者、测量：我们的目的是开发一种计算机程序，将 24 张肢端肥大症患者的面部照片与 25 名正常受试者的照片区分开来。做到这一点的关键是使用之前开发的数据库，该数据库由 200 名正常人头部的三维表示组成（SIGGRAPH '99 会议录，1999 年）。我们将我们的 49 张二维照片转换为三维结构，然后使用计算机程序尝试将它们分为具有和不具有肢端肥大症特征的照片。我们比较了计算机的准确性和 10 位普通医生的准确性。第二个目的是通过主观分析检查我们的摄影数据库中正常受试者的肢端肥大症特征。
计算机模型的准确率为 86%；10 位医生的平均准确率为 26%。最差的医生为 16%，最好的为 90%。通过计算机平均可以将数据库中原始面部的 200 名正常受试者的面部分为具有较少和较多肢端肥大症特征的四个组。
目前的计算机模型可以将肢端肥大症患者的照片与正常受试者的照片区分开来，而且比普通医生的分类准确率高得多。即使是正常受试者也有一些肢端肥大症的特征。通过这种方法进行筛查可以通过程序自动化、软件开发和识别肢端肥大症患病率可能高于普通人群的目标人群来提高。
