West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, China.
School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China.
Forensic Sci Int. 2020 Sep;314:110350. doi: 10.1016/j.forsciint.2020.110350. Epub 2020 Jun 25.
The developmental patterns of the pelvic epiphyses are one of the anatomical markers used in the assessment of skeletal age and the legally relevant age threshold. In this study, four regression models and five classification models were developed for forensic age estimation and the determination of the 18-year threshold, respectively. A total of 2137 conventional pelvic radiographs (1215 males and 922 females) aged 10.00-25.99 years were analyzed, and the ossification and fusion of the iliac crest and ischial tuberosity epiphyses were scored separately. The epiphyses on both sides were used as inputs for all models. The accuracy of the regression models was compared using the mean absolute error (MAE) and root mean square error. The percentages of correct classifications were evaluated for the determination of the 18-year threshold. Support vector regression (SVR) and gradient boosting regression (GBR) showed higher accuracy for age estimation in both sexes. The lowest MAE was 1.38 years in males when using SVR and 1.16 years in females when using GBR. In the demarcation of minors and adults, the percentage of correct classification was over 92%, and the area under the receiver operating characteristic curves was over 0.91 in all models, except the Bernoulli naive Bayes classifier. This study demonstrated that the present models may be helpful for age estimation and the determination of the 18-year threshold. However, owing to the high effective dose of ionizing radiation used during conventional radiography of the pelvis, it is expected that these models will be tested with pelvic MRI for age estimation.
骨盆骺的发育模式是评估骨骼年龄和法定相关年龄界限的解剖学标志之一。本研究分别为法医年龄估计和 18 岁界限的确定开发了四个回归模型和五个分类模型。总共分析了 2137 张常规骨盆 X 光片（1215 名男性和 922 名女性），年龄在 10.00-25.99 岁之间，分别对骺的髂嵴和坐骨结节的骨化和融合进行评分。所有模型均使用两侧骺作为输入。使用平均绝对误差（MAE）和均方根误差比较回归模型的准确性。评估确定 18 岁界限的正确分类百分比。支持向量回归（SVR）和梯度提升回归（GBR）在两性中的年龄估计准确性更高。SVR 在男性中的 MAE 最低为 1.38 岁，GBR 在女性中的 MAE 最低为 1.16 岁。在未成年人和成年人的划分中，所有模型的正确分类百分比均超过 92%，除了伯努利朴素贝叶斯分类器外，所有模型的接收者操作特征曲线下的面积均超过 0.91。本研究表明，目前的模型可能有助于年龄估计和 18 岁界限的确定。然而，由于骨盆常规 X 光检查使用的电离辐射有效剂量较高，预计这些模型将通过骨盆 MRI 进行年龄估计测试。
