Department of Biomedical Engineering, Ankara University, Golbasi, Ankara, Turkey.
Department of Radiology, City Hospital, Bilkent, Ankara, Turkey; Department of Radiology, Yildirim Beyazit University, Ankara, Turkey; National MR Research Center (UMRAM), City Hospital, Bilkent University, Ankara, Turkey.
Comput Biol Med. 2020 Jan;116:103547. doi: 10.1016/j.compbiomed.2019.103547. Epub 2019 Nov 20.
Ventricles of the human brain enlarge with aging, neurodegenerative diseases, intrinsic, and extrinsic pathologies. The morphometric examination of neuroimages is an effective approach to assess structural changes occurring due to diseases such as hydrocephalus. In this study, we explored the effectiveness of commonly used morphological parameters in hydrocephalus diagnosis. For this purpose, the effect of six common morphometric parameters; Frontal Horns' Length (FHL), Maximum Lateral Length (MLL), Biparietal Diameter (BPD), Evans' Ratio (ER), Cella Media Ratio (CMR), and Frontal Horns' Ratio (FHR) were compared in terms of their importance in predicting hydrocephalus using a Random Forest classifier. The experimental results demonstrated that hydrocephalus can be detected with 91.46 % accuracy using all of these measurements. The accuracy of classification using only CMR and FHL reached up to 93.33 %. In terms of individual performances, CMR and FHL were the top performers whereas BPD and FHR did not contribute as much to the overall accuracy.
人脑的脑室随着年龄的增长、神经退行性疾病、内在和外在的病理而扩大。神经影像学的形态测量检查是评估由于脑积水等疾病引起的结构变化的有效方法。在这项研究中，我们探讨了常用形态参数在脑积水诊断中的有效性。为此，我们使用随机森林分类器比较了六个常见形态参数（额叶角长度[FHL]、最大侧长[MLL]、双额径[BPD]、埃文斯比[ER]、中脑比[CMR]和额叶角比[FHR]）在预测脑积水方面的重要性。实验结果表明，使用所有这些测量方法可以达到 91.46%的准确率来检测脑积水。仅使用 CMR 和 FHL 进行分类的准确率高达 93.33%。就个体表现而言，CMR 和 FHL 是表现最好的参数，而 BPD 和 FHR 对整体准确性的贡献不大。
