Yoshida Akifumi, Kondo Yohan, Yoshimura Norihiko, Kuramoto Tatsuya, Hasegawa Akira, Kanazawa Tsutomu
Department of Medical Technology, Niigata University of Health and Welfare, 1398 Shimamichou, Kita-ku, Niigata, 951-3198, Japan.
Graduate School of Health Sciences, Niigata University, 2-746 Asahimachi-dori, Chuo-ku, Niigata, 951-8518, Japan.
Radiol Phys Technol. 2022 Jun;15(2):156-169. doi: 10.1007/s12194-022-00657-3. Epub 2022 May 7.
This study aimed to determine whether a U-Net-based segmentation method could be used to automatically extract regions of the whole heart and atrioventricular regions from pediatric cardiac computed tomography images with high accuracy. Pediatric cardiac contrast computed tomography images with no abnormalities (n = 20; patient age, 0-13 years; mean 5 years) were used for segmentation of the whole heart and each atrioventricular region using U-Net. Segmentation accuracy was evaluated using the Dice similarity coefficient. The mean Dice similarity coefficient for the whole-heart segmentation was high at 0.95. There were no significant differences between age categories. The median Dice similarity coefficients for segmentation of the atria and ventricles were good (> 0.86). There were significant differences between age categories at some sites. Differences in the Dice similarity coefficient may have occurred because the target diseases and examination procedures differed according to subject age. There was no clear tendency for similar values between subjects of school age, close to adulthood, and newborns; good agreement was obtained in all age categories. These results suggest that U-Net-based segmentation may be useful for automatic extraction of the whole heart and atrioventricular regions from pediatric computed tomography images.
本研究旨在确定基于U-Net的分割方法是否可用于从儿科心脏计算机断层扫描图像中高精度地自动提取全心区域和房室区域。使用无异常的儿科心脏对比计算机断层扫描图像（n = 20；患者年龄，0 - 13岁；平均5岁），通过U-Net对全心和每个房室区域进行分割。使用Dice相似系数评估分割精度。全心分割的平均Dice相似系数较高，为0.95。各年龄组之间无显著差异。心房和心室分割的Dice相似系数中位数良好（> 0.86）。在某些部位，各年龄组之间存在显著差异。Dice相似系数的差异可能是由于目标疾病和检查程序因受试者年龄而异。学龄期、接近成年期和新生儿的受试者之间没有明显的相似值趋势；所有年龄组均获得了良好的一致性。这些结果表明，基于U-Net的分割可能有助于从儿科计算机断层扫描图像中自动提取全心和房室区域。
