In kidney transplantation, a contrast CT scan is obtained in the donor candidate to detect subclinical pathology in the kidney. Recent work from the Aging Kidney Anatomy study has characterized kidney, cortex, and medulla volumes using a manual image-processing tool. However, this technique is time consuming and impractical for clinical care, and thus, these measurements are not obtained during donor evaluations. This study proposes a fully automated segmentation approach for measuring kidney, cortex, and medulla volumes.

A total of 1930 contrast-enhanced CT exams with reference standard manual segmentations from one institution were used to develop the algorithm. A convolutional neural network model was trained (n=1238) and validated (n=306), and then evaluated in a hold-out test set of reference standard segmentations (n=386). After the initial evaluation, the algorithm was further tested on datasets originating from two external sites (n=1226).

The automated model was found to perform on par with manual segmentation, with errors similar to interobserver variability with manual segmentation. Compared with the reference standard, the automated approach achieved a Dice similarity metric of 0.94 (right cortex), 0.90 (right medulla), 0.94 (left cortex), and 0.90 (left medulla) in the test set. Similar performance was observed when the algorithm was applied on the two external datasets.

A fully automated approach for measuring cortex and medullary volumes in CT images of the kidneys has been established. This method may prove useful for a wide range of clinical applications.

在肾移植中，对候选供体进行对比 CT 扫描，以检测肾脏的亚临床病理。衰老肾脏解剖学研究的最新工作使用手动图像处理工具对肾脏、皮质和髓质体积进行了表征。然而，这种技术耗时且对于临床护理来说不切实际，因此，在捐赠者评估期间无法获得这些测量结果。这项研究提出了一种用于测量肾脏、皮质和髓质体积的全自动分割方法。

该算法使用了来自一个机构的总共 1930 次对比增强 CT 检查以及参考标准手动分割。训练卷积神经网络模型 ( n = 1238) 并验证 ( n = 306)，然后在参考标准分割的保留测试集中进行评估 ( n = 386)。初步评估后，该算法在来自两个外部站点 ( n = 1226) 的数据集上进行了进一步测试。

发现自动化模型的性能与手动分割相当，但存在与手动分割的观察者间变异类似的错误。与参考标准相比，自动化方法在测试集中实现了 0.94（右皮质）、0.90（右髓质）、0.94（左皮质）和 0.90（左髓质）的 Dice 相似度度量。当该算法应用于两个外部数据集时，观察到类似的性能。

一种用于测量肾脏 CT 图像中的皮质和髓质体积的全自动方法已经建立。该方法可能对广泛的临床应用有用。