Evaluation of a Deep-Learning Auto-Segmentation Model of Cardiac Substructures

Abstract

Increasing evidence has suggested that limiting dose not only to the whole heart but also to cardiac substructures can potentially reduce cardiac toxicities. Manual contouring of cardiac substructure can be challenging and time-consuming. To address this concern, we developed a deep learning (DL) model, trained on convolutional neural network algorithms in large external datasets, for auto-segmentation of cardiac substructures. This study aimed to evaluate the quality of the cardiac substructure contours generated by the DL algorithm. We identified 28 patients with esophagus or gastroesophageal junction cancer from a single institution who received radiation to the esophagus between January 2017 and December 2022. For each case, the DL-generated cardiac substructures (4 heart chambers - left/right atrium [L/RA] and L/R ventricle [L/RV], 4 coronary arteries - L common [LCA], L anterior descending [LAD], L circumflex [LCx], and R common [RCA], and great vessels - ascending aorta [AA], pulmonary artery [PA], and superior vena cava [SVC]) were modified by two radiation oncologists (RO) using the contouring atlas developed by Duane et al. Spatial overlapping of the contours were then assessed using the Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD-95), and normalized surface dice at 2 mm tolerance (NSD-2). The mean values of DSC, HD-95, and NSD-2 are shown in Table 1. Overall, the mean DSC, HD-95, and NSD-2 for the heart chambers ranged from 0.82 to 0.92, 0.40 cm to 1.52 cm, and 0.68 to 0.85, respectively. Ranges of the mean DSC, HD-95, and NSD-2 for the coronary vessels were 0.41 to 0.74, 0.18 cm to 0.98 cm, and 0.66 to 0.77, respectively. Lastly, comparison of the great vessel contours yielded the following ranges for mean DSC, HD-95, and NSD-2 respectively: 0.72 to 0.92, 0.30 cm to 1.64 cm, and 0.65 to 0.83. Our study demonstrates that auto-segmentation of cardiac substructures by DL-powered models can be comparable to manual contours for certain cardiac substructures, namely the four heart chambers and great vessels. Further improvement of the DL on contouring of coronary vessels would be needed prior to the autosegmentation model being widely adopted.