Abstract P3-19-14: Development of simplified auto-segmentable functional cardiac atlas
Authors: Loap Pierre , De Marzi Ludovic , Kirov Krassen , Servois Vincent , Fourquet Alain , Khoubeyb Abdelhafidh , Kirova Youlia 
Published: March 2022

Objective: There are increasing evidences that radiation doses to specific cardiac substructures are associated with cardiac adverse events. Manual delineation of cardiac substructures is time consuming, and auto-segmentation of cardiac substructure atlases has consequently been evaluated. However, proper delineation of small substructures, such as the left anterior descending coronary artery (LADCA), is challenging and conduction system substructures have never been considered, despite frequent reports of radiation-induced arrhythmias for thoracic irradiation. The aim of this study was to propose and evaluate a simplified auto-segmentable functional cardiac atlas. Methods: We created a cardiac substructure atlas from 20 breast cancer patients’ CT scans consisting of the four cardiac cavities, of a high-risk cardiac zone (HRCZ) as a LADCA surrogate and of the two cardiac conduction nodes. Performance evaluation of atlas-based auto-segmentation (ABAS) was evaluated on a validation data set consisting of 20 additional CT scans. Dice similarity coefficients (DSC) were used to evaluate the concordance level between the manual and the automatic segmentations. Results: The average duration of manual segmentation of the proposed cardiac atlas ranged between fifteen to twenty minutes, while ABAS lasted two minutes. The median DSC for the delineated cardiac substructures was 0.718. The highest similarity between manual and automatic segmentation was observed for the left ventricle with a median DSC of 0.87, while the lowest similarity between manual and automatic segmentation was observed for the NAV with a median DSC of 0.15. Regardless of the considered cardiac substructure, auto-segmentation tended to result into smaller volumes than manual segmentation. While the volumes were not statistically different for the left ventricle, the volumes were statistically different for the other substructures. While smaller, the auto-segmented NAV and SAN were systematically localized within the manual contours. The auto-segmented NAV could be approximated by a 1.6-cm sphere and the auto-segmented SAN by a 1.0-cm sphere. Conclusion: We proposed a simplified functional cardiac atlas, for which coronary delineation difficulties were circumvent using a surrogate high risk cardiac zone and cardiac conduction system was considered. Most cardiac substructures were associated with acceptable ABAS properties. Such atlas could be potentially evaluated for epidemiological studies and clinical practice.

Table 1.performance of atlas-based auto-segmentation of the proposed simplified cardiac atlasCardiac substructureDSC Overlap index [range]Cardiac cavitiesLeft ventricle0.87 [0.57-0.92]Right ventricle0.76 [0.45-0.85]Left atria0.77 [0.61-0.84]Right atria0.76 [0.54-0.85]High risk cardiac zone0.65 [0.38-0.79]Cardiac conduction systemSinoatrial node0.56 [0.27-0.67]Atrio-ventricular node0.15 [0.00-0.35]

Citation Format: Pierre Loap, Ludovic De Marzi, Krassen Kirov, Vincent Servois, Alain Fourquet, Abdelhafidh Khoubeyb, Youlia Kirova. Development of simplified auto-segmentable functional cardiac atlas [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-19-14.