Abstract PS15-15: Atlas-based auto-segmentation of a high risk cardiac zone on non-contrast computed tomography (CT) scans for indirect optimization of left anterior descending coronary artery (LADCA) dosimetry for breast radiotherapy
Authors: Pierre Loap, Nicolas Tkatchenko, Eliot Nicolas, Youlia Kirova
Journal: Cancer Research (2021)

Abstract Background : Breast radiotherapy is associated with an increased cardiotoxicity risk which could be decreased by taking into account the left anterior descending coronary artery (LADCA) during treatment planning. However, LADCA manual contouring is time-consuming, complex and poorly reproducible on non-contrast simulation computed tomography (CT) scans where it is often hardly noticeable. Alternatively, auto-segmentation algorithms have been proposed for cardiac substructure contouring but they are usually unreliable for LADCA automatic delineation in daily practice. Purpose : The aim of this study was to implement and to evaluate auto-segmentation of a “high risk cardiac zone” which would be a reproducible LADCA surrogate and which would be reliably delineated by atlas-based algorithms for dosimetric purpose when planning breast radiotherapy on non-contrast CT scans. Materials/methods : 40 breast cancer patients treated with intensity modulated radiation therapy were randomly selected from our institutional database. “High risk cardiac zones” (HRCZ) were defined as segments of the anterior cardiac wall centered around the inter-ventricular groove from top to bottom (where the LADCA anatomically lies), with a constant 1cm-thickness and a symmetrical lateral margin on both sides of the groove. For each patient, eight HRCZ were contoured, differing by their width, ranging between 1 cm and 8 cm, in steps of 1 cm. Each contour was validated by a staff of three radiation oncologists. An atlas was constituted using the HRCZ contours of 20 patients and implemented in the “Workflow Box” (Mirada Medical) atlas-based auto-segmentation (ABAS) software. The ABAS algorithm delineated the HRCZ on the 20 remaining patients and the auto-contouring performances were evaluated by comparison with the manual HRCZ contours (defined as the reference contours), using dice-similarity coefficients (DSC) and Jaccard indexes, as a function of the HRCZ width. Results : Performances of the atlas-based auto-segmentation algorithm for HRCZ delineation are reported in table 1, as a function of HRCZ width. Auto-segmentation performance and reproducibility improved with HRCZ width, as evidenced by increased DSC and Jaccard indexes and lower relative standard variations; in particular, for a HRCZ width larger than 4 cm, HRCZ automatic segmentation was constantly satisfactory (DSC &amp;gt; 0.6; relative standard variation &amp;lt; 20%). Conclusion : We implemented and evaluated auto-segmentation of high risk cardiac zones (HRCZ) on non-contrast CT scans, defined as segments of the anterior cardiac wall geometrically centered around the inter-ventricular groove from top to bottom (where LADCA anatomically lies) with a constant thickness of 1cm and a total width ranging between 1 cm and 8 cm. For HRCZ width larger than 4cm, auto-segmented HRCZ contours were constantly reliable and may be used as LADCA surrogate for heart dosimetric optimization during breast radiotherapy planning on non-contrast CT scans. Table 1: performance of atlas-based auto-segmentation of high risk cardiac zones (HRCZ)HRCZ width (cm)DSC (mean)DSC SDDSC RSDJaccard Index (mean)Jaccard SDJaccard RSD10.3000.11563.35%0.1870.16254.04%20.5370.12533.14%0.3790.14026.05%30.6220.10623.06%0.4590.10416.69%40.6590.09919.95%0.4980.09314.06%50.6740.10219.81%0.5150.09213.67%60.6820.10419.77%0.5240.09213.43%70.6870.10419.67%0.5300.09113.27%80.6930.10519.57%0.5370.09213.23%Table 1: performance of atlas-based auto-segmentation of high risk cardiac zones (HRCZ), a LADCA surrogate, as a function of HRCZ width. DSC: Dice Similarity coefficient; sd : standard deviation; rsd : relative standard deviation. Citation Format: Pierre Loap, Nicolas Tkatchenko, Eliot Nicolas, Youlia Kirova. Atlas-based auto-segmentation of a high risk cardiac zone on non-contrast computed tomography (CT) scans for indirect optimization of left anterior descending coronary artery (LADCA) dosimetry for breast radiotherapy [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS15-15.