Copenhagen, Denmark
Onsite/Online

ESTRO 2022

Session Item

Imaging acquisition and processing
Poster (digital)
Physics
Development of simplified auto-segmentable functional cardiac atlas
Pierre Loap, France
PO-1600

Abstract

Development of simplified auto-segmentable functional cardiac atlas
Authors:

Pierre Loap1, Ludovic De Marzi1, Krassen Kirov2, Vincent Servois3, Alain Fourquet1, Abdelhafidh Khoubeyb2, Youlia Kirova1

1Institut Curie, Department of Radiation Oncology, Paris, France; 2Institut Curie, Department of Anesthesiology, Paris, France; 3Institut Curie, Department of Radiology, Paris, France

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Purpose or 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.

Material and 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 (illustrated in Figure 1) ranged between fifteen to twenty minutes, while ABAS lasted two minutes. The median DSC for the delineated cardiac substructures was 0.718 (Figure 2). 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 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.

Figure 1: Simplified functional cardiac atlas. The left ventricle is delineated in red, the right ventricle in dark green, the left auricle in light green, the left auricle in pink, the high-risk cardiac zone  in green, the SAN in blue and the AVN in purple. A. Axial plane. B. 3D representation.


Figure 2: performance of atlas-based auto-segmentation of the proposed simplified functional cardiac atlas. DSC: Dice Similarity Coefficient. LA : left auricle. RA : right auricle. LV : left ventricle. RV : right ventricle. HRCZ : high risk cardiac zone. SAN : sinoatrial node. AVN : atrio-ventricular node.


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.