Atlas-based auto-segmentation for delineating the heart and cardiac substructures in breast cancer radiation therapy

Abstract

Background

This study aimed to develop and validate an automatic multi-atlas segmentation method for delineating the heart and substructures in breast cancer radiation therapy (RT).

Material and methods

The atlas database consisted of non-contrast-enhanced planning CT scans from 42 breast cancer patients, each with one manual delineation of the heart and 22 cardiac substructures. Half of the patients were scanned during free-breathing, the rest were scanned during a deep inspiration breath-hold. The auto-segmentation was developed in the MIM software system and validated geometrically and dosimetrically in two steps: The first validation in a small dataset to ensure consistency of the atlas. This was succeeded by a final test where multiple manual delineations in CT scans of 12 breast cancer patients were compared to the auto-segmentation. For geometric evaluation, the dice similarity coefficient (DSC) and the mean surface distance (MSD) were used. For dosimetric evaluation, the RT doses to each substructure in the manual and the automatic delineations were compared.

Results

In the first validation, a high geometric and dosimetric performance between the automatic and manual delineations was observed for all substructures. The final test confirmed a high agreement between the automatic and manual delineations for the heart (DSC = 0.94) and the cardiac chambers (DSC: 0.75–0.86). The difference in MSD between the automatic and manual delineations was low (<4 mm) in all structures. Finally, a high correlation between mean RT doses for the automatic and the manual delineations was observed for the heart and substructures.

Conclusions

An automatic segmentation tool for delineation of the heart and substructures in breast cancer RT was developed and validated with a high correlation between the automatic and manual delineations. The atlas is pivotal for large-scale evaluations of radiation-associated heart disease.

Keywords:

• Atlas based auto-segmentation
• cardiac substructures
• breast cancer
• radiation therapy

Acknowledgments

The authors thank the Danish Comprehensive Cancer Center Onco-Cardiology Group and Novo Nordisk Fonden.

MIM Software Inc. Cleveland, OH is acknowledged for providing a license for research use of the MIM software.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

MLHM, ELL, LH, DSM, and BVO are supported by DCCC Radiotherapy – The Danish National Research Center for Radiotherapy (grant no R191-A11526). Furthermore, MLHM is supported by Danish Cancer Society and Aarhus University. DSM is supported by Danish Cancer Society (grant no. R209-A13036). BVO is supported by Danish Cancer Society and Novo Nordisk Fonden.