Development and validation of an age-scalable cardiac model with substructures for dosimetry in late-effects studies of childhood cancer survivors. (December 2020)

• Record Type: Journal Article
• Authors: Shrestha, Suman; Gupta, Aashish C.; Bates, James E.; Lee, Choonsik; Owens, Constance A.; Hoppe, Bradford S.; Constine, Louis S.; Smith, Susan A.; Qiao, Ying; Weathers, Rita E.; Yasui, Yutaka; Court, Laurence E.; Paulino, Arnold C.; Pinnix, Chelsea C.; Kry, Stephen F.; Followill, David S.; Armstrong, Gregory T.; Howell, Rebecca M.
• Is Part Of: Radiotherapy and oncology. Volume 153(2020)
• Page Start: 163
• Page End: 171
• Publication Date: 2020-12
• Subjects: Late effects -- Radiation therapy -- Cardiac toxicity -- Computational phantom -- Childhood cancer; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2020.10.017
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: Developed an anatomically realistic age-scalable cardiac model with 14 substructures. New cardiac model is representative of pediatric heart anatomy for childhood cohorts. Good agreement (within 4.2% on average) with CT-based planning (ground truth) doses. Report heart dose and dose volume metrics for 4957 childhood cancer survivors. Mean dose and dose-volume metrics were on average 10% lower compared to prior model. Abstract: Background and Purpose: Radiation therapy is a risk factor for late cardiac disease in childhood cancer survivors. Several pediatric cohort studies have established whole heart dose and dose–volume response models. Emerging data suggest that dose to cardiac substructures may be more predictive than whole heart metrics. In order to develop substructure dose-response models, the heart model previously used for pediatric cohort dosimetry needed enhancement and substructure delineation. Methods: To enhance our heart model, we combined the age-scalable capability of our computational phantom with the anatomically-delineated (with substructures) heart models from an international humanoid phantom series. We examined cardiac volume similarity/overlap between registered age-scaled phantoms (1, 5, 10, and 15 years) with the enhanced heart model and the reference phantoms of the same age; dice similarity coefficient (DSC) and overlap coefficient (OC) were calculated for each matched pair. To assess the accuracy of our enhanced heart model, we compared doses from computed tomography-based planning (ground truth) with reconstructed heart doses. We also compared doses calculated with the prior and enhanced heart models for a cohort of nearly 5000 childhood cancer survivors. Results: We developed a realistic cardiac model with 14-substructures, scalable across a broad age range (1–15 years); average DSC and OC were 0.84 ± 0.05 and 0.90 ± 0.05, respectively. The average percent difference between reconstructed and ground truth mean heart doses was 4.2%. In the cohort dosimetry analysis, dose and dose-volume metrics were approximately 10% lower on average when the enhanced heart model was used for dose reconstructions. Conclusion: We successfully developed and validated an anatomically realistic age-scalable cardiac model that can be used to establish substructure dose-response models for late cardiac disease in childhood cancer survivor cohorts.