Quantifying medical exposures to radiation in children with congenital heart defects using advanced Monte Carlo methods and patient-inspired anatomical models

Congenital heart defects (CHDs) are abnormalities of the heart and intrathoracic great vessels present from birth, with varying degrees of health severity; some may necessitate no intervention, while others may require immediate surgical intervention. Given that CHDs are the most frequent type of birth defect, many children worldwide will undergo numerous imaging examinations utilizing ionizing radiation, spanning from initial diagnosis to treatment and long-term follow-up. Considering the latency period for the development of leukemia from 5 to 7 years, and a minimum of 10 years for solid cancers, there is a tangible risk of developing radiation- induced malignancies for patients with extended lifespans. Both the National Academies and the United Nations are currently emphasizing the need to establish low-dose epidemiology cohorts for pediatric patients undergoing cardiac catheterization procedures, computed tomography scans, and general radiography examinations. This emphasis arises from the existing paucity of data on the correlation between multi-modality, cumulative, low radiation doses, and the corresponding cancer risk in children. Currently, there is no accurate platform for calculating patient-specific organ doses from medical exposures, which hinders our understanding of the link between radiation exposure and cancer incidence in this vulnerable population. Innovations in artificial intelligence-based automatic segmentation tools have allowed efficient extraction of patient anatomy from computed tomography scans to be used in the creation of whole-body phantoms suitable for Monte Carlo radiation transport simulations. Therefore, I hypothesize that the development of a software system integrated with the clinical workflow can use available patient imaging examinations to create accurate whole-body mesh models, which can then be used to calculate organ radiation doses accrued from the diagnosis and treatment of CHDs using Monte Carlo radiation transport simulations. The proposed project will be achieved by the completion of four Specific Aims: Aim 1: develop software tools that leverage available patient imaging exams to create morphometrically matched computational phantoms of the patient suitable for radiation transport simulations. Aim 2: develop a Monte Carlo software system that integrates with the clinical workflow to compute organ doses for pediatric patients undergoing cardiac catheterization procedures. Aim 3: use existing Monte Carlo dosimetry systems that integrate with the clinical workflow to compute organ doses for pediatric patients undergoing CT and radiography examinations. Aim 4: perform a retrospective study on patients recently treated at UF Health to compute organ doses for cardiac catheterization procedures, CT, and general radiography examinations. Completion of these aims will provide an accurate platform that answers the call for more low-dose and radiation epidemiological research as well as the potential for assisting physicians in patient cancer surveillance. Project Number: 1F31CA294904-01A1 | Fiscal Year: 2025 | NIH Institute/Center: National Cancer Institute (NCI) | Principal Investigator: Wyatt Smither | Institution: UNIVERSITY OF FLORIDA, GAINESVILLE, FL | Award Amount: $45,012 | Activity Code: F31 | Study Section: Special Emphasis Panel[ZRG1 F10C-B (20)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11165701