Childhood Cancer Data Initiative Annual Symposium (Abstract Registration): Submission #50
Submission information
Submission Number: 50
Submission ID: 150199
Submission UUID: 709c95da-fc6e-4f44-b920-d31f6260955b
Submission URI: /nci/ccdisymposium/abstract
Created: Fri, 08/29/2025 - 09:18
Completed: Fri, 08/29/2025 - 09:30
Changed: Fri, 08/29/2025 - 09:30
Remote IP address: 10.208.28.51
Submitted by: Anonymous
Language: English
Is draft: No
Abstract Submission for Poster Presentation ------------------------------------------- Abstract Title:: Radiation dosimetry for the first large-scale systemic comparison of the risk of second cancers in children treated with proton versus photon therapy Abstract:: The Pediatric Proton/Photon Therapy Comparison (PPTC) cohort study is the first large-scale study comparing the risk of second cancers in children treated with proton versus photon radiotherapy. The study aims to collect treatment records from 17 hospitals, targeting 10,000 patients for each modality. Because the cohort data are both large and distributed across multiple databases, we have deployed a cloud-based system to streamline data collection, monitoring, validation, and transfer to a high-performance computing (HPC) cluster. A total of 7,000 patients have been collected so far in an industry-standard medical image format (DICOM), including radiation field parameters, planning computed tomography (CT) images with clinician-delineated anatomical structures, and dose distributions from the treatment planning system (TPS). Another critical component is the development of scalable methods for estimating individualized, organ-level radiation dose for epidemiological dose-response analyses. Planning CT scans typically cover only the treatment region, often omitting organs of interest for late effects research. To address this, we developed a method to extend partial-body CT images using a library built from patient anatomies. In addition, due to variability and inconsistency in organ delineation and naming, we utilize a deep learning–based automatic segmentation tool to standardize organ delineation. Finally, we address limitations of TPS dose estimates by performing advanced Monte Carlo radiation transport simulations of both modalities. These simulations integrate patient data and detailed physics modeling and are efficiently executed on the NIH HPC cluster. This poster presents our efforts to implement a state-of-the-art dosimetry platform—from data collection to individualized dose calculations. Abstract:: {Empty} Authors:: 1. First Name: Jungwook Last Name: Shin Degree(s): Ph.D Organization: National Institutes of Health/National Cancer Institute 2. First Name: Matthew Middle Initial: M Last Name: Mille Degree(s): Ph.D Organization: National Institutes of Health/National Cancer Institute 3. First Name: Caroline Last Name: Esposito Degree(s): BA Organization: National Institutes of Health/National Cancer Institute 4. First Name: Todd Middle Initial: M Last Name: Gibson Degree(s): Ph.D Organization: National Institutes of Health/National Cancer Institute 5. First Name: Keith Middle Initial: T Last Name: Griffin Degree(s): Ph.D Organization: National Institutes of Health/National Cancer Institute 6. First Name: Jae Won Last Name: Jung Degree(s): Ph.D Organization: East Carolina University 7. First Name: Choonik Last Name: Lee Degree(s): Ph.D Organization: University of Michigan 8. First Name: Sergio Last Name: Morato Degree(s): Ph.D Organization: National Institutes of Health/National Cancer Institute 9. First Name: Torunn Middle Initial: I Last Name: Yock Degree(s): M.D Organization: Massachusetts General Hospital and Harvard Medical School 10. First Name: Amy Middle Initial: Berrington Last Name: de González Degree(s): D.Phill Organization: Institute for Cancer Research, UK 11. First Name: Choonsik Last Name: Lee Degree(s): Ph.D Organization: National Institutes of Health/National Cancer Institute 12. First Name: Cari Middle Initial: M Last Name: Kitahara Degree(s): Ph.D Organization: National Institutes of Health/National Cancer Institute Presenting Author:: Jungwook Shin on behalf of the Pediatric Proton/Photon Therapy Comparison cohort study consortium Institution:: National Institutes of Health/National Cancer Institute Email Address:: jungwook.shin@nih.gov