Childhood Cancer Data Initiative Annual Symposium (Abstract Registration): Submission #50

serial: '50'
sid: '150199'
uuid: 709c95da-fc6e-4f44-b920-d31f6260955b
uri: /nci/ccdisymposium/abstract
created: '1756473513'
completed: '1756474201'
changed: '1756474201'
in_draft: '0'
current_page: ''
remote_addr: 10.208.28.51
uid: '0'
langcode: en
webform_id: ccdi_symposium_abstract
entity_type: node
entity_id: '2139'
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data:
  authors_:
    - add_author_degree: Ph.D
      add_author_first_name: Jungwook
      add_author_last_name: Shin
      add_author_middle: ''
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
    - add_author_degree: Ph.D
      add_author_first_name: 'Matthew '
      add_author_last_name: Mille
      add_author_middle: M
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
    - add_author_degree: BA
      add_author_first_name: 'Caroline '
      add_author_last_name: Esposito
      add_author_middle: ''
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
    - add_author_degree: Ph.D
      add_author_first_name: Todd
      add_author_last_name: Gibson
      add_author_middle: M
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
    - add_author_degree: Ph.D
      add_author_first_name: Keith
      add_author_last_name: Griffin
      add_author_middle: T
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
    - add_author_degree: Ph.D
      add_author_first_name: 'Jae Won'
      add_author_last_name: Jung
      add_author_middle: ''
      add_author_organization: 'East Carolina University'
    - add_author_degree: Ph.D
      add_author_first_name: Choonik
      add_author_last_name: Lee
      add_author_middle: ''
      add_author_organization: 'University of Michigan'
    - add_author_degree: Ph.D
      add_author_first_name: Sergio
      add_author_last_name: Morato
      add_author_middle: ''
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
    - add_author_degree: M.D
      add_author_first_name: Torunn
      add_author_last_name: Yock
      add_author_middle: I
      add_author_organization: 'Massachusetts General Hospital and Harvard Medical School'
    - add_author_degree: D.Phill
      add_author_first_name: Amy
      add_author_last_name: 'de González'
      add_author_middle: Berrington
      add_author_organization: 'Institute for Cancer Research, UK'
    - add_author_degree: Ph.D
      add_author_first_name: Choonsik
      add_author_last_name: Lee
      add_author_middle: ''
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
    - add_author_degree: Ph.D
      add_author_first_name: Cari
      add_author_last_name: Kitahara
      add_author_middle: M
      add_author_organization: 'National Institutes of Health/National Cancer Institute'
  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_title_: 'Radiation dosimetry for the first large-scale systemic comparison of the risk of second cancers in children treated with proton versus photon therapy'
  email_address_: jungwook.shin@nih.gov
  institution_: 'National Institutes of Health/National Cancer Institute '
  presenting_author_: 'Jungwook Shin on behalf of the Pediatric Proton/Photon Therapy Comparison cohort study consortium'