Integration of Adaptive Proton Therapy in Pediatric Solid Tumors and Hodgkin's Lymphoma

Overview

Pediatric patients receiving proton therapy for solid tumors or Hodgkin's lymphoma may experience anatomical changes during treatment that can affect proton therapy accuracy. This prospective single-arm study uses regular low-dose imaging to monitor these changes and adjust treatment plans as needed. Participants will receive weekly or every-other-week CT scans, with MRI when appropriate, to assess whether the original plan remains accurate. Treatment plans will be updated if tumor coverage decreases by more than 5% or if radiation dose to normal tissues increases by more than 10%; otherwise, the original plan will continue. The study aims to determine how often plan adjustments are needed and to identify which disease sites are most likely to experience significant anatomical changes during treatment. Primary Objective: * Define the frequency of replanning necessary to ensure tumor coverage never falls below 95% (or 5% drop) of the prescribed daily dose in participants with intact (gross) tumors to keep the tumor control optimal throughout the multi-week treatment regimen. * Define the frequency of replanning necessary to ensure organs-at-risk (critical organs) do not deviate by more than 10% of the initially approved dose constraints to keep the normal tissue complication minimal throughout the multi-week treatment regimen. Secondary Objectives * Establish a cone beam CT (CBCT)-based framework for quantifying body surface changes throughout the treatment course. This goal will be achieved by developing a novel algorithm that detects and tracks external anatomical variations longitudinally, without requiring CBCT image enhancement, enabling precise assessment of daily participant setup consistency and anatomical stability. * Overcome daily CBCT quality limitations by generating synthetic CT images that accurately represent daily anatomy and support proton dose recalculation or verification planning. This goal will be achieved by developing a hybrid pipeline that integrates deep learning models with the deformable image registration algorithm, trained and validated on disease site-specific data. This will enable precise dose mapping and tissue density estimation, directly supporting adaptive planning decisions without the need of diagnostic- quality CT images.

Proton therapy is a type of radiation treatment that can target tumors very precisely while protecting healthy organs. This is especially important for children. However, during the several weeks of treatment, a child's body and tumor can change. These changes may cause the radiation dose to miss part of the tumor or give too much dose to nearby organs. In usual care, proton therapy plans are based on one CT scan taken before treatment starts. New scans are only done if the care team thinks a change has occurred. There is no standard process to regularly check whether the treatment plan is still accurate during therapy. This study tests a structured approach to monitoring and adjusting proton therapy plans during treatment in children with solid tumors or Hodgkin's lymphoma. About 100 pediatric patients receiving proton therapy at St. Jude Children's Research Hospital will take part. All patients will receive their prescribed proton therapy as usual. The study does not change the radiation dose or schedule. Participants will receive additional CT scans, and MRI when needed, during treatment. Imaging will be done weekly or every other week to check whether the original treatment plan still provides good tumor coverage and protects healthy organs. The treatment plan will be updated if: * Tumor coverage drops by more than 5%, or * Radiation dose to normal organs increases by 10% or more. If these changes are not seen, the original plan will continue. The extra imaging uses a low radiation dose. The goal of this study is to learn how often proton therapy plans need to be adjusted to keep treatment accurate and safe. Results may help improve proton therapy care for children in the future.