Acute and Late Pulmonary Effects After Radiation Therapy in Childhood Cancer Survivors: A PENTEC Comprehensive Review

Comparison of Risks of Late Effects From Radiation Therapy in Children Versus Adults: Insights From the QUANTEC, HyTEC, and PENTEC Efforts

Pediatric Normal Tissue Effects in the Clinic (PENTEC) seeks to refine quantitative radiation dose-volume relationships for normal-tissue complication probabilities (NTCPs) in survivors of pediatric cancer. This article summarizes the evolution of PENTEC and compares it with similar adult-focused efforts (eg, Quantitative Analysis of Normal Tissue Effects in the Clinic [QUANTEC] and Hypofractionated Treatment Effects in the Clinic [HyTEC]) with respect to content, oversight, support, scope, and methodology of literature review. It then summarizes key organ-specific findings from PENTEC in an attempt to compare NTCP estimates in children versus adults. In brief, select normal-tissue risks within developing organs and tissues (eg, maldevelopment of musculoskeletal tissue, teeth, breasts, and reproductive organs) are primarily relevant only in children. For some organs and tissues, children appear to have similar (eg, brain for necrosis, optic apparatus, parotid gland, liver), greater (eg, brain for neurocognition, cerebrovascular, breast for lactation), less (ovary), or perhaps slightly less (eg, lung) risks of toxicity versus adults. Similarly, even within the broad pediatric age range (including adolescence), for some endpoints, younger children have greater (eg, hearing and brain for neurocognition) or lesser (eg, ovary, thyroid) risks of radiation-associated toxicities. NTCP comparisons in adults versus children are often confounded by marked differences in treatment paradigms that expose normal tissues to radiation (ie, cancer types, prescribed radiation therapy dose and fields, and chemotherapy agents used). To add to the complexity, it is unclear if age is best analyzed as a continuous variable versus with age groupings (eg, infants, young children, adolescents, young adults, middle-aged adults, older adults). Further work is needed to better understand the complex manner in which age and developmental status affect risk.

Radiation Dose-Volume-Response Relationships for Adverse Events in Childhood Cancer Survivors: Introduction to the Scientific Issues in PENTEC

At its very core, radiation oncology involves a trade-off between the benefits and risks of exposing tumors and normal tissue to relatively high doses of ionizing radiation. This trade-off is particularly critical in childhood cancer survivors (CCS), in whom both benefits and risks can be hugely consequential due to the long life expectancy if the primary cancer is controlled. Estimating the normal tissue-related risks of a specific radiation therapy plan in an individual patient relies on predictive mathematical modeling of empirical data on adverse events. The Pediatric Normal-Tissue Effects in the Clinic (PENTEC) collaborative network was formed to summarize and, when possible, to synthesize dose-volume-response relationships for a range of adverse events incident in CCS based on the literature. Normal-tissue clinical radiation biology in children is particularly challenging for many reasons: (1) Childhood malignancies are relatively uncommon-constituting approximately 1% of new incident cancers in the United States-and biologically heterogeneous, leading to many small series in the literature and large variability within and between series. This creates challenges in synthesizing data across series. (2) CCS are at an elevated risk for a range of adverse health events that are not specific to radiation therapy. Thus, excess relative or absolute risk compared with a reference population becomes the appropriate metric. (3) Various study designs and quantities to express risk are found in the literature, and these are summarized. (4) Adverse effects in CCS often occur 30, 50, or more years after therapy. This limits the information content of series with even very extended follow-up, and lifetime risk estimates are typically extrapolations that become dependent on the mathematical model used. (5) The long latent period means that retrospective dosimetry is required, as individual computed tomography-based radiation therapy plans gradually became available after 1980. (6) Many individual patient-level factors affect outcomes, including age at exposure, attained age, lifestyle exposures, health behaviors, other treatment modalities, dose, fractionation, and dose distribution. (7) Prospective databases with individual patient-level data and radiation dosimetry are being built and will facilitate advances in dose-volume-response modeling. We discuss these challenges and attempts to overcome them in the setting of PENTEC.

Improving Pediatric Normal Tissue Radiation Dose-Response Modeling in Children With Cancer: A PENTEC Initiative

The development of normal tissue radiation dose-response models for children with cancer has been challenged by many factors, including small sample sizes; the long length of follow-up needed to observe some toxicities; the continuing occurrence of events beyond the time of assessment; the often complex relationship between age at treatment, normal tissue developmental dynamics, and age at assessment; and the need to use retrospective dosimetry. Meta-analyses of published pediatric outcome studies face additional obstacles of incomplete reporting of critical dosimetric, clinical, and statistical information. This report describes general methods used to address some of the pediatric modeling issues. It highlights previous single- and multi-institutional pediatric dose-response studies and summarizes how each PENTEC taskforce addressed the challenges and limitations of the reviewed publications in constructing, when possible, organ-specific dose-effect models.

A comprehensive review of 30 years of pediatric clinical trial radiotherapy dose constraints

BACKGROUND

Radiation therapy normal tissue dose constraints are critical when treating pediatric patients. However, there is limited evidence supporting proposed constraints, which has led to variations in constraints over the years. In this study, we identify these variations in dose constraints within pediatric trials both in the United States and in Europe used in the past 30 years.

PROCEDURE

All pediatric trials from the Children's Oncology Group website were queried from inception until January 2022 and a sampling of European studies was included. Dose constraints were identified and built into an organ-based interactive web application with filters to display data by organs at risk (OAR), protocol, start date, dose, volume, and fractionation scheme. Dose constraints were evaluated for consistency over time and compared between pediatric US and European trials RESULTS: One hundred five closed trials were included-93 US trials and 12 European trials. Thirty-eight separate OAR were found with high-dose constraint variability. Across all trials, nine organs had greater than 10 different constraints (median 16, range 11-26), including serial organs. When comparing US versus European dose tolerances, the United States constraints were higher for seven OAR, lower for one, and identical for five. No OAR had constraints change systematically over the last 30 years.

CONCLUSION

Review of pediatric dose-volume constraints in clinical trials showed substantial variability for all OAR. Continued efforts focused on standardization of OAR dose constraints and risk profiles are essential to increase consistency of protocol outcomes and ultimately to reduce radiation toxicities in the pediatric population.

Deep learning-based precise prediction and early detection of radiation-induced temporal lobe injury for nasopharyngeal carcinoma

Background

Radiotherapy is the mainstay of treatment for nasopharyngeal carcinoma. Radiation-induced temporal lobe injury (TLI) can regress or resolve in the early phase, but it is irreversible at a later stage. However, no study has proposed a risk-based follow-up schedule for its early detection. Planning evaluation is difficult when dose-volume histogram (DVH) parameters are similar and optimization is terminated.

Methods

This multicenter retrospective study included 6065 patients between 2014 and 2018. A 3D ResNet-based deep learning model was developed in training and validation cohorts and independently tested using concordance index in internal and external test cohorts. Accordingly, the patients were stratified into risk groups, and the model-predicted risks were used to develop risk-based follow-up schedules. The schedule was compared with the Radiation Therapy Oncology Group (RTOG) recommendation (every 3 months during the first 2 years and every 6 months in 3-5 years). Additionally, the model was used to evaluate plans with similar DVH parameters.

Findings

Our model achieved concordance indexes of 0.831, 0.818, and 0.804, respectively, which outperformed conventional prediction models (all P < 0.001). The temporal lobes in all the cohorts were stratified into three groups with discrepant TLI-free survival. Personalized follow-up schedules developed for each risk group could detect TLI 1.9 months earlier than the RTOG recommendation. According to a higher median predicted 3-year TLI-free survival (99.25% vs. 99.15%, P < 0.001), the model identified a better plan than previous models.

Interpretation

The deep learning model predicted TLI more precisely. The model-determined risk-based follow-up schedule detected the TLI earlier. The planning evaluation was refined because the model identified a better plan with a lower risk of TLI.

Funding

The Sun Yat-sen University Clinical Research 5010 Program (2015020), Guangdong Basic and Applied Basic Research Foundation (2022A1515110356), Medical Scientific Research Foundation of Guangdong Province (A2022367), and Guangzhou Science and Technology Program (2023A04J1788).