The risk of valvular heart disease in the French Childhood Cancer Survivors' Study: Contribution of dose-volume histogram parameters

BACKGROUND AND PURPOSE

Valvular Heart Disease (VHD) is a known complication of childhood cancer after radiotherapy treatment. However, the dose-volume-effect relationships have not been fully explored.

MATERIALS AND METHODS

We obtained individual heart Dose Volume Histograms (DVH) for survivors of the French Childhood Cancer Survivors Study (FCCSS) who had received radiotherapy. We calculated the Mean Dose to the Heart (MHD) in Gy, as well as the heart DVH parameters (V_{d Gy}, which represents the percentage of heart volume receiving at least d Gy), fixing the thresholds to 0.1 Gy, 5 Gy, 20 Gy, and 40 Gy. We analyzed them furtherly in the subpopulation of the cohort that was treated with a dose lower than 5 Gy (V_0.1Gy|_V5Gy=0%), 20 Gy (V_5Gy|_V20Gy=0%), and 40 Gy (V_20Gy|_V40Gy=0%), respectively. We investigated their role in the occurrence of a VHD in this population-based observational cohort study using the Cox proportional hazard model, adjusting for age at cancer diagnosis and chemotherapy exposure.

RESULTS

Median follow-up was 30.6 years. Eighty-one patients out of the 7462 (1 %) with complete data experienced a severe VHD (grade ≥ 3). The risk of VHD increased along with the MHD, and it was associated with high doses to the heart (V_40Gy < 50 %, hazard ratio (HR) = 7.96, 95 % CI: 4.26-14.88 and V_20Gy|_V40Gy=0% >50 %, HR = 5.03, 95 % CI: [2.35-10.76]). Doses 5-20 Gy to more than 50 % (V_5Gy|_V20Gy=0% >50 %) of the heart induced a marginally non-significant estimated risk. We also observed a remarkable risk increase with attained age.

CONCLUSIONS

Our results provide new insight into the VHD risk that may impact current treatments and long-term follow-up of childhood cancer survivors.

Image-based data mining applies to data collected from children

PURPOSE

Image-based data mining (IBDM) is a novel voxel-based method for analyzing radiation dose responses that has been successfully applied in adult data. Because anatomic variability and side effects of interest differ for children compared to adults, we investigated the feasibility of IBDM for pediatric analyses.

METHODS

We tested IBDM with CT images and dose distributions collected from 167 children (aged 10 months to 20 years) who received proton radiotherapy for primary brain tumors. We used data from four reference patients to assess IBDM sensitivity to reference selection. We quantified spatial-normalization accuracy via contour distances and deviations of the centers-of-mass of brain substructures. We performed dose comparisons with simplified and modified clinical dose distributions with a simulated effect, assessing their accuracy via sensitivity, positive predictive value (PPV) and Dice similarity coefficient (DSC).

RESULTS

Spatial normalizations and dose comparisons were insensitive to reference selection. Normalization discrepancies were small (average contour distance < 2.5 mm, average center-of-mass deviation < 6 mm). Dose comparisons identified differences (p < 0.01) in 81% of simplified and all modified clinical dose distributions. The DSCs for simplified doses were high (peak frequency magnitudes of 0.9-1.0). However, the PPVs and DSCs were low (maximum 0.3 and 0.4, respectively) in the modified clinical tests.

CONCLUSIONS

IBDM is feasible for childhood late-effects research. Our findings may inform cohort selection in future studies of pediatric radiotherapy dose responses and facilitate treatment planning to reduce treatment-related toxicities and improve quality of life among childhood cancer survivors.

American Society of Clinical Oncology 2021 Annual Meeting Highlights for Radiation Oncologists

The annual meeting of the American Society of Clinical Oncology is the largest multidisciplinary oncology-focused conference in the world. With more than 4900 total abstracts in 2021 alone, it is difficult for individuals to evaluate all the results. This article presents a review of 32 selected abstracts across all disease sites, focusing on those of greatest relevance to radiation oncologists.