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Development of Heart Prediction Model to Increase Accuracy of Dose Reconstruction for Radiotherapy Patients

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E Mosher

E Mosher1*, M Choi1 , E Jones2 , C Lee1 , (1) Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, (2) Radiology and Imaging Sciences Clinical Center, National Institutes of Health, Bethesda, MD


SU-F-T-119 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: To assess individual variation in heart volume and location in order to develop a prediction model of the heart. This heart prediction model will be used to calculate individualized heart doses for radiotherapy patients in epidemiological studies.

Methods: Chest CT images for 30 adult male and 30 adult female patients were obtained from NIH Clinical Center. Image-analysis computer programs were used to segment the whole heart and 8 sub-regions and to measure the volume of each sub- region and the dimension of the whole heart. An analytical dosimetry method was used for the 30 adult female patients to estimate mean heart dose during conventional left breast radiotherapy.

Results: The average volumes of the whole heart were 803.37 cm³ (COV 18.8%) and 570.19 cm³ (COV 18.8%) for adult male and female patients, respectively, which are comparable with the international reference volumes of 807.69 cm³ for males and 596.15 cm³ for females. Some patient characteristics were strongly correlated (R²>0.5) with heart volume and heart dimensions (e.g., Body Mass Index vs. heart depth in males: R²=0.54; weight vs. heart width in the adult females: R²=0.63). We found that the mean heart dose 3.805 Gy (assuming prescribed dose of 50 Gy) in the breast radiotherapy simulations of the 30 adult females could be an underestimate (up to 1.6-fold) or overestimate (up to 1.8-fold) of the patient-specific heart dose.

Conclusion: The study showed the significant variation in patient heart volumes and dimensions, resulting in substantial dose errors when a single average heart model is used for retrospective dose reconstruction. We are completing a multivariate analysis to develop a prediction model of the heart. This model will increase accuracy in dose reconstruction for radiotherapy patients and allow us to individualize heart dose calculations for patients whose CT images are not available.

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