A novel method for rapid estimation of active bone marrow dose for radiotherapy patients in epidemiological studies

Author:

Yeom Yeon Soo12,Braunstein Lior3,Morton Lindsay M.2,Bolton Kelly L.4,Choi Ji Won1,Choi Hyeong Yun2,Greenstein Natasha5,Lee Choonsik2

Affiliation:

1. Department of Radiation Convergence Engineering Yonsei University Wonju Gangwon Republic of Korea

2. Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Rockville Maryland USA

3. Department of Radiation Oncology Memorial Sloan Kettering Cancer Center New York New York USA

4. Department of Medicine Washington University School of Medicine St. Louis Missouri USA

5. Department of Physics Princeton University Princeton New Jersey USA

Abstract

AbstractBackgroundIn a dedicated effort to improve the assessment of clonal hematopoiesis (CH) and study leukemia risk following radiotherapy, we are developing a large‐scale cohort study among cancer patients who received radiation. To that end, it will be critical to analyze dosimetric parameters of red bone marrow (ABM) exposure in relation to CH and its progression to myeloid neoplasms, requiring reconstruction method for ABM doses of a large‐scale patients rapidly and accurately.PurposeTo support a large‐scale cohort study on the assessment of clonal hematopoiesis and leukemia risk following radiotherapy, we present a new method for the rapid reconstruction of ABM doses of radiotherapy among cancer patients.MethodsThe key idea of the presented method is to segment patient bones rapidly and automatically by matching a whole‐body computational human phantom, in which the skeletal system is divided into 34 bone sites, to patient CT images via 3D skeletal registration. The automatic approach was used to segment site‐specific bones for 40 radiotherapy patients. Also, we segmented the bones manually. The bones segmented both manually and automatically were then combined with the patient dose matrix calculated by the treatment planning system (TPS) to derive patient ABM dose. We evaluated the performance of the automatic method in geometric and dosimetric accuracy by comparison with the manual approach.ResultsThe pelvis showed the best geometric performance [volume overlap fraction (VOF): 52% (mean) with 23% (σ) and average distance (AD): 0.8 cm (mean) with 0.5 cm (σ)]. The pelvis also showed the best dosimetry performance [absorbed dose difference (ADD): 0.7 Gy (mean) with 1.0 Gy (σ)]. Some bones showed unsatisfactory performances such as the cervical vertebrae [ADD: 5.2 Gy (mean) with 10.8 Gy (σ)]. This impact on the total ABM dose, however, was not significant. An excellent agreement for the total ABM dose was indeed observed [ADD: 0.4 Gy (mean) with 0.4 Gy (σ)]. The computation time required for dose calculation using our method was robust (about one minute per patient).ConclusionsWe confirmed that our method estimates ABM doses across treatment sites accurately, while providing high computational efficiency. The method will be used to reconstruct patient‐specific ABM doses for dose‐response assessment in a large cohort study. The method can also be applied to prospective dose calculation within a clinical TPS to support clinical decision making at the point of care.

Funder

National Institutes of Health

National Research Foundation of Korea

Ministry of Education

Publisher

Wiley

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