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Monte Carlo-Based Organ Dose Reconstruction Using Pre-Contoured Human Model for Hodgkins Lymphoma Patients Treated by Cobalt-60 External Beam Therapy

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J Jung

J Jung1*, C Lee2 , J Kim3 , C Pelletier1 , A Pyakuryal4 , C Lee4 , (1) East Carolina University, Greenville, NC, (2) University of Michigan, Ann Arbor, MI, (3) University of Pittsburgh Medical Center, Pittsburgh, PA, (4) National Cancer Institute, Rockville, MD


SU-E-T-561 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: Organ doses for the Hodgkin’s lymphoma patients treated with cobalt-60 radiation were estimated using an anthropomorphic model and Monte Carlo modeling.

Methods: A cobalt-60 treatment unit modeled in the BEAMnrc Monte Carlo code was used to produce phase space data. The Monte Carlo simulation was verified with percent depth dose measurement in water at various field sizes. Radiation transport through the lung blocks were modeled by adjusting the weights of phase space data. We imported a precontoured adult female hybrid model and generated a treatment plan. The adjusted phase space data and the human model were imported to the XVMC Monte Carlo code for dose calculation. The organ mean doses were estimated and dose volume histograms were plotted.

Results: The percent depth dose agreement between measurement and calculation in water phantom was within 2% for all field sizes. The mean organ doses of heart, left breast, right breast, and spleen for the selected case were 44.3, 24.1, 14.6 and 3.4 Gy, respectively with the midline prescription dose of 40.0 Gy.

Conclusion: Organ doses were estimated for the patient group whose three-dimensional images are not available. This development may open the door to more accurate dose reconstruction and estimates of uncertainties in secondary cancer risk for Hodgkin’s lymphoma patients.

Funding Support, Disclosures, and Conflict of Interest: This work was partially supported by the intramural research program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics.

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