Work

Estimating radiation effective doses from whole body computed tomography scans based on U.S. soldier patient height and weight

Year: 2011

Type: article

Abstract: BACKGROUND: The purpose of this study is to explore how a patient's height and weight can be used to predict the effective dose to a reference phantom with similar height and weight from a chest abdomen pelvis computed tomography scan when machine-based parameters are unknown. Since machine-based scanning parameters can be misplaced or lost, a predictive model will enable the medical professional to quantify a patient's cumulative radiation dose. METHODS: One hundred mathematical phantoms of varying heights and weights were defined within an x-ray Monte Carlo based software code in order to calculate organ absorbed doses and effective doses from a chest abdomen pelvis scan. Regression analysis was used to develop an effective dose predictive model. The regression model was experimentally verified using anthropomorphic phantoms and validated against a real patient population. RESULTS: Estimates of the effective doses as calculated by the predictive model were within 10% of the estimates of the effective doses using experimentally measured absorbed doses within the anthropomorphic phantoms. Comparisons of the patient population effective doses show that the predictive model is within 33% of current methods of estimating effective dose using machine-based parameters. CONCLUSIONS: A patient's height and weight can be used to estimate the effective dose from a chest abdomen pelvis computed tomography scan. The presented predictive model can be used interchangeably with current effective dose estimating techniques that rely on computed tomography machine-based techniques.

Source: BMC Medical Imaging

DOI: 10.1186/1471-2342-11-20

Authors: Robert D Prins, Raymond H Thornton, C Ross Schmidtlein, Brian Quinn, Hung Ching, Lawrence T Dauer

Institutions: Memorial Sloan Kettering Cancer Center, Columbia University

Language: English

Topic: Radiation Dose and Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,090