Background: The purpose of this study is to explore how a patient�s height and weight can be used to predict\r\nthe effective dose to a reference phantom with similar height and weight from a chest abdomen pelvis computed\r\ntomography scan when machine-based parameters are unknown. Since machine-based scanning parameters can\r\nbe misplaced or lost, a predictive model will enable the medical professional to quantify a patient�s cumulative\r\nradiation dose.\r\nMethods: One hundred mathematical phantoms of varying heights and weights were defined within an x-ray\r\nMonte Carlo based software code in order to calculate organ absorbed doses and effective doses from a chest\r\nabdomen pelvis scan. Regression analysis was used to develop an effective dose predictive model. The regression\r\nmodel was experimentally verified using anthropomorphic phantoms and validated against a real patient\r\npopulation.\r\nResults: Estimates of the effective doses as calculated by the predictive model were within 10% of the estimates\r\nof the effective doses using experimentally measured absorbed doses within the anthropomorphic phantoms.\r\nComparisons of the patient population effective doses show that the predictive model is within 33% of current\r\nmethods of estimating effective dose using machine-based parameters.\r\nConclusions: A patient�s height and weight can be used to estimate the effective dose from a chest abdomen\r\npelvis computed tomography scan. The presented predictive model can be used interchangeably with current\r\neffective dose estimating techniques that rely on computed tomography machine-based techniques.
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