Mark Worrall1, Sarah Vinnicombe2,3, David Sutton1. 1. Medical Physics, Ninewells Hospital and Medical School, Ninewells Avenue, Dundee, Scotland. 2. Thirlestaine Breast Centre, Cheltenham General Hospital, Cheltenham, England. 3. University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland.
Abstract
OBJECTIVE: A computational model has been created to estimate the abdominal thickness of a patient following an X-ray examination; its intended application is assisting with patient dose audit of paediatric X-ray examinations. This work evaluates the accuracy of the computational model in a clinical setting for adult patients undergoing anteroposterior (AP) abdomen X-ray examinations. METHODS: The model estimates patient thickness using the radiographic image, the exposure factors with which the image was acquired, a priori knowledge of the characteristics of the X-ray unit and detector and the results of extensive Monte Carlo simulation of patient examinations. For 20 patients undergoing AP abdominal X-ray examinations, the model was used to estimate the patient thickness; these estimates were compared against a direct measurement made at the time of the examination. RESULTS: Estimates of patient thickness made using the model were on average within ±5.8% of the measured thickness. CONCLUSION: The model can be used to accurately estimate the thickness of a patient undergoing an AP abdominal X-ray examination where the patient's size falls within the range of the size of patients used to create the computational model. ADVANCES IN KNOWLEDGE: This work demonstrates that it is possible to accurately estimate the AP abdominal thickness of an adult patient using the digital X-ray image and a computational model.
OBJECTIVE: A computational model has been created to estimate the abdominal thickness of a patient following an X-ray examination; its intended application is assisting with patient dose audit of paediatric X-ray examinations. This work evaluates the accuracy of the computational model in a clinical setting for adult patients undergoing anteroposterior (AP) abdomen X-ray examinations. METHODS: The model estimates patient thickness using the radiographic image, the exposure factors with which the image was acquired, a priori knowledge of the characteristics of the X-ray unit and detector and the results of extensive Monte Carlo simulation of patient examinations. For 20 patients undergoing AP abdominal X-ray examinations, the model was used to estimate the patient thickness; these estimates were compared against a direct measurement made at the time of the examination. RESULTS: Estimates of patient thickness made using the model were on average within ±5.8% of the measured thickness. CONCLUSION: The model can be used to accurately estimate the thickness of a patient undergoing an AP abdominal X-ray examination where the patient's size falls within the range of the size of patients used to create the computational model. ADVANCES IN KNOWLEDGE: This work demonstrates that it is possible to accurately estimate the AP abdominal thickness of an adult patient using the digital X-ray image and a computational model.
Authors: E Vañó; D L Miller; C J Martin; M M Rehani; K Kang; M Rosenstein; P Ortiz-López; S Mattsson; R Padovani; A Rogers Journal: Ann ICRP Date: 2017-10
Authors: Kenneth Clark; Bruce Vendt; Kirk Smith; John Freymann; Justin Kirby; Paul Koppel; Stephen Moore; Stanley Phillips; David Maffitt; Michael Pringle; Lawrence Tarbox; Fred Prior Journal: J Digit Imaging Date: 2013-12 Impact factor: 4.056