title: The effect of dose heterogeneity on radiation risk in medical imaging.
abstract: The current estimations of risk associated with medical imaging procedures rely on assessing the organ dose via direct measurements or simulation. The dose to each organ is assumed to be homogeneous. To take into account the differences in radiation sensitivities, the mean organ doses are weighted by a corresponding tissue-weighting coefficients provided by ICRP to calculate the effective dose, which has been used as a surrogate of radiation risk. However, those coefficients were derived under the assumption of a homogeneous dose distribution within each organ. That assumption is significantly violated in most medical-imaging procedures. In helical chest CT, for example, superficial organs (e.g. breasts) demonstrate a heterogeneous dose distribution, whereas organs on the peripheries of the irradiation field (e.g. liver) might possess a discontinuous dose profile. Projection radiography and mammography involve an even higher level of organ dose heterogeneity spanning up to two orders of magnitude. As such, mean dose or point measured dose values do not reflect the maximum energy deposited per unit volume of the organ. In this paper, the magnitude of the dose heterogeneity in both CT and projection X-ray imaging was reported, using Monte Carlo methods. The lung dose demonstrated factors of 1.7 and 2.2 difference between the mean and maximum dose for chest CT and radiography, respectively. The corresponding values for the liver were 1.9 and 3.5. For mammography and breast tomosynthesis, the difference between mean glandular dose and maximum glandular dose was 3.1. Risk models based on the mean dose were found to provide a reasonable reflection of cancer risk. However, for leukaemia, they were found to significantly under-represent the risk when the organ dose distribution is heterogeneous. A systematic study is needed to develop a risk model for heterogeneous dose distributions.
authors.affiliation: Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, NC, USA. samei@duke.edu
authors.forename: Ehsan
authors.initials: E
authors.lastname: Samei
authors.forename: Xiang
authors.initials: X
authors.lastname: Li
authors.forename: Baiyu
authors.initials: B
authors.lastname: Chen
authors.forename: Robert
authors.initials: R
authors.lastname: Reiman
mesh_terms: D001822:Body Burden; D001940:Breast / Q000473:pathology* / Q000528:radiation effects*; D003198:Computer Simulation; D003952:Diagnostic Imaging; D005260:Female; D006801:Humans; D008327:Mammography; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D058958:Organs at Risk / Q000528:radiation effects*; D011829:Radiation Dosage; D013902:Radiography, Thoracic; D018570:Risk Assessment; D014057:Tomography, X-Ray Computed; D014965:X-Rays