Is patient size important in dose determination and optimization in cardiology?
Patient dose determination and optimization have become more topical in recent years with the implementation of the Medical Exposures Directive into national legislation, the Ionising Radiation (Medical Exposure) Regulations. This legislation incorporates a requirement for new equipment to provide a means of displaying a measure of patient exposure and introduces the concept of diagnostic reference levels. It is normally assumed that patient dose is governed largely by patient size; however, in cardiology, where procedures are often very complex, the significance of patient size is less well understood. This study considers over 9000 cardiology procedures, undertaken throughout the north of England, and investigates the relationship between patient size and dose. It uses simple linear regression to calculate both correlation coefficients and significance levels for data sorted by both room and individual clinician for the four most common examinations, left ventrical and/or coronary angiography, single vessel stent insertion and single vessel angioplasty. This paper concludes that the correlation between patient size and dose is weak for the procedures considered. It also illustrates the use of an existing method for removing the effect of patient size from dose survey data. This allows typical doses and, therefore, reference levels to be defined for the purposes of dose optimization.
Reay
J
J
Regional Medical Physics Department, Newcastle General Hospital, Newcastle Upon Tyne, NE4 6BE, UK.
Chapple
C L
CL
Kotre
C J
CJ
D001824:Body Constitution; D017023:Coronary Angiography; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D011829:Radiation Dosage; D011835:Radiation Protection / Q000379:methods*; D011874:Radiometry / Q000379:methods*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013223:Statistics as Topic