Patient characteristics associated with differences in radiation exposure from pediatric abdomen-pelvis CT scans: a quantile regression analysis

BACKGROUND Computed tomography (CT) is a widely used diagnostic tool in pediatric medicine. However, due to concerns regarding radiation exposure, it is essential to identify patient characteristics associated with higher radiation burden from CT imaging, in order to more effectively target efforts towards dose reduction. Our objective was to identify the effects of various demographic and clinical patient characteristics on radiation exposure from single abdomen/pelvis CT scans in children. METHODS CT scans performed at our institution between January 2013 and August 2015 in patients under 16 years of age were processed using a software tool that estimates patient-specific organ and effective doses and merges these estimates with data from the electronic health record and billing record. Quantile regression models at the 50th, 75th, and 90th percentiles were used to estimate the effects of patients' demographic and clinical characteristics on effective dose. RESULTS 2390 abdomen/pelvis CT scans (median effective dose 1.52mSv) were included. Of all characteristics examined, only older age, female gender, higher BMI, and whether the scan was a multiphase exam or an exam that required repeating for movement were significant predictors of higher effective dose at each quantile examined (all p<0.05). The effects of obesity and multiphase or repeat scanning on effective dose were magnified in higher dose scans. CONCLUSIONS Older age, female gender, obesity, and multiphase or repeat scanning are all associated with increased effective dose from abdomen/pelvis CT. Targeted efforts to reduce dose from abdominal CT in these groups should be undertaken.

[1]  Choonsik Lee,et al.  Assessing Organ Doses from Paediatric CT Scans—A Novel Approach for an Epidemiology Study (the EPI-CT Study) † , 2013, International journal of environmental research and public health.

[2]  Julia F. Barrett,et al.  Artifacts in CT: recognition and avoidance. , 2004, Radiographics : a review publication of the Radiological Society of North America, Inc.

[3]  H. Pan,et al.  WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age , 2006 .

[4]  F. Lee,et al.  Computed Tomography in Abdominal Imaging: How to Gain Maximum Diagnostic Information at the Lowest Radiation Dose , 2013 .

[5]  Turner M. Osler,et al.  ICDPIC: Stata module to provide methods for translating International Classification of Diseases (Ninth Revision) diagnosis codes into standard injury categories and/or scores , 2010 .

[6]  K. P. Kim,et al.  Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study , 2012, The Lancet.

[7]  Wesley E Bolch,et al.  Organ doses for reference pediatric and adolescent patients undergoing computed tomography estimated by Monte Carlo simulation. , 2012, Medical physics.

[8]  F. Sung,et al.  Paediatric head CT scan and subsequent risk of malignancy and benign brain tumour: a nation-wide population-based cohort study , 2014, British Journal of Cancer.

[9]  Shumei S. Guo,et al.  2000 CDC Growth Charts for the United States: methods and development. , 2002, Vital and health statistics. Series 11, Data from the National Health Survey.

[10]  J. Boone,et al.  Predictors of CT Radiation Dose and Their Effect on Patient Care: A Comprehensive Analysis Using Automated Data. , 2017, Radiology.

[11]  Wesley E Bolch,et al.  The UF/NCI family of hybrid computational phantoms representing the current US population of male and female children, adolescents, and adults—application to CT dosimetry , 2014, Physics in medicine and biology.

[12]  Jianqing Fan,et al.  Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties , 2001 .

[13]  D. Frush,et al.  Dose reduction in paediatric MDCT: general principles. , 2007, Clinical radiology.

[14]  J. Mathews,et al.  Cancer risk in 680 000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians , 2013, BMJ.

[15]  Sheila Weinmann,et al.  Use of diagnostic imaging studies and associated radiation exposure for patients enrolled in large integrated health care systems, 1996-2010. , 2012, JAMA.

[16]  Keith J Strauss,et al.  Image gently: Ten steps you can take to optimize image quality and lower CT dose for pediatric patients. , 2010, AJR. American journal of roentgenology.

[17]  J. Zember,et al.  Evaluation of an initiative to reduce radiation exposure from CT to children in a non-pediatric-focused facility , 2015, Emergency Radiology.

[18]  R. Behrman,et al.  Increased radiation dose to overweight and obese patients from radiographic examinations. , 2009, Radiology.

[19]  Shumei S. Guo,et al.  CDC GROWTH CHARTS FOR THE UNITED STATES: METHODS AND DEVELOPMENT 2000 , 2002 .

[20]  Mannudeep K Kalra,et al.  Computed tomography radiation dose optimization: scanning protocols and clinical applications of automatic exposure control. , 2005, Current problems in diagnostic radiology.

[21]  Wesley E. Bolch,et al.  NCICT: a computational solution to estimate organ doses for pediatric and adult patients undergoing CT scans , 2015, Journal of radiological protection : official journal of the Society for Radiological Protection.

[22]  P. Austin,et al.  The use of quantile regression in health care research: a case study examining gender differences in the timeliness of thrombolytic therapy , 2005, Statistics in medicine.

[23]  Yufeng Liu,et al.  VARIABLE SELECTION IN QUANTILE REGRESSION , 2009 .

[24]  Sheila Weinmann,et al.  The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk. , 2013, JAMA pediatrics.

[25]  Erik Holmberg,et al.  Radiation Effects on Breast Cancer Risk: A Pooled Analysis of Eight Cohorts , 2002, Radiation research.

[26]  Wesley E Bolch,et al.  Monte Carlo simulations of adult and pediatric computed tomography exams: validation studies of organ doses with physical phantoms. , 2012, Medical physics.

[27]  Jack Valentin,et al.  The 2007 Recommendations of the International Commission on Radiological Protection. ICRP publication 103. , 2007, Annals of the ICRP.

[28]  Aiping Ding,et al.  Extension of RPI-adult male and female computational phantoms to obese patients and a Monte Carlo study of the effect on CT imaging dose , 2012, Physics in medicine and biology.

[29]  Andrew D. A. Maidment,et al.  RADIANCE: An automated, enterprise-wide solution for archiving and reporting CT radiation dose estimates. , 2011, Radiographics : a review publication of the Radiological Society of North America, Inc.

[30]  J. Boone,et al.  CT dose index and patient dose: they are not the same thing. , 2011, Radiology.