Literature DB >> 24105448

Predicted cancer risks induced by computed tomography examinations during childhood, by a quantitative risk assessment approach.

Neige Journy1, Sophie Ancelet, Jean-Luc Rehel, Myriam Mezzarobba, Bernard Aubert, Dominique Laurier, Marie-Odile Bernier.   

Abstract

The potential adverse effects associated with exposure to ionizing radiation from computed tomography (CT) in pediatrics must be characterized in relation to their expected clinical benefits. Additional epidemiological data are, however, still awaited for providing a lifelong overview of potential cancer risks. This paper gives predictions of potential lifetime risks of cancer incidence that would be induced by CT examinations during childhood in French routine practices in pediatrics. Organ doses were estimated from standard radiological protocols in 15 hospitals. Excess risks of leukemia, brain/central nervous system, breast and thyroid cancers were predicted from dose-response models estimated in the Japanese atomic bomb survivors' dataset and studies of medical exposures. Uncertainty in predictions was quantified using Monte Carlo simulations. This approach predicts that 100,000 skull/brain scans in 5-year-old children would result in eight (90 % uncertainty interval (UI) 1-55) brain/CNS cancers and four (90 % UI 1-14) cases of leukemia and that 100,000 chest scans would lead to 31 (90 % UI 9-101) thyroid cancers, 55 (90 % UI 20-158) breast cancers, and one (90 % UI <0.1-4) leukemia case (all in excess of risks without exposure). Compared to background risks, radiation-induced risks would be low for individuals throughout life, but relative risks would be highest in the first decades of life. Heterogeneity in the radiological protocols across the hospitals implies that 5-10 % of CT examinations would be related to risks 1.4-3.6 times higher than those for the median doses. Overall excess relative risks in exposed populations would be 1-10 % depending on the site of cancer and the duration of follow-up. The results emphasize the potential risks of cancer specifically from standard CT examinations in pediatrics and underline the necessity of optimization of radiological protocols.

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Year:  2013        PMID: 24105448     DOI: 10.1007/s00411-013-0491-8

Source DB:  PubMed          Journal:  Radiat Environ Biophys        ISSN: 0301-634X            Impact factor:   1.925


  62 in total

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10.  Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging.

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