Does Imaging Technology Cause Cancer? Debunking the Linear No-Threshold Model of Radiation Carcinogenesis

• Published in: Technology in cancer research & treatment 2016-04, Vol.15 (2), p.249-256
• Main Authors: Siegel, Jeffry A., Welsh, James S.
• Format: Article
• Language: English
• Subjects: Carcinogenesis; Carcinogenesis - radiation effects; Computed tomography; Dose-Response Relationship, Radiation; Humans; Hypotheses; Ionizing radiation; Medical imaging; Neoplasms, Radiation-Induced - etiology; Nuclear medicine; Radiation Dosage; Radioactive Hazard Release; Risk; Scintigraphy; Tomography, X-Ray Computed - adverse effects
• ISSN: 1533-0346; 1533-0338
• DOI: 10.1177/1533034615578011

In the past several years, there has been a great deal of attention from the popular media focusing on the alleged carcinogenicity of low-dose radiation exposures received by patients undergoing medical imaging studies such as X-rays, computed tomography scans, and nuclear medicine scintigraphy. The media has based its reporting on the plethora of articles published in the scientific literature that claim that there is “no safe dose” of ionizing radiation, while essentially ignoring all the literature demonstrating the opposite point of view. But this reported “scientific” literature in turn bases its estimates of cancer induction on the linear no-threshold hypothesis of radiation carcinogenesis. The use of the linear no-threshold model has yielded hundreds of articles, all of which predict a definite carcinogenic effect of any dose of radiation, regardless of how small. Therefore, hospitals and professional societies have begun campaigns and policies aiming to reduce the use of certain medical imaging studies based on perceived risk:benefit ratio assumptions. However, as they are essentially all based on the linear no-threshold model of radiation carcinogenesis, the risk:benefit ratio models used to calculate the hazards of radiological imaging studies may be grossly inaccurate if the linear no-threshold hypothesis is wrong. Here, we review the myriad inadequacies of the linear no-threshold model and cast doubt on the various studies based on this overly simplistic model.