A key concern with the use of radiation sources (including nuclear power) is the health effects of low levels of radiation, especially the regulatory assumption that every additional increment of radiation increases the risk of cancer (linear no-threshold model, or LNT). The LNT model is nearly a century old. There are dozens if not hundreds of studies showing that this model is incompatible with animal, cellular, molecular, and epidemiological data for low-dose rates in the range of both background radiation levels and much of occupational exposure. The assumption that every increment of radiation equally increases the risk of cancer results in increased physical risks to workers involved with actions to reduce radiation exposure (such as risks from welding additional shielding in place or from additional construction activities to reduce post-closure waste site radiation levels) and avoidance of medical exposure even when radiation treatment has a lower risk than other options such as surgery. One fundamental shortcoming of the LNT model is that it does not account for natural processes that repair DNA damage. However, there is no contiguous mathematical model that estimates cancer risk for both high- and low-dose rates that incorporates what we have learned about DNA repair mechanisms and is sufficiently simple and conservative to address regulatory concerns. The author proposes a mathematical model that dramatically reduces the estimated cancer risks for low-dose rates while recognizing the linear relationship between cancer and dose at high-dose rates.
Keyphrases
- low dose
- high dose
- papillary thyroid
- dna damage
- dna repair
- squamous cell
- radiation induced
- healthcare
- childhood cancer
- minimally invasive
- radiation therapy
- oxidative stress
- machine learning
- heavy metals
- stem cell transplantation
- young adults
- coronary artery disease
- risk assessment
- transcription factor
- mental health
- atrial fibrillation
- big data
- replacement therapy