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Basic Radiobiology
Published in Kwan Hoong Ng, Ngie Min Ung, Robin Hill, Problems and Solutions in Medical Physics, 2023
Kwan Hoong Ng, Ngie Min Ung, Robin Hill
Solution:The LNT model is a model used in radiation protection to estimate the long-term, biological effect caused by ionising radiation. It assumed that the risk or damage due to radiation is directly proportional (“linear”) to the dose of radiation, at all dose levels. The LNT risk model is the current human health risk assessment paradigm.Threshold model assumes that radiation has no health effect up to a certain dose. After that dose, health effect from radiation exposure may be observed and the severity/risk of the effect increases with dose.Hormesis model assumes that radiation in high doses increases the incidence of cancer; however, doses up to some points (at low level) are beneficial to the person. Low doses of ionising radiation are hypothesised to be beneficial by stimulating the immune system and repair mechanisms.See Figure 9.2.
Diagnostic Imaging Using X-rays
Published in Debbie Peet, Emma Chung, Practical Medical Physics, 2021
Debbie Peet, Richard Farley, Elizabeth Davies
Further developments in computing may mean that it becomes more practical to produce more personalised phantom-based dose estimates. While work towards this has begun with the AAPMs Size Specific Dose Estimates it is likely that in the future this will be superseded by automated segmentation of CTs to allow individual dose estimates. The theory that underpins the concept of effective dose relies on the “Linear No Threshold model” described in Chapter 7. If this is proved to be incorrect, mechanisms for calculating effective dose will need to be adjusted accordingly. Other possibilities for the future are the development of more sensitive tests for DNA damage caused by radiation. This may allow personalised radiation doses, rather than using theoretical constructs that introduce large degrees of error.
Risk Characterization
Published in Ted W. Simon, Environmental Risk Assessment, 2019
Another classification of uncertainty exists as well. Parameter uncertainty arises from measurement error or whether the parameter values used in a risk assessment represent the target population accurately. Model uncertainty arises from lack of an adequate scientific basis for the theory underlying some aspect of the risk assessment. For example, page 165 of the “Blue Book” highlights the validity or lack thereof of the linear no-threshold model as an example of model uncertainty.2
The roles of intensity, exposure duration, and modulation on the biological effects of radiofrequency radiation and exposure guidelines
Published in Electromagnetic Biology and Medicine, 2022
The U.S. FCC was the first government entity to adopt exposure guidelines in 1968 for RFR. Thereafter, the fundamental acute threshold model never fully evolved with the science, although changes were added to clarify that singular model over the decades as new dosimetry measurements improved. As better understanding developed of how RFR couples with living systems, there were new additions to the guidelines regarding specific absorption rates (SARs, i.e., the rate of RF energy absorbed per unit mass of tissue); maximum permissible exposures (MPEs), different averaging times, whole-body as well as limited-body absorption allowances; wider frequency inclusions, and two-tiered allowances for the general population and occupational exposures, among others. But that has all been used within the framework of a basic acute threshold model.
“It’s a place that gives me hope”: A qualitative evaluation of a buprenorphine-naloxone group visit program in an urban federally qualified health center
Published in Substance Abuse, 2021
Sunny Lai, Erica Li, Alexis Silverio, Robin DeBates, Erin Lee Kelly, Lara Carson Weinstein
To increase uptake of MOUD, some organizations have advocated for “low-threshold” models to substance use care.4,12,14,16 While there is no universal standard, proposed features typically address accessibility and treatment design barriers.14 In our study, program participants mentioned 3 specific areas that facilitated their participation and engagement in the program: ease of access, integration in primary care, and group-based visit model. Rapid-entry scheduling enables people to access treatment quickly, which increases the proportion of people who initiate treatment.4 Group-based models increase access to MOUD and provide unique supportive mechanisms, such as emotional support, accountability, shared identity, and community.17 Integration in primary care can increase access to primary care, behavioral health, and psychosocial services, destigmatize treatment for substance use disorder, and facilitate care coordination and team-based care.18 Our findings provide qualitative support for the benefits of a “low-threshold” model.
Is there a role for the adverse outcome pathway framework to support radiation protection?
Published in International Journal of Radiation Biology, 2019
Vinita Chauhan, Zakaria Said, Joseph Daka, Baki Sadi, Deepti Bijlani, Francesco Marchetti, Danielle Beaton, Adelene Gaw, Chunsheng Li, Julie Burtt, Julie Leblanc, Marc Desrosiers, Marilyne Stuart, Mathieu Brossard, Ngoc Q. Vuong, Ruth Wilkins, Sami Qutob, James McNamee, Yi Wang, Carole Yauk
The radiation field is also faced with challenges similar to those that confront chemical toxicology, particularly with regards to high-to-low dose extrapolation and the use of apical endpoints to define risk. There is uncertainty in the frequency of adverse health outcomes at low doses and low dose rates which leads to discussions about the appropriateness of using the linear-non-threshold model for extrapolating from effects at higher doses to estimate adverse outcomes at low doses (Averbeck 2009). Linking stochastic health outcomes to early molecular changes may allow for the development of relevant biological signatures that could be assessed in human body fluids. Furthermore, knowledge surrounding mechanistically-shared pathways among different stressors is limited. The AOP framework could offer a means to help support the refinement of risk based upon combined exposures to agents that share mechanistically similar AOPs.