dose threshold
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2021 ◽  
Vol 19 (11) ◽  
pp. 141-150
Author(s):  
Ahmed H. Waheeb ◽  
Zeinab Eltaher ◽  
Mohamed N. Yassin ◽  
Magdy M. Khalil

This study examined the gamma passing rate (GPR) consistency during applying different kinds of gamma analyses and dosimeters to IMRT. Methods: Import treatment protocols for QA phantom irradiation have been recalculated. A gamma analysis was used for comparing the measured and calculated dose distribution of IMRT for different gamma criteria (2%/2mm, 3%/3mm, 4%/4mm, 3%/5mm, 3%/5mm). These criteria are evaluated when 5%, 10%, or 15% of the dose distribution is suppressed. Measured and calculated dose distribution was evaluated with gamma analysis to dose difference (DD) with DTA criteria (distance to agreement). IMRT QA plans to 25 patients from various sites were formed with the Varian Eclipse treatment planning system. Results: Results indicate different diverse hardware and software combinations show varied levels of agreement with expected analysis for the same pass-rate criterion. For a dosimetry audit of the IMRT technique, an EPID detector is superior to conventional methods comparable to Gafchromic EPT3 film and 2D array due to cost, time-consuming, and set up error to get result analysis. The gamma passing rate (GPR) average is increased by increasing the low-dose threshold for different dosimetric tools. For EPID, regardless of the gamma criterion employed, the %GP does not appear to be dependent on the low-dose threshold values (5%-15%) because it indicates that fulfilment the low-dose threshold to global normalization has little effect on patient-specific QA outcomes. Conclusions: It is concluded that GPRs differ depending on gamma, dosimetric tools, and the suppressing dose ratio. To get the best results of quality assurance, each institution should thus carefully develop its procedure for gamma analysis by defining the gamma index analysis and gamma criterion using its dosimetric tools.


Author(s):  
Franz Oesch ◽  
Daniela Fruth ◽  
Jan G. Hengstler ◽  
Eric Fabian ◽  
Franz Ingo Berger ◽  
...  

AbstractN-vinyl pyrrolidone (NVP) is produced up to several thousand tons per year as starting material for the production of polymers to be used in pharmaceutics, cosmetics and food technology. Upon inhalation NVP was carcinogenic in the rat, liver tumor formation is starting already at the rather low concentration of 5 ppm. Hence, differentiation whether NVP is a genotoxic carcinogen (presumed to generally have no dose threshold for the carcinogenic activity) or a non-genotoxic carcinogen (with a potentially definable threshold) is highly important. In the present study, therefore, the existing genotoxicity investigations on NVP (all showing consistently negative results) were extended and complemented with investigations on possible alternative mechanisms, which also all proved negative. All tests were performed in the same species (rat) using the same route of exposure (inhalation) and the same doses of NVP (5, 10 and 20 ppm) as had been used in the positive carcinogenicity test. Specifically, the tests included an ex vivo Comet assay (so far not available) and an ex vivo micronucleus test (in contrast to the already available micronucleus test in mice here in the same species and by the same route of application as in the bioassay which had shown the carcinogenicity), tests on oxidative stress (non-protein-bound sulfhydryls and glutathione recycling test), mechanisms mediated by hepatic receptors, the activation of which had been shown earlier to lead to carcinogenicity in some instances (Ah receptor, CAR, PXR, PPARα). No indications were obtained for any of the investigated mechanisms to be responsible for or to contribute to the observed carcinogenicity of NVP. The most important of these exclusions is genotoxicity. Thus, NVP can rightfully be regarded and treated as a non-genotoxic carcinogen and threshold approaches to the assessment of this chemical are supported. However, the mechanism underlying the carcinogenicity of NVP in rats remains unclear.


2021 ◽  
Author(s):  
Bernardo A Mello

A primary concern in epidemics is to minimize the probability of contagion, often resorting to reducing the number of contacted people. However, the success of that strategy depends on the shape of the dose-response curve, which relates the response of the exposed person to the pathogen dose received from surrounding infected people. If the reduction is achieved by spending more time with each contacted person, the pathogen charge received from each infected individual will be larger. The extended time spent close to each person may worsen the expected response if the dose-response curve is concave for small doses. This is the case when the expected response is negligible below a certain dose threshold and rises sharply above it. This paper proposes a mathematical model to calculate the expected response and uses it to identify the conditions when it would be advisable to reduce the contact time with each individual even at the cost of increasing the number of contacted people.


2021 ◽  
pp. 20210543
Author(s):  
Aaron D Sodickson

Radiation risks from diagnostic imaging have captured the attention of patients and medical practitioners alike, yet it remains unclear how these considerations can best be incorporated into clinical decision making. This manuscript presents a framework to consider these issues in a potentially at-risk population, the so called “frequent flyer” patients undergoing a large amount of recurrent imaging over time. Radiation risks from the low-dose exposures of diagnostic imaging are briefly reviewed, as applied to recurrent exposures. Some scenarios are then explored in which it may be helpful to incorporate knowledge of a patient’s imaging history. There is no simple or uniformly applicable approach to these challenging and often nuanced clinical decisions. The complexity and variability of the underlying disease states and trajectories argues against alerting mechanisms based on a simple cumulative dose threshold. Awareness of imaging history may instead be beneficial in encouraging physicians and patients to take the long view, and to identify those populations of frequent flyers that might benefit from alternative imaging strategies.


Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3549
Author(s):  
Minglei Kang ◽  
Shouyi Wei ◽  
J. Isabelle Choi ◽  
Charles B. Simone ◽  
Haibo Lin

To quantitatively assess target and organs-at-risk (OAR) dose rate based on three proposed proton PBS dose rate metrics and study FLASH intensity-modulated proton therapy (IMPT) treatment planning using transmission beams. An in-house FLASH planning platform was developed to optimize transmission (shoot-through) plans for nine consecutive lung cancer patients previously planned with proton SBRT. Dose and dose rate calculation codes were developed to quantify three types of dose rate calculation methods (dose-averaged dose rate (DADR), average dose rate (ADR), and dose-threshold dose rate (DTDR)) based on both phantom and patient treatment plans. Two different minimum MU/spot settings were used to optimize two different dose regimes, 34-Gy in one fraction and 45-Gy in three fractions. The OAR sparing and target coverage can be optimized with good uniformity (hotspot < 110% of prescription dose). ADR, accounting for the spot dwelling and scanning time, gives the lowest dose rate; DTDR, not considering this time but a dose-threshold, gives an intermediate dose rate, whereas DADR gives the highest dose rate without considering any time or dose-threshold. All three dose rates attenuate along the beam direction, and the highest dose rate regions often occur on the field edge for ADR and DTDR, whereas DADR has a better dose rate uniformity. The differences in dose rate metrics have led a large variation for OARs dose rate assessment, posing challenges to FLASH clinical implementation. This is the first attempt to study the impact of the dose rate models, and more investigations and evidence for the details of proton PBS FLASH parameters are needed to explore the correlation between FLASH efficacy and the dose rate metrics.


2020 ◽  
Vol 127 (11) ◽  
pp. 1455-1466
Author(s):  
Christoph Reiners ◽  
Valentina Drozd ◽  
Shunichi Yamashita

Abstract The thyroid gland is among the organs at the greatest risk of cancer from ionizing radiation. Epidemiological evidence from survivors of radiation therapy, atomic bombing, and the Chernobyl reactor accident, clearly shows that radiation exposure in childhood can cause thyroid cancer and benign thyroid nodules. Radiation exposure also may induce hypothyroidism and autoimmune reactions against the thyroid, but these effects are less well-documented. The literature includes only a few, methodologically weak animal studies regarding genetic/molecular mechanisms underlying hypothyroidism and thyroid autoimmunity after radiation exposure. Rather, evidence about radiation-induced hypothyroidism and thyroid autoimmunity derives mainly from follow-up studies in patients treated with external beam radiotherapy (EBRT) or iodine-131, and from epidemiological studies in the atomic bombing or nuclear accident survivors. Historically, hypothyroidism after external irradiation of the thyroid in adulthood was considered not to develop below a 10–20 Gy dose threshold. Newer data suggest a 10 Gy threshold after EBRT. By contrast, data from patients after iodine-131 “internal radiation therapy” of Graves´ disease indicate that hypothyroidism rarely occurs below thyroid doses of 50 Gy. Studies in children affected by the Chernobyl accident indicate that the dose threshold for hypothyroidism may be considerably lower, 3–5 Gy, aligning with observations in A-bomb survivors exposed as children. The reasons for these dose differences in radiosensitivity are not fully understood. Other important questions about the development of hypothyroidism after radiation exposure e.g., in utero, about the interaction between autoimmunity and hypofunction, and about the different effects of internal and external irradiation still must be answered.


2020 ◽  
Vol 19 (12) ◽  
pp. 1362-1371 ◽  
Author(s):  
Ben Ouyang ◽  
Wilson Poon ◽  
Yi-Nan Zhang ◽  
Zachary P. Lin ◽  
Benjamin R. Kingston ◽  
...  
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