Minimum latency effects for cancer associated with exposures to radiation or other carcinogens.

BACKGROUND: In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data. METHODS: We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability. RESULTS: There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability. CONCLUSIONS: Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques.

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms.

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

Evidence for Increased Susceptibility to Breast Cancer From Exposure to Ionizing Radiation Due to a Familial History of Breast Cancer: Results From the Swedish Hemangioma Cohort.

Women with a history of breast cancer among family members are at increased risk for breast cancer. However, it is unknown whether a familial breast cancer history (FBCH) also increases individual susceptibility to breast cancer from radiation exposure. In this cohort study, 17,200 female Swedish hemangioma patients with 1,079 breast cancer cases diagnosed between 1958 and 2013, exposed to ionizing radiation in infancy, were linked to their first-degree relatives. The association between FBCH and radiation-induced breast cancer risk was assessed. Further, the relevance for breast cancer radiotherapy and mammography screening was evaluated. On average, the radiation-induced excess relative risk and excess absolute risk of breast cancer at age 50 years were 0.51 Gy-1 (95% confidence interval (CI): 0.33, 0.71) and 10.8 cases/10,000 person-years/Gy (95% CI: 7.0, 14.6), respectively. Radiation risk was higher by a factor of 2.7 (95% CI: 1.0, 4.8; P = 0.05) if 1 first-degree relative was affected by breast cancer. For whole-breast standard radiotherapy at age 40 years with a contralateral breast dose of 0.72 Gy, the 20-year radiation-related excess risk of contralateral breast cancer was estimated to increase from 0.6% for women without FBCH to 1.7% for women with FBCH. In a biennial mammography screening program at ages 40-74 years, radiation risk up to age 80 years would increase from 0.11% for women without FBCH to 0.29% for women with FBCH.

Estimating long-term health risks after breast cancer radiotherapy: merging evidence from low and high doses.

In breast cancer radiotherapy, substantial radiation exposure of organs other than the treated breast cannot be avoided, potentially inducing second primary cancer or heart disease. While distant organs and large parts of nearby ones receive doses in the mGy-Gy range, small parts of the heart, lung and bone marrow often receive doses as high as 50 Gy. Contemporary treatment planning allows for considerable flexibility in the distribution of this exposure. To optimise treatment with regards to long-term health risks, evidence-based risk estimates are required for the entire broad range of exposures. Here, we thus propose an approach that combines data from medical and epidemiological studies with different exposure conditions. Approximating cancer induction as a local process, we estimate organ cancer risks by integrating organ-specific dose-response relationships over the organ dose distributions. For highly exposed organ parts, specific high-dose risk models based on studies with medical exposure are applied. For organs or their parts receiving relatively low doses, established dose-response models based on radiation-epidemiological data are used. Joining the models in the intermediate dose range leads to a combined, in general non-linear, dose response supported by data over the whole relevant dose range. For heart diseases, a linear model consistent with high- and low-dose studies is presented. The resulting estimates of long-term health risks are largely compatible with rate ratios observed in randomised breast cancer radiotherapy trials. The risk models have been implemented in a software tool PASSOS that estimates long-term risks for individual breast cancer patients.

Toxicity of internal mammary irradiation in breast cancer. Are concerns still justified in times of modern treatment techniques?

BACKGROUND: The purpose of this study was to estimate the additional risk of side effects attributed to internal mammary node irradiation (IMNI) as part of regional lymph node irradiation (RNI) in breast cancer patients and to compare it with estimated overall survival (OS) benefit from IMNI. MATERIAL AND METHODS: Treatment plans (n = 80) with volumetric modulated arc therapy (VMAT) were calculated for 20 patients (4 plans per patient) with left-sided breast cancer from the prospective GATTUM trial in free breathing (FB) and in deep inspiration breath hold (DIBH). We assessed doses to organs at risk ((OARs) lung, contralateral breast and heart) during RNI with and without additional IMNI. Based on the OAR doses, the additional absolute risks of 10-year cardiac mortality, pneumonitis, and secondary lung and breast cancer were estimated using normal tissue complication probability (NTCP) and risk models assuming different age and risk levels. RESULTS: IMNI notably increased the mean OAR doses. The mean heart dose increased upon IMNI by 0.2-3.4 Gy (median: 1.9 Gy) in FB and 0.0-1.5 Gy (median 0.4 Gy) in DIBH. However, the estimated absolute additional 10-year cardiac mortality caused by IMNI was <0.5% for all patients studied except 70-year-old high risk patients (0.2-2.4% in FB and 0.0-1.1% in DIBH). In comparison to this, the published oncological benefit of IMNI ranges between 3.3% and 4.7%. The estimated additional 10-year risk of secondary cancer of the lung or contralateral breast ranged from 0-1.5% and 0-2.8%, respectively, depending on age and risk levels. IMNI increased the pneumonitis risk in all groups (0-2.2%). CONCLUSION: According to our analyses, the published oncological benefit of IMNI outweighs the estimated risk of cardiac mortality even in case of (e.g., cardiac) risk factors during VMAT. The estimated risk of secondary cancer or pneumonitis attributed to IMNI is low. DIBH reduces the estimated additional risk of IMNI even further and should be strongly considered especially in patients with a high baseline risk.

Radio-biologically motivated modeling of radiation risks of mortality from ischemic heart diseases in the Canadian fluoroscopy cohort study.

Recent analyses of the Canadian fluoroscopy cohort study reported significantly increased radiation risks of mortality from ischemic heart diseases (IHD) with a linear dose-response adjusted for dose fractionation. This cohort includes 63,707 tuberculosis patients from Canada who were exposed to low-to-moderate dose fractionated X-rays in 1930s-1950s and were followed-up for death from non-cancer causes during 1950-1987. In the current analysis, we scrutinized the assumption of linearity by analyzing a series of radio-biologically motivated nonlinear dose-response models to get a better understanding of the impact of radiation damage on IHD. The models were weighted according to their quality of fit and were then mathematically superposed applying the multi-model inference (MMI) technique. Our results indicated an essentially linear dose-response relationship for IHD mortality at low and medium doses and a supra-linear relationship at higher doses (> 1.5 Gy). At 5 Gy, the estimated radiation risks were fivefold higher compared to the linear no-threshold (LNT) model. This is the largest study of patients exposed to fractionated low-to-moderate doses of radiation. Our analyses confirm previously reported significantly increased radiation risks of IHD from doses similar to those from diagnostic radiation procedures.

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence.

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

Correction to: Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003.

The article Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003, written by Helmut Schöllnberger.

Left-sided breast cancer and risks of secondary lung cancer and ischemic heart disease : Effects of modern radiotherapy techniques.

PURPOSE: Modern breast cancer radiotherapy techniques, such as respiratory-gated radiotherapy in deep-inspiration breath-hold (DIBH) or volumetric-modulated arc radiotherapy (VMAT) have been shown to reduce the high dose exposure of the heart in left-sided breast cancer. The aim of the present study was to comparatively estimate the excess relative and absolute risks of radiation-induced secondary lung cancer and ischemic heart disease for different modern radiotherapy techniques. METHODS: Four different treatment plans were generated for ten computed tomography data sets of patients with left-sided breast cancer, using either three-dimensional conformal radiotherapy (3D-CRT) or VMAT, in free-breathing (FB) or DIBH. Dose-volume histograms were used for organ equivalent dose (OED) calculations using linear, linear-exponential, and plateau models for the lung. A linear model was applied to estimate the long-term risk of ischemic heart disease as motivated by epidemiologic data. Excess relative risk (ERR) and 10-year excess absolute risk (EAR) for radiation-induced secondary lung cancer and ischemic heart disease were estimated for different representative baseline risks. RESULTS: The DIBH maneuver resulted in a significant reduction of the ERR and estimated 10-year excess absolute risk for major coronary events compared to FB in 3D-CRT plans (p = 0.04). In VMAT plans, the mean predicted risk reduction through DIBH was less pronounced and not statistically significant (p = 0.44). The risk of radiation-induced secondary lung cancer was mainly influenced by the radiotherapy technique, with no beneficial effect through DIBH. VMAT plans correlated with an increase in 10-year EAR for radiation-induced lung cancer as compared to 3D-CRT plans (DIBH p = 0.007; FB p = 0.005, respectively). However, the EARs were affected more strongly by nonradiation-associated risk factors, such as smoking, as compared to the choice of treatment technique. CONCLUSION: The results indicate that 3D-CRT plans in DIBH pose the lowest risk for both major coronary events and secondary lung cancer.

Correction to: Left-sided breast cancer and risks of secondary lung cancer and ischemic heart disease-Effects of modern radiotherapy techniques.

Correction to: Strahlenther Onkol 2017 https://doi.org/10.1007/s00066-017-1213-y Unfortunately, during copy editing, the titles of Fig. 2a and 2b were removed.The correct Fig. 2a and 2b are shown below. The original article has been corrected ….

Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003.

The scientific community faces important discussions on the validity of the linear no-threshold (LNT) model for radiation-associated cardiovascular diseases at low and moderate doses. In the present study, mortalities from cerebrovascular diseases (CeVD) and heart diseases from the latest data on atomic bomb survivors were analyzed. The analysis was performed with several radio-biologically motivated linear and nonlinear dose-response models. For each detrimental health outcome one set of models was identified that all fitted the data about equally well. This set was used for multi-model inference (MMI), a statistical method of superposing different models to allow risk estimates to be based on several plausible dose-response models rather than just relying on a single model of choice. MMI provides a more accurate determination of the dose response and a more comprehensive characterization of uncertainties. It was found that for CeVD, the dose-response curve from MMI is located below the linear no-threshold model at low and medium doses (0-1.4 Gy). At higher doses MMI predicts a higher risk compared to the LNT model. A sublinear dose-response was also found for heart diseases (0-3 Gy). The analyses provide no conclusive answer to the question whether there is a radiation risk below 0.75 Gy for CeVD and 2.6 Gy for heart diseases. MMI suggests that the dose-response curves for CeVD and heart diseases in the Lifespan Study are sublinear at low and moderate doses. This has relevance for radiotherapy treatment planning and for international radiation protection practices in general.

Integration of a radiation biomarker into modeling of thyroid carcinogenesis and post-Chernobyl risk assessment.

Strong evidence for the statistical association between radiation exposure and disease has been produced for thyroid cancer by epidemiological studies after the Chernobyl accident. However, limitations of the epidemiological approach in order to explore health risks especially at low doses of radiation appear obvious. Statistical fluctuations due to small case numbers dominate the uncertainty of risk estimates. Molecular radiation markers have been searched extensively to separate radiation-induced cancer cases from sporadic cases. The overexpression of the CLIP2 gene is the most promising of these markers. It was found in the majority of papillary thyroid cancers (PTCs) from young patients included in the Chernobyl tissue bank. Motivated by the CLIP2 findings we propose a mechanistic model which describes PTC development as a sequence of rate-limiting events in two distinct paths of CLIP2-associated and multistage carcinogenesis. It integrates molecular measurements of the dichotomous CLIP2 marker from 141 patients into the epidemiological risk analysis for about 13 000 subjects from the Ukrainian-American cohort which were exposed below age 19 years and were put under enhanced medical surveillance since 1998. For the first time, a radiation risk has been estimated solely from marker measurements. Cross checking with epidemiological estimates and model validation suggests that CLIP2 is a marker of high precision. CLIP2 leaves an imprint in the epidemiological incidence data which is typical for a driver gene. With the mechanistic model, we explore the impact of radiation on the molecular landscape of PTC. The model constitutes a unique interface between molecular biology and radiation epidemiology.

Anatomy-dependent lung doses from 3D-conformal breast-cancer radiotherapy.

This study aims to identify key anatomic features that govern the individual variability of lung doses from breast-cancer radiotherapy. 3D conformal, intensity-modulated and hybrid techniques with 50.4 Gy whole-breast dose were planned for 128 patients. From their CT images, 17 anatomic measures were assessed and tested as predictors for lung dose-volume characteristics. Tangential techniques yielded mean ipsilateral lung doses in the range of 3-11 Gy. This inter-patient variability was explained to almost 40% by central lung distance, and to almost 60% if this measure was complemented by midplane lung width and maximum heart distance. Also the variability in further dose-volume metrics such as volume fractions receiving 5, 20 or 40 Gy could be largely explained by the anatomy. Multi-field intensity-modulated radiotherapy reduced high-exposed lung volumes, but resulted in higher mean ipsilateral lung doses and larger low-dose burden. Contralateral lung doses ranged from 0.3 to 1 Gy. The results highlight that there are large differences in lung doses among breast-cancer patients. Most of this inter-individual variability can be explained by a few anatomic features. The results will be implemented in a dedicated software tool to provide personalized estimates of long-term health risks related to breast-cancer radiotherapy. The results may also be used to identify favourable as well as problematic anatomies, and serve as a quick quantitative benchmark for individual treatment plans.

Mammary Chain Irradiation in Left-Sided Breast Cancer: Can We Reduce the Risk of Secondary Cancer and Ischaemic Heart Disease with Modern Intensity-Modulated Radiotherapy Techniques?

INTRODUCTION: The aim of the present study was to estimate the impact of the addition of internal mammary chain (IMC) irradiation in node-positive left-sided breast cancer (BC) patients undergoing regional nodal irradiation (RNI) and comparatively evaluate excess relative and absolute risks of radiation-induced lung cancer/BC and ischaemic heart disease for intensity-modulated radiotherapy (IMRT) versus 3D conformal radiotherapy (3D-CRT). METHODS: Four treatment plans were created (3D-CRT and IMRT -/+ IMC) for each of the 10 evaluated patients, and estimates of excess relative risk (ERR) and 10-year excess absolute risk (EAR) were calculated for radiation-induced lung cancer/BC and coronary events using linear, linear-exponential and plateau models. RESULTS: The addition of IMC irradiation to RNI significantly increased the dose exposure of the heart, lung and contralateral breast using both techniques, increasing ERR for secondary lung cancer (58 vs. 44%, p = 0.002), contralateral BC (49 vs. 31%, p = 0.002) and ischaemic heart disease (41 vs. 27%, p = 0.002, IMRT plans). IMRT significantly reduced the mean cardiac dose and mean lung dose as compared to 3D-CRT, decreasing ERR for major coronary events (64% 3D-CRT vs. 41% IMRT, p = 0.002) and ERR for secondary lung cancer (75 vs. 58%, p = 0.004) in IMC irradiation, without a significant impact on secondary contralateral BC risks. CONCLUSION: Although IMC irradiation has been shown to increase survival rates in node-positive BC patients, it increased dose exposure of organs at risk in left-sided BC, resulting in significantly increased risks for secondary lung cancer/contralateral BC and ischaemic heart disease. In this setting, the adoption of IMRT seems advantageous when compared to 3D-CRT.

Analytical formulas representing track-structure simulations on DNA damage induced by protons and light ions at radiotherapy-relevant energies.

Track structure based simulations valuably complement experimental research on biological effects of ionizing radiation. They provide information at the highest level of detail on initial DNA damage induced by diverse types of radiation. Simulations with the biophysical Monte Carlo code PARTRAC have been used for testing working hypotheses on radiation action mechanisms, for benchmarking other damage codes and as input for modelling subsequent biological processes. To facilitate such applications and in particular to enable extending the simulations to mixed radiation field conditions, we present analytical formulas that capture PARTRAC simulation results on DNA single- and double-strand breaks and their clusters induced in cells irradiated by ions ranging from hydrogen to neon at energies from 0.5 GeV/u down to their stopping. These functions offer a means by which radiation transport codes at the macroscopic scale could easily be extended to predict biological effects, exploiting a large database of results from micro-/nanoscale simulations, without having to deal with the coupling of spatial scales and running full track-structure calculations.

Heart sparing radiotherapy in breast cancer: the importance of baseline cardiac risks.

BACKGROUND: Patients with left-sided breast cancer have an increased risk of cardiovascular disease (CVD) after radiotherapy (RT). While the awareness of cardiac toxicity has increased enormously over the last decade, the role of individual baseline cardiac risks has not yet been systematically investigated. Aim of the present study was to evaluate the impact of baseline CVD risks on radiation-induced cardiac toxicity. METHODS: Two hundred ten patients with left-sided breast cancer treated in the prospective Save-Heart Study using a deep inspiration breath-hold (DIBH) technique were analysed regarding baseline risk factors for CVD. Three frequently used prediction tools (Procam, Framingham and Reynolds score) were applied to evaluate the individual CVD risk profiles. Moreover, 10-year CVD excess absolute risks (EAR) were estimated using the individual mean heart dose (MHD) of treatment plans in free breathing (FB) and DIBH. RESULTS: The individual baseline CVD risk factors had a strong impact on the 10-year cumulative CVD risk. The mean baseline risks of the non-diabetic cohort (n = 200) ranged from 3.11 to 3.58%, depending on the risk estimation tool. A large number of the non-diabetic patients had a very low 10-year CVD baseline risk of ≤1%; nevertheless, 8-9% of patients reached ≥10% baseline 10-year CVD risk. In contrast, diabetic patients (n = 10) had significantly higher baseline CVD risks (range: 11.76-24.23%). The mean 10-year cumulative risk (Framingham score) following RT was 3.73% using the DIBH-technique (MHD:1.42Gy) and 3.94% in FB (MHD:2.33Gy), after adding a 10-year-EAR of + 0.34%(DIBH) and + 0.55%(FB) to the baseline risks, respectively. Smoking status was one of the most important and modifiable baseline risk factors. After DIBH-RT, the 182 non-smoking patients had a mean 10-year cumulative risk of 3.55% (3.20% baseline risk, 0.35% EAR) as compared to 6.07% (5.60% baseline risk, 0.47% EAR) for the 28 smokers. CONCLUSION: In the present study, all CVD prediction tools showed comparable results and could easily be integrated into daily clinical practice. A systematic evaluation and screening helps to identify high-risk patients who may benefit from primary prevention. This could result in an even higher benefit than from heart-sparing irradiation techniques alone.

Breast cancer risk among Swedish hemangioma patients and possible consequences of radiation-induced genomic instability.

Breast cancer incidence among 17,158 female Swedish hemangioma patients was analyzed with empirical excess relative risk models and with a biologically-based model of carcinogenesis. The patients were treated in infancy mainly by external application of radium-226. The mean and median absorbed doses to the breast were 0.29 and 0.04Gy, and a total of 678 breast cancer cases have been observed. Both models agree very well in the risk estimates with an excess relative risk and excess absolute risk at the age of 50 years, about the mean age of breast cancer incidence, of 0.25Gy(-1)(95% CI 0.14; 0.37) and 30.7 (10(5) BYR Gy)(-1) (95% CI 16.9; 42.8), respectively. Models incorporating effects of radiation-induced genomic instability were developed and applied to the hemangioma cohort. The biologically-based description of the radiation risk was significantly improved with a model of genomic instability at an early stage of carcinogenesis.

BIOPHYSICAL SIMULATION TOOL PARTRAC: MODELLING PROTON BEAMS AT THERAPY-RELEVANT ENERGIES.

The biophysical simulation tool PARTRAC has been primarily developed to model radiation physics, chemistry and biology on nanometre to micrometre scales. However, the tool can be applied in simulating radiation effects in an event-by-event manner over macroscopic volumes as well. Benchmark simulations are reported showing that PARTRAC does reproduce the macroscopic Bragg peaks of proton beams, although the penetration depths are underestimated by a few per cent for high-energy beams. PARTRAC also quantifies the increase in DNA damage and its complexity along the beam penetration depth. Enhanced biological effectiveness is predicted in particular within distal Bragg peak parts of therapeutic proton beams.

WHAT ANATOMIC FEATURES GOVERN PERSONAL LONG-TERM HEALTH RISKS FROM BREAST CANCER RADIOTHERAPY?

Breast cancer radiotherapy may in the long term lead to radiation-induced secondary cancer or heart disease. These health risks hugely vary among patients, partially due to anatomy-driven differences in doses deposited to the heart, ipsilateral lung and contralateral breast. We identify four anatomic features that largely cover these dosimetric variations to enable personalized risk estimates. For three exemplary, very different risk scenarios, the given parameter set reproduces 63-74% of the individual risk variability for left-sided breast cancer patients. These anatomic features will be used in the PASSOS software to support decision processes in breast-cancer therapy.

Minimum breast distance largely explains individual variability in doses to contralateral breast from breast-cancer radiotherapy.

PURPOSE: To provide personalized estimates of doses to contralateral breast (CB) from breast-cancer radiotherapy. METHODS: Whole-breast irradiations using 3D conformal, intensity-modulated and hybrid techniques with 50.4 Gy prescribed dose were planned for 128 breast-cancer patients. From their CT images, 17 anatomic measures were assessed and tested by model fitting as predictors for CB dose-volume characteristics. RESULTS: Multi-field intensity-modulated radiotherapy (IMRT) yielded mean CB doses of 0.8-7.1 Gy, with no correlation to the studied anatomic parameters. Tangential whole-breast irradiation led to much lower mean CB doses, 0.2-1.6 Gy. About 60% of this inter-patient variability was explained by individual variations in a single anatomic measure, the minimum breast distance (MBD), defined as the CB distance from the tangent to the treated breast. Per 1 cm increase in MBD, the mean CB dose decreased by 10-15%. As an alternative to MBD, dose estimates could be based on the breast-to-breast distance, which is highly correlated with MBD. CONCLUSION: The results enable personalized assessment of CB doses from tangential whole-breast irradiation, based only on parameters assessable from CT data. This may help support clinical decision-making processes as well as analyse retrospective studies on CB risks.