A joint physics and radiobiology DREAM team vision - Towards better response prediction models to advance radiotherapy.

Radiotherapy developed empirically through experience balancing tumour control and normal tissue toxicities. Early simple mathematical models formalized this practical knowledge and enabled effective cancer treatment to date. Remarkable advances in technology, computing, and experimental biology now create opportunities to incorporate this knowledge into enhanced computational models. The ESTRO DREAM (Dose Response, Experiment, Analysis, Modelling) workshop brought together experts across disciplines to pursue the vision of personalized radiotherapy for optimal outcomes through advanced modelling. The ultimate vision is leveraging quantitative models dynamically during therapy to ultimately achieve truly adaptive and biologically guided radiotherapy at the population as well as individual patient-based levels. This requires the generation of models that inform response-based adaptations, individually optimized delivery and enable biological monitoring to provide decision support to clinicians. The goal is expanding to models that can drive the realization of personalized therapy for optimal outcomes. This position paper provides their propositions that describe how innovations in biology, physics, mathematics, and data science including AI could inform models and improve predictions. It consolidates the DREAM team's consensus on scientific priorities and organizational requirements. Scientifically, it stresses the need for rigorous, multifaceted model development, comprehensive validation and clinical applicability and significance. Organizationally, it reinforces the prerequisites of interdisciplinary research and collaboration between physicians, medical physicists, radiobiologists, and computational scientists throughout model development. Solely by a shared understanding of clinical needs, biological mechanisms, and computational methods, more informed models can be created. Future research environment and support must facilitate this integrative method of operation across multiple disciplines.

Dependence of the AUC of NTCP models on the observational dose-range highlights cautions in comparison of discriminative performance.

BACKGROUND: Normal tissue complication probability (NTCP) models are probabilistic models that describe the risk of radio-induced toxicity in tissues or organs. In the field of radiotherapy, the area under the ROC curve (AUC) is widely used to estimate the performance in risk prediction of NTCP models. METHODS: In this work, we derived an analytical expression of the AUC for the logistic NTCP model in the case of both symmetrical and asymmetrical dose (to the normal tissue) windows around D50. Using numerical simulations, we studied the behavior of the AUC in general clinical settings, enforcing non-logistic NTCP models (Lyman-Kutcher-Burman and LogEUD) and including risk factors beyond the dose. We validated our findings using real-world radiotherapy data sets of prostate cancer patients. RESULTS: Our analytical expression of the AUC made explicit the dependence on both the steepness of the logistic curve (ß) and the dose window width (w), showing that an increase of w pushes AUC towards higher values. Increasing values of the AUC with increasing values of w were consistently observed across simulated data sets with diverse clinical settings from published studies and real clinical data sets. CONCLUSION: Our results reveal that the AUC of NTCP models inherits intrinsic characteristics from the clinical setting of the data set on which the models are developed, and warn against the use of the AUC to compare the performance of models constructed upon data from trials in which substantially different dose ranges were administered or accounting for different risk factors beyond the dose.

Survey on the interest and commitment of AIFM members to scientific activities (SicAS) - The initiative of the FutuRuS working group.

PURPOSE: The "FutuRuS" working group of the Italian Association of Medical Physics and Health Physics (AIFM) designed a survey (SicAS) to get feedback from its members regarding their interests and their experience in taking part in scientific activities and events, with the objective of focusing future efforts of the AIFM towards increasing the scientific activity of the medical physics expert (MPE). METHODS: SicAS was sent out in March 2022 to all AIFM members by newsletter and official communication. SicAS was structured into three sections: personal information and institution of affiliation information, involvement in scientific activities, interest in and commitment to scientific activities. Responses were collected in a fully anonymised mode from the Google Forms platform and analysed with descriptive statistics. RESULTS: Out of 1289 members (active at the end of 2021), 467 responded to the Survey (response rate of 36%). The Survey results highlighted that AIFM members ranked the involvement of the MPE in scientific activities as highly relevant to the profession. However, 34.7% indicated devoting less than 10% of their working time to scientific activities. 67.5% of the respondents were dissatisfied with the time spent on scientific activities. The primary barrier was the lack of time (77%), followed by a lack of mentoring (32%). CONCLUSIONS: SicAS highlighted the need for AIFM initiatives to support members' scientific activities. National societies should help develop and support networks between members, create links among universities, hospitals, research institutions and industries, and provide guidelines and learning platforms for enhancing the MPEs' involvement in scientific activities.

Overview of the synergistic use of radiotherapy and immunotherapy in cancer treatment: current challenges and scopes of improvement.

INTRODUCTION: Oncological treatments are changing rapidly due to the advent of several targeted anticancer drugs and regimens. The primary new area of research in oncological medicine is the implementation of a combination of novel therapies and standard care. In this scenario, radioimmunotherapy is one of the most promising fields, as proven by the exponential growth of publications in this context during the last decade. AREAS COVERED: This review provides an overview of the synergistic use of radiotherapy and immunotherapy and addresses questions like the importance of this subject, aspects clinicians look for in patients to administer this combined therapy, individuals who would benefit the most from this treatment, how to achieve abscopal effect and when does radio-immunotherapy become standard clinical practice. EXPERT OPINION: Answers to these queries generate further issues that need to be addressed and solved. The abscopal and bystander effects are not utopia, rather physiological phenomena that occur in our bodies. Nevertheless, substantial evidence regarding the combination of radioimmunotherapy is lacking. In conclusion, joining forces and finding answers to all these open questions is of paramount importance.

A global sensitivity analysis approach applied to a multiscale model of microvascular flow.

A global sensitivity analysis of a multiscale computational model of microvascular flow is presented. A total of 140 simulations have been completed and analyzed varying 6 input parameters and considering their effects on 7 output variables. Interestingly, the vascular network topology has been found as a determinant factor for both vasculature-related and interstitium-related quantities. Regarding the firsts, the vascular network topology has obtained a score of 5.5/6 and 6/6 for average and spatial distribution respectively (where 6 is the maximum and 1 is the minimum). On the other hand, considering interstitium-related quantities, the score is 4/6 and 5/6 for average and spatial distribution respectively. These results suggest that the network topology has a significant influence on the outcome of the computational analysis.

Bladder dose-surface maps and urinary toxicity: Robustness with respect to motion in assessing local dose effects.

The purpose of this study was to quantify the impact of inter-fraction modifications of bladder during RT of prostate cancer on bladder dose surface maps (DSM). Eighteen patients treated with daily image-guided Tomotherapy and moderate hypofractionation (70-72.8Gy at 2.5-2.6Gy/fr in 28 fractions and full bladder) were considered. Bladder contours were delineated on co-registered daily Megavoltage CT (MVCT) by a single observer and copied on the planning CT to generate dose-volume/surface histograms (DVH/DSH) and bladder DSMs. Discrepancies between planned and daily absorbed doses were analyzed through the average of individual systematic errors, the population systematic errors and the population random errors for the DVH/DSHs and DSMs. In total, 477 DVH/DSH and 472 DSM were available. DSH and DVH showed small population systematic errors of absolute surfaces (<3.4cm(2)) and volumes (<8.4cm(3)) at the highest doses. The dose to the posterior bladder base assessed on DSMs showed a mean systematic error below 1Gy, with population systematic and random errors within 4 and 3Gy, respectively. The region surrounding this area shows higher mean systematic errors (1-3Gy), population systematic (8-11Gy) and random (5-7Gy) errors. In conclusion, DVH/DSH and DSMs are quite stable with respect to inter-fraction variations in the high-dose region, within about 2cm from bladder base. Larger systematic variations occur in the anterior portion and cranially 2.5-3.5cm from the base. Results suggest that dose predictors related to the high dose area (including the trigone dose) are likely to be sufficiently reliable with respect to the expected variations due to variable bladder filling.

Modelling late stool frequency and rectal pain after radical radiotherapy in prostate cancer patients: Results from a large pooled population.

AIM: To investigate late gastrointestinal toxicity in a large pooled population of prostate cancer patients treated with radical radiotherapy. Normal tissue complication probability models were developed for late stool frequency and late rectal pain. METHODS AND MATERIALS: Population included 1336 patients, 3-year minimum follow-up, treated with 66-80Gy. Toxicity was scored with LENT-SOMA-scale. Two toxicity endpoints were considered: grade ⩾2 rectal pain and mean grade (average score during follow-up) in stool frequency >1. DVHs of anorectum were reduced to equivalent uniform dose (EUD). The best-value of the volume parameter n was determined through numerical optimization. Association between EUD/clinical factors and the endpoints was investigated by logistic analyses. Likelihood, Brier-score and calibration were used to evaluate models. External calibration was also carried out. RESULTS: 4% of patients (45/1122) reported mean stool frequency grade >1; grade ⩾2 rectal pain was present in the TROG 03.04 RADAR population only (21/677, 3.1%): for this endpoint, the analysis was limited to this population. Analysis of DVHs highlighted the importance of mid-range doses (30-50Gy) for both endpoints. EUDs calculated with n=1 (OR=1.04) and n=0.35 (OR=1.06) were the most suitable dosimetric descriptors for stool frequency and rectal pain respectively. The final models included EUD and cardiovascular diseases (OR=1.78) for stool frequency and EUD and presence of acute gastrointestinal toxicity (OR=4.2) for rectal pain. CONCLUSION: Best predictors of stool frequency and rectal pain are consistent with findings previously reported for late faecal incontinence, indicating an important role in optimization of mid-range dose region to minimize these symptoms highly impacting the quality-of-life of long surviving patients.

Bladder spatial-dose descriptors correlate with acute urinary toxicity after radiation therapy for prostate cancer.

PURPOSE: To assess bladder spatial-dose parameters predicting acute urinary toxicity after radiotherapy for prostate cancer (PCa) through a pixel-wise method for analysis of bladder dose-surface maps (DSMs). MATERIALS & METHODS: The final cohort of a multi-institutional study, consisting of 539 patients with PCa treated with conventionally (CONV:1.8-2Gy/fr) or moderately hypo-fractionated radiotherapy (HYPO:2.2-2.7Gy/fr) was considered. Urinary toxicity was evaluated through the International Prostate Symptoms Score (IPSS) administered before and after radiotherapy. IPSS increases ⩾10 and 15 points at the end of radiotherapy (ΔIPSS⩾10 and ΔIPSS⩾15) were chosen as endpoints. Average DSMs (corrected into 2Gy-equivalent doses) of patients with/without toxicity were compared through a pixel-wise method. This allowed the extraction of selected spatial descriptors discriminating between patients with/without toxicity. Previously logistic models based on dose-surface histograms (DSH) were considered and replaced with DSM descriptors. Discrimination power, calibration and log-likelihood were considered to evaluate the impact of the inclusion of spatial descriptors. RESULTS: Data of 375/539 patients were available. ΔIPSS⩾10 was recorded in 76/375 (20%) patients, while 30/375 (8%) experienced ΔIPSS⩾15. The posterior dose at 12mm from the bladder base (roughly corresponding to the trigone region) resulted significantly associated to toxicity in the whole/HYPO populations. The cranial extension of the 75Gy isodose along the bladder central axis was the best DSM-based predictor in CONV patients. Multi-variable models including DSM descriptors showed better discrimination (AUC=0.66-0.77) when compared to DSH-based models (AUC=0.58-0.71) and higher log-likelihoods. CONCLUSION: DSMs are correlated with the risk of acute GU toxicity. The incorporation of spatial descriptors improves discrimination and log-likelihood of multi-variable models including dosimetric and clinical parameters.

Fitting late rectal bleeding data using different NTCP models: results from an Italian multi-centric study (AIROPROS0101).

BACKGROUND AND PURPOSE: Recent investigations demonstrated a significant correlation between rectal dose-volume patterns and late rectal toxicity. The reduction of the DVH to a value expressing the probability of complication would be suitable. To fit different normal tissue complication probability (NTCP) models to clinical outcome on late rectal bleeding after external beam radiotherapy (RT) for prostate cancer. PATIENTS AND METHODS: Rectal dose-volume histograms of the rectum (DVH) and clinical records of 547 prostate cancer patients (pts) pooled from five institutions previously collected and analyzed were considered. All patients were treated in supine position with 3 or 4-field techniques: 123 patients received an ICRU dose between 64 and 70 Gy, 255 patients between 70 and 74 Gy and 169 patients between 74 and 79.2 Gy; 457/547 patients were treated with conformal RT and 203/547 underwent radical prostatectomy before RT. Minimum follow-up was 18 months. Patients were considered as bleeders if showing grade 2/3 late bleeding (slightly modified RTOG/EORTC scoring system) within 18 months after the end of RT. Four NTCP models were considered: (a) the Lyman model with DVH reduced to the equivalent uniform dose (LEUD, coincident with the classical Lyman-Kutcher-Burman, LKB, model), (b) logistic with DVH reduced to EUD (LOGEUD), (c) Poisson coupled to EUD reduction scheme and (d) relative seriality (RS). The parameters for the different models were fit to the patient data using a maximum likelihood analysis. The 68% confidence intervals (CI) of each parameter were also derived. RESULTS: Forty six out of five hundred and forty seven patients experienced grade 2/3 late bleeding: 38/46 developed rectal bleeding within 18 months and were then considered as bleeders The risk of rectal bleeding can be well calculated with a 'smooth' function of EUD (with a seriality parameter n equal to 0.23 (CI 0.05), best fit result). Using LEUD the relationship between EUD and NTCP can be described with a TD50 of 81.9 Gy (CI 1.8 Gy) and a steepness parameter m of 0.19 (CI 0.01); when using LOGEUD, TD50 is 82.2 Gy and k is 7.85. Best fit parameters for RS are s=0.49, gamma=1.69, TD50=83.1 Gy. Qualitative as well as quantitative comparisons (chi-squared statistics, P=0.005) show that the models fit the observed complication rates very well. The results found in the overall population were substantially confirmed in the subgroup of radically treated patients (LEUD: n=0.24 m=0.14 TD50=75.8 Gy). If considering just the grade 3 bleeders (n=9) the best fit is found in correspondence of a n-value around 0.06, suggesting that for severe bleeding the rectum is more serial. CONCLUSIONS: Different NTCP models fit quite accurately the considered clinical data. The results are consistent with a rectum 'less serial' than previously reported investigations when considering grade 2 bleeding while a more serial behaviour was found for severe bleeding. EUD may be considered as a robust and simple parameter correlated with the risk of late rectal bleeding.

Study of the dosimetric characteristics of cosmic radiation at civil aviation altitudes.

The dependence of the doses on solar activity for intermediate levels of the solar modulation parameter has been studied by means of simulations carried out by the Monte Carlo transport code FLUKA. The vertical cut-off rigidities investigated lie between 0.4 and 6.1 GV. The calculated results show that the linear dependence proposed in a previous work, for the effective dose rate as a function of the solar modulation parameter, can be considered as an acceptable approximation. In addition, some dosimetric characteristics of cosmic radiation and some properties of the dosemeters in use for monitoring in the cosmic ray environment have been analysed with a view to simplifying measurements. The depth-dose curves in the ICRU sphere and the response of a tissue-equivalent ionisation chamber have been determined by the FLUKA code for a number of cosmic ray spectra On the basis of the calculated results, it is concluded that a value of the depth. d, which would make the ambient dose equivalent a conservative predictor of the effective dose, cannot be specified for cosmic radiation. However, the operational quantity can be useful in order to verify the predictions of Monte Carlo calculations. It is demonstrated that a crude approximation of the ambient dose equivalent could be obtained by multiplying by 2 the absorbed dose measured by a tissue-equivalent ionisation chamber with wall thickness of 10 mm.

Calculation of the radiation environment caused by galactic cosmic rays for determining air crew exposure.

The spectra of secondary particles resulting from interactions of primary galactic cosmic rays with the nuclei in the atmosphere have been calculated using the Monte Carlo transport code FLUKA. The simulations have been carried out at solar minimum and solar maximum activity, for several values of the vertical geomagnetic cut-off. The effective dose rate and the ambient dose equivalent rate as a function of geomagnetic cut-off and altitude have been obtained using appropriate sets of conversion coefficients. The calculated results are discussed and compared with experimental data and other calculations. A simple method is proposed to calculate the radiation exposure at aircraft altitudes.

A method applicable to effective dose rate estimates for aircrew dosimetry.

The inclusion of cosmic radiation as occupational exposure under ICRP Publication 60 and the European Union Council Directive 96/29/Euratom has highlighted the need to estimate the exposure of aircrew. According to a report of the Group of Experts established under the terms of Article 31 of the European Treaty, the individual estimates of dose for flights below 15 km may be done using an appropriate computer program. In order to calculate the radiation exposure at aircraft altitudes, calculations have been performed by means of the Monte Carlo transport code FLUKA. On the basis of the calculated results, a simple method is proposed for the individual evaluation of effective dose rate due to the galactic component of cosmic radiation as a function of latitude and altitude.

Late rectal bleeding after 3D-CRT for prostate cancer: development of a neural-network-based predictive model.

The aim of this study was to develop a model exploiting artificial neural networks (ANNs) to correlate dosimetric and clinical variables with late rectal bleeding in prostate cancer patients undergoing radical radiotherapy and to compare the ANN results with those of a standard logistic regression (LR) analysis. 718 men included in the AIROPROS 0102 trial were analyzed. This multicenter protocol was characterized by the prospective evaluation of rectal toxicity, with a minimum follow-up of 36 months. Radiotherapy doses were between 70 and 80 Gy. Information was recorded for comorbidity, previous abdominal surgery, use of drugs and hormonal therapy. For each patient, a rectal dose-volume histogram (DVH) of the whole treatment was recorded and the equivalent uniform dose (EUD) evaluated as an effective descriptor of the whole DVH. Late rectal bleeding of grade ≥ 2 was considered to define positive events in this study (52 of 718 patients). The overall population was split into training and verification sets, both of which were involved in model instruction, and a test set, used to evaluate the predictive power of the model with independent data. Fourfold cross-validation was also used to provide realistic results for the full dataset. The LR was performed on the same data. Five variables were selected to predict late rectal bleeding: EUD, abdominal surgery, presence of hemorrhoids, use of anticoagulants and androgen deprivation. Following a receiver operating characteristic analysis of the independent test set, the areas under the curves (AUCs) were 0.704 and 0.655 for ANN and LR, respectively. When evaluated with cross-validation, the AUC was 0.714 for ANN and 0.636 for LR, which differed at a significance level of p = 0.03. When a practical discrimination threshold was selected, ANN could classify data with sensitivity and specificity both equal to 68.0%, whereas these values were 61.5% for LR. These data provide reasonable evidence that results obtained with ANNs are superior to those achieved with LR when predicting late radiotherapy-related rectal bleeding. The future introduction of patient-related personal characteristics, such as gene expression profiles, might improve the predictive power of statistical classifiers. More refined morphological aspects of the dose distribution, such as dose surface mapping, might also enhance the overall performance of ANN-based predictive models.