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Background and Purpose: Radiation-induced alopecia (RIA) is one of the most frequent and upsetting cosmetic side effects after radiotherapy (RT) for brain cancer. We report the incidence of RIA in a cohort of brain tumours patients treated with Proton Therapy (PT) and externally validate published NTCP models of grade 2 (G2) RIA for their implementation in clinical practice., Methods: Data for patients treated for brain tumours with scanning beam PT between 2018 and 2022 were extracted. Acute, late and permanent RIA events were evaluated according to CTCAE 5.0. Lyman-Kutcher-Burman (LKB) and multivariable logistic regression (MLR) published models were computed from the relative dose-surface histogram of the scalp. External validity of models was assessed in terms of discrimination and calibration., Results: In the 264 patients analysed, rates of any grade acute (≤90 days after PT completion), late (>90 days) and permanent RIA (persisting for> 12 months) were 61.8 %, 24.7 % and 14.4 %, respectively. In our independent cohort, LKB- and MLR-NTCP showed a good discrimination for G2 RIA (0.71≤ROC-AUC≤0.83) while model calibration was unsatisfactory possibly due to a different outcome evaluation between training and validation cohorts, as well as differences in clinical and treatment related variables between the two groups., Conclusions: Despite the reasonable sensitivity and specificity of the NTCP models for RIA in the validation cohort, our study emphasizes the significance of differences between the cohorts utilized for model development and validation. Specifically, variations in the reporting of clinical outcomes inevitably jeopardize the validation of NTCP models. A standardize and objective RIA scoring system is essential., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background and Purpose: Given the substantial lack of knowledge, we aimed to assess clinical/dosimetry predictors of late hematological toxicity on patients undergoing pelvic-nodes irradiation (PNI) for prostate cancer (PCa) within a prospective multi-institute study., Materials and Methods: Clinical/dosimetry/blood test data were prospectively collected including lymphocytes count (ALC) at baseline, mid/end-PNI, 3/6 months and every 6 months up to 5-year after PNI. DVHs of the Body, ileum (BMILEUM), lumbosacral spine (BMLS), lower pelvis (BMPELVIS), and whole pelvis (BMTOT) were extracted. Current analysis focused on 2-year CTCAEv4.03 Grade ≥ 2 (G2+) lymphopenia (ALC < 800/μL). DVH parameters that better discriminate patients with/without toxicity were first identified. After data pre-processing to limit overfitting, a multi-variable logistic regression model combining DVH and clinical information was identified and internally validated by bootstrap., Results: Complete data of 499 patients were available: 46 patients (9.2 %) experienced late G2+ lymphopenia. DVH parameters of BMLS/BMPELVIS/BMTOT and Body were associated to increased G2+ lymphopenia. The variables retained in the resulting model were ALC at baseline [HR = 0.997, 95 %CI 0.996-0.998, p < 0.0001], smoke (yes/no) [HR = 2.9, 95 %CI 1.25-6.76, p = 0.013] and BMLS-V ≥ 24 Gy (cc) [HR = 1.006, 95 %CI 1.002-1.011, p = 0.003]. When acute G3+ lymphopenia (yes/no) was considered, it was retained in the model [HR = 4.517, 95 %CI 1.954-10.441, p = 0.0004]. Performances of the models were relatively high (AUC = 0.87/0.88) and confirmed by validation., Conclusions: Two-year lymphopenia after PNI for PCa is largely modulated by baseline ALC, with an independent role of acute G3+ lymphopenia. BMLS-V24 was the best dosimetry predictor: constraints for BMTOT (V10Gy < 1520 cc, V20Gy < 1250 cc, V30Gy < 850 cc), and BMLS (V24y < 307 cc) were suggested to potentially reduce the risk., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: Proton treatment can potentially spare patients with H&N cancer for substantial treatment-related toxicities. The current study investigated the reproducibility of a decentralised model-based selection of patients for a proton treatment study when the selection plans were compared to the clinical treatment plans performed at the proton centre., Methods: Sixty-three patients were selected for proton treatment in the six Danish Head and Neck Cancer (DAHANCA) centres. The patients were selected based on normal tissue complication probability (NTCP) estimated from local photon and proton treatment plans, which showed a ΔNTCP greater than 5%-point for either grade 2 + dysphagia or grade 2 + xerostomia at six months. The selection plans were compared to the clinical treatment plans performed at the proton centre., Results: Of the 63 patients, 49 and 25 were selected based on an estimated benefit in risk of dysphagia and xerostomia, respectively. Eleven patients had a potential gain in both toxicities. The mean ΔNTCP changed from the local selection plan comparison to the clinical comparison from 6.9 to 5.3 %-points (p = 0.01) and 7.3 to 4.9 %-points (p = 0.03) for dysphagia and xerostomia, respectively. Volume differences in both CTV and OAR could add to the loss in ΔNTCP. 61 of the 63 clinical plans had a positive ΔNTCP, and 38 had a ΔNTCP of 5%-points for at least one of the two endpoints., Conclusion: A local treatment plan comparison can be used to select candidates for proton treatment. The local comparative proton plan overestimates the potential benefit of the clinical proton plan. Continuous quality assurance of the delineation procedures and planning is crucial in the subsequent randomised clinical trial setting., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Purpose: Radiation pneumonitis (RP) remains a major complication in non-small cell lung cancer (NSCLC) patients undergoing radiochemotherapy (RCHT). Traditionally, the mean lung dose (MLD) and the volume of the total lung receiving at least 20 Gy (V 20Gy ) are used to predict RP in patients treated with normo-fractionated photon therapy. However, other models, including the actual dose-distribution in the lungs using the effective α/β model or a combination of radiation doses to the lungs and heart, have been proposed for predicting RP. Moreover, the models established for photons may not hold for patients treated with passively-scattered proton therapy (PSPT). Therefore, we here tested and validated novel predictive parameters for RP in NSCLC patient treated with PSPT., Methods: Data on the occurrence of RP, structure files and dose-volume histogram parameters for lungs and heart of 96 NSCLC patients, treated with PSPT and concurrent chemotherapy, was retrospectively retrieved from prospective clinical studies of two international centers. Data was randomly split into a training set (64 patients) and a validation set (32 patients). Statistical analyses were performed using binomial logistic regression., Results: The biologically effective dose (BED) of the'lungs - GTV' significantly predicted RP ≥ grade 2 in the training-set using both a univariate model (p = 0.019, AUC train  = 0.72) and a multivariate model in combination with the effective α/β parameter of the heart (p BED  = 0.006, [Formula: see text] = 0.043, AUC train  = 0.74). However, these results did not hold in the validation-set (AUC val  = 0.52 andAUC val  = 0.50, respectively). Moreover, these models were found to neither outperform a model built with the MLD (p = 0.015, AUC train = 0.73, AUC val = 0.51), nor a multivariate model additionally including the V 20Gy of the heart (p MLD  = 0.039, p V20Gy,heart  = 0.58, AUC train  = 0.74, AUC val = 0.53)., Conclusion: Using the effective α/β parameter of the lungs and heart we achieved similar performance to commonly used models built for photon therapy, such as MLD, in predicting RP ≥ grade 2. Therefore, prediction models developed for photon RCHT still hold for patients treated with PSPT., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background and Purpose: Model-based selection of proton therapy patients relies on a predefined reduction in normal tissue complication probability (NTCP) with respect to photon therapy. The decision is necessarily made based on the treatment plan, but NTCP can be affected when the delivered treatment deviates from the plan due to delivery inaccuracies. Especially for proton therapy of lung cancer, this can be important because of tissue density changes and, with pencil beam scanning, the interplay effect between the proton beam and breathing motion., Materials and Methods: In this work, we verified whether the expected benefit of proton therapy is retained despite delivery inaccuracies by reconstructing the delivered treatment using log-file based dose reconstruction and inter- and intrafractional accumulation. Additionally, the importance of two uncertain parameters for treatment reconstruction, namely deformable image registration (DIR) algorithm and α/β ratio, was assessed., Results: The expected benefit or proton therapy was confirmed in 97% of all studied cases, despite regular differences up to 2 percent point (p.p.) NTCP between the delivered and planned treatments. The choice of DIR algorithm affected NTCP up to 1.6 p.p., an order of magnitude higher than the effect of α/β ratio., Conclusion: For the patient population and treatment technique employed, the predicted clinical benefit for patients selected for proton therapy was confirmed for 97.0% percent of all cases, although the NTCP based proton selection was subject to 2 p.p. variations due to delivery inaccuracies., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Uveal melanoma (UM) represents the most common primary intraocular tumor, and nowadays eye plaque brachytherapy (EPB) is the most frequently used visual acuity preservation treatment option for small to medium sized UMs. The excellent local tumor control (LTC) rate achieved by EPB may be associated with severe complications and adverse events. Several dosimetric and clinical risk factors for the development of EPB-related ocular morbidity can be identified. However, morbidity predictive models specifically developed for EPB are still scarce. PRISMA methodology was used for the present systematic review of articles indexed in PubMed in the last sixteen years on EPB treatment of UM which aims at determining the major factors affecting local tumor control and ocular morbidities. To our knowledge, for the first time in EPB field, local tumor control probability (TCP) and normal tissue complication probability (NTCP) modelling on pooled clinical outcomes were performed. The analyzed literature (103 studies including 21,263 UM patients) pointed out that Ru-106 EPB provided high local control outcomes while minimizing radiation induced complications. The use of treatment planning systems (TPS) was the most influencing factor for EPB outcomes such as metastasis occurrence, enucleation, and disease specific survival, irrespective of radioactive implant type. TCP and NTCP parameters were successfully extracted for 5-year LTC, cataract and optic neuropathy. In future studies, more consistent recordings of ocular morbidities along with accurate estimation of doses through routine use of TPS are needed to expand and improve the robustness of toxicity risk prediction in EPB., Competing Interests: Conflict of Interest None., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background and Purpose: Anatomical changes during the stereotactic body radiation therapy (SBRT) of early stage non-small cell lung cancer (NSCLC) may cause the delivered dose to deviate from the planned dose. We investigate if normal tissue complication probability (NTCP) models based on the delivered dose predict radiation-induced rib fractures better than models based on the planned dose., Material and Methods: 437 NSCLC patients treated to a median dose of 3x18 Gy were included. Delivered dose was estimated by accumulating EQD2-corrected fraction doses after being deformed with daily CBCT-to-planning CT deformable image registration. Dosimetric parameters D x (dose to a relative volume x) were extracted for each rib included in the CBCTs field-of-view. An NTCP model was constructed for both planned and delivered dose, optimizing the parameters TD 50 (dose with 50% toxicity risk), m (steepness of the curve) and x, using maximum likelihood estimation. Best NTCP model was determined using Akaike weights (Aw). Differences between the models were tested for significance using the Vuong's test., Results: Median time to fracture of 110 fractured ribs was 22.5 months. The maximum rib dose, D 0 , best predicted fractures for both planned and delivered dose. The average delivered D 0 was significantly lower than planned (p < 0.001). NTCP model based on the delivered D 0 was the best, with Aw = 0.95. The models were not significantly different., Conclusion: Delivered maximum dose to the ribs was significantly lower than planned. The NTCP model based on delivered dose improved predictions of radiation-induced rib fractures but did not reach statistical significance., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Purpose: To evaluate the feasibility of semi-automatic Quality of Life (QOL)-weighted normal tissue complication probability (NTCP)-guided VMAT treatment plan optimisation in head and neck cancer (HNC) and compare predicted QOL to that obtained with conventional treatment., Materials and Methods: This study included 30 HNC patients who were treated with definitive radiotherapy. QOL-weighted NTCP-guided VMAT plans were optimised directly on 80 multivariable NTCP models of 20 common toxicities and symptoms on 4 different time points (6, 12, 18 and 24 months after radiotherapy) and each NTCP model was weighted relative to its impact on QOL. Planning results, NTCP and predicted QOL were compared with the clinical conventional VMAT plans., Results: QOL-weighted NTCP-guided VMAT plans were clinically acceptable, had target coverage equally adequate as the clinical plans, but prioritised sparing of organs at risk (OAR) related to toxicities and symptoms that had the highest impact on QOL. NTCP was reduced for, e.g., dysphagia (-6.1% for ≥grade 2/-7.6% for ≥grade 3) and moderate-to-severe fatigue/speech problems/hoarseness (-0.7%/-1.5%/-2.5%) at 6 months, respectively. Concurrently, the average NTCP of toxicities related to salivary function increased with +0.4% to +5.7%. QOL-weighted NTCP-guided plans were produced in less time, were less dependent on the treatment planner experience and yielded more consistent results. The average predicted QOL improved by 0.7, 0.9, 1.0, and 1.1 points on a 0-100 scale (p < 0.001) at 6, 12, 18, and 24 months, respectively, compared to the clinical plans., Conclusion: Semi-automatic QOL-weighted NTCP-guided VMAT treatment plan optimisation is feasible. It prioritised sparing of OARs related to high-impact toxicities and symptoms and resulted in a systematic improvement of predicted QOL compared to conventional VMAT., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Purpose: To externally validate previously published Normal Tissue Complication Probability (NTCP) models developed by separate teams for grade 3 oral mucositis (g3OM)., Materials and Methods: Two models were validated: a logistic model, based on 144 head and neck cancer (HNC) patients receiving induction chemotherapy followed by chemo-IMRT; a multivariable logistic model for prediction of g3OM for 253 patients receiving radical treatment for the head and neck squamous cell carcinoma (HNSCC). The EORTC HNCG-ROG 1219 DAHANCA trial dataset, consisting of 169 patients was used as the validation cohort. This cohort was treated with accelerated fractionated chemo-IMRT, with/without the hypoxic radiosensitizer Nimorazole for HNSCC. External validity was assessed using the scaled Brier score. Calibration was assessed in terms of calibration curves as well as measures of mean and weak calibration. Hosmer-Lemeshow was used for goodness-of-fit test. Discrimination was calculated using the area under the receiver operating curve (AUC-ROC)., Results: The prevalence of g3OM in the validation cohort (35.5%) was similar to that of two development cohorts, i.e. 38.7% and 31.9% for Bhide logistic and Otter multivariable logistic models respectively. The scaled Brier scores showed good overall model performance. Perfect calibration was observed in the prevalence range of 20% to 40%. AUC-ROC was acceptable in external validation (0.67). The Hosmer-Lemeshow test showed good agreement between predicted and observed outcomes for two models., Conclusion: The NTCP models were validated and lead to valid predictions in a wide range of diverse treatment techniques and patient characteristics, also when Nimorazole is added as hypoxic radiosensitizer., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Proton radiotherapy (PT) is used increasingly for paediatric brain cancer patients. However, as demonstrated here, the knowledge on normal tissue dose constraints, to minimize side-effects, for this cohort is limited., Methods: A search strategy was systematically conducted on MEDLINE® database. 65 papers were evaluated ranging from 2013 to 2021., Results: Large variations in normal tissue tolerance and toxicity reporting across PT studies makes estimation of normal tissue dose constraints difficult, with the potential for significant late effects to go unmeasured. Mean dose delivered to the pituitary gland varies from 20 to 30 Gy across literature. Similarly, the hypothalamic dose delivery ranges from 20 to 54.6 Gy for paediatric patients., Conclusion: There is a significant lack of radiobiological data for paediatric brain cancer patients undergoing proton therapy, often using data from x-ray radiotherapy and adult populations. The way forward is through standardisation of reporting in order to validate relevant dose constraints., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Purpose: The aim of this study is to establish the relative impact of physician-rated toxicities and patient-rated symptoms in head and neck cancer (HNC) on quality of life (QOL) and to weigh the various toxicities and symptoms during treatment plan optimization and selection., Materials and Methods: This prospective cohort study comprised 1083 HNC patients (development: 750, validation: 333) treated with definitive radiotherapy with or without chemotherapy. Clinical factors were scored at baseline. Physician-rated and patient-rated outcome measures and QOL (EORTC QLQ-HN35 and QLQ-C30) were prospectively scored at baseline and 6, 12, 18 and 24 months after radiotherapy. The impact of 20 common toxicities and symptoms (related to swallowing, salivary function, speech, pain and general complaints) on QOL (0-100 scale) was established for each time point by combining principal component analysis and multivariable linear regression., Results: Radiation-induced toxicities and symptoms resulted in a significant decline in QOL of patients with 12.4 ± 12.8 points at 6 months to 16.6 ± 17.1 points at 24 months. The multivariable linear models described the QOL points subtracted for each toxicity and symptom after radiotherapy. For example, xerostomia and weight loss had a significant but minor effect (on average -0.5 and -0.6 points) while speech problems and fatigue had a much greater impact (on average -11.9 and -17.4 points) on QOL. R 2 goodness-of-fit values for the QOL models ranged from 0.64 (6 months) to 0.72 (24 months)., Conclusion: The relative impact of physician-rated toxicities and patient-rated symptoms on QOL was quantified and can be used to optimize, compare and select HNC radiotherapy treatment plans, to balance the relevance of toxicities and to achieve the best QOL for individual patients., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background/purpose: Rates of acute esophagitis in breast cancer patients undergoing regional nodal irradiation (RNI) are under-reported. We set to identify esophageal dose-volume constraints associated with grade 2 esophagitis (G2E). We hypothesized that the G2E rate was higher with intensity modulated radiation therapy (IMRT) vs. 3D conformal radiation therapy (3DCRT)., Materials/methods: We identified patients that received RNI (50 Gy/25 fractions) from 1/2013 to 6/2019. We retrospectively contoured the esophagus in a consistent manner and recorded esophageal mean dose, max dose, and V10-V50. Our primary endpoint was the G2E rate. Receiver operating characteristics curves analysis (e.g., Youden's J statistic) were used to determine the cutpoints for the dosimetric parameters which were then tested in logistic regression models., Results: We identified 531 patients (50% left-sided; 41% IMRT; 16.2% G2E). G2E was significantly higher in IMRT vs. 3DCRT patients (23.6% vs. 10.9%, p < 0.0001). All esophageal dosimetric parameters were significantly associated with G2E after adjusting for age and laterality. The cutpoints for esophageal mean dose, V10 and V20 were 11 Gy, 30%, and 15%, respectively. The associations between the dichotomized dose-volume parameters and G2E were OR = 3.82 (95% CI 2.28-6.40, p < 0.0001) for esophageal mean dose, OR = 5.37 (95% CI 3.01-9.58, p < 0.0001) for esophageal V10, and OR = 3.23 (95% CI 1.93-5.41, p < 0.0001) for esophageal V20., Conclusion: In patients receiving RNI with modern techniques, we found that G2E occurs in >15%, and more frequently with IMRT. These data strongly support the routine contouring of the esophagus in RNI planning, and our constraints should be incorporated in future prospective protocols of RNI., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose: The goal of this study was to assess whether a model-based approach applied retrospectively to a completed randomized controlled trial (RCT) would have significantly altered the selection of patients of the original trial, using the same selection criteria and endpoint for testing the potential clinical benefit of protons compared to photons., Methods and Materials: A model-based approach, based on three widely used normal tissue complication probability (NTCP) models for radiation pneumonitis (RP), was applied retrospectively to a completed non-small cell lung cancer RCT (NCT00915005). It was assumed that patients were selected by the model-based approach if their expected ΔNTCP value was above a threshold of 5%. The endpoint chosen matched that of the original trial, the first occurrence of severe (grade ≥3) RP., Results: Our analysis demonstrates that NTCP differences between proton and photon therapy treatments may be too small to support a model-based trial approach for lung cancer using RP as the normal tissue endpoint. The analyzed lung trial showed that less than 19% (32/165) of patients enrolled in the completed trial would have been enrolled in a model-based trial, prescribing photon therapy to all other patients. The number of patients enrolled was also found to be dependent on the type of NTCP model used for evaluating RP, with the three models enrolling 3%, 13% or 19% of patients. This result does show limitations in NTCP models which would affect the success of a model-based trial approach. No conclusion regarding the development of RP in patients randomized by the model-based approach could statistically be made., Conclusions: Uncertainties in the outcome models to predict NTCP are the inherent drawback of a model-based approach to clinical trials. The impact of these uncertainties on enrollment in model-based trials depends on the predicted difference between the two treatment arms and on the set threshold for patient stratification. Our analysis demonstrates that NTCP differences between proton and photon therapy treatments may be too small to support a model-based trial approach for specific treatment sites, such as lung cancer, depending on the chosen normal tissue endpoint., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose: To develop normal tissue complication probability (NTCP) models for radiation-induced alopecia (RIA) in brain tumor patients treated with proton therapy (PT)., Methods and Materials: We analyzed 116 brain tumor adult patients undergoing scanning beam PT (median dose 54 GyRBE; range 36-72) for CTCAE v.4 grade 2 (G2) acute (≤90 days), late (>90 days) and permanent (>12 months) RIA. The relative dose-surface histogram (DSH) of the scalp was extracted and used for Lyman-Kutcher-Burman (LKB) modelling. Moreover, DSH metrics (Sx: the surface receiving ≥ X Gy, D 2% : near maximum dose, D mean : mean dose) and non-dosimetric variables were included in a multivariable logistic regression NTCP model. Model performances were evaluated by the cross-validated area under the receiver operator curve (ROC-AUC)., Results: Acute, late and permanent G2-RIA was observed in 52%, 35% and 19% of the patients, respectively. The LKB models showed a weak dose-surface effect (0.09 ≤ n ≤ 0.19) with relative steepness 0.29 ≤ m ≤ 0.56, and increasing tolerance dose values when moving from acute and late (22 and 24 GyRBE) to permanent RIA (44 GyRBE). Multivariable modelling selected S 21Gy for acute and S 25Gy , for late G2-RIA as the most predictive DSH factors. Younger age was selected as risk factor for acute G2-RIA while surgery as risk factor for late G2-RIA. D 2% was the only variable selected for permanent G2-RIA. Both LKB and logistic models exhibited high predictive performances (ROC-AUCs range 0.86-0.90)., Conclusion: We derived NTCP models to predict G2-RIA after PT, providing a comprehensive modelling framework for acute, late and permanent occurrences that, once externally validated, could be exploited for individualized scalp sparing treatment planning strategies in brain tumor patients., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The area under the ROC curve (AUC) is commonly used as a measure for the discriminative performance of NTCP models. Here, we demonstrate that for typical patient cohorts, the AUC is an unsuitable measure for that purpose since it is typically limited to values below 0.8 and it exhibits large statistical variation., Competing Interests: Conflict of interest There is no conflict of interest., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background and Purpose: Anatomical changes induce differences between planned and delivered dose. Adaptive radiotherapy (ART) may reduce these differences but the optimal implementation is insufficiently clear. The aims of this study were to quantify the difference between planned and delivered dose in HNC patients, assess the consequential difference in normal tissue complication probability (ΔNTCP) and to explore the value of ΔNTCP as an objective selection strategy for ART., Materials and Methods: For 52 patients, daily doses were accumulated to estimate the delivered dose. The difference from planned dose was analyzed for CTVs and 9 organs-at-risk (OAR). ΔNTCP was calculated for xerostomia, dysphagia, parotid gland dysfunction and tube feeding dependency at 6 months. ART was deemed necessary if ΔNTCP was >5%. The positive predicted value (PPV) was calculated for identification of ART-patients by clinical judgement, and ΔNTCP at fraction 10 and 15., Results: ΔNTCP >5% was seen five times for dysphagia and twice for the other toxicities. Only 5/9 patients with any ΔNTCP >5% clinically received ART, although ART had been done for 13/52 patients (PPV: 0.38). PPV was 0.86 and 0.75 for accumulated dose at fraction 10 and 15, respectively, using a ΔNTCP cut-off for the allocation of ART of 5%. Using other ΔNTCP cut-offs did not substantially improve PPV. With this cut-off the negative predictive value was 0.93 for ΔNTCP method of fraction 10 and fraction 15, and 0.90 for clinical judgement., Conclusion: To identify patients accurately for ART, NTCP calculations based on the dose differences between planned and delivered dose at fraction 10 are superior to clinical judgement., Competing Interests: Declaration of Competing Interest Dr. Heukelom reports grants from European Union 7th Framework, personal fees from Dutch Cancer Society, personal fees from Rene Vogels stichting, during the conduct of the study. Dr. Fuller reports grants from Elekta AB, during the conduct of the study; grants from National Institute for Dental and Craniofacial Research, grants from National Cancer Institute, outside the submitted work. Dr. Sonke reports grants from EU 7th framework program, during the conduct of the study; grants from Elekta AB, other from Elekta AB, outside the submitted work; In addition, Dr. Sonke has a patent Computed Tomography Scanning with royalties paid to Elekta AB, a patent Motion Artefact Reduction in CT Scanning issued to NA, a patent Methods and System for Protecting Critical Structures During Radiation Treatment with royalties paid to Elekta AB, and a patent Radiotherapy and Imaging Methods and Apparatus with royalties paid to Elekta AB., (Copyright © 2019. Published by Elsevier B.V.)

Background and Purpose: High-dose fractionated radiotherapy is often necessary to achieve long-term tumor control in several types of tumors involving or within close proximity to the brain. There is limited data to guide on optimal constraints to the adjacent nontarget brain. This investigation explored the significance of the three-dimensional (3D) dose distribution of passive scattering proton therapy to the brain with other clinicopathological factors on the development of symptomatic radiation necrosis., Materials and Methods: All patients with head and neck, skull base, or intracranial tumors who underwent proton therapy (minimum prescription dose of 59.4 Gy(RBE)) with collateral moderate to high dose radiation exposure to the nontarget brain were retrospectively reviewed. A mixture cure model with respect to necrosis-free survival was used to derive estimates for the normal tissue complication probability (NTCP) model while adjusting for potential confounding factors., Results: Of 179 identified patients, 83 patients had intracranial tumors and 96 patients had primary extracranial tumors. The optimal dose measure obtained to describe the occurrence of radiation necrosis was the equivalent uniform dose (EUD) with parameter a = 9. The best-fit parameters of logistic NTCP models revealed D 50  = 57.7 Gy for intracranial tumors, D 50  = 39.5 Gy for extracranial tumors, and γ 50  = 2.5 for both tumor locations. Multivariable analysis revealed EUD and primary tumor location to be the strongest predictors of brain radiation necrosis., Conclusion: In the current clinical volumetric data analyses with multivariable modelling, EUD was identified as an independent and strong predictor for brain radiation necrosis from proton therapy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Purpose/objectives: To develop normal tissue complication probability (NTCP) models for postoperative pulmonary and cardiac complications and one-year mortality after preoperative chemoradiotherapy and surgery in oesophageal cancer patients., Methods: 691 patients from two institutions (2002-2017) were included; 134 treated with protons. Multivariable logistic regression analyses on 601 patients studied the predictive value of clinical/treatment-related (gender, age, body mass index (BMI), smoking, cardiac comorbidity, chronic obstructive pulmonary disease, histology, cT/N) and dosimetric variables (absolute/relative lung/heart volumes receiving or spared from xGy, mean doses, planning target volume) for the presence of pulmonary complications, cardiac complications and one-year mortality. Model validation was performed using a nonrandom split-sample of 90 patients. Model performance was assessed by AUC and calibration plots., Results: Respectively 144/601 (24.0%) and 165/601 (27.5%) patients developed a pulmonary or cardiac complication. For pulmonary complications, an NTCP model with optimism-corrected AUC of 0.75 (95%CI = 0.73-0.76) was obtained. The model contained mean lung dose (OR = 1.15, 95%CI = 1.09-1.22, p < 0.001), increasing age (OR = 1.03, 95%CI = 1.01-1.06, p = 0.002), BMI (OR = 1.04, 95%CI = 0.99-1.08, p = 0.084) and squamous cell carcinoma (OR = 3.22, 95%CI = 1.97-5.24, p < 0.001) as predictors. In validation, AUC of 0.79 was obtained (calibration slope 1.26). For cardiac complications, only age (OR = 1.06, 95%CI = 1.04-1.09, p < 0.001) with optimism-corrected AUC of 0.67 (95%CI = 0.65-0.68) was selected. For one-year mortality, an NTCP model with optimism-corrected AUC of 0.63 (95%CI = 0.58-0.66) was obtained. Lung absolute V 35 (OR = 1.0016, 95%CI = 1.0007-1.0026, p = 0.001), cN (OR = 2.45, 95%CI = 1.18-5.09, p = 0.017), cT4 (OR = 2.51, 95%CI = 1.10-5.74, p = 0.029) and cardiac comorbidity (OR = 2.91, 95%CI = 1.46-5.77, p = 0.002) were selected as predictors. At validation, AUC of 0.57 was obtained (calibration slope 0.75)., Conclusion: We were able to build and validate NTCP models for the presence of a postoperative pulmonary complication and for one-year mortality after trimodality treatment in oesophageal cancer., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Purpose: To investigate if a local dose-effect (LDE) relationship for perfusion loss improves the NTCP model fit for SBRT induced radiation pneumonitis (RP) compared to conventional LDEs., Methods and Materials: Multi-institutional data of 1015 patients treated with SBRT were analyzed. Dose distributions were converted to NTD with α/β = 3 Gy. The Lyman-Kutcher-Burman NTCP model was fitted to the incidence grade ≥2 RP by maximum likelihood estimation with mean lung dose (MLD), equivalent uniform doses (EUD) using three LDE functions (power-law (EUD power ), logistic with 2 free parameters (EUD log-free ) and logistic with fixed parameters describing local perfusion loss (EUD Perfusion )) and volume above a threshold dose (V x ). Models were compared with the Akaike weights (Aw) derived from the Akaike information criteria (AIC)., Results: The median time to grade ≥2 RP was 4.2 months and plateaued after 17 months at 5.4%. A strong dose-effect relationship for RP incidence was observed. The EUD Perfusion based NTCP model had the lowest AIC. The Aw were 0.53, 0.19, 0.11, 0.11, 0.05 for the EUD Perfusion , V x , MLD, EUD log-free and EUD power LDEs respectively., Conclusion: A LDE for perfusion loss provided modest improvement in NTCP model fit for SBRT induced radiation pneumonitis., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Purpose: This study investigated whether Magnetic Resonance image biomarkers (MR-IBMs) were associated with xerostomia 12 months after radiotherapy (Xer 12m ) and to test the hypothesis that the ratio of fat-to-functional parotid tissue is related to Xer 12m . Additionally, improvement of the reference Xer 12m model based on parotid gland dose and baseline xerostomia, with MR-IBMs was explored., Methods: Parotid gland MR-IBMs of 68 head and neck cancer patients were extracted from pre-treatment T1-weighted MR images, which were normalized to fat tissue, quantifying 21 intensity and 43 texture image characteristics. The performance of the resulting multivariable logistic regression models after bootstrapped forward selection was compared with that of the logistic regression reference model. Validity was tested in a small external cohort of 25 head and neck cancer patients., Results: High intensity MR-IBM P90 (the 90th intensity percentile) values were significantly associated with a higher risk of Xer 12m . High P90 values were related to high fat concentration in the parotid glands. The MR-IBM P90 significantly improved model performance in predicting Xer 12m (likelihood-ratio-test; p = 0.002), with an increase in internally validated AUC from 0.78 (reference model) to 0.83 (P90). The MR-IBM P90 model also outperformed the reference model (AUC = 0.65) on the external validation cohort (AUC = 0.83)., Conclusion: Pre-treatment MR-IBMs were associated to radiation-induced xerostomia, which supported the hypothesis that the amount of predisposed fat within the parotid glands is associated with Xer 12m . In addition, xerostomia prediction was improved with MR-IBMs compared to the reference model., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose/objective: Assess to what extent the use of automated treatment planning would have reduced organ-at-risk dose delivery observed in the randomized HYPRO trial for prostate cancer, and estimate related toxicity reductions. Investigate to what extent improved plan quality for hypofractionation scheme as achieved with automated planning can potentially reduce observed enhanced toxicity for the investigated hypofractionation scheme to levels observed for conventional fractionation scheme., Material/methods: For 725 trial patients, VMAT plans were generated with an algorithm for automated multi-criterial plan generation (autoVMAT). All clinically delivered plans (CLINICAL), generated with commonly applied interactive trial-and-error planning were also available for the investigations. Analyses were based on dose-volume histograms (DVH) and predicted normal tissue complication probabilities (NTCP) for late gastrointestinal (GI) toxicity., Results: Compared to CLINICAL, autoVMAT plans had similar or higher PTV coverage, while large and statistically significant OAR sparing was achieved. Mean doses in the rectum, anus and bladder were reduced by 7.8 ± 4.7 Gy, 7.9 ± 6.0 Gy and 4.2 ± 2.9 Gy, respectively (p < 0.001). NTCPs for late grade ≥2 GI toxicity, rectal bleeding and stool incontinence were reduced from 23.3 ± 9.1% to 19.7 ± 8.9%, from 9.7 ± 2.8% to 8.2 ± 2.8%, and from 16.8 ± 8.5% to 13.1 ± 7.2%, respectively (p < 0.001). Reductions in rectal bleeding NTCP were observed for all published Equivalent Uniform Dose volume parameters, n. AutoVMAT allowed hypofractionation with predicted toxicity similar to conventional fractionation with CLINICAL plans., Conclusion: Compared to CLINICAL, autoVMAT had superior plan quality, with meaningful NTCP reductions for both conventional fractionation and hypofractionation schemes. AutoVMAT plans might reduce toxicity for hypofractionation to levels that were clinically observed (and accepted) for conventional fractionation. This may be relevant when considering clinical use of the investigated hypofractionation schedule with relatively high fraction dose (3.4 Gy)., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background and Purpose: Incidental irradiation of normal brain tissue during radiotherapy is linked to cognitive decline, and may be mediated by damage to healthy cortex. Non-coplanar techniques may be used for cortical sparing. We compared normal brain sparing and probability of cortical atrophy using 4π radiation therapy planning vs. standard fixed gantry intensity-modulated radiotherapy (IMRT)., Material and Methods: Plans from previously irradiated brain tumor patients ("original IMRT", n = 13) were re-planned to spare cortex using both 4π optimization ("4π") and IMRT optimization ("optimized IMRT"). Homogeneity index (HI), gradient measure, doses to cortex and white matter (excluding tumor), brainstem, optics, and hippocampus were compared with matching PTV coverage. Probability of three grades of post-treatment cortical atrophy was modeled based on previously established dose response curves., Results: With matching PTV coverage, 4π significantly improved HI by 27% (p = 0.005) and gradient measure by 8% (p = 0.001) compared with optimized IMRT. 4π optimization reduced mean and equivalent uniform doses (EUD) to all standard OARs, with 14-15% reduction in hippocampal EUD (p ≤ 0.003) compared with the other two plans. 4π significantly reduced dose to fractional cortical volumes (V 50 , V 40 and V 30 ) compared with the original IMRT plans, and reduced cortical V 30 by 7% (p = 0.008) compared with optimized IMRT. White matter EUD, mean dose, and fractional volumes V 50 , V 40 and V 30 were also significantly lower with 4π (p ≤ 0.001). With 4π, probability of grade 1, 2 and 3 cortical atrophy decreased by 12%, 21% and 26% compared with original IMRT and by 8%, 14% and 3% compared with optimized IMRT, respectively (p ≤ 0.001)., Conclusions: 4π radiotherapy significantly improved cortical sparing and reduced doses to standard brain OARs, white matter, and the hippocampus. This was achieved with superior PTV dose homogeneity. Such sparing could reduce the probability of cortical atrophy that may lead to cognitive decline., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background and Purpose: Current prediction of radiation-induced xerostomia 12months after radiotherapy (Xer 12m ) is based on mean parotid gland dose and baseline xerostomia (Xer baseline ) scores. The hypothesis of this study was that prediction of Xer 12m is improved with patient-specific characteristics extracted from 18 F-FDG PET images, quantified in PET image biomarkers (PET-IBMs)., Patients and Methods: Intensity and textural PET-IBMs of the parotid gland were collected from pre-treatment 18 F-FDG PET images of 161 head and neck cancer patients. Patient-rated toxicity was prospectively collected. Multivariable logistic regression models resulting from step-wise forward selection and Lasso regularisation were internally validated by bootstrapping. The reference model with parotid gland dose and Xer baseline was compared with the resulting PET-IBM models., Results: High values of the intensity PET-IBM (90th percentile (P90)) and textural PET-IBM (Long Run High Grey-level Emphasis 3 (LRHG3E)) were significantly associated with lower risk of Xer 12m . Both PET-IBMs significantly added in the prediction of Xer 12m to the reference model. The AUC increased from 0.73 (0.65-0.81) (reference model) to 0.77 (0.70-0.84) (P90) and 0.77 (0.69-0.84) (LRHG3E)., Conclusion: Prediction of Xer 12m was significantly improved with pre-treatment PET-IBMs, indicating that high metabolic parotid gland activity is associated with lower risk of developing late xerostomia. This study highlights the potential of incorporating patient-specific PET-derived functional characteristics into NTCP model development., (Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background and Purpose: The aim is to determine the radiobiological parameters of four popular normal tissue complication probability (NTCP) models that describe the dose-response relations of salivary glands and pharyngeal constrictors to the severity of patient reported xerostomia and dysphagia, respectively 6 and 12months post chemo-radiotherapy, furthermore, to evaluate the goodness-of-fit of the NTCP models for different combinations of glands and constrictors., Material and Methods: Forty-three patients were treated on a prospective multi-institutional phase II study (ClinicalTrials.gov, NCT01530997) assessing the efficacy of de-intensified chemoradiotherapy in patients with favorable risk, HPV-associated oropharyngeal squamous cell carcinoma. All patients received 60Gy intensity modulated radiotherapy with concurrent weekly intravenous cisplatinum. All patients reported severity of their xerostomia and dysphagia (pre- and post-treatment) using the patient reported outcome version of the CTCAE (PRO-CTCAE). A change in severity (from baseline) of ≥2 was considered clinically meaningful. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit, and Relative Seriality Logit (RSL) NTCP models were used to fit the patients' dose/volume data to changes in PRO-CTCAE severity of xerostomia and dysphagia (from baseline to 6 and 12months post-treatment). The correlation of the models with the patient outcomes was performed for different combinations of salivary glands and different sections of pharyngeal constrictors. The goodness-of-fit of the different models was assessed through the area under the receiver operating characteristic curve (AUC), maximum of the log-likelihood function, normal error distribution and Akaike information criterion (AIC)., Results: The dose/volume metrics of the combined contralateral (parotid+submandibular) glands appear to correlate best with xerostomia, at both 6- and 12-months. Among the different sections of pharyngeal constrictors, the dose/volume metrics of the superior pharyngeal constrictors appear to correlate best with dysphagia at 6months. The AUC values ranged from 0.72 to 0.85 in the case of xerostomia and 0.73 to 0.74 in the case of dysphagia over the different models. The four NTCP models showed similar goodness-of-fit. The differences in AIC between the different models were less than 2 and ranged within 0.7 and 0.8 in the cases of xerostomia and dysphagia, respectively. The calculated parameters of the LKB model were D 50 =26.9Gy, m=0.63, n=1.0 for the combined contralateral glands at 12months and D 50 =62.0Gy, m=0.10, n=0.49 for the superior pharyngeal constrictors at 6months., Conclusions: The values of the parameters of four NTCP models were determined for salivary glands and pharyngeal constrictors. All four models could fit the clinical data equally well. The NTCP predictions of the combined contralateral glands and superior pharyngeal constrictors showed the best correlation with the patient reported outcomes of xerostomia and dysphagia, respectively., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background and Purpose: Gastro-intestinal toxicity is dose-limiting in abdominal radiotherapy and correlated with duodenum dose-volume parameters. We aimed to derive updated NTCP model parameters using published data and prospective radiotherapy quality-assured cohort data., Material and Methods: A systematic search identified publications providing duodenum dose-volume histogram (DVH) statistics for clinical studies of conventionally-fractionated radiotherapy. Values for the Lyman-Kutcher-Burman (LKB) NTCP model were derived through sum-squared-error minimisation and using leave-one-out cross-validation. Data were corrected for fraction size and weighted according to patient numbers, and the model refined using individual patient DVH data for two further cohorts from prospective clinical trials., Results: Six studies with published DVH data were utilised, and with individual patient data included outcomes for 531 patients in total (median follow-up 16months). Observed gastro-intestinal toxicity rates ranged from 0% to 14% (median 8%). LKB parameter values for unconstrained fit to published data were: n=0.070, m=0.46, TD 50(1) [Gy]=183.8, while the values for the model incorporating the individual patient data were n=0.193, m=0.51, TD 50(1) [Gy]=299.1., Conclusions: LKB parameters derived using published data are shown to be consistent to those previously obtained using individual patient data, supporting a small volume-effect and dependence on exposure to high threshold dose., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Background and Purpose: To determine a dose-effect relation for radiation induced rib fractures after stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC). Automatic rib delineation has enabled the analysis of a large patient group., Material and Methods: Four-hundred and sixty-six patients with stage I/II NSCLC received SBRT with a median of 54Gy in 3 fractions. The optimal EQD2-corrected dose parameter to predict (a)symptomatic fractures was found using Cox regression. Three normal tissue complication probability (NTCP) models based on this optimal parameter were constructed: (1) at a median follow up (FU) of 26months, (2) for all data, with time to toxicity taken into account and (3) at a FU of 26months, excluding low dose ribs., Results: The median time to fracture was 22 (range 5-51) months. Maximum rib dose best predicted fractures. The TD 50 (dose with 50% complication) of the second NTCP model was 375Gy. The TD 50 was significantly higher for the other models indicating an under-estimation of the dose effect at the median follow-up time and/or when excluding low dose ribs., Conclusions: The risk of symptomatic rib fractures after SBRT was significantly correlated to dose, and was <5% at 26months when D max <225Gy., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background and Purpose: Current models for the prediction of late patient-rated moderate-to-severe xerostomia (XER 12m ) and sticky saliva (STIC 12m ) after radiotherapy are based on dose-volume parameters and baseline xerostomia (XER base ) or sticky saliva (STIC base ) scores. The purpose is to improve prediction of XER 12m and STIC 12m with patient-specific characteristics, based on CT image biomarkers (IBMs)., Methods: Planning CT-scans and patient-rated outcome measures were prospectively collected for 249 head and neck cancer patients treated with definitive radiotherapy with or without systemic treatment. The potential IBMs represent geometric, CT intensity and textural characteristics of the parotid and submandibular glands. Lasso regularisation was used to create multivariable logistic regression models, which were internally validated by bootstrapping., Results: The prediction of XER 12m could be improved significantly by adding the IBM "Short Run Emphasis" (SRE), which quantifies heterogeneity of parotid tissue, to a model with mean contra-lateral parotid gland dose and XER base . For STIC 12m , the IBM maximum CT intensity of the submandibular gland was selected in addition to STIC base and mean dose to submandibular glands., Conclusion: Prediction of XER 12m and STIC 12m was improved by including IBMs representing heterogeneity and density of the salivary glands, respectively. These IBMs could guide additional research to the patient-specific response of healthy tissue to radiation dose., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Background and Purpose: To develop a multivariable prediction model for the risk of grade⩾2 fibrosis in the boost area after breast conserving surgery (BCS) followed by three-dimensional conformal radiotherapy (RT) with a simultaneous integrated photon boost (3D-CRT-SIB), five years after RT., Material and Methods: This prospective cohort study included 1,030 patients treated with RT for breast cancer (stage 0-III), after BCS. Data regarding physician-rated fibrosis and dose-volume parameters were available in 546 patients. A multivariable logistic regression model for grade⩾2 fibrosis was generated., Results: At 5years, grade⩾2 fibrosis was observed in 13.4% of the patients. The multivariable analysis resulted in a prediction model for grade⩾2 fibrosis in the boost area including three independent variables: patient age, breast volume receiving⩾55Gy (V55 CTV breast) and the maximum radiation dose in the breast (D max )., Conclusions: A multivariable prediction model was developed including age, V55 CTV breast and D max for grade⩾2 fibrosis in the boost area after breast cancer RT using a 3D-CRT-SIB technique. This model can be used to estimate the risk of fibrosis and to optimize dose distributions aiming at reducing this risk., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Background and Purpose: To investigate the dose-response relation between the dose to the vagina and the patient-reported symptom 'absence of vaginal elasticity' and how time to follow-up influences this relation., Material and Methods: The study included 78 long-term gynecological cancer survivors treated between 1991 and 2003 with external beam radiation therapy. Of those, 24 experienced absence of vaginal elasticity. A normal tissue complication model is introduced that takes into account the influence of time to follow-up on the dose-response relation and the patient's age. The best estimates of the dose-response parameters were calculated using Probit, Probit-Relative Seriality (RS) and Probit-time models. Log likelihood (LL) values and the Akaike Information Criterion (AIC) were used to evaluate the model fit., Results: The dose-response parameters for 'absence of vaginal elasticity' according to the Probit and Probit-time models with the 68% Confidence Intervals (CI) were: LL=-39.8, D 50 =49.7 (47.2-52.4) Gy, γ 50 =1.40 (1.12-1.70) and LL=-37.4, D 50 =46.9 (43.5-50.9) Gy, γ 50 =1.81 (1.17-2.51) respectively., Conclusions: The proposed model, which describes the influence of time to follow-up on the dose-response relation, fits our data best. Our data indicate that the steepness of the dose-response curve of the dose to the vagina and the symptom 'absence of vaginal elasticity' increases with time to follow-up, while D 50 decreases., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Background and Purpose: Curative radiotherapy for prostate cancer may lead to anorectal side effects, including rectal bleeding, fecal incontinence, increased stool frequency and rectal pain. The main objective of this study was to develop multivariable NTCP models for these side effects., Material and Methods: The study sample was composed of 262 patients with localized or locally advanced prostate cancer (stage T1-3). Anorectal toxicity was prospectively assessed using a standardized follow-up program. Different anatomical subregions within and around the anorectum were delineated. A LASSO logistic regression analysis was used to analyze dose volume effects on toxicity., Results: In the univariable analysis, rectal bleeding, increase in stool frequency and fecal incontinence were significantly associated with a large number of dosimetric parameters. The collinearity between these predictors was high (VIF>5). In the multivariable model, rectal bleeding was associated with the anorectum (V70) and anticoagulant use, fecal incontinence was associated with the external sphincter (V15) and the iliococcygeal muscle (V55). Finally, increase in stool frequency was associated with the iliococcygeal muscle (V45) and the levator ani (V40). No significant associations were found for rectal pain., Conclusions: Different anorectal side effects are associated with different anatomical substructures within and around the anorectum. The dosimetric variables associated with these side effects can be used to optimize radiotherapy treatment planning aiming at prevention of specific side effects and to estimate the benefit of new radiation technologies., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Background and Purpose: Determination of a dose-effect relation for rib fractures in a large patient group has been limited by the time consuming manual delineation of ribs. Automatic segmentation could facilitate such an analysis. We determine the accuracy of automatic rib segmentation in the context of normal tissue complication probability modeling (NTCP)., Materials and Methods: Forty-one patients with stage I/II non-small cell lung cancer treated with SBRT to 54 Gy in 3 fractions were selected. Using the 4DCT derived mid-ventilation planning CT, all ribs were manually contoured and automatically segmented. Accuracy of segmentation was assessed using volumetric, shape and dosimetric measures. Manual and automatic dosimetric parameters Dx and EUD were tested for equivalence using the Two One-Sided T-test (TOST), and assessed for agreement using Bland-Altman analysis. NTCP models based on manual and automatic segmentation were compared., Results: Automatic segmentation was comparable with the manual delineation in radial direction, but larger near the costal cartilage and vertebrae. Manual and automatic Dx and EUD were significantly equivalent. The Bland-Altman analysis showed good agreement. The two NTCP models were very similar., Conclusions: Automatic rib segmentation was significantly equivalent to manual delineation and can be used for NTCP modeling in a large patient group., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Purpose: The aim of this study was to estimate normal tissue complication probability (NTCP) parameters for late rectal complications after carbon ion radiotherapy (C-ion RT) for prostate cancer., Methods and Materials: A total of 163 patients were used to derive NTCP parameters. These patients were treated with relative biological effectiveness (RBE)-weighted dose ranging from 57.6 Gy (RBE) up to 72 Gy (RBE) and included in dose escalation trials. The Lyman-Kutcher-Burman (LKB) model was used and the model parameters were fit to the relation between dose and complication observed after C-ion RT., Results: The resulting NTCP parameters were the volume effect parameter; n=0.035 (95% CI: 0.024-0.047), the steepness of the NTCP curve; m=0.10 (0.084-0.13), the tolerance dose associated with 50% probability of complication; TD50=63.6 Gy (RBE) (61.8-65.4 Gy (RBE)) for Grade⩾1, n=0.012 (0.0050-0.023), m=0.046 (0.033-0.062), TD50=69.1 Gy (RBE) (67.6-70.9 Gy (RBE)) for Grade⩾2., Conclusion: A new set of rectal NTCP parameters in C-ion RT was determined. The rather small n values suggest that the rectum was consistent with being strictly serial organ. The new derived parameter values facilitate estimation of rectal NTCP in C-ion RT., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Purpose: We used normal tissue complication probability (NTCP) modeling to explore the impact of heart irradiation on radiation-induced lung fibrosis (RILF)., Materials and Methods: We retrospectively reviewed for RILF 148 consecutive Hodgkin lymphoma (HL) patients treated with sequential chemo-radiotherapy (CHT-RT). Left, right, total lung and heart dose-volume and dose-mass parameters along with clinical, disease and treatment-related characteristics were analyzed. NTCP modeling by multivariate logistic regression analysis using bootstrapping was performed. Models were evaluated by Spearman Rs coefficient and ROC area., Results: At a median time of 13months, 18 out of 115 analyzable patients (15.6%) developed RILF after treatment. A three-variable predictive model resulted to be optimal for RILF. The two models most frequently selected by bootstrap included increasing age and mass of heart receiving >30Gy as common predictors, in combination with left lung V5 (Rs=0.35, AUC=0.78), or alternatively, the lungs near maximum dose D2% (Rs=0.38, AUC=0.80)., Conclusion: CHT-RT may cause lung injury in a small, but significant fraction of HL patients. Our results suggest that aging along with both heart and lung irradiation plays a fundamental role in the risk of developing RILF., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Purpose: To test the hypothesis that delineation of swallowing organs at risk (SWOARs) based on different guidelines results in differences in dose-volume parameters and subsequent normal tissue complication probability (NTCP) values for dysphagia-related endpoints., Materials and Methods: Nine different SWOARs were delineated according to five different delineation guidelines in 29 patients. Reference delineation was performed according to the guidelines and NTCP-models of Christianen et al. Concordance Index (CI), dosimetric consequences, as well as differences in the subsequent NTCPs were calculated., Results: The median CI of the different delineation guidelines with the reference guidelines was 0.54 for the pharyngeal constrictor muscles, 0.56 for the laryngeal structures and 0.07 for the cricopharyngeal muscle and esophageal inlet muscle. The average difference in mean dose to the SWOARs between the guidelines with the largest difference (maxΔD) was 3.5±3.2Gy. A mean ΔNTCP of 2.3±2.7% was found. For two patients, ΔNTCP exceeded 10%., Conclusions: The majority of the patients showed little differences in NTCPs between the different delineation guidelines. However, large NTCP differences >10% were found in 7% of the patients. For correct use of NTCP models in individual patients, uniform delineation guidelines are of great importance., (Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.)

Introduction: The dose-volume effect of radiation therapy on breast tissue is poorly understood. We estimate NTCP parameters for breast fibrosis after external beam radiotherapy., Materials and Methods: We pooled individual patient data of 5856 patients from 2 trials including whole breast irradiation followed with or without a boost. A two-compartment dose volume histogram model was used with boost volume as the first compartment and the remaining breast volume as second compartment. Results from START-pilot trial (n=1410) were used to test the predicted models., Results: 26.8% patients in the Cambridge trial (5 years) and 20.7% patients in the EORTC trial (10 years) developed moderate-severe breast fibrosis. The best fit NTCP parameters were BEUD3(50)=136.4 Gy, γ50=0.9 and n=0.011 for the Niemierko model and BEUD3(50)=132 Gy, m=0.35 and n=0.012 for the Lyman Kutcher Burman model. The observed rates of fibrosis in the START-pilot trial agreed well with the predicted rates., Conclusions: This large multi-centre pooled study suggests that the effect of volume parameter is small and the maximum RT dose is the most important parameter to influence breast fibrosis. A small value of volume parameter 'n' does not fit with the hypothesis that breast tissue is a parallel organ. However, this may reflect limitations in our current scoring system of fibrosis., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Background and Purpose: We reported the incidence of severe late esophagus toxicity (LET) in locally advanced NSCLC patients treated with intensity-modulated radiation therapy (IMRT) and concurrent chemotherapy. Acute esophagus toxicity (AET) and the dose to the esophagus were analyzed for their associations with severe LET., Material and Methods: Two hundred and thirty-one patients treated from 2008 to 2011 with hypofractionated IMRT (66Gy/24fx) and concurrent daily low dose cisplatin were included. The association between AET and severe LET (grade ≥ 3 RTOG/EORTC) was tested through Cox-proportional-hazards model. Equivalent uniform dose (EUD) to the esophagus and the volume percentage receiving more than x Gy (Vx) were applied by Lyman-Kutcher-Burman (LKB) model., Results: A total of 171 patients were eligible for this study. Severe LET was observed in 6% patients. Both the maximum grade and the recovery rate of AET were significantly associated with severe LET. In the EUDn-LKB model, the fitted values and 95% confidence intervals (CIs) were TD50=76.1 Gy (73.2-78.6), m=0.03 (0.02-0.06) and n=0.03 (0-0.08). In the Vx-LKB model, the fitted values and 95% CIs were Tx50=23.5% (16.4-46.6), m=0.44 (0.32-0.60) and x=76.7 Gy (74.7-77.5)., Conclusions: Severe AET, EUD (n=0.03) and V76.7 to the esophagus were significantly associated with severe LET. An independent validation study is required., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Purpose: To model the local dose-effect relation for lung perfusion reduction in lung cancer patients treated with stereotactic body radiotherapy (SBRT)., Materials and Methods: Forty-two patients having upper-lobe peripheral tumours <5 cm treated with SBRT (3×18 Gy) underwent single-photon emission computed-tomography (SPECT) scans to measure the lung perfusion 2 weeks pre-SBRT, 4-months post-SBRT, and for 8 patients 15-months post-SBRT. The relation between the calculated relative local perfusion reduction and the normalised total dose (α/β=3 Gy) at 4-months post-SBRT was modeled by 3-parameter logistic model and 2-parameter linear-maximum model., Results: The relation between local dose and perfusion reduction at 4-months post-SBRT showed a maximum effect of 42.6% at doses >100 Gy and was best described by the logistic model with parameters (95% CI): M=42.6% (40.7-44.6), D50=28.7 Gy (26.3-31.1) and k=2.2 (1.8-2.5). A significant increase of this maximum effect to 65.2% was found at 15-months post-SBRT., Conclusions: The relation between local dose and perfusion reduction in patients treated with SBRT can be modeled by a 3-parameter logistic model. This demonstrated relationship 4-months post-SBRT approaches a plateau for doses >100 Gy, where 90% of the maximum lung-perfusion reduction is observed at NTD=78 Gy. A further perfusion reduction compared to 4-months post-SBRT was observed fifteen months post-SBRT., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)