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Stereotactic radiation therapy (SRT) is a proven effective treatment for brain metastases (BM); however, symptomatic radiation necrosis (RN) is a late effect that may impact on patient’s quality of life. The aim of our study was to retrospectively evaluate survival outcomes and characterize the occurrence of RN in a cohort of BM patients treated with ablative SRT at Federico II University Hospital. Clinical and dosimetric factors of 87 patients bearing a total of 220 BMs treated with SRT from 2016 to 2022 were analyzed. Among them, 46 patients with 127 BMs having clinical and MRI follow-up (FUP) ≥ 6 months were selected for RN evaluation. Dosimetric parameters of the uninvolved brain (brain without GTV) were extracted. The crude local control was 91% with neither clinical factors nor prescription dose correlating with local failure (LF). At a median FUP of 9 (1–68) months, the estimated median overall survival (OS), progression-free survival (PFS), and brain progression-free survival (bPFS) were 16, 6, and 9 months, respectively. The estimated OS rates at 1 and 3 years were 59.8% and 18.3%, respectively; bPFS at 1 and 3 years was 29.9% and 13.5%, respectively; PFS at 1 and 3 years was 15.7% and 0%, respectively; and local failure-free survival (LFFS) at 1 and 3 years was 87.2% and 83.8%, respectively. Extracranial disease status was an independent factor related to OS. Fourteen (30%) patients manifested RN. At multivariate analysis, adenocarcinoma histology, left location, and absence of chemotherapy were confirmed as independent risk factors for any-grade RN. Nine (20%) patients developed symptomatic (G2) RN, which improved or stabilized after 1–16 months of steroid therapy. With prompt recognition and, when necessary, medical therapy, RN radiological and clinical amelioration can be obtained.

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.

Purpose To introduce a class of fast 3D quantitative MRI (qMRI) schemes (RESUMEN, for N = 1 , … , 4 ) that allow for a thorough characterization of microstructural properties of brain tissues. Methods An arbitrary multi-echo GRE acquisition optimized for quantitative susceptibility mapping (QSM) is complemented with an appropriate low flip-angle GRE sequence drawn from four possible choices. The acquired signals are processed to analytically derive the longitudinal relaxation ( R 1 ) and free induction decay ( R 2 ∗ ) rates, as well as the proton density (PD) and QSM. A comprehensive modeling of the excitation and B 1 - profiles and of the RF-spoiling is included in the acquisition and processing pipeline. Results The RESUMEN maps appear homogeneous throughout the field-of-view and exhibit comparable values and high SNR across the considered range of N values. Conclusions The introduced schemes represent a class of robust and flexible strategies to derive a thorough and fast qMRI study, suitable for a whole-brain acquisition with isotropic voxel resolution of 700 μ m in less than 15 min.

Radiation therapy (RT) plays a fundamental role in the multidisciplinary treatment and management of thoracic cancers, and in particular, RT is the most used non-surgical treatment modality for lung cancer, which in turn is the most common type of thoracic malignancy [...]

Recently, 2D or 3D methods for dose distribution analysis have been proposed as evolutions of the Dose Volume Histogram (DVH) approaches. Those methods, collectively referred to as pixel- or voxel-based (VB) methods, evaluate local dose response patterns and go beyond the organ-based philosophy of Normal Tissue Complication Probability (NTCP) modelling. VB methods have been introduced in the context of radiation oncology in the very last years following the virtuous example of neuroimaging experience. In radiation oncology setting, dose mapping is a suitable scheme to compare spatial patterns of local dose distributions between patients who develop toxicity and who do not. In this critical review, we present the methods that include spatial dose distribution information for evaluating different toxicity endpoints after radiation therapy. The review addresses two main topics. First, the critical aspects in dose map building, namely the spatial normalization of the dose distributions from different patients. Then, the issues related to the actual dose map comparison, i.e. the viable options for a robust VB statistical analysis and the potential pitfalls related to the adopted solutions. To elucidate the different theoretical and technical issues, the covered topics are illustrated in relation to practical applications found in the existing literature. We conclude the overview on the VB philosophy in radiation oncology by introducing new phenomenological approaches to NTCP modelling that accounts for inhomogeneous organ radiosensitivity.

To investigate the interplay between spatial dose patterns and single nucleotide polymorphisms in the development of radiation-induced lymphopenia (RIL) in 186 non-small-cell lung cancer (NSCLC) patients undergoing chemo-radiotherapy (RT).This study included NSCLC patients enrolled in a randomized trial of protons vs. photons with available absolute lymphocyte counts at baseline and during RT and XRCC1-rs25487 genotyping data. After masking the GTV, planning CT scans and dose maps were spatially normalized to a common anatomical reference. A Voxel-Based Analysis (VBA) was performed to assess voxel-wise relationships of dosiomic and genomic explanatory variables with RIL. The underlying generalized linear model was designed to include both the explanatory variables (3D dose distributions and the XRCC1-rs25487 genotypes) and possible nuisance variables significantly correlated with RIL. The maps of model coefficients as well as their significance maps were generated.Measures for RIL definition during RT were characterized, including kinetic parameters for lymphocyte loss. The VBA generated three-dimensional maps of correlation between RIL and dose in lymphoid organs as well as organs with abundant blood pools. The identified voxel-wise relationships account for XRCC1-rs25487 polymorphism and demonstrate the variant AA genotype being detrimental to lymphocyte depletion (p = 0.03).The performed analyses blindly highlighted relevant anatomical regions that contributed most to lymphocyte depletion during RT and the interplay of the variant XRCC1-rs25487 AA genotype with the dose delivered to the primary lymphoid organs. These findings may help to guide the development of dosimetric RIL mitigation strategies for the application of effective individualized RT.

Anthracyclines are widely used in anticancer protocols, but can induce cardiotoxicity by mechanisms that mainly involve oxidative damage and mitochondrial dysfunction. Radiotherapy can also impair cardiac function by promoting myocardial fibrosis, microvascular damage and decreased density of myocardial capillaries. Hence, we aim at investigating prospectively whether radiotherapy impacts heart function in lymphoma patients who had been already treated with anthracyclines. Twenty-nine consecutive patients with Hodgkin or non-Hodgkin lymphomas underwent echocardiography at baseline (before antineoplastic treatments), and then every two months, until 6 months after treatments completion. Echo evaluation included standard 2D and Speckle Tracking. Twenty-two patients treated with anthracycline-based regimens were eligible. Out of the 22 patients, 8 received chemotherapy only (subgroup 1), while 14 underwent radiotherapy after chemotherapy (subgroup 2). At the end of chemotherapy, ejection fraction was significantly reduced in the whole population. At 6 months after completion of therapies, E/E' increased and Global Longitudinal Strain was compromised in subgroup 2, suggesting additional damage induced by radiotherapy after chemotherapy. On the basis of the data from our small prospective study we can hypothesize that in lymphoma patients anthracyclines can worsen cardiac function, and radiotherapy may have an additional unfavorable myocardial impact.

Purpose Radiation pneumonitis (RP) is commonly associated with thoracic radiation therapy, and its incidence is related to dose and volume of the normal lung in the path of radiation. Our aim was to investigate dose patterns associated with RP in patients enrolled in a randomized trial of intensity modulated radiation therapy (IMRT) versus passive scattering proton therapy (PSPT) for locally advanced non-small cell lung cancer. Methods We analyzed 178 patients prospectively treated with PSPT or IMRT for non-small cell lung cancer to a prescribed dose of 66 or 74 Gy in conventional daily fractionation with concurrent chemotherapy. Forty patients (22%) developed clinically symptomatic RP. Voxel-based analysis of local dose differences was done with a nonparametric permutation test accounting for multiple comparisons. From the obtained 3-dimensional significance maps, we derived clusters of voxels that exhibited dose differences between groups at a statistical significance level of 0.05. Results The voxel-based analysis highlighted that (1) significant dose differences between patients with and without RP were found in the lower part of the lungs and in the heart and (2) the anatomic regions significantly spared by PSPT and the clusters in which doses were significantly correlated with RP development were disjoint. Conclusions The analyzed trial data provide an unprecedented opportunity to substantiate previous hypotheses regarding the role of the heart and the lower lungs in the development of RP. Knowledge of this relationship between RP and thoracic regional radiosensitivity should be considered in clinical practice and in the design of future trials.

Purpose To present a new formalism for a robust computation of Dose-Surface Histograms (DSHs) to be exploited in the analysis of surface effects in radiation induced toxicity phenomena. Methods A new formal recipe for the DSH extraction is described. It is based on the computation of the Dose-Volume Histogram (DVH) on a 3D structure in the limit of vanishing thickness to approach the two-dimensional organ manifold. The theory is customized for the application to skin description. Results The derived formalism resulted in a redefinition of the generalized equivalent uniform dose (gEUD) and, accordingly, in an extension of the scope of the classical Lyman-Kutcher-Burman (LKB) Normal Tissue Complication Probability (NTCP) to a DSH-based toxicity modeling. Conclusions Our approach properly fits the intrinsic 3D nature of the DSH computation issue, and guarantees the rotational invariance and the robustness of the results. The proposed formalism can be easily implemented in treatment planning systems for dose optimization and potentially paves the way to a consistent analysis of radiation-induced morbidity endpoints related to surface effects in hollow organs.

To introduce a class of fast 3D quantitative MRI (qMRI) schemes (RESUMEAn arbitrary multi-echo GRE acquisition optimized for quantitative susceptibility mapping (QSM) is complemented with an appropriate low flip-angle GRE sequence drawn from four possible choices. The acquired signals are processed to analytically derive the longitudinal relaxation (RThe RESUMEThe introduced schemes represent a class of robust and flexible strategies to derive a thorough and fast qMRI study, suitable for a whole-brain acquisition with isotropic voxel resolution of 700 μm in less than 15 min.

Purpose To investigate thoracic dose–response patterns for pericardial effusion (PCE) and mortality in patients treated for locally advanced Non-Small-Cell Lung Cancer (NSCLC) by Intensity Modulated RT (IMRT) or Passive-Scattering Proton Therapy (PSPT). Methods Among 178 patients, 43.5% developed grade ≥ 2 PCE. Clinical and dosimetric factors associated with PCE or overall survival (OS) were identified via multi-variable Cox proportional hazards modeling. The Voxel-Based Analyses (VBAs) of local dose differences between patients with and without PCE and mortality was performed. The robustness of VBA results was assessed by a novel characterization of spatial properties of dose distributions based on probabilistic independent component analysis (PICA) and connectograms. Results Several non-dosimetric variables were selected by the multivariable analysis for the considered outcomes, while the time-dependent PCE onset was uncorrelated with the OS (p = 0.34) at a multi-variable Cox analysis. Despite the significant PSPT dosimetric advantage, the RT technique did not affect the occurrence of PCE or OS. VBAs highlighted largely overlapping clusters significantly associated with PCE endpoints in heart and lungs. No significant dosimetric patterns related to mortality endpoints were found. PICA identified 43 components homogeneously scattered within thorax, while connectograms showed modest correlations between doses in main cardio-pulmonary substructures. Conclusions Spatially resolved analysis highlighted dose patterns related to radiation-induced cardiac toxiciy and the observed organ-based dose–response mismatch in PSPT and IMRT. Indeed, the thoracic regions spared by PSPT poorly overlapped with the areas involved in PCE development, as highlited by VBA. PICA and connectograms proved valuable tools for assessing the robusteness of obtained VBA inferences.

Simple Summary The pathophysiology of radiation pneumonitis (RP) after thoracic cancer radiation treatments is still not completely understood although the identification of underlying RP mechanisms may improve the therapeutic window of thoracic cancer patients. The aim of our retrospective study was to explore the dose–response patterns associated with RP by a multi-center voxel-based analysis. In a heterogeneously treated population of 382 thoracic cancer patients, we confirmed the previously described heart–lung interaction in the development of RP. The empowerment of VBA with a novel description of dose map spatial properties based on probabilistic independent component analysis (PICA) and connectograms provided valuable additional and independent information on the radiobiology of RP. Abstract This study investigates the dose–response patterns associated with radiation pneumonitis (RP) in patients treated for thoracic malignancies with different radiation modalities. To this end, voxel-based analysis (VBA) empowered by a novel strategy for the characterization of spatial properties of dose maps was applied. Data from 382 lung cancer and mediastinal lymphoma patients from three institutions treated with different radiation therapy (RT) techniques were analyzed. Each planning CT and biologically effective dose map (α/β = 3 Gy) was spatially normalized on a common anatomical reference. The VBA of local dose differences between patients with and without RP was performed and the clusters of voxels with dose differences that significantly correlated with RP at a p-level of 0.05 were generated accordingly. The robustness of VBA inference was evaluated by a novel characterization for spatial properties of dose maps based on probabilistic independent component analysis (PICA) and connectograms. This lays robust foundations to the obtained findings that the lower parts of the lungs and the heart play a prominent role in the development of RP. Connectograms showed that the dataset can support a radiobiological differentiation between the main heart and lung substructures.

Applied Sciences 11(15), 6806 (2021). doi:10.3390/app11156806, Published by MDPI, Basel

The aim of our study is to characterize the risk of radiation-induced esophagitis (RE) in a cohort of Non-Small-Cell Lung Cancer (NSCLC) patients treated with concurrent chemotherapy and photon/proton therapy. For each patient, the RE was graded according to the CTCAE v.3. The esophageal dose-volume histograms (DVHs) were extracted. Voxel-based analyses (VBAs) were performed to assess the spatial patterns of the dose differences between patients with and without RE of grade ≥ 2. Two hierarchical NTCP models were developed by multivariable stepwise logistic regression based on non-dosimetric factors and on the DVH metrics for the whole esophagus and its anatomical subsites identified by the VBA. In the 173 analyzed patients, 76 (44%) developed RE of grade ≥ 2 at a median follow-up time of 31 days. The VBA identified regions of significant association between dose and RE in a region encompassing the thoracic esophagus. We developed two NTCP models, including the RT modality and a dosimetric factor: V55Gy for the model related to the whole esophagus, and the mean dose for the model designed on the thoracic esophagus. The cross-validated performance showed good predictions for both models (ROC-AUC of 0.70 and 0.73, respectively). The only slight improvement provided by the analysis of the thoracic esophageal subsites might be due to the relevant sparing of cervical and lower thoracic esophagus in the analyzed cohort. Further studies on larger cohorts and a more heterogeneous set of dose distributions are needed to validate these preliminary findings and shed further light on the spatial patterns of RE development.

editorial comment of the potential effect of COVID 19 on radiation related lung toxicity

Purpose: The aim of the study was to exploit the feasibility of thermoluminescent dosimeters (TLDs) in radiation therapy techniques in which high dose per fraction is involved. Methods: Dose–response of TLD-100 (LiF: Mg, Ti) was investigated in both 6-MV photon and 6-MeV electron beams. The element correction factor (ECF) generation method was applied to check the variability of the TLDs response. Two batches of 50 TLDs were divided into groups and exposed in the dose range 0 to 30 Gy. Regression analysis was performed with both linear and quadratic models. For each irradiation beam, the calibration curves were obtained in 3 dose range 0 to 8 Gy, 0 to 10 Gy, and 0 to 30 Gy. The best-fitting model was assessed by the Akaike Information Criterion test. Results: The ECF process resulted a useful tool to reduce the coefficients of variation from original values higher than 5% to about 3.5%, for all the batches exposed. The results confirm the linearity of dose–response curve below the dose level of 10 Gy for photon and electron beam and the supralinear trend above. Conclusion: The TLDs are suitable dosimeters for dose monitoring and verification in radiation treatment involving dose up to 30 Gy in a single fraction.

To devise a novel Spatial Normalization framework for Voxel-based analysis (VBA) in brain radiotherapy. VBAs rely on accurate spatial normalization of different patients' planning CTs on a common coordinate system (CCS). The cerebral anatomy, well characterized by MRI, shows instead poor contrast in CT, resulting in potential inaccuracies in VBAs based on CT alone.We analyzed 50 meningioma patients treated with proton-therapy, undergoing planning CT and T1-weighted (T1w) MRI. The spatial normalization pipeline based on MR and CT images consisted in: intra-patient registration of CT to T1w, inter-patient registration of T1w to MNI space chosen as CCS, doses propagation to MNI. The registration quality was compared with that obtained by Statistical Parametric Mapping software (SPM), used as benchmark. To evaluate the accuracy of dose normalization, the dose organ overlap (DOO) score was computed on gray matter, white matter and cerebrospinal fluid before and after normalization. In addition, the trends in the DOOs distribution were investigated by means of cluster analysis.The registration quality was higher for the proposed method compared to SPM (p 0.001). The DOO scores showed a significant improvement after normalization (p 0.001). The cluster analysis highlighted 2 clusters, with one of them including the majority of data and exhibiting acceptable DOOs.Our study presents a robust tool for spatial normalization, specifically tailored for brain dose VBAs. Furthermore, the cluster analysis provides a formal criterion for patient exclusion in case of non-acceptable normalization results. The implemented framework lays the groundwork for future reliable VBAs in brain irradiation studies.

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, D2%: near maximum dose, Dmean: 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 S21Gy for acute and S25Gy, 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. D2% 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.

Purpose: To identify predictors of hypothyroidism after chemoradiation therapy for Hodgkin lymphoma (HL) and to compare outcomes after intensity modulated radiation therapy (IMRT) with those after 3-dimensional (3D) conformal radiation therapy (CRT). Methods and Materials: Ninety patients who underwent involved-site IMRT in 2009 through 2014 were evaluated for treatment-induced hypothyroidism, defined as elevated thyroid-stimulating hormone or decreased free thyroxine levels (or both). Receiver operating characteristic curve analysis identified individuals at low versus high risk based on dosimetric variables. Dosimetric cutoff points were verified with an external data set of 50 patients who underwent 3D-CRT. Results: In the IMRT group, most patients (75 [83%]) had stage II HL, and the median prescribed dose was 30.6 Gy; in the 3D-CRT group, 32 patients (64%) had stage II HL, and the median prescribed dose was 32.0 Gy. No differences were found in the proportions of patients with bilateral (P =.982) or unilateral (P =.074) neck involvement between the 2 groups. Hypothyroidism rates were marginally higher in the IMRT group, with estimated 3-year rates of freedom from hypothyroidism of 56.1% in the 3D-CRT group and 40% in the IMRT group (P =.057). Univariate analysis showed that smaller thyroid volume and higher thyroid dose were associated with hypothyroidism in both groups (P =25 Gy (V25) and the absolute volume of the thyroid gland spared from 25 Gy (VS25Gy) were the strongest predictors of hypothyroidism (P =.001 and P

Simple Summary Dyspnea is a common symptomatic side-effect of thoracic radiation therapy. The aim of this study is to build a predictive model of any-grade radiation-induced dyspnea within six months after stereotactic body radiation therapy in patients treated for non-small cell lung cancer. The occurrence of pre-treatment chronic obstructive pulmonary disease and higher relative lungs volume receiving more than 15 Gy as well as heart volume were shown to be risk factors for dyspnea. The obtained results encourage further studies on the topic, which could validate the present organ-based findings and explore the voxel-based landscape of radiation dose sensitivity in the development of dyspnea. Abstract In this study, we investigated the prognostic factors for radiation-induced dyspnea after hypo-fractionated radiation therapy (RT) in 106 patients treated with Stereotactic Body RT for Non-Small-Cell Lung Cancer (NSCLC). The median prescription dose was 50 Gy (range: 40–54 Gy), delivered in a median of four fractions (range: 3–12). Dyspnea within six months after SBRT was scored according to CTCAE v.4.0. Biologically Effective Dose (α/β = 3 Gy) volume histograms for lungs and heart were extracted. Dosimetric parameters along with patient-specific and treatment-related factors were analyzed, multivariable logistic regression method with Leave-One-Out (LOO) internal validation applied. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC) and calibration plot parameters. Fifty-seven patients (53.8%) out of 106 developed dyspnea of any grade after SBRT (25/57 grade ≥ 2 cases). A three-variable predictive model including patient comorbidity (COPD), heart volume and the relative lungs volume receiving more than 15 Gy was selected. The model displays an encouraging performance given by a training ROC-AUC = 0.71 [95%CI 0.61–0.80] and a LOO-ROC-AUC = 0.64 [95%CI 0.53–0.74]. Further modeling efforts are needed for dyspnea prediction in hypo-fractionated treatments in order to identify patients at high risk for developing lung toxicity more accurately.

Thoracic radiation therapy (RT) is often associated with lung side effects, whose etiology is still controversial. Our aim was to explore correlations between local dose in the thoracic anatomy and the radiation-induced lung damage (RILD). To this end, we designed a robust scheme for voxel-based analysis (VBA) to explore dose patterns associated with RILD in non-small-cell lung cancer (NSCLC) patients receiving stereotactic body RT (SBRT). We analyzed 106 NSCLC SBRT patients (median prescription dose: 50 Gy; range: [40-54] Gy) in 4 fractions (range: [3-5]) with clinical and dosimetric records suitable for the analysis. The incidence of acute G1 RILD (RTOG grade ⩾ 1) was 68%. Each planning CT and dose map was spatially normalized to a common anatomical reference using a B-spline inter-patient registration algorithm after masking the gross tumor volume. The tumor-subtracted dose maps were converted into biologically effective dose maps (α/β = 3 Gy). VBA was performed according to a non-parametric permutation test accounting for multiple comparison, based on a cluster analysis method. The underlying general linear model of RILD was designed to include dose maps and each non-dosimetric variable significantly correlated with RILD. The clusters of voxels with dose differences significantly correlated with RILD at a given p -level (S p ) were generated. The only non-dosimetric variable significantly correlated with RILD was the chronic obstructive pulmonary disease (p = 0.034). Patients with G1 RILD received significantly (p ⩽ 0.05) higher doses in two voxel clusters S 0.05 in the lower-left lung (14 cm3) and in an area (64 cm3) largely included within the ventricles. The applied VBA represents a powerful tool to probe the dose susceptibility of inhomogeneous organs in clinical radiobiology studies. The identified subregions with dose differences associated with G1 RILD in both the heart and lower lungs endorse a trend of previously reported hypotheses on lung toxicity radiobiology.

The contemporary approach to the management of a cancer patient requires an "ab initio" involvement of different medical domains in order to correctly design an individual patient's pathway toward cure. With new therapeutic tools in every medical field developing faster than ever before the patient care outcomes can be achieved if all surgical, drug, and radiation options are considered in the design of the appropriate therapeutic strategy for a given patient. Radiation therapy (RT) is a clinical discipline in which experts from different fields continuously interact in order to manage the multistep process of the radiation treatment. RT is found to be an appropriate intervention for diverse indications in about 50% of cancer patients during the course of their disease. Technologies are essential in dealing with the complexity of RT treatments and for driving the increasingly sophisticated RT approaches becoming available for the treatment of Cancer. High conformal techniques, namely intensity modulated or volumetric modulated arc techniques, ablative techniques (Stereotactic Radiotherapy and Stereotactic Radiosurgery), particle therapy (proton or carbon ion therapy) allow for success in treating irregularly shaped or critically located targets and for the sharpness of the dose fall-off outside the target. The advanced on-board imaging, including real-time position management systems, makes possible image-guided radiation treatment that results in substantial margin reduction and, in select cases, implementation of an adaptive approach. The therapeutic gains of modern RT are also due in part to the enhanced anticancer activity obtained by coadministering RT with chemotherapy, targeted molecules, and currently immune checkpoints inhibitors. These main clinically relevant steps forward in Radiation Oncology represent a change of gear in the field that may have a profound impact on the management of cancer patients.

Modelling Radiotherapy Side Effects advances in RT. Modeling radiation-induced heart disease has been hampered both by the relatively low incidence of complications and the lack of long-term results from 3D-based thoracic RT. However, in the last decade we have seen increasing development of studies that are based on both long follow-up and large populations, which are evaluating the determinants of the risk and the radiation dose-response. In this chapter, a review of the available dosimetric constraints, an analysis of the interaction between them and other relevant patient and treatment-related factors and models on CV toxicity following RT is presented. The main criteria used in this review are fractionation patterns and diagnosis.

Mathematical models of normal tissue complication probability (NTCP) able to robustly predict radiation-induced morbidities (RIM) play an essential role in the identification of a personalized optimal plan, and represent the key to maximizing the benefits of technological advances in radiation therapy (RT). Most modern RT techniques pose, however, new challenges in estimating the risk of RIM. The aim of this report is to schematically review NTCP models in the framework of advanced radiation therapy techniques. Issues relevant to hypofractionated stereotactic body RT and ion beam therapy are critically reviewed. Reirradiation scenarios for new or recurrent malignances and NTCP are also illustrated. A new phenomenological approach to predict RIM is suggested.

Background: Different modern radiation therapy treatment solutions for breast cancer (BC) and regional nodal irradiation (RNI) have been proposed. In this study, we evaluate the potential reduction in radiation-induced skin morbidity obtained by intensity modulated proton therapy (IMPT) compared with intensity modulated photon therapy (IMXT) for left-side BC and RNI. Material and Methods: Using CT scans from 10 left-side BC patients, treatment plans were generated using IMXT and IMPT techniques. A dose of 50 Gy (or Gy [RBE] for IMPT) was prescribed to the target volume (involved breast, the internal mammary, supraclavicular, and infraclavicular nodes). Two single filed optimization IMPT (IMPT1 and IMPT2) plans were calculated without and with skin optimization. For each technique, skin dose-metrics were extracted and normal tissue complication probability (NTCP) models from the literature were employed to estimate the risk of radiation-induced skin morbidity. NTCPs for relevant organs-at-risk (OARs) were also considered for reference. The non-parametric Anova (Friedman matched-pairs signed-rank test) was used for comparative analyses. Results: IMPT improved target coverage and dose homogeneity even if the skin was included into optimization strategy (HIIMPT2 = 0.11 vs. HIIMXT = 0.22 and CIIMPT2 = 0.96 vs. CIIMXT = 0.82, p < .05). A significant relative skin risk reduction (RR = NTCPIMPT/NTCPIMXT) was obtained with IMPT2 including the skin in the optimization with a RR reduction ranging from 0.3 to 0.9 depending on the analyzed skin toxicity endpoint/model. Both IMPT plans attained significant OARs dose sparing compared with IMXT. As expected, the heart and lung doses were significantly reduced using IMPT. Accordingly, IMPT always provided lower NTCP values. Conclusions: IMPT guarantees optimal target coverage, OARs sparing, and simultaneously minimizes the risk of skin morbidity. The applied model-based approach supports the potential clinical relevance of IMPT for left-side BC and RNI and might be relevant for the setup of cost-effectiveness evaluation strategies based on NTCP predictions, as well as for establishing patient selection criteria.

In radiation oncology, the need for a modern Normal Tissue Complication Probability (NTCP) philosophy to include voxel-based evidence on organ radio-sensitivity (RS) has been acknowledged. Here a new formalism (Probabilistic Atlas for Complication Estimation, PACE) to predict radiation-induced morbidity (RIM) is presented. The adopted strategy basically consists in keeping the structure of a classical, phenomenological NTCP model, such as the Lyman-Kutcher-Burman (LKB), and replacing the dose distribution with a collection of RIM odds, including also significant non-dosimetric covariates, as input of the model framework. The theory was first demonstrated in silico on synthetic dose maps, classified according to synthetic outcomes. PACE was then applied to a clinical dataset of thoracic cancer patients classified for lung fibrosis. LKB models were trained for comparison. Overall, the obtained learning curves showed that the PACE model outperformed the LKB and predicted synthetic outcomes with an accuracy >0.8. On the real patients, PACE performance, evaluated by both discrimination and calibration, was significantly higher than LKB. This trend was confirmed by cross-validation. Furthermore, the capability to infer the spatial pattern of underlying RS map for the analyzed RIM was successfully demonstrated, thus paving the way to new perspectives of NTCP models as learning tools.