Pelvic bone marrow dose-volume predictors of late lymphopenia following pelvic lymph node radiation therapy for prostate cancer.

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.

Modeling hypoxia-induced radiation resistance and the impact of radiation sources.

Hypoxia contributes significantly to resistance in radiotherapy. Our research rigorously examines the influence of microvascular morphology on radiotherapy outcome, specifically focusing on how microvasculature shapes hypoxia within the microenvironment and affects resistance to a standard treatment regimen (30×2GyRBE). Our computational modeling extends to the effects of different radiation sources. For photons and protons, our analysis establishes a clear correlation between hypoxic volume distribution and treatment effectiveness, with vascular density and regularity playing a crucial role in treatment success. On the contrary, carbon ions exhibit distinct effectiveness, even in areas of intense hypoxia and poor vascularization. This finding points to the potential of carbon-based hadron therapy in overcoming hypoxia-induced resistance to RT. Considering that the spatial scale analyzed in this study is closely aligned with that of imaging data voxels, we also address the implications of these findings in a clinical context envisioning the possibility of detecting subvoxel hypoxia.

Comparing Performances of Predictive Models of Toxicity after Radiotherapy for Breast Cancer Using Different Machine Learning Approaches.

PURPOSE: Different ML models were compared to predict toxicity in RT on a large cohort (n = 1314). METHODS: The endpoint was RTOG G2/G3 acute toxicity, resulting in 204/1314 patients with the event. The dataset, including 25 clinical, anatomical, and dosimetric features, was split into 984 for training and 330 for internal tests. The dataset was standardized; features with a high p-value at univariate LR and with Spearman ρ>0.8 were excluded; synthesized data of the minority were generated to compensate for class imbalance. Twelve ML methods were considered. Model optimization and sequential backward selection were run to choose the best models with a parsimonious feature number. Finally, feature importance was derived for every model. RESULTS: The model's performance was compared on a training-test dataset over different metrics: the best performance model was LightGBM. Logistic regression with three variables (LR3) selected via bootstrapping showed performances similar to the best-performing models. The AUC of test data is slightly above 0.65 for the best models (highest value: 0.662 with LightGBM). CONCLUSIONS: No model performed the best for all metrics: more complex ML models had better performances; however, models with just three features showed performances comparable to the best models using many (n = 13-19) features.

Skin dose-volume predictors of moderate-severe late side effects after whole breast radiotherapy.

BACKGROUND: Toxicity after whole breast Radiotherapy is a relevant issue, impacting the quality-of-life of a not negligible number of patients. We aimed to develop a Normal Tissue Complication Probability (NTCP) model predicting late toxicities by combining dosimetric parameters of the breast dermis and clinical factors. METHODS: The skin structure was defined as the outer CT body contour's 5 mm inner isotropic expansion. It was retrospectively segmented on a large mono-institutional cohort of early-stage breast cancer patients enrolled between 2009 and 2017 (n = 1066). Patients were treated with tangential-field RT, delivering 40 Gy in 15 fractions to the whole breast. Toxicity was reported during Follow-Up (FU) using SOMA/LENT scoring. The study endpoint was moderate-severe late side effects consisting of Fibrosis-Atrophy-Telangiectasia-Pain (FATP G ≥ 2) developed within 42 months after RT completion. A machine learning pipeline was designed with a logistic model combining clinical factors and absolute skin DVH (cc) parameters as output. RESULTS: The FATP G2 + rate was 3.8 %, with 40/1066 patients experiencing side effects. After the preprocessing of variables, a cross-validation was applied to define the best-performing model. We selected a 4-variable model with Post-Surgery Cosmetic alterations (Odds Ratio, OR = 7.3), Aromatase Inhibitors (as a protective factor with OR = 0.45), V20 Gy (50 % of the prescribed dose, OR = 1.02), and V42 Gy (105 %, OR = 1.09). Factors were also converted into an adjusted V20Gy. CONCLUSIONS: The association between late reactions and skin DVH when delivering 40 Gy/15 fr was quantified, suggesting an independent role of V20 and V42. Few clinical factors heavily modulate the risk.

Curative carbon ion radiotherapy in a head and neck mucosal melanoma series: Facing the future within multidisciplinarity.

PURPOSE: To evaluate efficacy and toxicity of carbon ion radiotherapy (CIRT) in locally advanced head and neck mucosal melanoma (HNMM) patients treated at our Institute. MATERIALS AND METHODS: Between June 2013 and June 2020, 40 HNMM patients were treated with CIRT. Prescription dose was 65.6-68.8 Gy relative biological effectiveness [RBE] in 16 fractions. Twelve (30%) patients received only biopsy, 28 (70%) surgical resection before CIRT. Immunotherapy was administered before and/or after CIRT in 45% of patients, mainly for distant progression (89%). RESULTS: Median follow-up was 18 months. 2-year Local Relapse Free Survival (LRFS), Overall Survival (OS), Progression Free Survival (PFS) and Distant Metastasis Free Survival (DMFS) were 84.5%, 58.6%, 33.2% and 37.3%, respectively. At univariate analysis, LRFS was significantly better for non-recurrent status, < 2 surgeries before CIRT and treatment started < 9 months from the initial diagnosis, with no significant differences for operated versus unresected patients. After relapse, immunotherapy provided longer median OS (17 months vs 3.6, p-value<0.001). Late toxicity ≥ G3 (graded with CTCAE 5.0 scale) was reported in 10% of patients. CONCLUSION: CIRT in advanced HNMM patients is safe and locally effective. Prospective trials are warranted to assess the role of targeted/immune- systemic therapy to improve OS.

Validation of prediction models for radiation-induced late rectal bleeding: Evidence from a large pooled population of prostate cancer patients.

PURPOSE: To validate published models for the risk estimate of grade ≥ 1 (G1+), grade ≥ 2 (G2+) and grade = 3 (G3) late rectal bleeding (LRB) after radical radiotherapy for prostate cancer in a large pooled population from three prospective trials. MATERIALS AND METHODS: The external validation population included patients from Europe, and Oceanian centres enrolled between 2003 and 2014. Patients received 3DCRT or IMRT at doses between 66-80 Gy. IMRT was administered with conventional or hypofractionated schemes (2.35-2.65 Gy/fr). LRB was prospectively scored using patient-reported questionnaires (LENT/SOMA scale) with a 3-year follow-up. All Normal Tissue Complication Probability (NTCP) models published until 2021 based on the Equivalent Uniform Dose (EUD) from the rectal Dose Volume Histogram (DVH) were considered for validation. Model performance in validation was evaluated through calibration and discrimination. RESULTS: Sixteen NTCP models were tested on data from 1633 patients. G1+ LRB was scored in 465 patients (28.5%), G2+ in 255 patients (15.6%) and G3 in 112 patients (6.8%). The best performances for G2+ and G3 LRB highlighted the importance of the medium-high doses to the rectum (volume parameters n = 0.24 and n = 0.18, respectively). Good performance was seen for models of severe LRB. Moreover, a multivariate model with two clinical factors found the best calibration slope. CONCLUSION: Five published NTCP models developed on non-contemporary cohorts were able to predict a relative increase in the toxicity response in a more recent validation population. Compared to QUANTEC findings, dosimetric results pointed toward mid-high doses of rectal DVH. The external validation cohort confirmed abdominal surgery and cardiovascular diseases as risk factors.

High weekly integral dose and larger fraction size increase risk of fatigue and worsening of functional outcomes following radiotherapy for localized prostate cancer.

Introduction: We hypothesized that increasing the pelvic integral dose (ID) and a higher dose per fraction correlate with worsening fatigue and functional outcomes in localized prostate cancer (PCa) patients treated with external beam radiotherapy (EBRT). Methods: The study design was a retrospective analysis of two prospective observational cohorts, REQUITE (development, n=543) and DUE-01 (validation, n=228). Data were available for comorbidities, medication, androgen deprivation therapy, previous surgeries, smoking, age, and body mass index. The ID was calculated as the product of the mean body dose and body volume. The weekly ID accounted for differences in fractionation. The worsening (end of radiotherapy versus baseline) of European Organisation for Research and Treatment of Cancer EORTC) Quality of Life Questionnaire (QLQ)-C30 scores in physical/role/social functioning and fatigue symptom scales were evaluated, and two outcome measures were defined as worsening in ≥2 (WS2) or ≥3 (WS3) scales, respectively. The weekly ID and clinical risk factors were tested in multivariable logistic regression analysis. Results: In REQUITE, WS2 was seen in 28% and WS3 in 16% of patients. The median weekly ID was 13.1 L·Gy/week [interquartile (IQ) range 10.2-19.3]. The weekly ID, diabetes, the use of intensity-modulated radiotherapy, and the dose per fraction were significantly associated with WS2 [AUC (area under the receiver operating characteristics curve) =0.59; 95% CI 0.55-0.63] and WS3 (AUC=0.60; 95% CI 0.55-0.64). The prevalence of WS2 (15.3%) and WS3 (6.1%) was lower in DUE-01, but the median weekly ID was higher (15.8 L·Gy/week; IQ range 13.2-19.3). The model for WS2 was validated with reduced discrimination (AUC=0.52 95% CI 0.47-0.61), The AUC for WS3 was 0.58. Conclusion: Increasing the weekly ID and the dose per fraction lead to the worsening of fatigue and functional outcomes in patients with localized PCa treated with EBRT.

Patient-Factors Influencing the 2-Year Trajectory of Mental and Physical Health in Prostate Cancer Patients.

This study aimed to examine the physical and mental Quality of Life (QoL) trajectories in prostate cancer (PCa) patients participating in the Pros-IT CNR study. QoL was assessed using the Physical (PCS) and Mental Component Score (MCS) of Short-Form Health Survey upon diagnosis and two years later. Growth mixture models were applied on 1158 patients and 3 trajectories over time were identified for MCS: 75% of patients had constantly high scores, 13% had permanently low scores and 12% starting with low scores had a recovery; the predictors that differentiated the trajectories were age, comorbidities, a family history of PCa, and the bowel, urinary and sexual functional scores at diagnosis. In the physical domain, 2 trajectories were defined: 85% of patients had constantly high scores, while 15% started with low scores and had a further slight decrease. Two years after diagnosis, the psychological and physical status was moderately compromised in more than 10% of PCa patients. For mental health, the trajectory analysis suggested that following the compromised patients at diagnosis until treatment could allow identification of those more vulnerable, for which a level 2 intervention with support from a non-oncology team supervised by a clinical psychologist could be of help.

Treatment time and circadian genotype interact to influence radiotherapy side-effects. A prospective European validation study using the REQUITE cohort.

BACKGROUND: Circadian rhythm impacts broad biological processes, including response to cancer treatment. Evidence conflicts on whether treatment time affects risk of radiotherapy side-effects, likely because of differing time analyses and target tissues. We previously showed interactive effects of time and genotypes of circadian genes on late toxicity after breast radiotherapy and aimed to validate those results in a multi-centre cohort. METHODS: Clinical and genotype data from 1690 REQUITE breast cancer patients were used with erythema (acute; n=340) and breast atrophy (two years post-radiotherapy; n=514) as primary endpoints. Local datetimes per fraction were converted into solar times as predictors. Genetic chronotype markers were included in logistic regressions to identify primary endpoint predictors. FINDINGS: Significant predictors for erythema included BMI, radiation dose and PER3 genotype (OR 1.27(95%CI 1.03-1.56); P < 0.03). Effect of treatment time effect on acute toxicity was inconclusive, with no interaction between time and genotype. For late toxicity (breast atrophy), predictors included BMI, radiation dose, surgery type, treatment time and SNPs in CLOCK (OR 0.62 (95%CI 0.4-0.9); P < 0.01), PER3 (OR 0.65 (95%CI 0.44-0.97); P < 0.04) and RASD1 (OR 0.56 (95%CI 0.35-0.89); P < 0.02). There was a statistically significant interaction between time and genotypes of circadian rhythm genes (CLOCK OR 1.13 (95%CI 1.03-1.23), P < 0.01; PER3 OR 1.1 (95%CI 1.01-1.2), P < 0.04; RASD1 OR 1.15 (95%CI 1.04-1.28), P < 0.008), with peak time for toxicity determined by genotype. INTERPRETATION: Late atrophy can be mitigated by selecting optimal treatment time according to circadian genotypes (e.g. treat PER3 rs2087947C/C genotypes in mornings; T/T in afternoons). We predict triple-homozygous patients (14%) reduce chance of atrophy from 70% to 33% by treating in mornings as opposed to mid-afternoon. Future clinical trials could stratify patients treated at optimal times compared to those scheduled normally. FUNDING: EU-FP7.

Knowledge-based multi-institution plan prediction of whole breast irradiation with tangential fields.

PURPOSE: To quantify inter-institute variability of Knowledge-Based (KB) models for right breast cancer patients treated with tangential fields whole breast irradiation (WBI). MATERIALS AND METHODS: Ten institutions set KB models by using RapidPlan (Varian Inc.), following previously shared methodologies. Models were tested on 20 new patients from the same institutes, exporting DVH predictions of heart, ipsilateral lung, contralateral lung, and contralateral breast. Inter-institute variability was quantified by the inter-institute SDint of predicted DVHs/Dmean. Association between lung sparing vs PTV coverage strategy was also investigated. The transferability of models was evaluated by the overlap of each model's geometric Principal Component (PC1) when applied to the test patients of the other 9 institutes. RESULTS: The overall inter-institute variability of DVH/Dmean ipsilateral lung dose prediction, was less than 2% (20%-80% dose range) and 0.55 Gy respectively (1SD) for a 40 Gy in 15 fraction schedule; it was < 0.2 Gy for other OARs. Institute 6 showed the lowest mean dose prediction value and no overlap between PTV and ipsilateral lung. Once excluded, the predicted ipsilateral lung Dmean was correlated with median PTV D99% (R2 = 0.78). PC1 values were always within the range of applicability (90th percentile) for 7 models: for 2 models they were outside in 1/18 cases. For the model of institute 6, it failed in 7/18 cases. The impact of inter-institute variability of dose calculation was tested and found to be almost negligible. CONCLUSIONS: Results show limited inter-institute variability of plan prediction models translating in high inter-institute interchangeability, except for one of ten institutes. These results encourage future investigations in generating benchmarks for plan prediction incorporating inter-institute variability.

Personalized Dosimetry in Targeted Radiation Therapy: A Look to Methods, Tools and Critical Aspects.

Targeted radiation therapy (TRT) is a strategy increasingly adopted for the treatment of different types of cancer. The urge for optimization, as stated by the European Council Directive (2013/59/EURATOM), requires the implementation of a personalized dosimetric approach, similar to what already happens in external beam radiation therapy (EBRT). The purpose of this paper is to provide a thorough introduction to the field of personalized dosimetry in TRT, explaining its rationale in the context of optimization and describing the currently available methodologies. After listing the main therapies currently employed, the clinical workflow for the absorbed dose calculation is described, based on works of the most experienced authors in the literature and recent guidelines. Moreover, the widespread software packages for internal dosimetry are presented and critical aspects discussed. Overall, a selection of the most important and recent articles about this topic is provided.

Health-related quality of life 24 months after prostate cancer diagnosis: an update from the Pros-IT CNR prospective observational study.

BACKGROUND: This study analyzes patient health-related quality of life (QoL) 24-month after prostate cancer (PCa) diagnosis within the PROState cancer monitoring in ITaly from the National Research Council (Pros-IT CNR) study. METHODS: Pros-IT CNR is an ongoing, longitudinal and observational study, considering a convenience sample of patients enrolled at PCa diagnosis and followed at 6, 12, 24, 36, 48 and 60 months from the diagnosis. Patients were grouped according to the treatment received: nerve sparing radical prostatectomy (NSRP), non-nerve sparing radical prostatectomy (NNSRP), radiotherapy (RT), RT plus androgen deprivation (RT plus ADT) and active surveillance (AS). QoL was measured through the Italian versions of SF-12 and UCLA-PCI questionnaires at diagnosis and at 6-12 and 24-month. The minimal clinically important difference (MCID) was defined as half a standard deviation of the baseline domain. RESULTS: Overall, 1537 patients were included in the study. The decline in urinary function exceeded the MCID at each timepoint only in the NSRP and NNSRP groups (at 24 months -14.7, P<0.001 and -19.7, P<0.001, respectively). The decline in bowel function exceeded the MCID only in the RT (-9.1, P=0.02) and RT plus ADT groups at 12 months (-10.3, P=0.001); after 24 months, most patients seem to recover their bowel complaints. The decline in sexual function exceeded the MCID at each timepoint in the NNSRP, NSRP and RT plus ADT groups (at 6 months -28.7, P<0.001, -37.8, P<0.001, -20.4, P<0.001, respectively). CONCLUSIONS: Although all the treatments were relatively well-tolerated over the 24 month period following PCa diagnosis, each had a different impact on QoL.

Stomach and duodenum dose-volume constraints for locally advanced pancreatic cancer patients treated in 15 fractions in combination with chemotherapy.

Purpose: To assess dosimetry predictors of gastric and duodenal toxicities for locally advanced pancreatic cancer (LAPC) patients treated with chemo-radiotherapy in 15 fractions. Methods: Data from 204 LAPC patients treated with induction+concurrent chemotherapy and radiotherapy (44.25 Gy in 15 fractions) were available. Forty-three patients received a simultaneous integrated boost of 48-58 Gy. Gastric/duodenal Common Terminology Criteria for Adverse Events v. 5 (CTCAEv5) Grade ≥2 toxicities were analyzed. Absolute/% duodenal and stomach dose-volume histograms (DVHs) of patients with/without toxicities were compared: the most predictive DVH points were identified, and their association with toxicity was tested in univariate and multivariate logistic regressions together with near-maximum dose (D0.03) and selected clinical variables. Results: Toxicity occurred in 18 patients: 3 duodenal (ulcer and duodenitis) and 10 gastric (ulcer and stomatitis); 5/18 experienced both. At univariate analysis, V44cc (duodenum: p = 0.02, OR = 1.07; stomach: p = 0.01, OR = 1.12) and D0.03 (p = 0.07, OR = 1.19; p = 0.008, OR = 1.12) were found to be the most predictive parameters. Stomach/duodenum V44Gy and stomach D0.03 were confirmed at multivariate analysis and found to be sufficiently robust at internal, bootstrap-based validation; the results regarding duodenum D0.03 were less robust. No clinical variables or %DVH was significantly associated with toxicity. The best duodenum cutoff values were V44Gy < 9.1 cc (and D0.03 < 47.6 Gy); concerning the stomach, they were V44Gy < 2 cc and D0.03 < 45 Gy. The identified predictors showed a high negative predictive value (>94%). Conclusion: In a large cohort treated with hypofractionated radiotherapy for LAPC, the risk of duodenal/gastric toxicities was associated with duodenum/stomach DVH. Constraining duodenum V44Gy < 9.1 cc, stomach V44Gy < 2 cc, and stomach D0.03 < 45 Gy should keep the toxicity rate at approximately or below 5%. The association with duodenum D0.03 was not sufficiently robust due to the limited number of events, although results suggest that a limit of 45-46 Gy should be safe.

Modelling Radiation-Induced Salivary Dysfunction during IMRT and Chemotherapy for Nasopharyngeal Cancer Patients.

BACKGROUND: Radiation-induced xerostomia is one of the most prevalent adverse effects of head and neck cancer treatment, and it could seriously affect patients' qualities of life. It results primarily from damage to the salivary glands, but its onset and severity may also be influenced by other patient-, tumour-, and treatment-related factors. We aimed to build and validate a predictive model for acute salivary dysfunction (aSD) for locally advanced nasopharyngeal carcinoma (NPC) patients by combining clinical and dosimetric factors. METHODS: A cohort of consecutive NPC patients treated curatively with IMRT and chemotherapy at 70 Gy (2-2.12 Gy/fraction) were utilised. Parotid glands (cPG, considered as a single organ) and the oral cavity (OC) were selected as organs-at-risk. The aSD was assessed at baseline and weekly during RT, grade ≥ 2 aSD chosen as the endpoint. Dose-volume histograms were reduced to the Equivalent Uniform Dose (EUD). Dosimetric and clinical/treatment features selected via LASSO were inserted into a multivariable logistic model. Model validation was performed on two cohorts of patients with prospective aSD, and scored using the same schedule/scale: a cohort (NPC_V) of NPC patients (as in model training), and a cohort of mixed non-NPC head and neck cancer patients (HNC_V). RESULTS: The model training cohort included 132 patients. Grade ≥ 2 aSD was reported in 90 patients (68.2%). Analyses resulted in a 4-variables model, including doses of up to 98% of cPG (cPG_D98%, OR = 1.04), EUD to OC with n = 0.05 (OR = 1.11), age (OR = 1.08, 5-year interval) and smoking history (OR = 1.37, yes vs. no). Calibration was good. The NPC_V cohort included 38 patients, with aSD scored in 34 patients (89.5%); the HNC_V cohort included 93 patients, 77 with aSD (92.8%). As a general observation, the incidence of aSD was significantly different in the training and validation populations (p = 0.01), thus impairing calibration-in-the-large. At the same time, the effect size for the two dosimetric factors was confirmed. Discrimination was also satisfactory in both cohorts: AUC was 0.73, and 0.68 in NPC_V and HNC_V cohorts, respectively. CONCLUSION: cPG D98% and the high doses received by small OC volumes were found to have the most impact on grade ≥ 2 acute xerostomia, with age and smoking history acting as a dose-modifying factor. Findings on the development population were confirmed in two prospectively collected validation populations.

A Mesoscale Computational Model for Microvascular Oxygen Transfer.

We address a mathematical model for oxygen transfer in the microcirculation. The model includes blood flow and hematocrit transport coupled with the interstitial flow, oxygen transport in the blood and the tissue, including capillary-tissue exchange effects. Moreover, the model is suited to handle arbitrarily complex vascular geometries. The purpose of this study is the validation of the model with respect to classical solutions and the further demonstration of its adequacy to describe the heterogeneity of oxygenation in the tissue microenvironment. Finally, we discuss the importance of these effects in the treatment of cancer using radiotherapy.

Radiobiological Studies of Microvascular Damage through In Vitro Models: A Methodological Perspective.

Ionizing radiation (IR) is used in radiotherapy as a treatment to destroy cancer. Such treatment also affects other tissues, resulting in the so-called normal tissue complications. Endothelial cells (ECs) composing the microvasculature have essential roles in the microenvironment's homeostasis (ME). Thus, detrimental effects induced by irradiation on ECs can influence both the tumor and healthy tissue. In-vitro models can be advantageous to study these phenomena. In this systematic review, we analyzed in-vitro models of ECs subjected to IR. We highlighted the critical issues involved in the production, irradiation, and analysis of such radiobiological in-vitro models to study microvascular endothelial cells damage. For each step, we analyzed common methodologies and critical points required to obtain a reliable model. We identified the generation of a 3D environment for model production and the inclusion of heterogeneous cell populations for a reliable ME recapitulation. Additionally, we highlighted how essential information on the irradiation scheme, crucial to correlate better observed in vitro effects to the clinical scenario, are often neglected in the analyzed studies, limiting the translation of achieved results.

A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort.

Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors. Methods: The study involved REQUITE prostate cancer patients treated with external beam radiotherapy who had complete 2-year follow-up. We used five separate late toxicity endpoints: ≥grade 1 late rectal bleeding, ≥grade 2 urinary frequency, ≥grade 1 haematuria, ≥ grade 2 nocturia, ≥ grade 1 decreased urinary stream. Forty-three single nucleotide polymorphisms (SNPs) already reported in the literature to be associated with the toxicity endpoints were included in the analysis. No SNP had been studied before in the REQUITE cohort. Deep Sparse AutoEncoders (DSAE) were trained to recognize features (SNPs) identifying patients with no toxicity and tested on a different independent mixed population including patients without and with toxicity. Results: One thousand, four hundred and one patients were included, and toxicity rates were: rectal bleeding 11.7%, urinary frequency 4%, haematuria 5.5%, nocturia 7.8%, decreased urinary stream 17.1%. Twenty-four of the 43 SNPs that were associated with the toxicity endpoints were validated as identifying patients with toxicity. Twenty of the 24 SNPs were associated with the same toxicity endpoint as reported in the literature: 9 SNPs for urinary symptoms and 11 SNPs for overall toxicity. The other 4 SNPs were associated with a different endpoint. Conclusion: Deep learning algorithms can validate SNPs associated with toxicity after radiotherapy for prostate cancer. The method should be studied further to identify polygenic SNP risk signatures for radiotherapy toxicity. The signatures could then be included in integrated normal tissue complication probability models and tested for their ability to personalize radiotherapy treatment planning.

Role of IMRT/VMAT-Based Dose and Volume Parameters in Predicting 5-Year Local Control and Survival in Nasopharyngeal Cancer Patients.

Objective: This study aimed to look into the relationship between intensity-modulated-radiotherapy (IMRT)- or volumetric-modulated-arc-therapy (VMAT)-based dose-volume parameters and 5-year outcome for a consecutive series of non-metastatic nasopharyngeal cancer (NPC) patients (pts) treated in a single institution in a non-endemic area in order to identify potential prognostic factors. Materials and methods: A retrospective analysis of consecutive non-metastatic NPC pts treated curatively with IMRT or VMAT and chemotherapy (CHT) between 2004 and 2014 was conducted. One patient was in stage I (0.7%), and 24 pts (17.5%) were in stage II, 38 pts (27.7%) in stage III, 29 pts (21.2%) in stage IVA, and 45 pts (32.8%) in stage IVB. Five pts (3.6%) received radiotherapy (RT) alone. Of the remaining 132 pts (96.4%), 30 pts (21.9%) received CHT concomitant to RT, and 102 pts (74.4%) were treated with induction CHT followed by RT-CHT. IMRT was given with standard fractionation at a total dose of 70 Gy. Clinical outcomes investigated in the study were local control (LC), disease-free survival (DFS), and overall survival (OS). Kaplan-Meier (KM) analysis was performed for the outcomes considering dose and coverage parameters, staging, and RT technique. Results: Overall, 137 pts were eligible for this retrospective analysis. With a median follow-up of 70 months (range 12-143), actuarial rates at 5 years were LC 90.4, DFS 77.2, and OS 82.8%. For this preliminary study, T stage was dichotomized as T1, T2, T3 vs. T4. At 5 years, the group T1-T2-T3 reported an LC of 93%, a DFS of 79%, and an OS of 88%, whereas T4 pts reported LC, DFS, and OS, respectively, of 56, 50, and 78%. Pts with V95% > 95.5% had better LC (p = 0.006). Pts with D99% > 63.8 Gy had better LC (p = 0.034) and OS (p = 0.005). The threshold value of 43.2 cm3 of GTVT was prognostic for LC (p = 0.016). To predict the risk of local recurrence at 5 years, we constructed a nomogram which combined GTVT with D99% relative to HRPTV. Conclusions: We demonstrated the prognostic value of some dose-volume parameters, although in a retrospective series, this is potentially useful to improve planning procedure. In addition, for the first time in a non-endemic area, a threshold value of GTVT, prognostic for LC, has been confirmed.

SPOP Deregulation Improves the Radiation Response of Prostate Cancer Models by Impairing DNA Damage Repair.

Speckle-type POZ (pox virus and zinc finger protein) protein (SPOP) is the most commonly mutated gene in prostate cancer (PCa). Recent evidence reports a role of SPOP in DNA damage response (DDR), indicating a possible impact of SPOP deregulation on PCa radiosensitivity. This study aimed to define the role of SPOP deregulation (by gene mutation or knockdown) as a radiosensitizing factor in PCa preclinical models. To express WT or mutant (Y87N, K129E and F133V) SPOP, DU145 and PC-3 cells were transfected with pMCV6 vectors. Sensitivity profiles were assessed using clonogenic assay and immunofluorescent staining of γH2AX and RAD51 foci. SCID xenografts were treated with 5 Gy single dose irradiation using an image-guided small animal irradiator. siRNA and miRNA mimics were used to silence SPOP or express the SPOP negative regulator miR-145, respectively. SPOP deregulation, by either gene mutation or knockdown, consistently enhanced the radiation response of PCa models by impairing DDR, as indicated by transcriptome analysis and functionally confirmed by decreased RAD51 foci. SPOP silencing also resulted in a significant downregulation of RAD51 and CHK1 expression, consistent with the impairment of homologous recombination. Our results indicate that SPOP deregulation plays a radiosensitizing role in PCa by impairing DDR via downregulation of RAD51 and CHK1.

In silico model of the early effects of radiation therapy on the microcirculation and the surrounding tissues.

BACKGROUND: Radiation-induced organ dysfunction are frequently described by Normal Tissue Complication Probability models. The approximations of this radiobiological approach do not allow to consider the important role played by the microvasculature not only in the dose-response of the blood vessels but also of the organs where it is located. To this purpose, we presented a computational model that describes the fluid dynamics of microcirculation when the parameters of the network and the surrounding tissues are affected by radio-induced changes. MATERIALS AND METHODS: The effects of the ionizing radiation on the capillary bed are mediated by the inflammatory response. We derived from a literature search the possible morphological and functional variations of the network due to the process of the acute inflammation. Specifically, we considered vasodilation, increased membrane permeability with consequent fluid extravasation and increased wall elasticity. These perturbations to the system were included in a computational model, already able to describe the physics of the microcirculation and its exchanges with the surrounding tissues. RESULTS: Two computational descriptions were considered. In the first one, we changed a set of 4 parameters associated with the increased fluid exchange from the health scenario at the baseline to a seriously compromised scenario with the edema formation. The second study investigated the effect of a perturbation to the vessel wall elasticity. CONCLUSIONS: These simulations represent a first step towards the challenging objective of understanding and describing in a mechanistic way the effects of radiation on the vascular microenvironment.