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Bone metastases (BMs) are the most common cause of cancer-related pain and radiation therapy plays a key role in treating pain caused by it. The half-body irradiation (HBI) is a modality that can be used to treat patients with multiple painful BMs. In the modern era, concerns about toxicity and the availability of new agents requiring robust bone marrow function have limited the use of HBI in advanced cancer. Concerns about HBI toxicity stem from outdated techniques; modern methods like volumetric modulated arc therapy (VMAT) and helical tomotherapy now allow safer irradiation of complex target volumes. We conducted a systematic review to present updated information about HBI efficacy and potential toxicity. Pain relief usually occurs very quickly 2–3 weeks after HBI. The overall pain response rate was high in all the series, accounting for a median of 84 % (75.6–89 %), with a median of 36 % complete pain response. The toxicity is usually limited to G1/G2, with very rare G3 cases. More than 50 % of patients can reduce analgesic intake after HBI. Additionally, with modern radiotherapy techniques, quality of life is improved in most patients. HBI is a safe and effective method and should once again be reconsidered for more frequent use.

Purpose or Objective—The aim of the study is to evaluate the efficacy and safety of SBRT on detectable prostate bed recurrence in RT-naïve prostate cancer patients. Materials and methods: Eighty-six patients who underwent SBRT for macroscopic bed recurrence after prostatectomy were retrospectively included. Patients were treated based on mpMRI or choline/PSMA PET. Results: The median time to biochemical relapse (BCR) after RP was 46 months, with a median PSA at restaging of 1.04 ng/mL. Forty-six patients were staged with mpMRI and choline/PSMA PET, while ten and thirty were treated based on PET and MRI only, respectively. Only one late G ≥ 2 GI toxicity was observed. With a median BCR follow-up of 14 months, twenty-nine patients experienced a BCR with a median PSA at recurrence of 1.66 ng/mL and a median survival free from the event of 40.1 months. The median time to BCR was 17.9 months. Twenty-seven patients had clinical relapse (CR), with a median CR follow-up of 16.27 months and a median time to CR of 23.0 months. Biochemical recurrence-free survival at one and two years was 88% and 66%, respectively, while clinical recurrence-free survival at one and two years was 92% and 82%, respectively. Regarding local relapses, seven were in the field of treatment, while eight of them were outside the field of treatment. Conclusions: Data showed that SBRT targeting only the macroscopic bed recurrence instead of the whole prostate bed is safe and effective. Additional data and longer follow-ups will provide a clearer indication of the appropriate treatment and staging methodology for these patients.

In this technical development report, we present the strategic placement of fiducial markers within the prostate under the guidance of computed tomography (CT) and electromagnetic navigation (EMN) for the delivery of ultra-hypofractionated cyberknife (CK) therapy in a patient with localized prostate cancer (PCa) who had previously undergone chemo-radiotherapy for rectal cancer and subsequent abdominoperineal resection due to local recurrence. The patient was positioned in a prone position with a pillow under the pelvis to facilitate access, and an electromagnetic fiducial marker was placed on the patient’s skin to establish a stable position. CT scans were performed to plan the procedure, mark virtual points, and simulate the needle trajectory using the navigation system. Local anesthesia was administered, and a 21G needle was used to place the fiducial markers according to the navigation system information. A confirmatory CT scan was obtained to ensure proper positioning. The implantation procedure was safe, without any acute side effects such as pain, hematuria, dysuria, or hematospermia. Our report highlights the ability to use EMN systems to virtually navigate within a pre-acquired imaging dataset in the interventional room, allowing for non-conventional approaches and potentially revolutionizing fiducial marker positioning, offering new perspectives for PCa treatment in selected cases.

Radiotherapy in expiration breath-hold (EBH) has the potential to reduce treatment volumes of abdominal targets compared to an internal target volume concept in free-breathing. The reproducibility of EBH and required safety margins were investigated to quantify this volumetric benefit. Pre- and post-treatment diaphragm position difference and the positioning variability were determined on computed tomography. Systematic and random errors for EBH position reproducibility and positioning variability were calculated, resulting in margins of 7 to 12 mm depending on the prescription isodose and fractionation. A reduced volume was shown for EBH for lesions with superior-inferior breathing motion above 4 to 8 mm.

Abstract Background Contouring of anatomical regions is a crucial step in the medical workflow and is both time-consuming and prone to intra- and inter-observer variability. This study compares different strategies for automatic segmentation of the prostate in T2-weighted MRIs. Methods This study included 100 patients diagnosed with prostate adenocarcinoma who had undergone multi-parametric MRI and prostatectomy. From the T2-weighted MR images, ground truth segmentation masks were established by consensus from two expert radiologists. The prostate was then automatically contoured with six different methods: (1) a multi-atlas algorithm, (2) a proprietary algorithm in the Syngo.Via medical imaging software, and four deep learning models: (3) a V-net trained from scratch, (4) a pre-trained 2D U-net, (5) a GAN extension of the 2D U-net, and (6) a segmentation-adapted EfficientDet architecture. The resulting segmentations were compared and scored against the ground truth masks with one 70/30 and one 50/50 train/test data split. We also analyzed the association between segmentation performance and clinical variables. Results The best performing method was the adapted EfficientDet (model 6), achieving a mean Dice coefficient of 0.914, a mean absolute volume difference of 5.9%, a mean surface distance (MSD) of 1.93 pixels, and a mean 95th percentile Hausdorff distance of 3.77 pixels. The deep learning models were less prone to serious errors (0.854 minimum Dice and 4.02 maximum MSD), and no significant relationship was found between segmentation performance and clinical variables. Conclusions Deep learning-based segmentation techniques can consistently achieve Dice coefficients of 0.9 or above with as few as 50 training patients, regardless of architectural archetype. The atlas-based and Syngo.via methods found in commercial clinical software performed significantly worse (0.855 $$-$$ - 0.887 Dice).

Osteoradionecrosis (ORN) is a serious long-term complication of head and neck radiotherapy (RT), which is often triggered by dental extractions. It results from avascular aseptic necrosis due to irradiated bone damage. ORN is challenging to treat and can lead to severe complications. Furthermore, ORN causes pain and distress, significantly reducing the patient’s quality of life. There is currently no established preventive strategy. This narrative review aims to provide an update for the clinicians on the risk of ORN associated with oral surgery in head and neck RT patients, with a focus on the timing suitable for the oral surgery and possible ORN preventive treatments. An electronic search of articles was performed by consulting the PubMed database. Intervention and observational studies were included. A multidisciplinary approach to the patient is highly recommended to mitigate the risk of RT complications. A dental visit before commencing RT is highly advised to minimize the need for future dental extractions after irradiation, and thus the risk of ORN. Post-RT preventive strategies, in case of dento-alveolar surgery, have been proposed and include antibiotics, hyperbaric oxygen (HBO), and the combined use of pentoxifylline and tocopherol (“PENTO protocol”), but currently there is a lack of established standards of care. Some limitations in the use of HBO involve the low availability of HBO facilities, its high costs, and specific clinical contraindications; the PENTO protocol, on the other hand, although promising, lacks clinical trials to support its efficacy. Due to the enduring risk of ORN, removable prostheses are preferable to dental implants in these patients, as there is no consensus on the appropriate timing for their safe placement. Overall, established standards of care and high-quality evidence are lacking concerning both preventive strategies for ORN as well as the timing of the dental surgery. There is an urgent need to improve research for more efficacious clinical decision making.

Abstract Objective Deploying an automatic segmentation model in practice should require rigorous quality assurance (QA) and continuous monitoring of the model’s use and performance, particularly in high-stakes scenarios such as healthcare. Currently, however, tools to assist with QA for such models are not available to AI researchers. In this work, we build a deep learning model that estimates the quality of automatically generated contours. Methods The model was trained to predict the segmentation quality by outputting an estimate of the Dice similarity coefficient given an image contour pair as input. Our dataset contained 60 axial T2-weighted MRI images of prostates with ground truth segmentations along with 80 automatically generated segmentation masks. The model we used was a 3D version of the EfficientDet architecture with a custom regression head. For validation, we used a fivefold cross-validation. To counteract the limitation of the small dataset, we used an extensive data augmentation scheme capable of producing virtually infinite training samples from a single ground truth label mask. In addition, we compared the results against a baseline model that only uses clinical variables for its predictions. Results Our model achieved a mean absolute error of 0.020 ± 0.026 (2.2% mean percentage error) in estimating the Dice score, with a rank correlation of 0.42. Furthermore, the model managed to correctly identify incorrect segmentations (defined in terms of acceptable/unacceptable) 99.6% of the time. Conclusion We believe that the trained model can be used alongside automatic segmentation tools to ensure quality and thus allow intervention to prevent undesired segmentation behavior.

Abstract Background Prostate cancer (PCa) is the second most common cancer in men worldwide. The standard non-surgical approach for localized PCa is radiotherapy (RT), but one of the limitations of high-dose RT is the potential increase in gastrointestinal and genitourinary toxicities. We present the protocol of the Microstyle study, a multicentre randomized two-arm crossover clinical trial. The primary outcome will be assessed at the end of 6-month intervention, by measuring the change in adherence to a healthy lifestyle score. The hypothesis is that modifying lifestyle we change microbiome and improve quality of life and decrease side effects of RT. Methods Study participants will be recruited among men undergoing RT in two Italian centers (Milan and Naples). We foresee to randomize 300 patients in two intervention arms: Intervention Group (IG) and Control Group (CG). Participants allocated to the IG will meet a dietitian and a physiotherapist before RT to receive personalized diet and exercise recommendations, according to their health status, to improve overall lifestyle and reduce side effects (bowel and/or urinary problems). Dietitian and physiotherapist will work together to set individualized goals to reduce or eliminate side effects and pain according to their health status. All participants (IG) will be given a pedometer device (steps counter) in order to monitor and to spur participants to increase physical activity and reduce sedentary behavior. Participants included in the CG will receive baseline general advice and materials available for patients undergoing RT. According to the cross-over design, the CG will cross to the intervention approach after 6-month, to actively enhance compliance towards suggested lifestyle recommendations for all patients. Discussion This trial is innovative in its design because we propose a lifestyle intervention during RT, that includes both dietary and physical activity counselling, as well as monitoring changes in microbiome and serum biomarkers. The promotion of healthy behaviour will be initiated before initiation of standard care, to achieve long lasting effects, controlling side effects, coping with feelings of anxiety and depression and improve efficacy of RT. Trial registration ClincalTrial.gov registration number: NCT05155618 . Retrospectively registered on December 13, 2021. The first patient was enrolled on October 22, 2021.

(1) Background: In the RADIOSA phase II randomized clinical trial (NCT03940235), the biology task entails the identification of predictive and prognostic biomarkers in the context of oligorecurrent, castration-sensitive prostate cancer in order to distinguish polymetastatic from oligometastatic disease. This may lay the groundwork for personalized treatments for those patients who could really benefit from metastasis-directed therapies. (2) Methods: Oligorecurrent PCa pts with three or fewer bone or lymph nodal localizations were randomized 1:1 to receive SBRT alone (arm A) or SBRT + 6 months of ADT (arm B). Common serum-derived biomarkers were collected at baseline, and at 3 months after RT. The prognostic nutritional index, an immune and nutrition-based prognostic score, and the controlling nutritional status (CONUT) score, a scoring system for evaluating patient’s nutritional status, were calculated in accordance with the body of available literature. As inflammatory indicators, neutrophil–lymphocyte ratio (NLR) and the NLR–albumin ratio (NLRAR) were assessed. Changes in these parameters between baseline and the 3-month timepoint were evaluated both in absolute and relative values. Changes in these parameters between baseline and the 3-month timepoint were evaluated. Significant differences in the trend of these parameters were assessed using the non-parametric Wilcoxon rank-sum test. A network analysis to analyze the relationships between different features stratifying patients according to the arm of study and site of metastases was performed. (3) Results: The current analysis comprised 88 patients (45 arm A, SBRT only, and 43 arm B, SBRT + ADT). When patients were stratified by ADT administration, cholesterol values showed an increasing trend in the group receiving ADT (p = 0.005) which was no longer significant at 1 year. When patients were stratified by site of metastases (52 lymph nodal, 29 bone localizations), the value of NLR was found to be increased in patients with bone localizations (p < 0.05). In addition, the network analysis showed that BMI and NRI are strongly and directly linked for patients at baseline and that this correlation is no longer found at three months. Finally, when patients were divided according to time from surgery to oligorecurrence (enrollment) the patients with a longer time (>6.7 years) showed an increase in CONUT score from baseline. All the other nutritional and inflammatory scores or parameters investigated in the present analysis showed no statistically significant differences at baseline, three months, 1 year, and in absolute change. (4) Conclusions: The nutritional and inflammatory parameters do not seem to represent valuable candidates for possible use in clinical decision making in our cohort of patients and a reliable biological characterization of the oligometastatic state in prostate cancer still seems far from being achieved. Ongoing molecular analysis will show if there is a role of mutational landscape in the definition of the oligometastatic state.

When researchers are faced with building machine learning (ML) radiomic models, the first choice they have to make is what model to use. Naturally, the goal is to use the model with the best performance. But what is the best model? It is well known in ML that modern techniques such as gradient boosting and deep learning have better capacity than traditional models to solve complex problems in high dimensions. Despite this, most radiomics researchers still do not focus on these models in their research. As access to high-quality and large data sets increase, these high-capacity ML models may become even more relevant. In this article, we use a large dataset of 949 prostate cancer patients to compare the performance of a few of the most promising ML models for tabular data: gradient-boosted decision trees (GBDTs), multilayer perceptions, convolutional neural networks, and transformers. To this end, we predict nine different prostate cancer pathology outcomes of clinical interest. Our goal is to give a rough overview of how these models compare against one another in a typical radiomics setting. We also investigate if multitask learning improves the performance of these models when multiple targets are available. Our results suggest that GBDTs perform well across all targets, and that multitask learning does not provide a consistent improvement.

Abstract Background Radio-chemotherapy with CDDP is the standard for H&N squamous cell cancer. CDDP 100 mg/m2/q3 is the standard; alternative schedules are used to reduce toxicity, mostly 40 mg/m2/q1. Methods Patients were treated from 1/2010 to 1/2017 in two Radiation Oncology Centres. Propensity score analysis (PS) was retrospectively used to compare these two schedules. Results Patients analyzed were 166. Most (114/166) had 1w-CDDP while 52 had 3w-CDDP. In the 3w-CDDP group, patients were younger, with better performance status, smaller disease extent and a more common nodal involvement than in the 1w-CDDP. Acute toxicity was similar in the groups. Treatment compliance was lower in the w-CCDP. Overall survival before PS was better for female, for oropharyngeal disease and for 3w-CDDP group. After PS, survival was not related to the CDDP schedule. Conclusions 3w-CDDP remains the standard for fit patients, weekly schedule could be safely used in selected patients.

The aim is to evaluate the feasibility of ultra-hypofractionated (UH) SBRT with CyberKnife® (CK) radiosurgery (Accuray Inc., Sunnyvale, California, USA) for localized prostate cancer (PCa) with a concomitant focal boost to the dominant intraprostatic lesion (DIL). Patients with intermediate/high-risk PCa, with at least one visible DIL on multi-parametric MRI, were included. For each, two CK-SBRT in silico plans were calculated using 95% and 85% isodose lines (CK-95%, CK-85%) and compared with the UH-DWA plan delivered with VERO®. All plans simulated a SIB prescription of 40 Gy to PTV-DIL and 36.25 Gy to the whole prostate (PTV-prostate) in five fractions every other day. Fifteen patients were considered. All plans reached the primary planning goal (D95% > 95%) and compliance with organs at risk (OARs) constraints. DVH metrics median values increased (p < 0.05) from UH-DWA to CK-85%. The conformity index of PTV-DIL was 1.00 for all techniques, while for PTV-prostate was 0.978, 0.984, and 0.991 for UH-DWA, CK-95%, and CK-85%, respectively. The CK-85% plans were able to reach a maximum dose of 47 Gy to the DIL while respecting OARs constraints. CK-SBRT plus a focal boost to the DIL for localized PCa appears to be feasible. These encouraging dosimetric results are to be confirmed in upcoming clinical trials such as the phase-II “PRO-SPEED” IEO trial.

Context: The optimal management of oligometastatic prostate cancer (PCa) is still debated. Objective: The purpose of the present systematic review and meta-analysis is to collect the available evidence to date to better define the role of stereotactic body radiotherapy (SBRT) in selected patients with oligorecurrent PCa. Evidence acquisition: Study methodology complied with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). All prospective studies including PCa patients with nodal and/or bone oligometastases (one to five lesions) were considered eligible. Heterogeneity between study-specific estimates was tested using chi-square statistics and measured with the I2 index. A pooled estimate was obtained by fitting both fixed-effect and DerSimonian and Laird random-effect model. Evidence synthesis: Overall, six works (two randomized and the remainder observational) published between 2013 and 2020 were considered eligible. Globally, data from 445 patients were incorporated, of whom 396 were treated with SBRT (329 in observational studies and the remaining 67 in randomized ones). Regarding local progression-free survival (PFS), five studies reported values close to 100%, while one reported a value of 80% in the observation arm. The benefit in terms of biochemical PFS brought by SBRT was evident in all considered studies. Such a difference in cumulative probabilities between the intervention arm and the comparator arm is maintained even 24 mo after the baseline. All studies but one considered toxicity among the endpoints of interest. Most events were classified as either G1 or G2, and the only G ≥ 3 adverse event was reported in one trial. Conclusions: SBRT is highly cost effective, safe, and with an almost inexistent toxicity risk that makes it the perfect candidate for the optimal management of PCa oligometastatic patients. However, more solid data and a higher level of evidence are needed to affirm its role in the management of these patients. Patient summary: In this work, we reviewed available evidence on the use of stereotactic body radiotherapy in treating oligometastatic prostate cancer patients. We found good evidence that radiotherapy brings important benefits in overall treatment efficacy without major side effects.

We conducted a systematic review and meta-analysis to investigate the role of alcohol consumption with the prognosis of prostate cancer (PCa). Published reports were gathered on 15 October 2022, from PUBMED/MEDLINE and EMBASE. We found 19 independent eligible studies on the association between consumption of alcoholic beverages and the risk of fatal PCa (n = 5), PCa mortality (n = 5) in healthy subjects, and PCa patients’ survival (n = 7) or surrogates thereof (n = 2). We used random effects meta-analysis to obtain a summary risk estimate (SRE) and 95% confidence intervals (95%CI) for incidence of fatal PCa and PCa mortality. The meta-analysis revealed no association between alcohol consumption and fatal prostate cancer incidence risk in healthy subjects with an indication for publication bias, but omitting the study that mainly increased the between-study heterogeneity, the SRE becomes significant (SRE 1.33, 95%CI 1.12–1.58), and the heterogeneity disappeared (I2 = 0%) with no indication of publication bias. No association of alcohol consumption was found with mortality risk in PCa patients (SRE 0.97, 95%CI 0.92–1.03) and PCa mortality risk in healthy subjects (SRE 1.03, 95%CI 0.82–1.30). In conclusion, this study suggests that there is some evidence of an association between high alcohol consumption and an increased risk of incidence of fatal prostate cancer in healthy subjects. Given the inconsistencies this result warrants further confirmation.

PurposeThis study represents a descriptive analysis of preliminary results of a Phase II trial on a novel mixed beam radiotherapy (RT) approach, consisting of carbon ions RT (CIRT) followed by intensity-modulated photon RT, in combination with hormonal therapy, for high-risk prostate cancer (HR PCa) with a special focus on acute toxicity.MethodsPrimary endpoint was the evaluation of safety in terms of acute toxicity. Secondary endpoints were early and long-term tolerability of treatment, quality of life (QoL), and efficacy. Data on acute and late toxicities were collected according to RTOG/EORTC. QoL of enrolled patients was assessed by IPSS, EORTC QLQ-C30, EORTC QLQ-PR25, and sexual activity by IIEF-5.ResultsTwenty-six patients were enrolled in the study, but only 15 completed so far the RT course and were included. Immediately after CIRT, no patients experienced GI/GU toxicity. At 1 and 3 months from the whole course RT completion, no GI/GU toxicities greater than grade 2 were observed. QoL scores were overall satisfactory.ConclusionsThe feasibility of the proposed mixed treatment schedule was assessed, and an excellent acute toxicity profile was recorded. Such findings instil confidence in the continuation of this mixed approach, with evaluation of long-term tolerability and efficacy.

Background and PurposeMachine learning (ML) is emerging as a feasible approach to optimize patients’ care path in Radiation Oncology. Applications include autosegmentation, treatment planning optimization, and prediction of oncological and toxicity outcomes. The purpose of this clinically oriented systematic review is to illustrate the potential and limitations of the most commonly used ML models in solving everyday clinical issues in head and neck cancer (HNC) radiotherapy (RT).Materials and MethodsElectronic databases were screened up to May 2021. Studies dealing with ML and radiomics were considered eligible. The quality of the included studies was rated by an adapted version of the qualitative checklist originally developed by Luo et al. All statistical analyses were performed using R version 3.6.1.ResultsForty-eight studies (21 on autosegmentation, four on treatment planning, 12 on oncological outcome prediction, 10 on toxicity prediction, and one on determinants of postoperative RT) were included in the analysis. The most common imaging modality was computed tomography (CT) (40%) followed by magnetic resonance (MR) (10%). Quantitative image features were considered in nine studies (19%). No significant differences were identified in global and methodological scores when works were stratified per their task (i.e., autosegmentation).Discussion and ConclusionThe range of possible applications of ML in the field of HN Radiation Oncology is wide, albeit this area of research is relatively young. Overall, if not safe yet, ML is most probably a bet worth making.

Rectum and bladder volumes play an important role in the dose distribution reproducibility in prostate cancer adenocarcinoma (PCa) radiotherapy, especially for particle therapy, where density variation can strongly affect the dose distribution. We investigated the reliability and reproducibility of our image-guided radiotherapy (IGRT) and treatment planning protocol for carbon ion radiotherapy (CIRT) within the phase II mixed beam study (AIRC IG 14300) for the treatment of high-risk PCa. In order to calculate the daily dose distribution, a set of synthetic computed tomography (sCT) images was generated from the cone beam computed tomography (CBCT) images acquired in each treatment session. Planning target volume (PTV) together with rectum and bladder volume variation was evaluated with sCT dose-volume histogram (DVH) metric deviations from the planning values. The correlations between the bladder and rectum volumes, and the corresponding DVH metrics, were also assessed. No significant difference in the bladder, rectum, and PTV median volumes between the planning computed tomography (pCT) and the sCT was found. In addition, no significant difference was assessed when comparing the average DVHs and median DVH metrics between pCT and sCT. Dose deviations determined by bladder and rectum filling variations demonstrated that dose distributions were reproducible in terms of both target coverage and organs at risk (OARs) sparing.

Although radiation therapy (RT) provides several therapeutic advantages in terms of cancer control and quality of life, it continues to be a poorly understood field by most students and health workers. Theoretical lessons are not sufficient, while practical exercitations are time-consuming, both in terms of man- and machine-hours. Furthermore, RT candidates often have several prejudices that may affect their treatment choices, favoring the more well-known surgical or chemotherapy approaches or resulting in a high level of anxiety during treatment. Moreover, the misperception of low treatment control and its related side effects could worsen the patients’ psychological distress, already brought by a cancer diagnosis. Augmented reality (AR) and virtual reality (VR) could be a valid instrument for promoting the awareness of radiation oncology as a discipline with its own identity and respect in the scientific community. The aim of the present work is to provide a glance at the recent developments in AR/VR to support students’ education, personnel training and patients’ empowerment in this clinical setting. The main findings of our work show that such technologies have already become a reality in many institutions worldwide and it has been shown to be an effective strategy for raising educational standards, improving health workers’ skills and promoting patients’ well-being and compliance. These results seem to promote the further implementation of AR/VR technologies and their development as a driving force of a much-hoped-for revolution in the way patients are treated and radiation oncology is taught.

In this paper, we aim to evaluate the entity of inter-fraction organ motion and deformation in stereotactic body radiotherapy (SBRT) treatments for nodal oligometastatic prostate cancer (PCa). Thirty-three patients with lymph nodes showing oligometastatic PCa treated with SBRT were included. Organs at risk (OARs) were delineated using both simulation computer tomography (s-CT) and daily cone beam CTs (CBCTs) using the Raystation planning system. For each OAR, the union volume (UV) between all the CBCTs and s-CT was computed. An expanded volume (EV) of the s-CT OARs was applied using six different margins (3, 5, 8, 10, 15, and 20 mm). A percentage volume (V%) was computed to assess the intersection between each EV and UV. The OAR deformation and motion were further evaluated using the dice similarity coefficient (DSC) and mean distance to agreement (Mean_DA). The percentage maximum dose variations for all the OARs were estimated. A recalculation with higher dose prescriptions was performed by prescribing 36 Gy/3 fx, as well as 45 Gy/3 fx. The cauda showed the highest matching (DSC = 0.72; Mean_DA = 0.14 cm), and the colon showed the lowest one (DSC = 0.37; Mean_DA = 0.44 cm). The minimum margin, which ensured a V% > 95%, was 3 mm (97.5%) for the cauda and 15 mm (96.6%) for the colon. All the OARs reached the compliance of the constraints in each session. Regarding 36 Gy-plans, the ileum punctual compliance Dmax failed in 58.8% of patients, and it failed in 70.6% of the patients for the ileum, 7.14% for the colon, and 12.5% for the bladder in the case of 45 Gy-plans. This study is an ancillary study of the RADIOSA clinical trial (AIRC IG-22159) and can be used as a benchmark for dose escalation.

Radiotherapy represents a highly targeted and efficient treatment choice in many cancer types, both with curative and palliative intents. Nevertheless, radioresistance, consisting in the adaptive response of the tumor to radiation-induced damage, represents a major clinical problem. A growing body of the literature suggests that mechanisms related to mitochondrial changes and metabolic remodeling might play a major role in radioresistance development. In this work, the main contributors to the acquired cellular radioresistance and their relation with mitochondrial changes in terms of reactive oxygen species, hypoxia, and epigenetic alterations have been discussed. We focused on recent findings pointing to a major role of mitochondria in response to radiotherapy, along with their implication in the mechanisms underlying radioresistance and radiosensitivity, and briefly summarized some of the recently proposed mitochondria-targeting strategies to overcome the radioresistant phenotype in cancer.

Various definitions are currently in use to describe high-risk prostate cancer. This variety in definitions is important for patient counseling, since predicted outcomes depend on which classification is applied to identify patient’s prostate cancer risk category. Historically, strategies for the treatment of localized high-risk prostate cancer comprise local approaches such as surgery and radiotherapy, as well as systemic approaches such as hormonal therapy. Nevertheless, since high-risk prostate cancer patients remain the group with higher-risk of treatment failure and mortality rates, nowadays, novel treatment strategies, comprising hypofractionated-radiotherapy, second-generation antiandrogens, and hadrontherapy, are being explored in order to improve their long-term oncological outcomes. This narrative review aims to report the current management of high-risk prostate cancer and to explore the future perspectives in this clinical setting.

Abstract Background Prostate cancer (PCa) is the second most common cancer among men. New imaging-modalities have increased the diagnosed patients with limited number of metastasis after primary curative therapy, introducing so-called oligometastatic state. Stereotactic body radiotherapy (SBRT) is emerging as a low-toxicity treatment to erase PCa localizations and postpone androgen deprivation therapy (ADT). A deeper understanding of the predictive role of biomarkers is desirable for a targeted treatment selection and surveillance programs. The aims of the RADIOSA trial are: 1.Compare SBRT +/− ADT for oligorecurrent-castration-sensitive PCa (OCS-PCa) in terms of efficacy, toxicity and Quality of Life (QoL).2.Develop biology/imaging based prognostic tool that allows identifying OCS-PCa subclasses. Methods This is a randomized phase II clinical trial, recruiting 160 OCS-PCa in 3 years, with progression-free survival (PFS) as primary endpoint. Three tasks will be developed: 1.Randomized clinical study (3 years for accrual and 2 years for follow-up and data analysis);2.Imaging study, including imaging registration and METastasis Reporting and Data System (MET-RADS) criteria;3.Pre-clinical study, development of a biobank of blood samples for the analysis of neutrophil-to-lymphocyte ratio and preparatory for a subsequent miRNA profiling. We aim to determine which arm is justified for testing in a subsequent Phase III trial. A decision-tree algorithm, based on prognosis, biological phenotype and imaging profile, will be developed. Discussion Recruiting will start in July 2019. SBRT will allow obtaining excellent PFS, local control, QoL and low toxicity. In SBRT arm, ADT deferral will allow for a drug-holiday, delaying the detrimental impact on QoL. A sufficient number of blood samples will be collected to perform biological patient profiling. A stratification tool will be established with an analysis of morphological and functional imaging, based on the use of MET-RADS criteria. So, in conclusion, RADIOSA aims to define the optimal management of bone/nodal PCa relapses in a SBRT regimen. This study will increase our knowledge on low-burden metastatic PCa in the era of high precision and high technology personalized medicine, offering highly effective therapy in terms of clinical outcome and cost-effectiveness. Trial registration The RADIOSA study was prospectively registered at clinicaltrials.gov (NCT03940235, May 2019).

In order to limit radiotherapy (RT)-related side effects, effective toxicity prediction and assessment schemes are essential. In recent years, the growing interest toward artificial intelligence and machine learning (ML) within the science community has led to the implementation of innovative tools in RT. Several researchers have demonstrated the high performance of ML-based models in predicting toxicity, but the application of these approaches in clinics is still lagging, partly due to their low interpretability. Therefore, an overview of contemporary research is needed in order to familiarize practitioners with common methods and strategies. Here, we present a review of ML-based models for predicting and classifying RT-induced complications from both a methodological and a clinical standpoint, focusing on the type of features considered, the ML methods used, and the main results achieved. Our work overviews published research in multiple cancer sites, including brain, breast, esophagus, gynecological, head and neck, liver, lung, and prostate cancers. The aim is to define the current state of the art and main achievements within the field for both researchers and clinicians.

The markers of the tumor microenvironment (TME) are promising prognostic and predictive factors in oral squamous cell carcinoma (OSCC). The current study aims to analyze the immunohistochemical expression of programmed cell death-ligand 1 (PD-L1) and interleukin-33 (IL-33) in a cohort of 95 chemonaïve OSCCs. PD-L1 and IL-33 were assessed separately in tumor cells (TCs) and tumor-infiltrating lymphocytes (TILs). High PD-L1 expression in TILs was associated with better overall survival (OS) in univariate analysis. Tumors localized in the floor of the oral cavity and tongue tended to have a lower percentage of PD-L1-positive TCs when compared to other locations. PD-L1 expression on TCs had no prognostic significance when the whole cohort was analyzed. However, along with the T descriptor (TNM 8th), it was included in the multivariable model predicting death in carcinomas of the floor of the oral cavity and tongue (HR = 2.51, 95% CI = 1.97–5.28). In other locations, only nodal status was identified as an independent prognostic factor in multivariate analysis (HR = 0.24, 95% CI = 0.08–0.70). Expression of IL-33 had no impact on survival, but it was differently expressed in various locations. In conclusion, the prognostic significance of PD-L1 in oral cancer depends on the tumor site and type of cell expressing immune checkpoint receptor (TCs vs. TILs).

Dental implants are, nowadays, established surgical devices for the restoration of lost teeth. Considered as an alternative for traditional prosthetic appliances, dental implants surpass them in reliability and patient feedback. Local drug delivery around the implants promotes osseointegration and reduces peri-implantitis. However, there are currently no methods of a multiple, precise topical administration of drugs to the implant area. Engineering coatings on the implants, drug application on carriers during implantation, or gingival pockets do not meet all requirements of dental surgeons. Therefore, there is a need to create porous implants and other medical devices that will allow a multiple drug delivery at a controlled dose and release profile without traumatic treatment. Due to the growing demand for the use of biologically active agents to support dental implant treatment at its various stages (implant placement, long-term use of dental superstructures, treatment of the peri-implant conditions) and due to the proven effectiveness of the topical application of pharmacological biologically active agents to the implant area, the authors would like to present a review and show the methods and devices that can be used by clinicians for local drug administration to facilitate dental implant treatment. Our review concludes that there is a need for research in the field of inventions such as new medical devices or implants with gradient solid–porous structures. These devices, in the future, will enable to perform repeatable, controllable, atraumatic, and repeatable injections of active factors that may affect the improvement of osteointegration and the longer survival of implants, as well as the treatment of peri-implantitis.

Abstract The risk of radiation-induced toxicity in patients treated for head and neck (HN) cancer with radiation therapy (RT) is traditionally estimated by condensing the 3D dose distribution into a monodimensional cumulative dose-volume histogram which disregards information on dose localization. We hypothesized that a voxel-based approach would identify correlations between radiation-induced morbidity and local dose release, thus providing a new insight into spatial signature of radiation sensitivity in composite regions like the HN district. This methodology was applied to a cohort of HN cancer patients treated with RT at risk of radiation-induced acute dysphagia (RIAD). We implemented an inter-patient elastic image registration framework that proved robust enough to match even the most elusive HN structures and to provide accurate dose warping. A voxel-based statistical analysis was then performed to test regional dosimetric differences between patients with and without RIAD. We identified a significantly higher dose delivered to RIAD patients in two voxel clusters in correspondence of the cricopharyngeus muscle and cervical esophagus. Our study goes beyond the well-established organ-based philosophy exploring the relationship between radiation-induced morbidity and local dose differences in the HN region. This approach is generally applicable to different HN toxicity endpoints and is not specific to RIAD.

We aimed to describe the relationships between the relative fat fraction (%FF), muscle-normalized diffusion-weighted (DW) image signal intensity and water apparent diffusion coefficient (ADC), sex and age for normal bone marrow, in the normal population. Our retrospective cohort consisted of 100 asymptomatic individuals, equally divided by sex and 10-year age groups, who underwent whole-body MRI at 1.5 T for early cancer detection. Semi-automated segmentation of global bone marrow volume was performed using the DW images and the resulting segmentation masks were projected onto the ADC and %FF maps for extraction of parameter values. Differences in the parameter values between sexes at age ranges were assessed using the Mann–Whitney and Kruskal–Wallis tests. The Spearman correlation coefficient r was used to assess the relationship of each imaging parameter with age, and of %FF with ADC and normalized DW signal intensity values. The average %FF of normal bone marrow was 65.6 ± 7.2%, while nSIb50, nSIb900 and ADC were 1.7 ± 0.5, 3.2 ± 0.9 and 422 ± 67 μm2/s, respectively. The bone marrow %FF values increased with age in both sexes (r = 0.63 and r = 0.64, respectively, p < 0.001). Values of nSIb50 and nSIb900 were higher in younger women compared to men of the same age groups (p < 0.017), but this difference decreased with age. In our cohort of asymptomatic individuals, the values of bone marrow relative %FF, normalized DW image signal intensity and ADC indicate higher cellularity in premenopausal women, with increasing bone marrow fat with aging in both sexes.

Using semi-automated software simplifies quantitative analysis of the visible burden of disease on whole-body MRI diffusion-weighted images. To establish the intra- and inter-observer reproducibility of apparent diffusion coefficient (ADC) measures, we retrospectively analyzed data from 20 patients with bone metastases from breast (BCa; n = 10; aged 62.3 ± 14.8) or prostate cancer (PCa; n = 10; aged 67.4 ± 9.0) who had undergone examinations at two timepoints, before and after hormone-therapy. Four independent observers processed all images twice, first segmenting the entire skeleton on diffusion-weighted images, and then isolating bone metastases via ADC histogram thresholding (ADC: 650–1400 µm2/s). Dice Similarity, Bland-Altman method, and Intraclass Correlation Coefficient were used to assess reproducibility. Inter-observer Dice similarity was moderate (0.71) for women with BCa and poor (0.40) for men with PCa. Nonetheless, the limits of agreement of the mean ADC were just ±6% for women with BCa and ±10% for men with PCa (mean ADCs: 941 and 999 µm2/s, respectively). Inter-observer Intraclass Correlation Coefficients of the ADC histogram parameters were consistently greater in women with BCa than in men with PCa. While scope remains for improving consistency of the volume segmented, the observer-dependent variability measured in this study was appropriate to distinguish the clinically meaningful changes of ADC observed in patients responding to therapy, as changes of at least 25% are of interest.

Oral squamous cell carcinoma (OSCC) accounts for 95% of the lesions in the oral cavity. Despite development in OSCC management, the outcome is still unsatisfactory. Identification of new therapies in OSCC is urgently needed. One objective of such treatment may be a signaling pathway of phosphatidylinositol 3-kinase. The study group included 92 patients treated for OSCC at the University Clinical Centre in Gdańsk, Poland. Study was performed on formalin-fixed paraffin-embedded samples from primary OSCC. Phosphatidylinositol-4,5-bisphosphate 3-kinase (PIK3CA) and phosphatase and tensin homolog encoded on chromosome 10 (PTEN) protein expression was assessed by immunohistochemistry (IHC). PIK3CA gene copy number was analyzed using chromogenic and silver in situ hybridization where molecular probes are marked by chromogens and silver ions. PIK3CA IHC H-score ≥ 70 was found in 51.65% patients, and loss of PTEN protein was noticed in 31.46% cases. PIK3CA amplification was detected in 5 tumors. In the case of PTEN protein expression, there was an inverse correlation with the T stage of the primary tumor (r = −0.243) and positive correlation with a 5-year survival (r = 0.235). The number of copies of the PIK3CA gene was associated with the tumor grading (r = 0.208). The present study shows that loss of PTEN protein and the grading (p = 0.040), distant metastases (p = 0.033), smoking (p = 0.016), and alcohol abuse (p = 0.042) were prognostic factors for the survival of patients with OSCC. In contrast, the presence of amplification and OSCC on the floor of the mouth resulted in a nearly six-fold increase in the risk of shortening survival (p = 0.037). Our finding suggests a potential prognostic significance of PTEN loss and PIK3CA amplification in OSCC. Future studies are needed to confirm our results.