Delphi consensus on stereotactic ablative radiotherapy for oligometastatic and oligoprogressive renal cell carcinoma-a European Society for Radiotherapy and Oncology study endorsed by the European Association of Urology.

The purpose of this European Society for Radiotherapy and Oncology (ESTRO) project, endorsed by the European Association of Urology, is to explore expert opinion on the management of patients with oligometastatic and oligoprogressive renal cell carcinoma by means of stereotactic ablative radiotherapy (SABR) on extracranial metastases, with the aim of developing consensus recommendations for patient selection, treatment doses, and concurrent systemic therapy. A questionnaire on SABR in oligometastatic renal cell carcinoma was prepared by a core group and reviewed by a panel of ten prominent experts in the field. The Delphi consensus methodology was applied, sending three rounds of questionnaires to clinicians identified as key opinion leaders in the field. At the end of the third round, participants were able to find consensus on eight of the 37 questions. Specifically, panellists agreed to apply no restrictions regarding age (25 [100%) of 25) and primary renal cell carcinoma histology (23 [92%] of 25) for SABR candidates, on the upper threshold of three lesions to offer ablative treatment in patients with oligoprogression, and on the concomitant administration of immune checkpoint inhibitor. SABR was indicated as the treatment modality of choice for renal cell carcinoma bone oligometatasis (20 [80%] of 25) and for adrenal oligometastases 22 (88%). No consensus or major agreement was reached regarding the appropriate schedule, but the majority of the poll (54%-58%) retained the every-other-day schedule as the optimal choice for all the investigated sites. The current ESTRO Delphi consensus might provide useful direction for the application of SABR in oligometastatic renal cell carcinoma and highlight the key areas of ongoing debate, perhaps directing future research efforts to close knowledge gaps.

A multicenter high-quality data registry for advanced proton therapy approaches: the POWER registry.

BACKGROUND: Paucity and low evidence-level data on proton therapy (PT) represent one of the main issues for the establishment of solid indications in the PT setting. Aim of the present registry, the POWER registry, is to provide a tool for systematic, prospective, harmonized, and multidimensional high-quality data collection to promote knowledge in the field of PT with a particular focus on the use of hypofractionation. METHODS: All patients with any type of oncologic disease (benign and malignant disease) eligible for PT at the European Institute of Oncology (IEO), Milan, Italy, will be included in the present registry. Three levels of data collection will be implemented: Level (1) clinical research (patients outcome and toxicity, quality of life, and cost/effectiveness analysis); Level (2) radiological and radiobiological research (radiomic and dosiomic analysis, as well as biological modeling); Level (3) biological and translational research (biological biomarkers and genomic data analysis). Endpoints and outcome measures of hypofractionation schedules will be evaluated in terms of either Treatment Efficacy (tumor response rate, time to progression/percentages of survivors/median survival, clinical, biological, and radiological biomarkers changes, identified as surrogate endpoints of cancer survival/response to treatment) and Toxicity. The study protocol has been approved by the IEO Ethical Committee (IEO 1885). Other than patients treated at IEO, additional PT facilities (equipped with Proteus®ONE or Proteus®PLUS technologies by IBA, Ion Beam Applications, Louvain-la-Neuve, Belgium) are planned to join the registry data collection. Moreover, the registry will be also fully integrated into international PT data collection networks.

Extreme-hypofractionated RT with concomitant boost to the DIL in PCa: a 5-year update on oncological and patient-reported outcomes for the phase II trial "GIVE ME FIVE".

AIM: The present work reports updated oncological results and patients-reported outcomes at 5 years of phase II trial "Short-term high precision RT for early prostate cancer with SIB to the dominant intraprostatic lesion (DIL) for patients with early-stage PCa". METHODS: Data from patients enrolled within AIRC IG-13218 (NCT01913717) trial were analyzed. Clinical and GU/GI toxicity assessment and PSA measurements were performed every 3 months for at least 2 years after RT end. QoL of enrolled patients was assessed by IPSS, EORTC QLQ-C30, EORTC QLQ-PR25, and IIEF-5. Patients' score changes were calculated at the end of RT and at 1, 12, and 60 months after RT. RESULTS: A total of 65 patients were included. At a median follow-up of 5 years, OS resulted 86%. Biochemical and clinical progression-free survival at 5 years were 95%. The median PSA at baseline was 6.07 ng/ml, while at last follow-up resulted 0.25 ng/ml. IPSS showed a statistically significant variation in urinary function from baseline (p = 0.002), with the most relevant deterioration 1 month after RT, with a recovery toward baseline at 12 months (p ≤ 0.0001). A numerical improvement in QoL according to the EORTC QLQ-C30 has been reported although not statistically significant. No change in sexual activity was recorded after RT. CONCLUSIONS: The study confirms that extreme hypofractionation with a DIL boost is safe and effective, with no severe effects on the QoL. The increasing dose to the DIL does not worsen the RT toxicity, thus opening the possibility of an even more escalated treatment.

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institution cohort. METHODS: Patients who underwent multiparametric MRI and prostatectomy in our institution in 2015-2018 were considered; a total of 949 patients were included. Gradient-boosted decision tree models were separately trained using clinical features alone and in combination with radiological reporting and/or prostate radiomic features to predict pathological T, pathological N, ISUP score, and their change from preclinical assessment. Model behavior was analyzed in terms of performance, feature importance, Shapley additive explanation (SHAP) values, and mean absolute error (MAE). The best model was compared against a naïve model mimicking clinical workflow. RESULTS: The model including all variables was the best performing (AUC values ranging from 0.73 to 0.96 for the six endpoints). Radiomic features brought a small yet measurable boost in performance, with the SHAP values indicating that their contribution can be critical to successful prediction of endpoints for individual patients. MAEs were lower for low-risk patients, suggesting that the models find them easier to classify. The best model outperformed (p ≤ 0.0001) clinical baseline, resulting in significantly fewer false negative predictions and overall was less prone to under-staging. CONCLUSIONS: Our results highlight the potential benefit of integrative ML models for pathological status prediction in PCa. Additional studies regarding clinical integration of such models can provide valuable information for personalizing therapy offering a tool to improve non-invasive prediction of pathological status. CLINICAL RELEVANCE STATEMENT: The best machine learning model was less prone to under-staging of the disease. The improved accuracy of our pathological prediction models could constitute an asset to the clinical workflow by providing clinicians with accurate pathological predictions prior to treatment. KEY POINTS: • Currently, the most common strategies for pre-surgical stratification of prostate cancer (PCa) patients have shown to have suboptimal performances. • The addition of radiological features to the clinical features gave a considerable boost in model performance. Our best model outperforms the naïve model, avoiding under-staging and resulting in a critical advantage in the clinic. •Machine learning models incorporating clinical, radiological, and radiomics features significantly improved accuracy of pathological prediction in prostate cancer, possibly constituting an asset to the clinical workflow.

Multi-omics integrative modelling for stereotactic body radiotherapy in early-stage non-small cell lung cancer: clinical trial protocol of the MONDRIAN study.

BACKGROUND: Currently, main treatment strategies for early-stage non-small cell lung cancer (ES-NSCLC) disease are surgery or stereotactic body radiation therapy (SBRT), with successful local control rates for both approaches. However, regional and distant failure remain critical in SBRT, and it is paramount to identify predictive factors of response to identify high-risk patients who may benefit from more aggressive approaches. The main endpoint of the MONDRIAN trial is to identify multi-omic biomarkers of SBRT response integrating information from the individual fields of radiomics, genomics and proteomics. METHODS: MONDRIAN is a prospective observational explorative cohort clinical study, with a data-driven, bottom-up approach. It is expected to enroll 100 ES-NSCLC SBRT candidates treated at an Italian tertiary cancer center with well-recognized expertise in SBRT and thoracic surgery. To identify predictors specific to SBRT, MONDRIAN will include data from 200 patients treated with surgery, in a 1:2 ratio, with comparable clinical characteristics. The project will have an overall expected duration of 60 months, and will be structured into five main tasks: (i) Clinical Study; (ii) Imaging/ Radiomic Study, (iii) Gene Expression Study, (iv) Proteomic Study, (v) Integrative Model Building. DISCUSSION: Thanks to its multi-disciplinary nature, MONDRIAN is expected to provide the opportunity to characterize ES-NSCLC from a multi-omic perspective, with a Radiation Oncology-oriented focus. Other than contributing to a mechanistic understanding of the disease, the study will assist the identification of high-risk patients in a largely unexplored clinical setting. Ultimately, this would orient further clinical research efforts on the combination of SBRT and systemic treatments, such as immunotherapy, with the perspective of improving oncological outcomes in this subset of patients. TRIAL REGISTRATION: The study was prospectively registered at clinicaltrials.gov (NCT05974475).

Management of radiation-induced oral mucositis in head and neck cancer patients: a real-life survey among 25 Italian radiation oncology centers.

AIM: Radiation-induced oral mucositis (RIOM) is the most frequent side effect in head and neck cancer (HNC) patients treated with curative radiotherapy (RT). A standardized strategy for preventing and treating RIOM has not been defined. Aim of this study was to perform a real-life survey on RIOM management among Italian RT centers. METHODS: A 40-question survey was administered to 25 radiation oncologists working in 25 different RT centers across Italy. RESULTS: A total of 1554 HNC patients have been treated in the participating centers in 2021, the majority (median across the centers 91%) with curative intent. Median treatment time was 41 days, with a mean percentage of interruption due to toxicity of 14.5%. Eighty percent of responders provide written oral cavity hygiene recommendations. Regarding RIOM prevention, sodium bicarbonate mouthwashes, oral mucosa barrier agents, and hyaluronic acid-based mouthwashes were the most frequent topic agents used. Regarding RIOM treatment, 14 (56%) centers relied on literature evidence, while internal guidelines were available in 13 centers (44%). Grade (G)1 mucositis is mostly treated with sodium bicarbonate mouthwashes, oral mucosa barrier agents, and steroids, while hyaluronic acid-based agents, local anesthetics, and benzydamine were the most used in mucositis G2/G3. Steroids, painkillers, and anti-inflammatory drugs were the most frequent systemic agents used independently from the RIOM severity. CONCLUSION: Great variety of strategies exist among Italian centers in RIOM management for HNC patients. Whether different strategies could impact patients' compliance and overall treatment time of the radiation course is still unclear and needs further investigation.

Comparison of automated segmentation techniques for magnetic resonance images of the prostate.

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[Formula: see text]0.887 Dice).

What is the best time for postoperative radiation therapy in pN1 prostate cancer?

We retrospectively compared long-term biochemical recurrence rates (BCR) in pN1 PCa patients that underwent adjuvant radiotherapy (aRT) vs. no aRT/early salvage (esRT) after robot-assisted radical prostatectomy and extended pelvic lymphadenectomy. All PCa pN1 M0 patients treated at a single high-volume center between 2010 and 2020 were analyzed. Patients with <10 LNs yield, or >10 positive LNs, or persistently detectable PSA after RARP were excluded. Kaplan-Meier (KM) plots depicted BCR rates. Multivariable Cox regression models (MCRMs) focused on predictors of BCR. The cumulative incidence plot depicted BCR rates after propensity score (PS) matching (ratio 1:1). 220 pN1 patients were enrolled, 133 (60.4%) treated with aRT and 87 (39.6%) with no-aRT/esRT. aRT patients were older, with higher rates of postoperative ISUP grade group 4-5, and higher rates of pT3b stage. The actuarial BCR was similar (aRT 39.8% vs. no-aRT/esRT 40.2%; p=1). Median time to BCR was 62 vs. 38 months in aRT vs. no-aRT/esRT patients (p=0.001). In MCRMs, patients managed with no-aRT/esRT were associated with higher rates of BCR over time (hazard ratio [HR]: 3.27, p<0.001). ISUP grade group 5 (HR: 2.18, p<0.01) was an independent predictor of BCR. In PS-matched cumulative incidence plots, the BCR rate was significantly higher in the aRT group (76.4 vs. 40.4%; p<0.01). Patients managed with no-aRT/esRT experienced BCR approximately two years before the aRT group. Despite, the important BCR benefit after aRT, this treatment strategy is underused in daily practice.

Unraveling Mitochondrial Determinants of Tumor Response to Radiation Therapy.

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.

Hippocampal region avoidance in whole brain radiotherapy in brain metastases: For all or for some? A real-world feasibility report.

PURPOSE: Hippocampal sparing whole-brain radiotherapy (HS-WBRT) showed significantly lower long-term side effects compared to standard WBRT. Aim of this study is to describe a HS-WBRT real-world monoinstitutional experience within a retrospective cohort. METHODS: Patients who completed HS-WBRT course, with Karnofsky Performance Status ⩾ 60 and radiological diagnosis of brain metastases (BMs) were enrolled. Treatment was performed using helical Tomotherapy scheduled in 30 Gy in 10 or 12 fractions or 25 Gy in 10 fractions. Oncological outcomes were clinically and radiologically assessed every three months. Toxicity was graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events 4.3. RESULTS: One hundred and nineteen patients from 2016 to 2020 met inclusion criteria; after a median follow-up of 18 months, 29 patients were alive; 6- and 12-months overall survival rates were 66% and 41%, respectively. HS-WBRT response was assessed for 72 patients. Median time to any progression and intracranial failure (IF) was 4.5 and 13.7 months, respectively. The 6- and 12-month IF rates were 85% and 57%. Among 40 patients (34%) who experienced IF, 17 (42%) were oligometastatic, 23 (58%) polymetastatic and 15/40 developed IF within the hippocampi avoidance zone. No grade (G) ⩾ 2 acute toxicities were reported and one G2 (dizziness) late toxicity was described. CONCLUSIONS: HS-WBRT is well tolerated, and despite the hippocampal sparing region, the oncological control is satisfying. Further investigation is warranted to find patients who could most benefit from a HS-WBRT approach.

Dosimetric and NTCP analyses for selecting parotid gland cancer patients for proton therapy.

PURPOSE/OBJECTIVE: To perform a dosimetric and a normal tissue complication probability (NTCP) comparison between intensity modulated proton therapy and photon volumetric modulated arc therapy in a cohort of patients with parotid gland cancers in a post-operative or radical setting. MATERIALS AND METHODS: From May 2011 to September 2021, 37 parotid gland cancers patients treated at two institutions were eligible. Inclusion criteria were as follows: patients aged ⩾ 18 years, diagnosis of parotid gland cancers candidate for postoperative radiotherapy or definitive radiotherapy, presence of written informed consent for the use of anonymous data for research purposes. Organs at risk (OARs) were retrospectively contoured. Target coverage goal was defined as D95 > 98%. Six NTCP models were selected. NTCP profiles were calculated for each patient using an internally-developed Python script in RayStation TPS. Average differences in NTCP between photon and proton plans were tested for significance with a two-sided Wilcoxon signed-rank test. RESULTS: Seventy-four plans were generated. A lower Dmean to the majority of organs at risk (inner ear, cochlea, oral cavity, pharyngeal constrictor muscles, contralateral parotid and submandibular gland) was obtained with intensity modulated proton therapy vs volumetric modulated arc therapy with statistical significance (p < .05). Ten (27%) patients had a difference in NTCP (photon vs proton plans) greater than 10% for hearing loss and tinnitus: among them, seven qualified for both endpoints, two patients for hearing loss only, and one for tinnitus. CONCLUSIONS: In the current study, nearly one-third of patients resulted eligible for proton therapy and they were the most likely to benefit in terms of prevention of hearing loss and tinnitus.

3D-printed boluses for radiotherapy: influence of geometrical and printing parameters on dosimetric characterization and air gap evaluation.

The work investigates the implementation of personalized radiotherapy boluses by means of additive manufacturing technologies. Boluses materials that are currently used need an excessive amount of human intervention which leads to reduced repeatability in terms of dosimetry. Additive manufacturing can solve this problem by eliminating the human factor in the process of fabrication. Planar boluses with fixed geometry and personalized boluses printed starting from a computed tomography scan of a radiotherapy phantom were produced. First, a dosimetric characterization study on planar bolus designs to quantify the effects of print parameters such as infill density and geometry on the radiation beam was made. Secondly, a volumetric quantification of air gap between the bolus and the skin of the patient as well as dosimetric analyses were performed. The optimization process according to the obtained dosimetric and airgap results allowed us to find a combination of parameters to have the 3D-printed bolus performing similarly to that in conventional use. These preliminary results confirm those in the relevant literature, with 3D-printed boluses showing a dosimetric performance similar to conventional boluses with the additional advantage of being perfectly conformed to the patient geometry.

Muscle-invasive bladder cancer in elderly and frail people: Is hypofractionated radiotherapy a feasible approach when no other local options are available?

AIM: The study aims to report the feasibility and safety of palliative hypofractionated radiotherapy targeting macroscopic bladder tumors in a monocentric cohort of frail and elderly bladder cancer patients not eligible for curative treatments. METHODS: Patients who underwent hypofractionated radiotherapy to the gross disease or to the tumor bed after transurethral resection of bladder tumor from 2017 to 2021 at the European Institute of Oncology IRCCS, were retrospectively considered. Schedules of treatment were 30 and 25 Gy in 5 fractions (both every other day, and consecutive days). Treatment response was evaluated with radiological investigation and/or cystoscopy. Toxicity assessment was carried out according to RTOG/EORTC v2.0 criteria. RESULTS: A total of 16 patients were included in the study, of these 11 received hypofractionated radiotherapy on the macroscopic target volume and five on the tumor bed after transurethral resection of bladder tumor. No grade (G) >2 acute toxicities were described after treatment for both groups. Only one patient in the group receiving radiotherapy on the macroscopic disease reported G4 GU late toxicity. Ten patients had available follow-up status (median FU time 18 months), of them six had complete response, one had stable disease, and three had progression of disease. The overall response rate and disease control rate were 60% and 70%, respectively. CONCLUSION: Our preliminary data demonstrate that palliative hypofractionated radiotherapy for bladder cancer in a frail and elderly population is technically feasible, with an acceptable toxicity profile. These outcomes emphasize the potential of this approach in a non-radical setting and could help to provide more solid indications in this underrepresented setting of patients.

Tools to Guide Radiation Oncologists in the Management of DCIS.

Similar to invasive breast cancer, ductal carcinoma in situ is also going through a phase of changes not only from a technical but also a conceptual standpoint. From prescribing radiotherapy to everyone to personalized approaches, including radiotherapy omission, there is still a lack of a comprehensive framework to guide radiation oncologists in decision making. Many pieces of the puzzle are finding their place as high-quality data mature and are disseminated, but very often, the interpretation of risk factors and the perception of risk remain very highly subjective. Sharing the therapeutic choice with patients requires effective communication for an understanding of risks and benefits, facilitating an informed decision that does not increase anxiety and concerns about prognosis. The purpose of this narrative review is to summarize the current state of knowledge to highlight the tools available to radiation oncologists for managing DCIS, with an outlook on future developments.

Photon vs proton hypofractionation in prostate cancer: A systematic review and meta-analysis.

BACKGROUND: High-level evidence on hypofractionated proton therapy (PT) for localized and locally advanced prostate cancer (PCa) patients is currently missing. The aim of this study is to provide a systematic literature review to compare the toxicity and effectiveness of curative radiotherapy with photon therapy (XRT) or PT in PCa. METHODS: PubMed, Embase, and the Cochrane Library databases were systematically searched up to April 2022. Men with a diagnosis of PCa who underwent curative hypofractionated RT treatment (PT or XRT) were included. Risk of grade (G) ≥ 2 acute and late genitourinary (GU) OR gastrointestinal (GI) toxicity were the primary outcomes of interest. Secondary outcomes were five-year biochemical relapse-free survival (b-RFS), clinical relapse-free, distant metastasis-free, and prostate cancer-specific survival. Heterogeneity between study-specific estimates was assessed using Chi-square statistics and measured with the I2 index (heterogeneity measure across studies). RESULTS: A total of 230 studies matched inclusion criteria and, due to overlapped populations, 160 were included in the present analysis. Significant lower rates of G ≥ 2 acute GI incidence (2 % vs 7 %) and improved 5-year biochemical relapse-free survival (95 % vs 91 %) were observed in the PT arm compared to XRT. PT benefits in 5-year biochemical relapse-free survival were maintained for the moderate hypofractionated arm (p-value 0.0122) and among patients in intermediate and low-risk classes (p-values < 0.0001 and 0.0368, respectively). No statistically relevant differences were found for the other considered outcomes. CONCLUSION: The present study supports that PT is safe and effective for localized PCa treatment, however, more data from RCTs are needed to draw solid evidence in this setting and further effort must be made to identify the patient subgroups that could benefit the most from PT.

Post-operative intensity-modulated vs 3D conformal radiotherapy after conservative surgery for laryngeal tumours of the supraglottic region: a dosimetric analysis on 20 patients.

Objective: To perform a dosimetric comparison between intensity modulated radiotherapy (IMRT) and 3D conformal radiotherapy in patients with locally advanced (stage III and IV) tumours of the supraglottic region treated with conservative surgery and post-operative radiotherapy. Methods: An in-silico plan using a 3D conformal shrinking field technique was retrospectively produced for 20 patients and compared with actually delivered IMRT plans. Eighteen structures (arytenoids, constrictor muscles, base of tongue, floor of mouth, pharyngeal axis, oral cavity, submandibular glands and muscles of the swallowing functional units [SFU]) were considered. Results: IMRT allowed a reduction of maximum and mean doses to 9 and 14 structures, respectively (p < .05). Conclusions: IMRT achieved a reduction of unnecessary dose to the remnant larynx and the majority of surrounding SFUs. Further prospective analyses and correlations with functional clinical outcomes are required to confirm these dosimetric findings.

Upfront Advanced Radiotherapy and New Drugs for NSCLC Patients with Synchronous Brain Metastases: Is the Juice Worth the Squeeze? A Real-World Analysis from Lombardy, Italy.

AIM: Healthcare administrative databases represent a valuable source for real-life data analysis. The primary aim of this study is to compare effectiveness and cost profile in non-small-cell lung cancer (NSCLC) patients harboring synchronous brain metastases (BMs) who received non-chemo first-line systemic therapy with or without advanced radiotherapy (aRT). METHODS: Diagnostic ICD-9-CM codes were used for identifying all patients with a new diagnosis of lung cancer between 2012 and 2019. Among these, patients who had started a first-line systemic treatment with either TKIs or pembrolizumab, alone or in combination with intensity-modulated or stereotactic RT, were selected. Clinical outcomes investigated included overall survival (OS), progression-free survival (PFS), and time-to-treatment failure (TTF). The cost outcome was defined as the average per capita cumulative healthcare direct costs of the treatment, including all inpatient and outpatient costs. RESULTS: The final cohort included 177 patients, of whom 58 were treated with systemic treatment plus aRT (STRT) and 119 with systemic treatment alone. The addition of aRT to systemic treatment was associated with a significantly better OS (p = 0.020) and PFS (p = 0.041) than systemic therapy alone. The ICER (incremental cost-effectiveness ratio) value indicated an average cost of €3792 for each month of survival after STRT treatment and confirmed clinical effectiveness but higher healthcare costs. CONCLUSIONS: This real-world study suggests that upfront aRT for NCLSC patients with synchronous BMs represents a valid treatment strategy, boosting the efficacy of novel and emerging drug classes with sustainable costs for the health service. TRANSLATIONAL RELEVANCE: The present real-world study reports that the use of upfront advanced radiotherapyaRT and new-generation systemic agents, such as TKIs and pembrolizumab, may have higher oncological control and an improved cost-effectiveness profile than the use of new-generation systemic agents alone in NCLSC patients with synchronous brain metastases. Acquired evidence can also be used to inform policymakers that adding advanced radiotherapy results is a sustainable cost for the health service. Since approximately 50% of patients do not meet RCT inclusion criteria, a significant proportion of them is receiving treatment that is not evidence-informed; therefore, these results warrant further studies to identify the best radiotherapy timing and possible dose escalation approaches to improving treatment efficacy in patient subgroups not typically represented in randomized controlled trials.

A Bibliometric Analysis of the Oligometastatic State over the Last Two Decades: A Shifting Paradigm for Oncology? An AIRO Oligometastatic Study Group.

The term "oligometastasis" represents a relatively novel idea, which denotes a condition characterized by cancer dissemination with a limited number of lesions (usually fewer than five). The aim of the present study is to report a bibliometric analysis of the oligometastatic disease/state, incorporating all relevant studies on the topic for more than 20 years. The research strategy included at least one the terms "Oligmetastases", "Oligometastasis", "Oligometastatic", "Oligoprogression, "Oligoprogressive", "Oligorecurrent", or "Oligorecurrency" in the title, abstract, and/or keywords. All English-language documents from 1 January 1995 (the year of the earliest available document in Scopus) to 31 December 2022 were considered for the analysis. R code (R version 4.2.0) with R Studio (version 2022.12.0-353) and the Bibliometrix package (version 4.0.1) were used for the analysis. A total of 3304 documents, mainly articles (n = 2083, 63.0%) and reviews (n = 813, 24.6%), were collected from 1995 to 2022. The average annual growth rate of literature on the topic was 26.7%. Overall 15,176 authors published on the topic, with an average of eight authors/publication. From 1995, 69 countries contributed to the literature, with the USA and Italy being the top contributors. Among all keywords used by authors, the top three were oligometastases (19%), SBRT (18%), and radiation therapy (8%). Themes regarding "locoregional treatment", "organ motion", and "immunotherapy" were the most recent trend topics, mainly developed from 2019 to 2022, while "high-dose chemotherapy", "whole-brain radiotherapy", and "metastatic breast cancer" saw their main development during 2009-2018. Our study shows the exceptionally flourishing scientific production on the oligometastatic state, summarizing the most influential studies and highlighting the future developments and interests. This analysis will serve as a benchmark to identify this area for the attention of researchers worldwide and contribute to the increasing scientific work.

More than Five Decades of Proton Therapy: A Bibliometric Overview of the Scientific Literature.

BACKGROUND: The therapeutic potential of proton therapy (PT) was first recognized in 1946 by Robert Wilson, and nowadays, over 100 proton centers are in operation worldwide, and more than 60 are under construction or planned. Bibliometric data can be used to perform a structured analysis of large amounts of scientific data to provide new insights, e.g., to assess the growth and development of the field and to identify research trends and hot topics. The aim of this study is to provide a comprehensive bibliometric analysis of the current status and trends in scientific literature in the PT field. METHODS: The literature on PT until the 31st December 2022 in the Scopus database was searched, including the following keywords: proton AND radiotherapy AND cancer/tumor in title, abstract, and/or keywords. The open-source R Studio's Bibliometrix package and Biblioshiny software (version 2.0) were used to perform the analysis. RESULTS: A total of 7335 documents, mainly articles (n = 4794, 65%) and reviews (n = 1527, 21%), were collected from 1946 to 2022 from 1054 sources and 21,696 authors. Of these, roughly 84% (n = 6167) were produced in the last 15 years (2008-2022), in which the mean annual growth rate was 13%. Considering the corresponding author's country, 79 countries contributed to the literature; the USA was the top contributor, with 2765 (38%) documents, of whom 84% were single-country publications (SCP), followed by Germany and Japan, with 535 and 531 documents of whom 66% and 93% were SCP. Considering the themes subanalysis (2002-2022), a total of 7192 documents were analyzed; among all keywords used by authors, the top three were radiotherapy (n = 1394, 21% of documents), intensity-modulated radiotherapy (n = 301, 5%), and prostate cancer (n = 301, 5%). Among disease types, prostate cancer is followed by chordoma, head and neck, and breast cancer. The change in trend themes demonstrated the fast evolution of hotspots in PT; among the most recent trends, the appearance of flash, radiomics, relative biological effectiveness (RBE), and linear energy transfer (LET) deserve to be highlighted. CONCLUSIONS: The results of the present bibliometric analysis showed that PT is an active and rapidly increasing field of research. Themes of the published works encompass the main aspects of its application in clinical practice, such as the comparison with the actual photon-based standard of care technique and the continuing technological advances. This analysis gives an overview of past scientific production and, most importantly, provides a useful point of view on the future directions of the research activities.

Automatic Segmentation with Deep Learning in Radiotherapy.

This review provides a formal overview of current automatic segmentation studies that use deep learning in radiotherapy. It covers 807 published papers and includes multiple cancer sites, image types (CT/MRI/PET), and segmentation methods. We collect key statistics about the papers to uncover commonalities, trends, and methods, and identify areas where more research might be needed. Moreover, we analyzed the corpus by posing explicit questions aimed at providing high-quality and actionable insights, including: "What should researchers think about when starting a segmentation study?", "How can research practices in medical image segmentation be improved?", "What is missing from the current corpus?", and more. This allowed us to provide practical guidelines on how to conduct a good segmentation study in today's competitive environment that will be useful for future research within the field, regardless of the specific radiotherapeutic subfield. To aid in our analysis, we used the large language model ChatGPT to condense information.