Edy Ippolito

Background and purpose Radiation necrosis (RN) is a significant complication of stereotactic radiotherapy (SRT) for brain metastases. We investigated whether pre-treatment cerebral small vessel disease (cSVD) burden, particularly perivascular spaces (PVSs), is associated with RN risk. Materials and methods This single-center retrospective study included 71 patients treated with fractionated SRT for brain metastases. RN was diagnosed by consensus using multiparametric MRI including DSC perfusion. Pre-treatment cSVD markers were evaluated according to STRIVE criteria, with PVSs graded using Potter’s criteria in the basal ganglia (BG), centrum semiovale (CS), and midbrain (MB). Associations with RN were assessed using Firth’s penalized logistic regression adjusted for age and sex. Results RN developed in 33 patients (46.5%). Higher PVS grades in the CS were significantly associated with increased RN risk (grade 1: OR 6.35, 95% CI 1.86–21.72, p = 0.003; grade 2: OR 26.26, 95% CI 3.64–189.61, p = 0.001). Associations were also observed for higher PVS burden in the BG and MB, although these rested on small subsets with wide confidence intervals. Other cSVD markers showed no significant associations. Confidence intervals were wide due to sparse data in higher PVS grades. Conclusions This exploratory study suggests a potential association between pre-treatment PVS burden and RN risk. However, sparse data, wide confidence intervals, and the absence of lesion-level dosimetric adjustment limit conclusions. These preliminary findings warrant validation in larger, prospective cohorts with comprehensive dosimetric analysis.

Background/Objectives: Early progression (EP) occurs in a subset of patients with locally advanced pancreatic cancer (LAPC), limiting the clinical benefit of treatment, and it remains difficult to predict. Methods: We developed a multiparametric predictive model integrating baseline ¹⁸F-FDG PET/CT radiomic features with clinical and biological data. A total of 242 radiomic features were extracted from each imaging modality (CT and PET), including first-order, gray-level co-occurrence matrix (GLCM), and local binary pattern (LBP-TOP) features, and combined with PET-derived metrics and clinical variables. Model development included cross-validation procedures and rigorous feature selection, followed by the training of a two-level decision tree classifier. Results: The model achieved an accuracy of 80.7% and an area under the curve (AUC) of 0.83. Integrated analysis of CT and PET texture enabled the identification of patients at high risk of EP prior to treatment initiation. Conclusions: PET/CT-based radiomic biomarkers, combined with clinical data, can non-invasively capture tumor heterogeneity and improve risk stratification in LAPC, supporting more personalized therapeutic decision-making.

Over the past two decades, interest in prone-position whole breast irradiation (WBI) as an effective and practical alternative to supine treatment has been growing a lot. Although solid scientific data has provided evidence of substantial dosimetric benefit with decreased toxicity, there is still conflict in the radiotherapy community over whether to adopt prone-position WBI as a valid alternative to supine radiotherapy (RT) in routine clinical practice. A large number of prone trials have been conducted to assess and address concerns related to prone treatment in large and pendulous breasts and in left and right breast cancer (BC), nodal irradiation, and its reproducibility with deep inspiration breath hold (DIBH) delivery with photons or protons. Appropriate atlases have been defined to improve prone nodal irradiation. Additionally, more comfortable customized immobilization couches have been constructed to permit IMRT beams and VMAT arrangements with modern LINACs. Although our search in literature databases shows a growing body of evidence from the past two decades on this issue, prone WBI is still underused. Given the paradox of the advances and benefits of this positioning and the lack of drive in the radiotherapy community towards its clinical implementation, the purpose of this comprehensive review is to evaluate the true advantages of this position in real life and contextualize it in scenarios like large breasts, left-sided breast cancer, and nodal irradiation to encourage its implementation in clinical practice.

Background: CDK4/6 inhibitor plus ET is a standard treatment for advanced HR+ BC. This study evaluates the efficacy and safety of CDK4/6 inhibitors with concurrent RT (SBRT and non-SBRT) in terms of pain, analgesic therapy changes, toxicities, and net clinical benefit (NCB). Methods: BC patients with bone metastases treated with RT and CDK4/6 inhibitor in the prospective observational COMBART study were analyzed. Pain was measured with the NRS. The NCB was defined by pain reduction (NRS), toxicity, and treatment changes. Adverse events (AEs) were graded per CTCAE v5.0. Statistical tests included chi-square and t-test. Results: Forty patients were treated with CDK4/6 inhibitor (palbociclib 30.8%, ribociclib 51.3%, abemaciclib 17.9%) and RT (131 lesions; 100 SBRT, 31 non-SBRT). The mean NRS score dropped from 3.52 (pre-treatment) to 1.31 (post-treatment) (p < 0.001), with better outcomes for patients treated with moderate hypofractionation (58.6% vs. 39.9% pain relief, p = 0.016). Pain relief was independent of the type of CDK4/6 inhibitor used (p = NS). Analgesic reduction was most common with palbociclib (35.4%, p = 0.001). Eight toxicities (grade 1–2) were reported. The NCB was 0.6 overall, higher with non-SBRT (0.74 vs. 0.52). Conclusions: RT plus CDK4/6 inhibitor, especially with moderate hypofractionation, significantly reduced pain with manageable toxicity. Analgesic therapy can often continue without stopping CDK4/6 inhibitor.

Background: Radiation necrosis is a significant late adverse effect of stereotactic radiotherapy (fSRT) for brain metastases, characterized by inflammatory processes and necrotic degeneration of healthy brain tissue.Objective: To evaluate the relationship between the incidence of radiation necrosis and the distribution of lesions across different brain regions treated with fSRT, with a focus on the potential involvement of stem cell niches.Methods: We conducted a post-hoc analysis of two separate prospective datasets consisting of data from 41 patients previously treated for brain metastases at Campus Bio-Medico University Hospital. Patients underwent fSRT using volumetric-modulated arc radiotherapy (VMAT), with MRI data collected pre- and post-treatment. Lesions were assessed for the presence of radiation necrosis based on radiological and clinical criteria, with a specific focus on their proximity to stem cell niches. A mixed-effects logistic regression model, including age and sex as covariates, was used to identify associations between brain region, stem cell niches, and the likelihood of radiation necrosis.Results: Of 167 lesions observed, 42 (25.1%) were classified as radiation necrosis. The Deep-Periventricular region showed a significantly higher likelihood of radiation necrosis compared to other brain regions (log-OR: 1.25, 95% CI: 0.20–2.30, p = 0.02). Lesions in proximity to stem cell niches were significantly associated with an increased risk of radiation necrosis (log-OR: 1.61, 95% CI: 0.27–2.94, p = 0.018). These findings highlight the differential vulnerability of brain regions and suggest a potential role of stem cell niches in the pathogenesis of radiation necrosis.Conclusion: This study underscores the importance of brain region and stem cell niche involvement in the development of radiation necrosis following stereotactic radiotherapy. These findings might have implications for optimizing radiotherapy planning and developing targeted strategies to mitigate the risk of radiation necrosis. Future research should focus on exploring the molecular mechanisms underlying these associations and evaluating potential neuroprotective interventions.

Background: Pancreatic cancer, with its poor prognosis, is frequently diagnosed in elderly patients who may be ineligible for surgery or chemoradiation due to age or comorbidities. Stereotactic body radiotherapy (SBRT) offers a targeted approach by delivering precise, high-dose radiation to a limited volume in few fractions. This study aims to evaluate the efficacy and safety of SBRT in elderly pancreatic cancer patients. Methods: Patients with pancreatic cancer received SBRT using Volumetric Modulated Arc Therapy in schedules of five dose fractions tailored to the tolerance of adjacent tissues. Progression-free survival (PFS), local progression-free survival (LPFS), metastasis-free survival (MFS) and overall survival (OS) were analysed. Toxicities were graded according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Results: Median follow-up was 9.5 months (range, 4–37.2 months). The 1-year, 2-year and 3-year LPFS rates were 88%, 73% and 54%, respectively (median not reached). Median PFS, MFS and OS were 29.6 months, 32.6 months, and 24.1 months, respectively. SBRT was well tolerated with acute and late toxicity rates of 6% and 9%, respectively. Conclusionsd: SBRT appears to be an effective and safe option for elderly pancreatic cancer patients, achieving high local control with minimal toxicity.

Accurate prognosis of Non-Small Cell Lung Cancer (NSCLC) is crucial for enhancing patient care and treatment outcomes. Despite the advancements in deep learning, the task of overall survival prediction in NSCLC has not fully leveraged these techniques, yet. This study introduces a novel methodology for predicting 2-year overall survival (OS) in NSCLC patients using CT scans. Our approach integrates CT scan representations produced by EfficientNetB0 with a soft attention mechanism to identify the most relevant slices for survival risk prediction, which are then analyzed by a risk-assessment network. To validate our method and ensure reproducibility, we employed the public LUNG1 dataset and a smaller private dataset. Our approach was compared to a benchmark 3D network and two variants of our methodology: on the LUNG1 it outperformed the competitors achieving a mean Ctd-index of 0.584 over 10-fold cross-validation. On the LUNG1 we also demonstrated the adaptability of our method with 4 other 2D backbones replacing the EfficientNetB0, confirming that our mechanism of combining 2D slice representations to construct a 3D volume representation is more effective for OS prediction compared to a traditional 3D approach. Finally, we used transfer learning on the private dataset, showing that it can significantly enhance performance in limited data scenarios, increasing the Ctd-index by 0.076 compared to model without transfer learning.