Historically, several classification systems have been used for brachytherapy, and they were based on the type of clinical purpose, type of implant and timing of the implant, dose-rate, and type of loading for treatment delivery. However, over the last decades, there have been some major...

Interventional radiotherapy (IRT, brachytherapy) is a highly effective treatment method for non-melanoma skin cancer (NMSC). Traditionally, the maximum depth of NMSC lesions considered eligible for contact IRT was 5 mm; however, following several national surveys and recent recommendations, such...

Purpose: To evaluate the performance of eleven Knowledge-Based (KB) models for planning optimization (RapidPlan^tm (RP), Varian) of Volumetric Modulated Arc Therapy (VMAT) applied to whole breast comprehensive of nodal stations, internal mammary and/or supraclavicular regions. Methods and materials: Six RP models have been generated and trained based on 120 VMAT plans data set with different criteria. Two extra-structures were delineated: a PTV for the optimization and a ring structure. Five more models, twins of the previous models, have been created without the need of these structures. Results: All models were successfully validated on an independent cohort of 40 patients, 30 from the same institute that provided the training patients and 10 from an additional institute, with the resulting plans being of equal or better quality compared with the clinical plans. The internal validation shows that the models reduce the heart maximum dose of about 2 Gy, the mean dose of about 1 Gy and the V_20Gy of 1.5 Gy on average. Model R and L together with model B without optimization structures ensured the best outcomes in the 20% of the values compared to other models. The external validation observed an average improvement of at least 16% for the V_5Gy of lungs in RP plans. The mean heart dose and for the V_20Gy for lung IPSI were almost halved. The models reduce the maximum dose for the spinal canal of more than 2 Gy on average Conclusions: All KB models allow a homogeneous plan quality and some dosimetric gains, as we saw in both internal and external validation. Sub-KB models, developed by splitting right and left breast cases or including only whole breast with locoregional lymph nodes, have shown good performances, comparable but slightly worse than the general model. Finally, models generated without the optimization structures, performed better than the original ones.

Background: Quantum Neural Networks (QNNs) combine quantum computing and artificial intelligence to provide powerful solutions for high-dimensional data analysis. In magnetic resonance imaging (MRI), they address the challenges of advanced imaging sequences and data complexity, enabling faster optimization, enhanced feature extraction, and real-time clinical applications. Methods: A literature review using Scopus, PubMed, IEEE Xplore, ACM Digital Library and arXiv identified 84 studies on QNNs in MRI. After filtering for peer-reviewed original research, 20 studies were analyzed. Key parameters such as datasets, architectures, hardware, tasks, and performance metrics were summarized to highlight trends and gaps. Results: The analysis identified datasets supporting tasks like tumor classification, segmentation, and disease prediction. Architectures included hybrid models (e.g., ResNet34 with quantum circuits) and novel approaches (e.g., Quantum Chebyshev Polynomials). Hardware ranged from high-performance GPUs to quantum-specific devices. Performance varied, with accuracy up to 99.5% in some configurations but lower results for complex or limited datasets. Conclusions: The findings provide the first glimpse into the potential of QNNs in MRI, demonstrating accuracy and specificity in diagnostic tasks and biomarker detection. However, challenges such as dataset variability, limited quantum hardware access, and reliance on simulators remain. Future research should focus on scalable quantum hardware, standardized datasets, and optimized architectures to support clinical applications and precision medicine.

(1) Background: Periorificial face cancer (PFC), defined as both squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) arising around the eyelids, the nose vestibule and the lips, has very high incidence rates worldwide. The aim of our retrospective analysis, focusing on local control (LC) and patients’ degree of satisfaction with the cosmetic outcome, is to present the results of a single institutional series of patients affected by PFC and treated by interventional radiotherapy (brachytherapy–IRT). (2) Methods: We retrospectively evaluated patients affected by PFC who were treated at our Interventional Oncology Center (IOC) with interstitial IRT from 2012 to 2021 with doses and volumes specific for each subsite considered. (3) Results: We report the results of 40 patients affected by PFC and treated by HDR interstitial IRT. The median follow-up was 24 months. The actuarial 3-year LC was 94%. Regarding patients’ satisfaction, we found that 93% of patients were satisfied and only 7% of patients were not completely satisfied with the final cosmetic result. (4) Conclusions: Interstitial HDR IRT could be an effective therapeutic option providing adequate disease control and preventing potentially disfiguring surgical approaches. More numerous and standardized studies are warranted to confirm the available evidence.

Interventional radiotherapy (brachytherapy) has become the new therapeutic standard in the management of early stages nasal vestibule tumors; in fact it allows for high local control rates and low toxicity profiles. However, since more and more patients will receive interventional radiotherapy (brachytherapy) as primary treatment, it is desirable to implement novel strategies to reduce the dose to organs at risk with the future aim to result in further lowering long-term side effects. Materials and methods: We were able to identify two different strategies to reduce dose to the treatment volume, including the implantation technique (the implant can be interstitial, endocavitary or mixed and the catheters may be placed either using the Paris system rules or the anatomical approach) and the dose distribution within the implant (the most commonly used parameter to consider is the dose non-uniformity ratio). We subsequently propose two novel strategies to reduce dose to organs at risk, including the use of metal shields for fixed organs as in the case of the eyes and the use of a mouth swab to push away mobile organs, such in the case of the mandible. We used two different algorithms to verify the values namely the TG-43 and the TG-186. Results: We provided an accurate literature review regarding strategies to reduce toxicity to the treatment volume, underlining the pros and cons of all implantation techniques and about the use dose non-uniformity ratio. Regarding the innovative strategies to reduce the dose to organs at risk, we investigated the use of eye shielding and the use of swabs to push away the mandible by performing an innovative calculation using two different algorithms in a series of three consecutive patients. Our results show that the dose reduction, both in the case of the mandible and in the case of eye shielding, was statistically significant. Conclusion: Proper knowledge of the best implantation technique and dose non-uniformity ratio as highlighted by existing literature is mandatory in order to reduce toxicity within the treatment volume. With regard to the dose reduction to the organs at risk we have demonstrated that the use of eye shielding and mouth swab could play a pivotal role in clinical practice; in fact, they are effective at lowering the doses to the surrounding organs and do not require any change to the current clinical workflow.