Induction chemotherapy (ICT), a new standard in the management of locally advanced nasopharyngeal carcinoma (NPC), is increasingly used in endemic regions. Radiation therapy (RT) target volume delineation protocols and dose level prescriptions vary significantly in the literature. High-level evidence to support a particular approach is currently lacking. We developed an international consensus guideline toward harmonizing practices based on a literature review and expert opinion.

We evaluated the role of adjuvant radiation therapy after D2 lymphadenectomy for gastric cancer (GC), identified patients most likely to benefit from postoperative radiation therapy, and defined the optimal target volume for adjuvant radiation therapy by analyzing recurrence patterns.

Peer review is essential for radiation therapy quality assurance (RTQA) and recent studies show that peer review upstream of treatment planning is feasible and can improve radiation therapy quality. Herein, we describe protocol deviations detected by our peer review process by the type of deviation, disease site, and physician characteristics.

To investigate the benefits and challenges of implementing a medical physics consult program in a small clinic.

Adaptive radiation therapy (ART) represents an evolution in the field of radiation oncology, addressing the complexities of tumor motion and anatomical variability that often challenge conventional treatment techniques. In abdominopelvic cancers, where the proximity of organs at risk (OARs) and variability in patient anatomy necessitate precise dose delivery, online adaptive radiation therapy (OART) has emerged as a technique to limit dose to OARs while optimizing dose delivery to target volumes. Computed tomography-guided OART is a time-efficient modality utilizes high-resolution cone beam computed tomography (CBCT) and artificial intelligence (AI) to enable real-time plan adaptation to daily anatomical changes, improving target coverage and minimizing exposure to healthy tissues. Herein, we describe the CT-based OART framework, evaluating the multidisciplinary approach and the critical role of template generation in ensuring treatment accuracy and workflow efficiency. The discussion progresses to site-specific applications, exploring the dosimetric and clinical implications of OART in gastrointestinal, genitourinary, and gynecologic cancers. Finally, the paper highlights future directions, including emerging technologies and the integration of adaptive techniques into routine clinical practice, paving the way for broader implementation of OART across various cancer types.

Vestibular Schwannomas (VS) are benign tumors arising from vestibulocochlear nerve Schwann cells. Single or multifractional stereotactic radiation therapy (SRT) is commonly used for treatment of these tumors and accurate target delineation is critical for the focused radiation delivery, maximizing tumor control while minimizing toxicity. Contrast-enhanced MRI is the gold standard for diagnosis, monitoring of VS and is critical in precise target delineation for SRT planning. Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) has established clinical utility for diagnosis and monitoring of prostate cancer. However other central nervous system neoplasms including VS have also been found to be PSMA tracer avid. We present the first clinical use of PSMA PET for SRT in a patient with VS who was unable to undergo MRI.

PURPOSE We report the 6-year results of a phase II study on hypofractionated radiotherapy (HFRT) targeting the primary and regional lymph nodes in ten fractions (fxs). MATERIALS AND METHODS A schedule of 34 Gy/10 fxs/2 wks to the whole breast/chest wall and to the draining lymph nodes was used. Both acute and late toxicities were collected. All pts but those who underwent mastectomy without reconstruction or with temporary expander were asked to rate their cosmetic outcome according to the Harvard scale. Toxicity was assessed weekly during RT and then at each follow-up (fup) examination. Cancer related endpoints were evaluated from the date of RT start to the diagnosis of local relapse/distant metastases or the last fup respectively. RESULTS From February 2015 to March 2019, 59 women (median age 60 yrs, IQR: 48.3-68.8 yrs) with stage II to IIIA breast cancer who underwent axillary dissection and conservative surgery (83%) or mastectomy (17%) were accrued. One patient was lost to fup immediately after the end of RT. At the median fup of 77.11 months (range: 24-102 months), the cumulative incidence of any grade loco-regional late toxicity estimated with the Kaplan-Meier method is 43.4% (95%CI) (30.0% and 46.1% for patients undergone mastectomy and lumpectomy, respectively). Peak- 2 events have been observed for fibrosis (1 pt, 1.7%), telangiectasia (1 pts, 1.7%) and lymphoedema (1 patient, 1.7%). One patient (1.7%) experienced grade 3 breast retraction at 36 month fup. The cosmetic outcome resulted to be excellent, good, fair and poor in 61.7%, 25%, 7.6% and 5.7%, respectively. At 72 months the specific-disease free survival was 96.5%; distant metastasis-free survival (DMFS) and OS rates were 88% and 94.4% respectively. CONCLUSIONS Our results support the activity of a 10-fxs Hypo-RT schedule targeting the primary site as well as the draining lymph node stations after surgery for locally advanced BC.

This guideline provides evidence-based recommendations addressing the indications for definitive treatment of primary squamous cell carcinoma of the anal canal and anal margin.

In a radiation oncology clinic, machine downtime can be a serious burden to the entire department. This study investigates using increasingly popular generative AI techniques to assist medical physicists in troubleshooting Linear Accelerator (LINAC) issues. Google's NotebookLM, supplemented with background information on LINAC issues/solutions was used as a Machine Troubleshooting Assistant for this purpose. Two board-certified Medical Physicists evaluated the LLM's responses based on hallucination, relevancy, correctness, and completeness. Results indicated that responses improved with increasing source data context and more specific prompt construction. Keeping risk-mitigation and the inherent limitations of AI in mind, this work offers a viable, low-risk method to improve efficiency in radiation oncology. This work uses a "Machine Troubleshooting Assistance" application to provide an adaptable example of how radiation oncology clinics can begin using generative AI to enhance clinical efficiency.