Large language model-augmented learning for auto-delineation of treatment targets in head-and-neck cancer radiotherapy.

Background And Purpose: Radiation therapy (RT) is highly effective, but its success depends on accurate, manual target delineation, which is time-consuming, labor-intensive, and prone to variability. Despite AI advancements in auto-contouring normal tissues, accurate RT target volume delineation remains challenging. This study presents Radformer, a novel visual language model that integrates text-rich clinical data with medical imaging for accurate automated RT target volume delineation.

An automated treatment planning portfolio for whole breast radiotherapy.

Background: Automation in radiotherapy presents a promising solution to the increasing cancer burden and workforce shortages. However, existing automated methods for breast radiotherapy lack a comprehensive, end-to-end solution that meets varying standards of care.

Purpose: This study aims to develop a complete portfolio of automated radiotherapy treatment planning for intact breasts, tailored to individual patient factors, clinical approaches, and available resources.

Radiotherapy with cetuximab or durvalumab for locoregionally advanced head and neck cancer in patients with a contraindication to cisplatin (NRG-HN004): an open-label, multicentre, parallel-group, randomised, phase 2/3 trial.

Background: Management of patients with locoregionally advanced head and neck squamous cell carcinoma (HNSCC) when cisplatin is contraindicated is controversial. We aimed to assess whether radiotherapy with concurrent and adjuvant durvalumab would improve outcomes compared with radiotherapy with cetuximab.

Methods: NRG-HN004 was designed as an open-label, multicentre, parallel-group, randomised, phase 2/3 trial with safety lead-in conducted at 89 academic and community medical centres in North America.

Analyzing the Relationship between Dose and Geometric Agreement Metrics for Auto-Contouring in Head and Neck Normal Tissues.

This study aimed to determine the relationship between geometric and dosimetric agreement metrics in head and neck (H&N) cancer radiotherapy plans. A total 287 plans were retrospectively analyzed, comparing auto-contoured and clinically used contours using a Dice similarity coefficient (DSC), surface DSC (sDSC), and Hausdorff distance (HD). Organs-at-risk (OARs) with ≥200 cGy dose differences from the clinical contour in terms of D (D0.

Landmark-based auto-contouring of clinical target volumes for radiotherapy of nasopharyngeal cancer.

Background: The delineation of clinical target volumes (CTVs) for radiotherapy for nasopharyngeal cancer is complex and varies based on the location and extent of disease.

Purpose: The current study aimed to develop an auto-contouring solution following one protocol guidelines (NRG-HN001) that can be adjusted to meet other guidelines, such as RTOG-0225 and the 2018 International guidelines.

Methods: The study used 2-channel 3-dimensional U-Net and nnU-Net framework to auto-contour 27 normal structures in the head and neck (H&N) region that are used to define CTVs in the protocol.

The Assistant Clinical Research Coordinator Program: A Pathway for Recruitment in Radiation Oncology.

Purpose: Recruiting prospective physicians to radiation oncology can be challenging, because of limited familiarity with the field. The Assistant Clinical Research Coordinator (ACRC) program can help provide trainees early exposure to radiation oncology.

Methods And Materials: The ACRC program involves hiring a college graduate to provide administrative and research support for faculty members.

Th2 Cells Are Associated with Tumor Recurrence Following Radiation.

The curative treatment of multiple solid tumors, including head and neck squamous cell carcinoma (HNSCC), utilizes radiation. The outcomes for HPV/p16-negative HNSCC are significantly worse than HPV/p16-positive tumors, with increased radiation resistance leading to worse locoregional recurrence (LRR) and ultimately death. This study analyzed the relationship between immune function and outcomes following radiation in HPV/p16-negative tumors to identify mechanisms of radiation resistance and prognostic immune biomarkers.

Evaluating automatically generated normal tissue contours for safe use in head and neck and cervical cancer treatment planning.

Purpose: Volumetric-modulated arc therapy (VMAT) is a widely accepted treatment method for head and neck (HN) and cervical cancers; however, creating contours and plan optimization for VMAT plans is a time-consuming process. Our group has created an automated treatment planning tool, the Radiation Planning Assistant (RPA), that uses deep learning models to generate organs at risk (OARs), planning structures and automates plan optimization. This study quantitatively evaluates the quality of contours generated by the RPA tool.

Artificial Intelligence-Based Radiotherapy Contouring and Planning to Improve Global Access to Cancer Care.

Purpose: Increased automation has been identified as one approach to improving global cancer care. The Radiation Planning Assistant (RPA) is a web-based tool offering automated radiotherapy (RT) contouring and planning to low-resource clinics. In this study, the RPA workflow and clinical acceptability were assessed by physicians around the world.

Adjuvant Radiation Therapy for Salivary Duct and Epithelial Myoepithelial Salivary Carcinoma.

Salivary gland cancers are rare in general and salivary duct carcinoma and epithelial myoepithelial carcinomas are rare subtypes. This topic discussion will review the characteristics of these uncommon cancers. Additionally, it will briefly discuss available guidelines for salivary cancers and summarize author opinions on the role of adjuvant radiation therapy for these cases.

Patterns of failure for recurrent head and neck squamous cell carcinoma treated with salvage surgery and postoperative IMRT reirradiation.

Purpose/objectives: The purpose of this study was to evaluate patterns of locoregional recurrence (LRR) after surgical salvage and adjuvant reirradiation with IMRT for recurrent head and neck squamous cell cancer (HNSCC).

Materials/methods: Patterns of LRR for 61 patients treated consecutively between 2003 and 2014 who received post-operative IMRT reirradiation to ≥ 60 Gy for recurrent HNSCC were determined by 2 methods: 1) physician classification via visual comparison of post-radiotherapy imaging to reirradiation plans; and 2) using deformable image registration (DIR). Those without evaluable CT planning image data were excluded.

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources.

Access to radiotherapy worldwide is limited. The Radiation Planning Assistant (RPA) is a fully automated, web-based tool that is being developed to offer fully automated radiotherapy treatment planning tools to clinics with limited resources. The goal is to help clinical teams scale their efforts, thus reaching more patients with cancer.

FAK Drives Resistance to Therapy in HPV-Negative Head and Neck Cancer in a p53-Dependent Manner.

Purpose: Radiation and platinum-based chemotherapy form the backbone of therapy in human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC). We have correlated focal adhesion kinase (FAK/PTK2) expression with radioresistance and worse outcomes in these patients. However, the importance of FAK in driving radioresistance and its effects on chemoresistance in these patients remains unclear.

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

Purpose: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation.

Performance Analysis of a Radiation Oncology Educational Podcast.

Purpose: Asynchronous podcast education is a popular supplementary tool, with up to 88% of medical residents reporting its use. Radiation oncology podcasts remain scarce. The authors analyzed the early performance, listenership, and engagement of the first education-specific radiation oncology medical podcast.

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.

Purpose: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).

Design: In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology.

Adaptive Region-Specific Loss for Improved Medical Image Segmentation.

Defining the loss function is an important part of neural network design and critically determines the success of deep learning modeling. A significant shortcoming of the conventional loss functions is that they weight all regions in the input image volume equally, despite the fact that the system is known to be heterogeneous (i.e.

Lessons and Opportunities for Biomarker-Driven Radiation Personalization in Head and Neck Cancer.

Head and neck cancer is notoriously challenging to treat in part because it constitutes an anatomically and biologically diverse group of cancers with heterogeneous prognoses. While treatment can be associated with significant late toxicities, recurrence is often difficult to salvage with poor survival rates and functional morbidity. Thus, achieving tumor control and cure at the initial diagnosis is the highest priority.

SUPPORT: SUrvey of Parental Leave POlicies of RadiaTion Oncology Programs and Residency Applicants.

Purpose: Recruitment to radiation oncology training programs has recently declined, and gender inequities persist in radiation oncology. Policies that promote inclusivity, such as the updated American College of Graduate Medical Education parental leave policy establishing minimum parental leave requirements, may support recruitment to radiation oncology.

Methods And Materials: We surveyed 2021-2022 radiation oncology residency applicants and program directors (PDs) about program-specific parental leave policies, transparency of parental leave information during the residency application and interview process, and perceptions of the effect of parenthood on residency training, career advancement, and well-being.