Radiation therapy exerts a tumoricidal local effect as well as both local and systemic immunomodulation. Immune checkpoint blockade has become a widely used treatment modality across cancer types with a rapidly growing list of agents and US Food and Drug Administration-approved indications. Moreover, there may be synergy between radiation therapy and immune checkpoint blockade. Various strategies have been used, but the optimal sequencing of these therapies is unclear. In this review, the authors discuss the major mechanisms of available immune checkpoint inhibitors and explore the available preclinical and clinical evidence regarding treatment sequencing. They also review safety considerations and conclude with possible future directions.

Clinician generated segmentation of tumor and healthy tissue regions of interest (ROIs) on medical images is crucial for radiotherapy. However, interobserver segmentation variability has long been considered a significant detriment to the implementation of high-quality and consistent radiotherapy dose delivery. This has prompted the increasing development of automated segmentation approaches. However, extant segmentation datasets typically only provide segmentations generated by a limited number of annotators with varying, and often unspecified, levels of expertise. In this data descriptor, numerous clinician annotators manually generated segmentations for ROIs on computed tomography images across a variety of cancer sites (breast, sarcoma, head and neck, gynecologic, gastrointestinal; one patient per cancer site) for the Contouring Collaborative for Consensus in Radiation Oncology challenge. In total, over 200 annotators (experts and non-experts) contributed using a standardized annotation platform (ProKnow). Subsequently, we converted Digital Imaging and Communications in Medicine data into Neuroimaging Informatics Technology Initiative format with standardized nomenclature for ease of use. In addition, we generated consensus segmentations for experts and non-experts using the Simultaneous Truth and Performance Level Estimation method. These standardized, structured, and easily accessible data are a valuable resource for systematically studying variability in segmentation applications.