Seminars in Radiation Oncology最新文献

The implementation and early adoption of online adaptive radiotherapy (oART) has required the presence of clinicians, physicists and radiation therapists (RTT) at the treatment console. The impact on each of them is unique to their profession and must be considered for safe and efficient implementation. In the short term future, widespread adoption will depend on the development of innovative workflows, and rethinking of traditional roles and responsibilities may be required. For the future, technologies such as artificial intelligence promise to change the workflow significantly in terms of speed, automation and decision-making. However, overall communication within the team will persist in being one of the most important aspects.

The increasing complexity of radiation therapy treatment presents new potentials for error and suboptimal care. High-performing programs thus not only require adherence to, but also ongoing improvement of, key safety and quality practices. In this article, we review these practices including standardization, risk analysis, peer review, and maintenance of strong safety culture, while also describing recent innovations and promising future directions. We specifically highlight the growing role of artificial intelligence in radiation oncology, both as a tool to deliver safe, high-quality care and as a potential new source of safety challenges.

Data demonstrates that hypofractionation is increasingly utilized based on evidence-based guidelines. The outdated Medicare fee-for-service approach penalizes radiation oncology (RO) practices from adopting hypofractionation, even as many patients benefit. To address the flawed fee-for-service payment system, which rewards volume over value, ASTRO introduced the Radiation Oncology Case Rate (ROCR) Value-Based Payment Program. ROCR shifts payment for RO services from fee-for-service to payment per patient or per episode. To address disparities, ROCR provides an evidence-based approach through the Health Equity Achievement in Radiation Therapy (HEART) initiative, providing transportation assistance payment for the underserved. Additionally, ROCR allows practices sufficient capital to maintain existing equipment and invest in new technology. This increases patient access to technological advancements allowing for more efficient, targeted, and personalized care with improved patient outcomes at a lower overall cost.

To further optimize radiotherapy, a more personalized treatment towards individual patient's risk profiles, dissecting both patient-specific tumor and normal tissue response to multimodality treatments is needed. Novel developments in radiobiology, using in vitro patient-specific complex tissue resembling 3D models and multiomics approaches at a spatial single-cell level, may provide unprecedented insight into the radiation responses of tumors and normal tissue. Here, we describe the necessary team effort, including all disciplines in radiation oncology, to integrate such data into clinical prediction models and link the relatively "big data" from the clinical practice, allowing accurate patient stratification for personalized treatment approaches.

With more treatment options in oncology lead to better outcomes and more favorable side effect profiles, patients are living longer—with higher quality of life—than ever, with a growing survivor population. As the needs of patients and providers evolve, and technology advances, cancer care is subject to change. This review explores the myriad of changes in the current oncology landscape with a focus on the patient perspective and patient-centered care.

Telemedicine allows providers and patients to communicate without being in the same room through video platforms or telephone. Like the increased use of telework for businesses, telemedicine exploded during the pandemic. While many workplaces and clinics have returned to some level of in-person interactions, the convenience and comfort have given telemedicine staying power. Patients can be seen from the comfort of their homes; family members can join from the same or a different location. Driving, obtaining childcare, or taking time off from work is unnecessary. Pediatric patients’ parents can pull them into the conversation at appropriate times and avoid the awkwardness of having them leave for portions of the discussion. Because virtual visits are more efficient for everyone, they can often be scheduled sooner than an in-person visit. While not every visit can be done without the patient physically with the provider, many can. This is particularly true for cancer patients, who often have several visits with multiple providers. For immunocompromised patients, there is an added benefit of avoiding exposure from travel and a hospital visit. Oncology and radiation oncology practices have widely adopted telemedicine. While legal and logistical barriers exist in some areas of the world, these are sure to be resolved to make this medicine feasible for all in the modern era.

Radiotherapy aims to achieve a high tumor control probability while minimizing damage to normal tissues. Personalizing radiotherapy treatments for individual patients, therefore, depends on integrating physical treatment planning with predictive models of tumor control and normal tissue complications. Predictive models could be improved using a wide range of rich data sources, including tumor and normal tissue genomics, radiomics, and dosiomics. Deep learning will drive improvements in classifying normal tissue tolerance, predicting intra-treatment tumor changes, tracking accumulated dose distributions, and quantifying the tumor response to radiotherapy based on imaging. Mechanistic patient-specific computer simulations (‘digital twins’) could also be used to guide adaptive radiotherapy. Overall, we are entering an era where improved modeling methods will allow the use of newly available data sources to better guide radiotherapy treatments.