Show Notes
Radiotherapy plays a vital role in cancer treatment. In Europe alone, incidents of cancer are projected to rise around 20% by 2040, mainly due to an increasingly aging population. It’s numbers like these that emphasize the importance of pushing boundaries in radiotherapy.
With AI-optimized workflows, it’s possible to speed up treatment planning and ensure highly personalized therapies and technology like auto contouring can protect healthy organs during irradiation by means of AI. This implementation, however, is often met with challenges like staff shortages and inconsistencies with data collection, highlighting the need for more efficient implementation strategies.
In this episode, experts in the fields of radiotherapy and cancer treatment address the amazing headway being made in the world of radiotherapy as well as some of the key roles that current technology can play in the future.
Host Sasa Mutic, President of Radiation Oncology Solutions at the Varian Business Area of Siemens Healthineers, is joined by Valery Lemmens, a member of the Board of Directors at Maastro Radiotherapy Clinic in the Netherlands and creator of the Dutch Cancer Atlas; as well as Joost Verhoeff, radiation oncologist and professor of radiotherapy at Amsterdam University Medical Center; and Indrin Chetty, Vice Chair and Director of the Division of Medical Physics at Cedars-Sinai in Los Angeles.
What you’ll learn in this episode: By using a digital twin, medical professionals can review existing health records and continually compare that information with patient data With adaptive radiotherapy, radiation dosages can be tailored to circumstances like tumor size, type, and position and proximity to vital organs The Dutch Cancer Atlas interprets and publishes data in a context that increases awareness of regional differences in cancer incidents The unique role that data plays in the advancement of cancer care The deep troves of data that already exist within radiotherapy departments can play a key role in the integration of AI into cancer treatments Widespread availability of data creates the opportunity for automated treatment planning and outcome prediction
Connect with Sasa Mutic LinkedIn
Connect with Valery Lemmens LinkedIn
Connect with Joost Verhoeff LinkedIn
Indrin Chetty LinkedIn Hosted on Acast. See acast.com/privacy for more information.
More from Healthcare Perspectives
In this episode of Healthcare Perspectives, host Isabel Nieto Alvarez, PhD, an expert for patient experience at Siemens Healthineers, is joined by Maria Bernathova, MD, breast radiologist and generative AI specialist, and Caroline Justich, breast cancer patient advocate and founder of the patient support initiative Be Accepted. Together, they discuss how better communication — and the responsible use of AI — could help patients feel more informed, involved, and supported throughout their care.
Across the globe, chronic kidney disease, diabetes, cardiovascular disease, and obesity continue to place a growing burden on healthcare systems. Many of these conditions develop silently, often remaining undetected until significant damage has already occurred.
Healthcare systems around the world are under increasing pressure to reduce their environmental footprint without compromising access to care, quality, or patient safety. One often overlooked opportunity is the refurbishment of imaging systems. By giving imaging systems a second life, healthcare providers can help preserve resources while continuing to deliver clinical performance.
Across the globe, radiology departments are grappling with a paradox: imaging volumes are climbing while the trained workforce needed to operate scanners is shrinking. Using AI-driven tools, a drive towards fully-automated radiology promises faster diagnoses, greater diagnostic accuracy, and more efficient workflows, improving both the patient and clinician experience. It is rapidly transforming the way medical imaging is performed, analyzed, and integrated into imaging workflows.
Medical imaging is already an integral part of modern healthcare, but as hospitals face growing imaging demand and staffing challenges, new solutions using artificial intelligence have become an effective way to help ease the load.