Sponsored by Sun Nuclear

Presented by 
Todd McNutt, MS, PhD
Johns Hopkins University and Co-founder of Oncospace Inc
and
Christian Velten, BSc, MSc, MS, PhD
Montefiore Health System & Albert Einstein College of Medicine

Live Session:
Friday, August 22, 2025
1:00 - 2:00 PM Eastern Time

The recorded session will be available within 24 hours of the live session. The recorded session needs to be completed by Wednesday, September 17, 2025, to earn CE credits.

Join Sun Nuclear for an in-depth clinical presentation exploring the transformative potential of Plan AI, an intelligent planning assistant now integrated under the Sun Nuclear portfolio. Originally developed by Oncospace, Plan AI leverages advanced algorithms to assist in generating high-quality radiation therapy plans efficiently.

This presentation will feature real-world applications of Plan AI in two of the nation’s prestigious academic medical centers: Johns Hopkins University and Montefiore Medical Center.

The Johns Hopkins perspective will provide an inside look at the genesis of Plan AI, discussing the clinical gaps it was designed to fill and the vision that drove its development. The presentation will include a demonstration of how Plan AI’s functionality within the RayStation treatment planning system.

Montefiore perspective will showcase how Plan AI is used within the Eclipse TPS. The presentation will walk you through the planning workflows with and without Plan AI and share results from research conducted on the quality of treatment plans generated using Plan AI.

Medical Dosimetrists will gain valuable insight into how Plan AI streamlines treatment planning by providing patient-specific optimization objectives from the outset, eliminating the need for trial-and-error iteration. It also delivers feedback on the achievability of organ-sparing goals, helping facilitate informed discussions with radiation oncologists relative to planning directives. In addition, Plan AI includes a robust Peer Review feature. After a plan has been created, Plan AI then lets dosimetrists and physicians evaluate results in the context of the predictions of achievable organ at risk sparing. The Peer Review offering is a centralized protocol library, with structured checklists, team-based assignments, discussion tools, CT image viewer, DVH display, and a clinical goals scorecard—empowering teams to collaborate effectively and consistently to evaluate plan quality.

Learner Outcomes:

1. Explain the origin and purpose of Plan AI, including the clinical needs it addresses and its evolution from Oncospace
2. Describe how Plan AI integrates into RayStation and Eclipse, enabling efficient, high-quality planning workflows
3. Assess the value of Plan AI across two diverse clinical environments, with use cases from Johns Hopkins and Montefiore
4. Evaluate Plan AI’s clinical utility for Medical Dosimetrists, including how it helps reduce trial-and-error, speeds up planning, and improves communication with radiation oncologists
5. Interpret findings from research on plan quality and outcomes, supporting evidence-based adoption of AI in treatment planning

Educational Level: Intermediate

Presenters:
Todd McNutt, PhD, DABR, is an Associate Professor of Radiation Oncology Physics at Johns Hopkins University and Co-founder of Oncospace Inc. He has over 25 years of experience applying novel software solutions to advance radiation oncology practice. After a decade of advancing the Pinnacle treatment planning system, he joined Johns Hopkins in 2005. Soon after joining Johns Hopkins, he started a big data project seeking to capture structured treatment and outcomes data on patients in the clinical workflow. From this project he and his team have explored several facets of applying machine learning and AI to radiation oncology. His work includes data standardization, knowledge-based planning, decision support with spatial dependence on radiation dose for treatment related toxicities, and anomaly detection for errant contouring and suspicious prescriptions. His vision is to apply AI methods towards automation of the straightforward aspects of radiation oncology and to utilize anomaly detection as safety rails, to allow clinicians the time to focus their efforts on the more complex patient needs. This effort culminated in the formation of Oncospace Inc. which is improving upon and disseminating the technologies for the community and was recently incorporated into Sun Nuclear.

Christian Velten, DABR, is a Medical Physicist at Montefiore Health System & Albert Einstein College of Medicine.  His specialties include Scientific computing, Stereotactic radiosurgery (SRS), Stereotactic radiation therapy (SRT), Brachytherapy, Treatment planning and Nuclear physics.  Christian has recently completed his PhD dissertation and will defend in September. 

This activity is part of the celebration of National Medical Dosimetrist's Day and is free to AAMD members and non-members. Once you have logged in, it will display as FREE and will not count against the annual CE credit allowance for Members.

ARRT CQR Credit Distribution
There is no credit distribution for this activity.