News | Treatment Planning | September 23, 2019

Patients treated at Princess Margaret Cancer Centre in Toronto, Canada, as part of comprehensive evaluation study

First Patients Treated With Machine Learning-generated Plans from RayStation 8B

September 23, 2019 — The first-ever patient radiation therapy treatments generated with machine learning in the RayStation treatment planning system (TPS) have been conducted. Patients with localized prostate cancer are being treated with the technology at the Princess Margaret Cancer Centre in Toronto, Canada, as part of a comprehensive evaluation study.

RaySearch released the machine learning features in RayStation 8B in late December 2018. This technology has been developed by RaySearch’s in-house machine learning department in collaboration with researchers at the Princess Margaret Cancer Centre and Techna Institute, crystalizing years of cutting-edge research led by medical physicist Tom Purdie, Ph.D., and computer scientist Chris McIntosh, Ph.D. The features represent the first applications of machine learning in a TPS on the radiation oncology market, according to RaySearch, producing high-quality radiation treatment plans in only minutes, without the need for any user intervention.

Since May 2019, every patient with localized prostate cancer treated at the Princess Margaret has been part of a prospective initiative under the direction of radiation oncologist Alejandro Berlin, M.D. The initiative was launched after observing excellent clinical results in a retrospective evaluation study conducted during 2018, in which machine learning plans were preferred or deemed equivalent to previous manual plans based on three blinded expert reviewers in 94 percent of cases.

The ongoing phase of this study presents physicians with two blinded treatment plans: a manually generated plan and a machine learning plan. The selected plan undergoes standard peer-review and quality assurance, and then patients proceed to treatment delivery with the preferred plan.

This worldwide endeavor will provide unique data to quantify the performance and preferability of machine learning plans in the real-world environment.

Berlin said, “It has been really exciting for the team to help materialize this machine learning advancement in the radiation oncology field, including deployment into the clinical realm. Our positive results to date validate our observations about the robustness of this planning solution”.

For more information: www.raysearchlabs.com


Related Content

News | Radiopharmaceuticals and Tracers

May 27, 2026 — Subtle Medical has received FDA clearance for its SubtleHD (PET), the company's next-generation AI ...

Time May 27, 2026
arrow
News | FDA

May 19, 2026 — DeepHealth has received the CE Mark for the Brain Health and Brain Age solutions within its Neuro Suite ...

Time May 26, 2026
arrow
News | Cardiac Imaging

May 21, 2026 — A team of researchers from Carnegie Mellon University, in collaboration with Cleveland Clinic’s ...

Time May 22, 2026
arrow
News | X-Ray

May 21, 2026 — RADIN Health and AZmed have announced the expansion of their strategic partnership and enhance radiology ...

Time May 22, 2026
arrow
News | Digital Pathology

May 7, 2026 — Roche has entered into a definitive merger agreement to acquire PathAI, a U.S.-based company in digital ...

Time May 21, 2026
arrow
News | Computed Tomography (CT)

May 12, 2026 – Bracco Imaging S.p.A. has purchased a mobile photon-counting CT scanner from MARS Bioimaging to support ...

Time May 20, 2026
arrow
Feature | Enterprise Imaging | Kyle Hardner

For radiology departments, the imbalance between surging imaging volume and a shortage of trained radiologists is taking ...

Time May 20, 2026
arrow
News | ASTRO

May 18, 2026 — The American Society for Radiation Oncology (ASTRO) and the European Society for Radiotherapy and ...

Time May 19, 2026
arrow
News | Interventional Radiology

May 12, 2026 — Siemens Healthineers has received clearance from the Food and Drug Administration for six new systems in ...

Time May 12, 2026
arrow
News | Magnetic Resonance Imaging (MRI)

May 11, 2026 – At the International Society for Magnetic Resonance in Medicine (ISMRM) 2026 Annual Meeting, GE ...

Time May 11, 2026
arrow
Subscribe Now