Siemens Healthineers Patent for Radiation Therapy Plan Generation
Summary
The USPTO has granted Siemens Healthineers International AG a patent for a method and system for generating radiation therapy treatment plans. The patented technology utilizes machine learning to predict optimal treatment beam entry angles for new patients based on medical image data.
What changed
The United States Patent and Trademark Office (USPTO) has granted patent US12586672B2 to Siemens Healthineers International AG for an "Intelligent treatable sectors for radiation therapy plan generation." The patent details a method involving monitoring a treatment plan optimizer computer model, generating a training dataset from this data, and subsequently training a machine learning model. This model is designed to predict a new range of angles for treatment beam entry for new patients by ingesting their specific medical image data.
This patent represents a novel approach to radiation therapy planning, leveraging AI and machine learning to enhance precision and potentially personalize treatment. While patents do not impose direct regulatory obligations on other entities, they can influence industry standards and future product development. Companies in the medical device and pharmaceutical sectors, particularly those involved in radiation oncology or AI-driven healthcare solutions, should be aware of this patented technology as it may impact their own research, development, and intellectual property strategies.
Source document (simplified)
Intelligent treatable sectors for radiation therapy plan generation
Grant US12586672B2 Kind: B2 Mar 24, 2026
Assignee
Siemens Healthineers International AG
Inventors
Heini Hyvönen, Mikko Hakala, Ville Pietilä, Hannu Laaksonen
Abstract
Disclosed herein are methods and systems for calculating radiation therapy treatment plan (RTTP) including a method that comprises monitoring, by a processor, a treatment plan optimizer computer model to identify a set of treatment plans, where the treatment plan optimizer computer model ingests a set of medical images and predicts each treatment plan comprising a respective range of angles for treatment beam entry; generating, by the processor, a training dataset comprising the monitored data; and training, by the processor, a machine learning model using the training dataset to predict a new range of angles for treatment beam entry for a new patient by ingesting new patient data of the new patient.
CPC Classifications
A61N 5/103 G16H 20/40
Filing Date
2023-03-31
Application No.
18129403
Claims
20
Named provisions
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