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System and method for learning models of radiotherapy treatment plans to predict radiotherapy dose distributions

A dose distribution, radiation therapy technology, applied in the field of radiation therapy systems, which can solve the problems of discomfort adaptive therapy use, lack of in-depth local expertise, etc., achieve planning accuracy and performance improvement, reduce subjectivity, reduce costs and delays. Effect

Active Publication Date: 2019-06-04
ELEKTA AB
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] These approaches are especially problematic for treatment clinics that lack in-depth local expertise and / or new equipment, and may not be suitable for use in adaptive therapy

Method used

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  • System and method for learning models of radiotherapy treatment plans to predict radiotherapy dose distributions
  • System and method for learning models of radiotherapy treatment plans to predict radiotherapy dose distributions
  • System and method for learning models of radiotherapy treatment plans to predict radiotherapy dose distributions

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Embodiment Construction

[0035] figure 1 An exemplary radiation therapy system 10 for providing radiation therapy to a patient is shown. The radiotherapy system 10 includes an image processing device 12 . The image processing device 12 may be connected to a network 20 . Network 20 may be connected to the Internet 22 . The network 20 may connect the image processing device 12 with one or more of a database 24, a hospital database 26, an oncology information system (OIS) 28, a radiation therapy device 30, an image acquisition device 32, a display device 34, and a user interface 36. . For example, network 20 may connect image processing device 12 with database 24 or hospital database 26 , display device 34 and user interface 36 . Also for example, the network 20 may connect the image processing device 12 with a radiotherapy device 30 , an image acquisition device 32 , a display device 34 and a user interface 36 . The image processing device 12 is configured to generate a radiotherapy treatment plan ...

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Abstract

The present invention relates to systems and methods for developing radiotherapy treatment plans though the use of machine learning approaches and neural network components. A neural network is trained using one or more three-dimensional medical images, one or more three-dimensional anatomy maps, and one or more dose distributions to predict a fluence map or a dose map. During training the neuralnetwork receives a predicted dose distribution determined by the neural network that is compared to an expected dose distribution. Iteratively the comparison is performed until a predetermined threshold is achieved. The trained neural network is then utilized to provide a three-dimensional dose distribution.

Description

[0001] Cross References to Related Applications [0002] This application claims the full benefit and priority of U.S. Provisional Patent Application No. 62 / 384,192, filed September 7, 2016, entitled "Learning Models of RadiotherapyTreatment Plans to Predict Therapy Dose Distributions," the disclosure of which is for all purposes Incorporated herein by reference in its entirety. technical field [0003] The present invention generally relates to radiation therapy systems. More specifically, embodiments of the disclosed invention present systems and methods for developing and implementing radiation therapy planning within a radiation therapy system utilizing machine learning algorithms and neural networks. Background technique [0004] Radiation therapy has been used to treat tumors in human (and animal) tissue. Intensity Modulated Radiation Therapy (IMRT) and Volume Modulated Arc Therapy (VMAT) have become the standard of care in modern cancer radiation therapy, offering g...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61N5/10G06N3/04G06N3/08G06N3/02G16H50/20
CPCA61N5/1031G06N3/084G16H50/20G16H30/20G16H40/63A61N5/1039G06N3/045A61N5/10G06N3/02G06N20/00G16H30/40G06N3/08
Inventor 林登·S·希巴德
Owner ELEKTA AB
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