Abstract: Systems and methods for accelerated online adaptive radiation therapy (“ART”) are described. The improvements to online ART are generally provided based on the use of textural analysis and machine learning algorithms implemented with a hardware processor and a memory. The described systems and methods enable more efficient and accurate online adaptive replanning (“OLAR”), which can also be implemented in clinically acceptable timeframes. For example, OLAR can be reduced from taking 10-30 minutes down to 5-10 minutes.

Abstract: Systems and methods for accelerated online adaptive radiation therapy (“ART”) are described. The improvements to online ART are generally provided based on the use of textural analysis and machine learning algorithms implemented with a hardware processor and a memory. The described systems and methods enable more efficient and accurate online adaptive replanning (“OLAR”), which can also be implemented in clinically acceptable timeframes. For example, OLAR can be reduced from taking 10-30 minutes down to 5-10 minutes.

Abstract: Systems and methods directed to adaptive radiotherapy planning are provided. In some aspects, provided system and method include producing synthetic images from magnetic resonance data using relaxometry maps. The method includes applying corrections to the data and generating relaxometry maps therefrom. In other aspects, a method for adapting a radiotherapy plan is provided. The method includes determining an objective function based on dose gradients from an initial dose distribution, and generating an optimized plan based on updated images, using aperture morphing and gradient maintenance algorithms without need for organ-at-risk contouring.

Abstract: Systems and methods directed to adaptive radiotherapy planning are provided. In some aspects, provided system and method include producing synthetic images from magnetic resonance data using relaxometry maps. The method includes applying corrections to the data and generating relaxometry maps therefrom. In other aspects, a method for adapting a radiotherapy plan is provided. The method includes determining an objective function based on dose gradients from an initial dose distribution, and generating an optimized plan based on updated images, using aperture morphing and gradient maintenance algorithms without need for organ-at-risk contouring.

Abstract: Systems and methods directed to adaptive radiotherapy planning are provided. In some aspects, provided system and method include producing synthetic images from magnetic resonance data using relaxometry maps. The method includes applying corrections to the data and generating relaxometry maps therefrom. In other aspects, a method for adapting a radiotherapy plan is provided. The method includes determining an objective function based on dose gradients from an initial dose distribution, and generating an optimized plan based on updated images, using aperture morphing and gradient maintenance algorithms without need for organ-at-risk contouring.

Abstract: Systems and methods directed to adaptive radiotherapy planning are provided. In some aspects, provided system and method include producing synthetic images from magnetic resonance data using relaxometry maps. The method includes applying corrections to the data and generating relaxometry maps therefrom. In other aspects, a method for adapting a radiotherapy plan is provided. The method includes determining an objective function based on dose gradients from an initial dose distribution, and generating an optimized plan based on updated images, using aperture morphing and gradient maintenance algorithms without need for organ-at-risk contouring.