Elekta, Inc.

Koninklijke Philips Corporation N.V.

Michel Moreau

Martin Emile Lachaine

Virgil Matthew Willcut

Fabienne Lathuiliere

Sami Hissoiny

Rupert Brooks

Leila Pishdad

Rupert Archie Brooks

Techniques for contouring of a region of interest based on imaging parameters of spatial imaging data and guided by user input of locations in the spatial imaging data, which may be used for segmentation or radiation treatment planning. An approach of combining a new paint brush tool with an edge-detection algorithm to correct for both the jagged contours and the painting routine not being executed often enough. By using an edge-detection algorithm, the user does not need to focus as much attention on moving the mouse accurately because the system will find the true organ boundary (e.g., using the image gradient) automatically, which may also lead to more time savings.

Structure contouring, such as for segmentation or radiation treatment planning, using a 3D paint brush combined with an edge-detection algorithm

The present disclosure relates to a method for use in adaptive radiotherapy and a treatment planning device. The method may comprise accessing a first medical image and a second medical image that represent a region of interest of a patient at different times. Each medical image is segmented into a target region and at least one non-target region. The method may further comprise accessing a deformation vector field including a plurality of vectors, wherein each vector defines a geometric transformation to map a respective voxel in the first medical image to a corresponding voxel in the second medical image. The method may further comprise generating a modified deformation vector field by: identifying a first vector in the deformation vector field that maps a voxel in the first medical image to a voxel that is in a non-target region in the second medical image; and determining whether the first vector causes a distance between the mapped voxel and the target region to increase and, if so, reducing the magnitude of the first vector. The method may further comprise post-processing the modified deformation vector field to compensate for changes in the shape or size of the target region.

Adaptive radiotherapy system

Radiation treatment planning and administration can include a Monte Carlo computer simulation tool to simulate photo-generated electrons in tissue. In the simulation, electrons that have left tissue voxels and entered air voxels can be evaluated to identify electrons that are circling along a spiraling trajectory in the air voxels. After at least one full spiraling circumference or other specified distance has been traversed using a detailed electron transport model, a simpler linear ballistic motion model can be instituted. This speeds simulation while accurately accounting for spiraling electrons that re-enter tissue voxels.

Radiation treatment planning or administration electron modeling

An adaptive therapy delivery system can receive imaging information including a volumetric image comprising a target such as a tumor or one or more other structures, and can receive imaging information corresponding to one or more imaging slices comprising different portions of the target, such as imaging slices acquired at different times after acquisition of the volumetric image. The system can spatially register information from an earlier-acquired image with a portion of the target included in a later-acquired one of the imaging slices. The system can then determine an updated location of the target indicated by the spatially-registered information. Using the updated location, the system can generate an updated therapy protocol to control delivery of a therapy beam.

Image guidance for radiation therapy

An image-guided therapy delivery system includes a therapy generator configured to generate a therapy beam directed to a time-varying therapy locus within a therapy recipient, an imaging input configured to receive imaging information about a time-varying target locus within the therapy recipient, and a therapy controller. The therapy generator includes a therapy output configured to direct the therapy beam according to a therapy protocol. The therapy controller is configured to automatically generate a predicted target locus using information indicative of an earlier target locus extracted from the imaging information, a cyclic motion model, and a specified latency, and automatically generate an updated therapy protocol to align the time-varying therapy locus with the predicted target locus.

Therapy control using motion prediction based on cyclic motion model

A treatment planning and delivery system includes a treatment planner () and a treatment device (). The treatment planner () develops a treatment plan that satisfies one or more of treatment objectives (), treatment device output objectives (), and treatment device parameter objectives (). The treatment plan is applied by the treatment device (), Examples of treatment device output and treatment device parameter objectives include spatial and temporal objectives.

Growing community of inventors

Verona, WI, United States of America

Michel Moreau