Disclosed herein are systems and methods for guiding the delivery of therapeutic radiation using incomplete or partial images acquired during a treatment session. A partial image does not have enough information to determine the location of a target region due to, for example, poor or low contrast and/or low SNR. The radiation fluence calculation methods described herein do not require knowledge or calculation of the target location, and yet may help to provide real-time image guided radiation therapy using arbitrarily low SNR images.

Example methods for adaptive radiotherapy treatment planning using deep learning engines are provided. One example method may comprise obtaining treatment image data associated with a first imaging modality and planning image data associated with a second imaging modality. The treatment image data may be acquired during a treatment phase of a patient. Also, planning image data associated with a second imaging modality may be acquired prior to the treatment phase to generate a treatment plan for the patient. The method may also comprise: in response to determination that an update of the treatment plan is required, processing, using the deep learning engine, the treatment image data and the planning image data to generate output data for updating the treatment plan.

A method and apparatus for radiation therapy using functional measurements of branching structures. The method includes determining a location of each voxel of a plurality of voxels in a reference frame of a radiation device. The method further includes obtaining measurements that indicate a tissue type at each voxel. The method further includes determining a subset of the voxels based on an anatomical parameter of a respective branching structure of a set of branching structures indicated by the measurements. The method further includes determining a subset of the voxels that enclose an organ-at-risk (OAR) volume. The method further includes determining a value of a utility measure at each voxel. The method further includes determining a series of beam shapes and intensities which minimize a value of an objective function based on a computed dose delivered to each voxel and the utility measure for that voxel summed over all voxels.

A method comprises identifying a treatment planning image of a target subject, the treatment planning image comprising information associated with an arrangement of structures within the target subject. The method further comprises generating, based on the information, a set of reference data associated with the target subject, the reference data indicating a plurality of positions of the target subject. The method further comprises generating target-subject-specific models based on the reference data and modifying one or more hyper-parameters of the target-subject-specific mode to generate second target-subject-specific models corresponding to a second position of the plurality of positions. The method further comprises controlling a radiation treatment delivery device based on the second target-subject-specific model to deliver a radiation treatment to the target subject.

The present invention relates to radiation therapy. In order to improve the accuracy in deformable image registration in radiation therapy planning, a method is provided that comprises a) receiving a dose distribution to be delivered during one or more treatment sessions according to a radiation therapy plan, b) receiving contours delineating at least one region of interest, ROI, of at least one of the medical images, c) receiving one or more treatment objectives associated with the at least one ROI that has delineated contours, d) determining one or more critical regions in at least one of the medical images, where a geometric error of the contours of the at least one ROI and/or an uncertainty in the electron density distribution leads to a violation of one or more treatment objectives with respect to the dose distribution, and e) improving the accuracy of a deformable image registration algorithm in the one or more critical regions for registering the at least two medical images, wherein the deformable image registration algorithm estimates a deformation between the at least two medical images.

Systems and methods for cardiac radioablation treatment planning are disclosed. In some examples, a computing device receives a first signal identifying a first event within a first workspace from a second computing device. The computing device determines a first action to apply to a first image displayed within a second workspace based on the first signal. The computing device generates a second image based on applying the first action to the first image within the second workspace, and displays the second image within the second workspace. In some examples, the first workspace is a radiation oncologist workspace and the second workspace is an electrophysiologist workspace. In some examples, the first workspace is an electrophysiologist oncologist workspace and the second workspace is a radiation oncologist workspace.

Magnetic resonance (MR) guided radiation therapy (MRgRT) enables control over the delivery of radiation based on patient motion indicated by MR imaging (MRI) images captured during radiation delivery. A method for MRgRT includes: simultaneously using one or more radiation therapy heads to deliver radiation and an MRI system to perform MRI; using a processor to determine whether one or more gates are triggered based on at least a portion of MRI images captured during the delivery of radiation; and in response to determining that one or more gates are triggered based on at least a portion of the MRI images captured during the delivery of radiation, suspending the delivery of radiation.

Systems and methods for implementing an adaptive therapy workflow that minimizes time needed to create a session patient model, select an appropriate plan for the treatment session, and treat the patient.

A method for treating a tumor, comprising identifying a tumor as a colorectal cancer tumor and implanting in the tumor identified as a colorectal cancer tumor, as least one diffusing alpha-emitter radiation therapy (DaRT) source (21) with a suitable radon release rate and for a given duration, such that the source (21) provides during the given duration a cumulated activity of released radon between 3.7 Mega becquerel (MBq) hour and 9.2 MBq hour, per centimeter length.

Systems, methods, and computer software are disclosed that allow the automatic recalling of imaging parameters from computer memory for controlling an MRI system to perform treatment-day scans of a patient on a treatment couch in a radiotherapy system, prior to treatment. The treatment-day scans can be automatically initialized and the MRI system can then be controlled to perform the treatment-day scans according to the recalled imaging parameters. Reoptimized radiation treatment plan(s) can be automatically generated and predicted doses to anatomical structures of the patient based on the plan(s) can be displayed. Clinicians can be enabled to perform numerous reoptimization tasks simultaneously through parallel workflow interfaces and then a radiation therapy device can be controlled to deliver radiation according to a selected radiation treatment plan.