Systems and methods are provided for registering images. The systems and methods perform operations comprising: receiving, at a first time point in a given radiation session, a first imaging slice corresponding to a first plane; encoding the first imaging slice to a lower dimensional representation; applying a trained machine learning model to the encoded first imaging slice to estimate an encoded version of a second imaging slice corresponding to a second plane at the first time point to provide a pair of imaging slices for the first time point; simultaneously spatially registering the pair of imaging slices to a volumetric image, received prior to the given radiation session, comprising a time-varying object to calculate displacement of the object; and generating an updated therapy protocol to control delivery of a therapy beam based on the calculated displacement of the object.

A system and method is provided for magnetic resonance imaging (MRI) guided respiratory gated radiotherapy using a respiratory motion model. MRI-guided respiratory gating is performed with a continuously updated model that represents a patient's internal anatomy as a mathematical function of an external respiratory surrogate. The motion model may be built and updated by acquiring images of a tissue in a subject and measuring, using the images, a position of the tissue in the images to determine motion of the tissue. The surrogate respiratory signal is acquired contemporaneously with acquiring the images. Motion of the tissue and the surrogate respiratory signal are correlated to create the motion model for the subject and gating a radiotherapy system may then be based upon the motion model. A multi-planar model-based respiratory gating may also be performed by sequentially imaging a stack of adjacent slice positions.

Disclosed herein are systems and methods for adapting and/or updating radiotherapy treatment plans based on biological and/or physiological data and/or anatomical data extracted or calculated from imaging data acquired in real-time (e.g., during a treatment session). Functional imaging data acquired at the time of radiation treatment is used to modify a treatment plan and/or dose delivery instructions to provide a prescribed dose distribution to patient target regions. Also disclosed herein are methods for evaluating treatment plans based on imaging data acquired in real-time.

A computer-based method of optimizing a radiotherapy treatment plan for a patient is proposed, wherein a complete treatment comprising both external beam therapy and brachytherapy is optimized in one procedure using an optimization problem comprising an objective function designed to optimize the total dose distribution as a combination of a first dose distribution to be provided by a first radiation set and a second dose distribution to be provided by a second radiation set. One of the radiation sets is external beam radiotherapy and the other is brachytherapy. The optimization is based on a total desired dose for the whole treatment, images of the patient before the treatment starts and an estimated image of the patient after the first radiation set has been delivered.

A computer-based method of optimizing a radiotherapy treatment plan for a patient is proposed, wherein a treatment plan to be provided by one radiation set is optimized taking into account a previously delivered dose delivered by a different radiation set. One of the radiation sets is external beam radiotherapy and the other is brachytherapy.

A base dose calculation tool for determining a base dose employed in treatment planning. Base therapy information is considered on a voxelized and temporal basis such that subsequent treatments may be planned. The base dose output is operable with existing treatment planning systems.

A radiation treatment session is initiated to deliver a therapeutic radiation beam from a therapeutic radiation source to a target. One or more X-ray radiation sources are caused to deliver an imaging radiation beam from the one or more X-ray radiation sources through the target to one or more X-ray detectors to acquire imaging data associated with the target during therapeutic radiation beam delivery. One or more volumetric images are constructed using the acquired imaging data.

Methods and systems are provided which relate to the planning and delivery of radiation treatments by modalities which involve moving a radiation source along a trajectory relative to a subject while delivering radiation to the subject. An artificial intelligence (AI) agent trained using reinforcement learning (and/or some other suitable form of machine learning) is used to control the radiation delivery parameters in effort to achieve desired delivery of radiation therapy. In some embodiments, the AI agent selects suitable control steps (e.g. radiation delivery parameters for particular time steps), while accounting for patient motions, difference(s) in patient anatomical geometry and/or the like.

An example method of radiation therapy in a radiation therapy system that includes a gantry with a treatment-delivering X-ray source and an imaging X-ray source mounted thereon is described. The method includes rotating the gantry in a first direction at a first rotational velocity about an open bore and concurrently rotating an annular support structure at a second rotational velocity about the open bore, wherein the second rotational velocity is less than the first rotational velocity. While continuing to rotate the gantry in the first direction about the open bore from a first position to a treatment position, the method also includes generating multiple images of a target volume disposed in the bore using the imaging X-ray source. Upon rotating the gantry to the treatment position, the method includes initiating delivery of a treatment beam to the target volume with the treatment-delivering X-ray source.

For delivering an image-guided radiation therapy treatment to a moving structure included in a region of a patient body a series of first images of the region of the patient body in different phases of a motion of the structure is acquired in accordance with a first imaging mode. The series of first images is associated with a series of second images of the patient body in essentially the same phases of the motion of the target structure, the second images being acquired in a second imaging mode. During the treatment, a third image is acquired using the second imaging mode during the radiation therapy treatment and a continuation of the radiation therapy treatment is planned on the basis of data relating to one of the first images selected on the basis of a comparison between the third image and the second images associated with the first images.