Alkylphosphocholine analogs incorporating a chelating moiety that is chelated to gadolinium are disclosed herein. The alkylphophocholine analogs are compounds having the formula: ##STR00001##
or a salt therof. R.sub.1 includes a chelating agent that is chelated to a gadolinium atom; a is 0 or 1; n is an integer from 12 to 30; m is 0 or 1; Y is —H, —OH, —COOH, —COOX, —OCOX, or —OX, wherein X is an alkyl or an arylalkyl; R.sub.2 is —N.sup.+H.sub.3, —N.sup.+H.sub.2Z, —N.sup.+HZ.sub.2, or —N.sup.+Z.sub.3, wherein each Z is independently an alkyl or an aroalkyl; and b is 1 or 2. The compounds can be used to detect solid tumors or to treat solid tumors. In detection/imaging applications, the gadolinium emits signals that are detectable using magnetic resonance imaging. In therapeutic treatment, the gadolinium emits tumor-targeting charged particles when exposed to epithermal neutrons.

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 method for delivering radiation treatment may include defining a preliminary trajectory including a plurality of control points. Each control point may be associated with position parameters of a gantry and a couch. The method may also include generating a treatment plan based on the preliminary trajectory by optimizing an intensity and position parameters of a collimator and MLC leaves for each control point. The method may also include decomposing the treatment plan into a delivery trajectory including the plurality of control points. Each of the plurality of control points may be further associated with the optimized intensity, the optimized position parameters of the collimator and the MLC leaves, an output rate, and a motion parameter of each of the gantry, the couch, the collimator, and the MLC leaves. The method may further include instructing a radiation delivery device to deliver the treatment plan according to the delivery trajectory.

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 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.

The present invention involves positionally identifying several anatomical structures of interest of a patient's anatomy on images which have been acquired at different points of time. For each anatomical structure a separate image fusion transformation between these images is performed. For at least one of the image fusion transformations it is then determined whether this transformation is within a predetermined threshold, wherein for this determination, at least one further image fusion transformation of another anatomical structure is taken into account.

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.

Disclosed is a computer-implemented method of determining a treatment plan, encompassing acquiring patient image data, acquiring target data describing targets, acquiring position data describing control points which define one or more arcs, and determining target projection data which describes outlines of the target in a beam's-eye view. Margin data is acquired. For the outlines, margins are applied to determine auxiliary outlines. Beam shaping device data is determined describing configurations of the collimator leaves so that irradiation of the auxiliary outlines is enabled. Based on these configurations, the irradiation amount is simulated for voxels of the patient image data. Constraints to be fulfilled by the treatment plan may be set. Configurations of blockings, arc-weights and margins are proposed. Only different combinations of these parameters are proposed while additional possible parameters are neglected. An optimization algorithm is used to minimize an objective function. The best configuration is selected as the treatment plan.