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.

The present disclosure relates a multi-leaf collimator. The multi-leaf collimator may include a plurality of leaves. At least two leaves of the plurality of leaves may be movable parallel to each another. For each leaf of at least some of the plurality of leaves, at least one portion of the leaf may have thicknesses varying along a longitudinal direction of the each leaf. The each leaf may have a first end and a second end along the longitudinal direction of the each leaf.

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 tracking method, a tracking system, and an electronic device are provided. The tracking method includes: acquiring an actual scattering image of a target object at time i, where i is an integer greater than 0, and the actual scattering image is generated according to rays scattered by body tissue where the target object is located; processing the actual scattering image or a reference image corresponding to the actual scattering image with a preset model, and determining a location offset of the target object at the time i according to the processing result; and tracking the target object according to the location offset of at least one time. The preset model is indicative of a location conversion relationship of corresponding pixels in images that are formed before and after the rays are scattered.

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 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.

After accessing optimization information for a particular patient and for a particular radiation treatment platform, a control circuit generates an optimized radiation treatment plan by processing the optimization information using direct-aperture-optimization that includes fluence-based sub-optimization. By one approach, the control circuit includes the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization. By one approach, the control circuit is configured to include only a few iterations of the fluence-based sub-optimization when including the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization.

Conventional single fraction 20-Gy broadbeam photonbeam or protonbeam chemo-radiosurgery does not sterilize EMT-MET cancer stem cell radiodurans but single fraction 100 to 10,000 Gy microbeam radiosurgery sterilizes them. Device and methods for microbeam chemo-radiosurgery including 250 MeV wakefield electronbeam is disclosed.

Surgery, chemotherapy and broadbeam and microbeam radiosurgery releases billions of abscopal metastasis causing, tumor specific plasma soluble proteins, cell membranes, apoptotic bodies, DNA and RNAs, exosomes like telomere-telomerase, ATM-ATM kinase and others. They and adaptive resistance to chemo-radiosurgery, paraneoplastic and non-paraneoplastic diseases causing immune complexes are removed by pulse flow combined continuous flow ultracentrifugation apheresis and immune affinity chromatography. Chemotherapy and high dose radiation exposed tumor cells and their exosomes are made sensitive to telomerase inhibiting and apoptosis inducing and least toxic epigallocatechin and to heparin bound receptors. They convert triple negative breast tumors into receptor positive tumors which open new avenues for treating most aggressive breast cancers.

Described herein are methods and systems for generating a MV detector image for evaluating the quality of radiation delivery according to a radiotherapy treatment plan. The MV detector image is generated from MV detector measurements of a small number of multi-leaf collimator (MLC) leaf openings.