A61N5/1037

FEATURE-SPACE CLUSTERING FOR PHYSIOLOGICAL CYCLE CLASSIFICATION
20220398717 · 2022-12-15 ·

Systems and methods are disclosed for performing operations comprising: receiving a plurality of training images representing different phases of a periodic motion of a target region in a patient; applying a model to the plurality of training images to generate a lower-dimensional feature space representation of the plurality of training images; clustering the lower-dimensional feature space representation of the plurality of training images into a plurality of groups corresponding to the different phases of the periodic motion; and classifying a motion phase associated with a new image of the target region in the patient based on the plurality of groups of the clustered lower-dimensional feature space representation of the plurality of training images.

DOSE MANAGEMENT BASED ON CRYOSTAT VARIATION
20220379139 · 2022-12-01 ·

Systems and methods for generating a radiotherapy treatment plan using information about gantry angle-indexed dose (GAID) variation are discussed. An exemplary system can include an interface to receive a beam model for use in the radiation machine, and a processor that can determine, for the radiation machine, a GAID variation represented by a plurality of radiation doses at different gantry angles. The processor can determine a radiation treatment plan for the patient using the beam model and the GAID variation.

Material inserts for radiation therapy

A system for treating a patient during radiation therapy is disclosed. The system includes a shell, a plurality of material inserts disposed in the shell, where each material insert of the plurality of material inserts respectively shapes a distribution of a dose delivered to the patient by a respective beam of a plurality of beams emitted from a nozzle of a radiation treatment system, and a scaffold component disposed in the shell that holds the plurality material inserts in place relative to the patient such that each material insert lies on a path of at least one of the beams.

ADAPTIVE DOSE ACCUMULATION ALGORITHM

Techniques for adjusting radiotherapy treatment for a patient in real time are provided. The techniques include operations comprising: obtaining, during delivery of a radiotherapy treatment fraction to a patient, one or more images of the patient at a first rate; generating patient motion information at a second rate based on the one or more images obtained at the first rate; receiving, during delivery of the radiotherapy treatment fraction, radiotherapy treatment device settings at a third rate; computing, during delivery of the radiotherapy treatment fraction, dose delivered to the patient with a first level of accuracy based on the generated patient motion information and the radiotherapy treatment device settings; and determining, during delivery of the radiotherapy treatment fraction, a real-time measure of accumulated dose delivered to the patient with a second greater level of accuracy than the first level of accuracy using one or more prior dose computations.

Streamlined, guided on-couch adaptive workflow

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.

System for delivering conformal radiation therapy while simultaneously imaging soft tissue

A device and a process for performing high temporal- and spatial-resolution MR imaging of the anatomy of a patient during intensity modulated radiation therapy (IMRT) to directly measure and control the highly conformal ionizing radiation dose delivered to the patient for the treatment of diseases caused by proliferative tissue disorders. This invention combines the technologies of open MRI, multileaf-collimator or compensating filter-based IMRT delivery, and cobalt teletherapy into a single co-registered and gantry mounted system.

Real-time patient motion monitoring using a magnetic resonance linear accelerator (MRLINAC)
11491348 · 2022-11-08 · ·

Systems and techniques may be used to estimate a real-time patient state during a radiotherapy treatment using a magnetic resonance linear accelerator (MR-Linac). For example, a method may include generating a dictionary of expanded potential patient measurements and corresponding potential patient states using a preliminary motion model. The method may include training, using a machine learning technique, a correspondence motion model relating an input patient measurement to an output patient state using the dictionary. The method may include estimating, using a processor, the patient state corresponding to a 2D MR image using the correspondence motion model. The method may include directing radiation therapy, using the MR-Linac, to a target according to the patient state.

ON-LINE ADAPTIVE DEEP INSPIRATION BREATH-HOLD TREATMENT

A computer-implemented method of performing a radiation therapy process includes: while a patient is disposed in a first position and maintains a first inspiration level, acquiring a set of projection images of a target volume associated with the patient; based on a treatment planning digital volume associated with the radiation therapy process and the set of projection images, generating a synthetic digital volume that includes the target volume; based on a treatment plan associated with the treatment planning digital volume and on the synthetic digital volume, generating a modified treatment fraction; and while the patient remains in the first position and maintains at least the first inspiration level, performing the modified treatment fraction.

REAL-TIME ANATOMIC POSITION MONITORING FOR RADIOTHERAPY TREATMENT CONTROL
20220347490 · 2022-11-03 ·

Systems and methods are disclosed for monitoring anatomic position of a human subject and modifying a radiotherapy treatment based on anatomic position changes, as determined with a regression model trained to estimate movement of a region of interest. Example operations for movement monitoring and therapy control include: obtaining 3D image data for a subject, which provides a reference volume and at least one defined region of interest; obtaining real-time 2D image data corresponding to the subject, captured during the radiotherapy treatment session; extracting features from the 2D image data; producing a relative motion estimation of a region of interest with a machine learning regression model, the model trained to estimate a spatial transformation from the 2D image data based on training from the reference volume; and controlling a radiotherapy beam of a radiotherapy machine used in the radiotherapy session, based on the relative motion estimation.

REAL-TIME MOTION MONITORING USING DEEP LEARNING
20230126640 · 2023-04-27 ·

Systems and methods may be used for estimating instantaneous patient motion (a patient state). The patient state may be estimated based on a 3D reference volume and a stream of images, for example from an image acquisition device. The stream of images may be received in real-time, for example during a radiation therapy treatment. An example method may include encoding the 3D reference volume using a 3D encoder branch of a patient state generator network, encoding the stream of images using a 2D encoder branch of the patient state generator network, and combining the encoded 3D reference volume and the encoded real-time stream of images. The method may include estimating a 3D spatial transform that maps the 3D reference volume to a current patient state by decoding the combined encoding using a 3D decoder branch of the patient state generator network.