Disclosed herein are systems and methods for identifying radiation therapy treatment data for patients. A processor accesses a neural network trained based on a first set of data generated from characteristic values of a first set of patients that received treatment at one or more first radiotherapy machines. The processor executes the neural network using a second set of data comprising characteristic values of a second set of patients receiving treatment at one or more second radiotherapy machines. The processor executes a calibration model using an output of the neural network based on the second set of data to output a calibration value. The processor executes the neural network using a set of characteristics of a first patient to output a first confidence score associated with a first treatment attribute. The processor then adjusts the first confidence score according to the calibration value to predict the first treatment attribute.

Disclosed is a computer-implemented method for determining a position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a corresponding computer program, a non-transitory program storage medium storing such a program and a computer for executing the program, as well as a system for the position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a system comprising an electronic data storage device and the aforementioned computer.

Disclosed herein is a medical instrument (100, 200, 300, 400, 500, 600, 900) comprising a subject support (102) configured for supporting a subject (110) in a Fowler's position during a magnetic resonance imaging examination. The subject support comprises a leg support region (104) configured for supporting a leg region of the subject horizontally. The subject support further comprises a thoracic support (106) configured for supporting an upper body region of the subject. The subject support is configured such that the thoracic support is inclined (108) with respect to the leg support region to hold the subject in the Fowler's position. The medical instrument further comprises a breast support (114). The breast support comprises a planar support surface (116) configured for supporting breasts of the subject. The breast support is connected to the subject support. The support surface is configured for being horizontal during the magnetic resonance imaging examination.

An example particle therapy system includes a toroid-shaped gantry having a central axis. The toroid-shaped gantry has a cover. The cover includes one or more segments that are rotatable at least partly around the central axis of the toroid-shaped gantry to create an unobstructed opening in the toroid-shaped gantry. The particle therapy system includes a patient couch configured to move relative to a hole in the toroid-shaped gantry, an imaging system coupled to an interior of the toroid-shaped gantry and configured for rotation about the hole in the toroid-shaped gantry, where the imaging system is configured to capture images of a patient on the patient couch, and a nozzle coupled to the interior of the toroid-shaped gantry and configured for rotation about the hole in the toroid-shaped gantry. The nozzle is configured to deliver radiation to a target in the patient based on one or more of the images.

Disclosed herein is a method of positioning a patient for radio-therapy treatment using a radiotherapy device. The method comprises determining an identity of a treatment beam that is to be used to treat the patient, determining an offset between a reference location and an isocentre location for the identified treatment beam that is to be used to treat the patient, and changing a spatial relationship between the patient and at least a part of the radiotherapy device, according to the determined offset.

Disclosed herein are systems and methods for identifying radiation therapy treatment data for patients. A processor accesses a neural network trained based on a first set of data generated from characteristic values of a first set of patients that received treatment at one or more first radiotherapy machines. The processor executes the neural network using a second set of data comprising characteristic values of a second set of patients receiving treatment at one or more second radiotherapy machines. The processor executes a calibration model using an output of the neural network based on the second set of data to output a calibration value. The processor executes the neural network using a set of characteristics of a first patient to output a first confidence score associated with a first treatment attribute. The processor then adjusts the first confidence score according to the calibration value to predict the first treatment attribute.

A method for planning a scan path for intraoperative radiation therapy may comprise acquiring a plurality of images of a region of interest through an auxiliary scanning component, establishing a 3D model of the region of interest based on the plurality of images of the region of interest, determining a radiation therapy volume based on the 3D model of the region of interest, and planning a scan path for a radiation therapy component to scan the radiation therapy volume.

To enable an appropriate and quick detection of a change in an internal structure of a patient, a computer program causes a computer to detect a change in an internal structure of a patient. The process includes calculating a second water equivalent thickness obtained from a second three-dimensional image being a three-dimensional image of a patient, which is newly obtained; a process of calculating a change of a first water equivalent thickness from the second water equivalent thickness, the first water equivalent thickness being obtained from a first three-dimensional image being a three-dimensional image of the patient in treatment planning; and a process of calculating a dose volume histogram change for calculating a change in a dose volume histogram from the treatment plan, based on the calculated water equivalent thickness change and correlation information indicating a correlation between a water equivalent thickness change value and dose distribution information.

Provided is a neutron beam transmission adjusting device including a neutron beam transmission unit including a neutron reactant and capable of modulating an energy and/or a flux of a neutron beam transmitted through the neutron beam transmission unit.

Disclosed herein are systems and methods for monitoring calibration of positron emission tomography (PET) systems. In some variations, the systems include an imaging assembly having a gantry comprising a plurality of positron emission detectors. A housing may be coupled to the gantry, and the housing may include a bore and a radiation source holder spaced away from a patient scan region within the bore. A processor may be configured to receive positron emission data from the positron emission detectors and to distinguish the positron emission data from the radiation source holder and from the patient scan region. A fault signal may be generated when the positron emission data from the radiation source holder exceeds one or more threshold parameters or criteria.