Elekta

A computer-implemented method for managing Cone Beam Computed Tomography, CBCT, imaging of a patient. The method comprises acquiring (102) radiotherapy treatment plan, RTP, information for a RTP. The RTP is for delivering a radiation dose distribution to the patient so as to respect at least one radiotherapy treatment objective. The method further comprises determining (104), based on the acquired RTP information, a measure of sensitivity of the RTP to changes in anatomy of the patient. The measure of sensitivity is a function of position in the patient or a function of radiotherapy beam direction in the RTP. The method further comprises generating (106), based on the determined measure of sensitivity, an imaging protocol for obtaining a reconstructed CBCT image of a volume of the patient by setting a value of at least one parameter in the imaging protocol such that image quality of the reconstructed CBCT image of the patient volume meets an image quality objective for an image processing task. The image quality objective prioritises image quality for positions within the patient volume at which the RTP is sensitive to changes in anatomy. The imaging protocol comprises values for at least one CBCT imaging acquisition parameter and/or at least one CBCT imaging reconstruction parameter.

Disclosed herein is a computer-implemented method for adaptive radiotherapy. The method comprises receiving symptom data, the symptom data being indicative of the existence and/or severity of a symptom experienced by a radiotherapy patient undergoing treatment according to a first radiotherapy treatment plan; obtaining first treatment plan data associated with the first radiotherapy treatment plan; and generating a second radiotherapy treatment plan based on the obtained first treatment plan data and the symptom data.

Disclosed herein are apparatus, methods, systems, and/or computer-readable media for measuring, detecting, determining and/or monitoring radiotherapy beam dose of a radiotherapy device. The apparatus, methods, systems, and/or computer-readable media disclosed herein provide an approach that involves use of a pair of plates for generating a voltage between the pair of plates, and a beam detection volume arranged at least in part between the pair of plates.

Disclosed herein is an extension for increasing a width of at least part of a radiotherapy couch top, the extension comprising: a planar portion configured to support part of a subject thereon; and a fixation mechanism configured to fix the extension onto the couch top such that the planar portion overlays at least part of the couch top.

Disclosed herein is a radiotherapy couch top configured to support a subject thereon and comprising: a first lateral width in a first longitudinal region of the radiotherapy couch top; a second lateral width in a second longitudinal region of the radiotherapy couch top, the second lateral width being smaller than the first lateral width; and a curved lower surface.

Disclosed herein is a radiotherapy couch top configured to support a subject thereon and comprising: a first longitudinal portion with a first lateral width; and a second longitudinal portion with a second lateral width, the second lateral width being smaller than the first lateral width, wherein the second longitudinal portion is integrally formed with the first longitudinal portion.

There is provided a radiotherapy system comprising: a rotatable gantry configured to rotate about a rotation axis; an on-gantry component mounted to the gantry, wherein the on-gantry component is configured to travel between at least a first position and a second position on the gantry, and wherein the on-gantry component is mounted to the gantry such that when the gantry is rotated in a first direction about the rotation axis, the on-gantry component is capable of travelling from the first position to the second position under the influence of gravity.

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Systems and methods are disclosed for monitoring and estimating an anatomic position of a human subject for a radiotherapy treatment session, based on use of an artificial intelligence (AI) model (e.g., a generative AI model comprising a Transformer deep learning neural network), are described. An example method of monitoring anatomic position with a trained AI model includes: receiving position information corresponding to observed positions of a tracked anatomical area of a patient, observed during the radiotherapy treatment session; providing the position information as an input to a trained model trained with temporal sequences of observed anatomical positions from training data; determining an estimated position of the tracked anatomical area of the patient at a future time, based on output of the trained model; and controlling the radiotherapy treatment session based on the estimated position of the tracked anatomical area of the patient.

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