Gamma ray detection system (10) comprising a computation system including a signal processing and control system (30), a detection module assembly (13) including at least one detection module (14) configured for detecting gamma ray emissions from a target zone (4), each detection module comprising at least one scintillator plate (16) having a major surface (40a) oriented to generally face the target zone and lateral minor surfaces (40b) defining edges of the scintillator layer, and a plurality of photon detectors oupled to said at least one scintillator plate and connected to the signal processing and control system. The scintillator plate comprises a material having isotopes intrinsically emitting radiation causing intrinsic scintillation events in one or more scintillator plates having an intensity measurable by the photon detectors. The gamma ray detection system comprises a calibration module configured to execute a spatial calibration procedure based on measurements of a plurality of said intrinsic scintillation events output (37) by the photon detectors, the spatial calibration procedure for determining spatial positions of scintillating events in the scintillator plate as a function of the outputs of the photon detectors.

To provide a BNCT treatment system capable of formulating a neutron irradiation mode based on diagnostic data on a subject to be treated. A BNCT treatment system 2, used for performing neutron capture therapy, includes: a Hexatron 3 including first to sixth neutron irradiation devices 3A to 3F which emit neutrons; and a controller 4 configured to control neutron irradiation by the first to sixth neutron irradiation devices 3A to 3F. The BNCT treatment system 2 includes: an HOP 5 configured to formulate a treatment plan (a mode for controlling neutron irradiation of the first to sixth neutron irradiation devices 3A to 3F by the controller 4) based on diagnostic data on a patient PA; an HSP 6 configured to monitor each component member; and a management unit 7 configured to manage the entire system.

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.

The present disclosure provides a system comprising a SPECT or PET device; a CT device; and a computer comprising memory and a processor in communication with the memory, the memory comprising a computer application program for a method of performing dosimetric analysis of an organ. The computer application program is executable by the processor to perform the method. The method comprising receiving single photon emission computed tomography (SPECT) or positron emission tomography (PET) images at time instances, the SPECT or PET images relating to the organ. The method then receives a computed tomography (CT) image at one of the time instances, the CT image relating to the organ. Virtual CT images are then generated at the other time instances based on the received SPECT or PET images and the CT image. An absorbed dose of ionising radiation on the organ can then be measured based on the received SPECT or PET images, the received CT image, and the generated virtual CT images. The method generates the virtual CT images using any one of: SPECT to SPECT (or PET to PET) registration, CT to SPECT (PET) registration, and SPECT (PET) to CT registration.

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.

The present disclosure relates to a method and apparatus for fast Monte Carlo (MC) dose calculation using a virtual source model (VSM). The method includes: receiving three-dimensional (3D) images obtained by a computed tomography (CT) system; receiving 3D planned dose images, 3D organ segmentation contour images, and radiotherapy plans generated by a treatment planning system (TPS); processing all 3D images to have the same spatial resolution and matrix size; processing 3D CT images to convert image intensity to density; processing the radiotherapy plans to generate instructions on how to simulate plan delivery; building VSM using inverse cumulative density function (CDF) tables for the simulation of radiotherapy plans, wherein the step of building VSM comprises: receiving output data files containing phase-space information for the radiation output of a specific medical linear accelerator treatment head; calculating the probability of particles' inplane and crossplane positions reverse transported from the phase-space surface back to the treatment head; calculating the Gaussian means and standard deviations of particles' positions at the treatment head and determining the criteria for particle source; calculating the probabilities for each particle source; calculating the probabilities for the medical linear accelerator treatment head to produce different particle species; binning the inplane position probability information of particles into a single histogram for each source and particle species; binning the crossplane position probability information of particles into histograms for each bin of the inplane position histogram for each source and particle species; binning the inplane direction cosine probability information of particles into histograms for each bin of the inplane position histogram for each source and particle species; binning the crossplane direction cosine probability information of particles into histograms for each bin of the crossplane position histogram for each source and particle species; binning the kinetic energy probability information of particles into radially binned histograms for each source and particle species; converting probability densities for inplane and crossplane positions, inplane and crossplane direction cosines, and kinetic energies histograms into cumulative probability densities for each source and particle species; and inverting cumulative probability densities and converting into probability binned inverse CDF tables; simulating and transporting external beams using VSM through virtual treatment machines to the 3D CT densities according to radiotherapy plans to produce 3D images of simulated patient dose;

Disclosed are a neutron capture therapy apparatus and an operation method of a monitoring system thereof. The neutron capture therapy apparatus includes a neutron beam irradiation system, a measurement system and a monitoring system. The neutron beam irradiation system is used for generating a neutron beam suitable for carrying out neutron irradiation therapy on a sick body, the measurement system is used for measuring real-time irradiation parameters during a neutron beam irradiation therapy process, and the monitoring system is used for controlling the whole neutron beam irradiation process. The monitoring system includes an input section for inputting preset irradiation parameters, a storage section for storing the irradiation parameters, a modification section for modifying some of the irradiation parameters in the storage section, and a display section for displaying the irradiation parameters in real time.

An example method of radiation therapy in a radiation therapy system that includes a gantry with a treatment-delivering X-ray source and an imaging X-ray source mounted thereon is described. The method includes rotating the gantry in a first direction at a first rotational velocity about an open bore and concurrently rotating an annular support structure at a second rotational velocity about the open bore, wherein the second rotational velocity is less than the first rotational velocity. While continuing to rotate the gantry in the first direction about the open bore from a first position to a treatment position, the method also includes generating multiple images of a target volume disposed in the bore using the imaging X-ray source. Upon rotating the gantry to the treatment position, the method includes initiating delivery of a treatment beam to the target volume with the treatment-delivering X-ray source.

Multi-modal imaging capsule for image-guided proton beam therapy, consisting of a biocompatible polymer layer, .sup.18O-enriched water, and a contrast agent. The biocompatible capsule may be inserted near or inside a tumor under the guidance of X-ray, magnetic resonance, or ultrasonography imaging. Upon proton beam irradiation, the capsule emits positrons, allowing the tumor to be imaged and tracked by a PET detector.

Dose analysis radiotherapy systems and methods for determine delivered radiotherapy dose, dose rate, irradiation time and position information and planned radiotherapy dose, dose rate, irradiation time and position information. The dose analysis systems and methods further compare the as delivered dose, dose rate, irradiation time and position information to the planned dose, dose rate, irradiation time and position information to generate a graphical representation of one or more of the delivered dose, dose rate, irradiation time and position information versus planned dose, dose rate, irradiation time and position information.