An implant planning system aids delivery of radiation to tumor sites of a patient. The system allows a user to test various combinations of virtual implants, each associated with a corresponding physical implant (e.g., a carrier with an embedded radioactive seed), and to view the dosage area of the virtual implants so that adjustments to the virtual implants may be made until a prescribed dose of radiation to a treatment area is achieved. A treatment plan developed based on the virtual implants may then be used in surgical implantation of the corresponding physical implants. For example, the implant configuration of the treatment plan may be projected onto a treatment surface of a patient, such as in a surgical room, so that physical implants may be placed according to the projected image of the virtual implants.

A photon source emits a flattening filter-free photon beam. A control circuit operably couples to a multi-layer multi-leaf collimator that is disposed between the photon source and a treatment area of a patient. The control circuit automatically arranges operation of some, but not all, of the layers of the multi-layer multi-leaf collimator to serve as a virtual flattening filter with respect to the flattening filter-free photon beam emitted by the photon source. By one approach, another of the layers of the multi-layer multi-leaf collimator serves to form a treatment aperture corresponding to a shape of the treatment area of the patient. By one approach the control circuit comprises an integral part of a treatment platform (as versus a dedicated treatment planning platform) and can carry out most or even essentially all of the planning steps that lead to administration of the treatment to a patient.

Disclosed herein are methods and systems to optimize a radiation therapy treatment plan using dose distribution values predicted via a trained artificial intelligence model. A server trains the AI model using a training dataset comprising data associated with a plurality of previously implemented radiation therapy treatments on a plurality of previous patients and dose distributions associated with one or more organs of each previous patient. The server then executes the trained AI model to predict dose distribution for a patient. The server then displays a heat map illustrating the predicted values, transmits the predicted values to a plan optimizer to generate an optimized treatment plan for the patient, and/or transmits an alert when a treatment plan generated by a plan optimizer deviates from rules and thresholds indicated within the patient's plan objectives.

A radiation therapy system includes an X-ray imaging system that is configured with a combined and simplified filter and collimator positioning mechanism. In addition, an X-ray imager of the RT system is only positioned at a few discrete locations within a plane that is a fixed distance from the imaging X-ray source when generating X-ray images. As a result, for each of these discrete imaging positions, the simplified filter and collimator positioning mechanism positions a specific collimator-filter combination in a specific location between the X-ray source and the imager.

To overcome the difficulties inherent in conventional treatment planning approaches, new techniques are described herein for providing an intuitive user interface for automatic structure derivation in patient modeling. In an embodiment, a graphical user interface is provided that provides a list of structures of a specified region. The interface uses medical terminology instead of mathematical one. In one or more embodiments, the list of structures may be a pre-defined list of structures that correspond to that region for the purposes of treatment planning. A user is able to actuate a toggle to include and/or exclude each of the structures separately. In one or more embodiments, the user is also able to actuate a toggle to define a perimeter around each included structure, and further define a margin around the perimeter. The user is also able to specify whether the desired output should include a union or the intersection of all included structures.

A method of generating a treatment plan for treating a patient with radiotherapy, the method includes obtaining a plurality of sample plans, which are generated by use of a knowledge base comprising historical treatment plans and patient data. The method also includes performing a multi-criteria optimization based on the plurality of sample plans to construct a Pareto frontier, where the plurality of sample plans are evaluated with at least two objectives measuring qualities of the plurality of sample plans such that treatment plans on the constructed Pareto frontier are Pareto optimal with respect to the objectives. The method further includes identifying a treatment plan by use of the constructed Pareto frontier.

Example methods and apparatuses of controlling a user interface with a plurality of input mechanisms are disclosed. One example method includes causing a first set of input mechanisms in the plurality of input mechanisms to be visually emphasized via a first visual technique while a second set of input mechanisms in the plurality of input mechanisms is not visually emphasized via the first visual technique, receiving a user input via an input mechanism that is included in the first set, based on the user input, determining a third set of input mechanisms in the plurality of input mechanisms and a fourth set of input mechanisms in the plurality of input mechanisms, and causing the third set of input mechanisms to be visually emphasized via the first visual technique while the fourth set of available input mechanisms is not visually emphasized via the first visual technique.

Disclosed are a neutron dose detection apparatus and a neutron capture therapy device. The neutron dose detection apparatus includes at least two counting rate channels and a counting rate channel selection unit used for selecting one of the at least one counting rate channels. The counting rate channel includes a detector used for detecting neutrons and outputting a signal, a signal processing unit used for processing the signal output by the detector, and a counter used for counting the signal output by the signal processing unit.

Disclosed herein are radiotherapy systems and methods that can display a workflow-oriented graphical user interface(s). In an embodiment, a system comprises a first display in communication with a server, the first display configured to display a first graphical user interface; a second display in communication with the server, the second display configured to display a second graphical user interface, wherein the server is configured to: present the first graphical user interface for displaying on the first display, wherein the first graphical user interface contains one or more pages corresponding to one or more stages of a radiotherapy treatment, wherein the server transitions from a first page of the one or more pages representing a first stage to a second page of the one or more pages representing a second stage responsive to an indication that at least a predetermined portion of tasks associated with the first stage has been satisfied.

For the delivery of high precision radiation treatment, the accuracy with which a target is irradiated at individual gantry, collimator and patient couch orientation is traditionally verified in 2D. With the QA device described herein, the coverage of the gantry is uniquely measured in 3D. The method of the present invention, combining with the collimator and patient couch measurements, allows the reconstruction of the target coverage in full 3D, which was not possible before. In addition, the method of the present invention can be applied to decompose the traditional quality assurance measurements of combined gantry, collimator and patient couch orientations with standard devices. Such an application provides a comprehensive description of the irradiation accuracy.