A computer-implemented method for use in determining a radiation dose distribution in a medical volume, comprises: receiving a volumetric dataset representing the medical volume; performing a selection process of a rendering process for generating a visualization of the volumetric dataset to select at least one sample point in the volumetric dataset on which to perform a radiation determination process; and performing, for the at least one sample point in the volumetric dataset, the radiation dose determination process to determine a radiation dose at the at least one sample point. The method may also include visualizing the volumetric dataset and/or the radiation dose distribution.

A dose rate-volume histogram can be generated for a target volume. The dose rate-volume histogram can be stored in computer system memory and used to generate a radiation treatment plan. The radiation treatment plan can be used as the basis for treating a patient using a radiation treatment system.

A method for delivering radiation treatment may include defining a preliminary trajectory including a plurality of control points. Each control point may be associated with position parameters of a gantry and a couch. The method may also include generating a treatment plan based on the preliminary trajectory by optimizing an intensity and position parameters of a collimator and MLC leaves for each control point. The method may also include decomposing the treatment plan into a delivery trajectory including the plurality of control points. Each of the plurality of control points may be further associated with the optimized intensity, the optimized position parameters of the collimator and the MLC leaves, an output rate, and a motion parameter of each of the gantry, the couch, the collimator, and the MLC leaves. The method may further include instructing a radiation delivery device to deliver the treatment plan according to the delivery trajectory.

It is provided a method for determining arc costs. The method comprises the steps of: determining a plurality of beam orientations; evaluating a set of at least one cost function comprising an intermediate exposure cost function that is evaluated by performing the substeps of: projecting the at least one target volumes on a beam plane; determining an alignment angle based on a collimator angle value; finding any intermediate area in the beam plane along the alignment angle between areas of the at least one target volume projection; determining a value of the intermediate exposure cost function. The method further comprises the steps of: finding a plurality of arcs, wherein each arc comprises a sequence of a plurality of beam orientations; and calculating, for each arc in the plurality of arcs, at least one arc cost based on the cost function values of the beam orientations of the arc.

Techniques for solving a radiotherapy treatment plan optimization problem are provided. The techniques include receiving a radiotherapy treatment plan optimization problem; processing the radiotherapy treatment plan optimization problem with a machine learning model to estimate one or more optimization variables of the radiotherapy treatment plan optimization problem, wherein the machine learning model is trained to establish a relationship between the one or more optimization variables and parameters of a plurality of training radiotherapy treatment plan optimization problems; and generating a solution to the radiotherapy treatment plan optimization problem based on the estimated one or more optimization variables of the radiotherapy treatment plan optimization problem.

A dose rate-volume histogram can be generated for a target volume. The dose rate-volume histogram can be stored in computer system memory and used to generate a radiation treatment plan. The radiation treatment plan can be used as the basis for treating a patient using a radiation treatment system.

A method for delivering radiation treatment may include defining a preliminary trajectory including a plurality of control points. Each control point may be associated with position parameters of a gantry and a couch. The method may also include generating a treatment plan based on the preliminary trajectory by optimizing an intensity and position parameters of a collimator and MLC leaves for each control point. The method may also include decomposing the treatment plan into a delivery trajectory including the plurality of control points. Each of the plurality of control points may be further associated with the optimized intensity, the optimized position parameters of the collimator and the MLC leaves, an output rate, and a motion parameter of each of the gantry, the couch, the collimator, and the MLC leaves. The method may further include instructing a radiation delivery device to deliver the treatment plan according to the delivery trajectory.

Systems and methods for determining a target multi-source model of a radiation source corresponding to an energy spectrum is provided. The systems may obtain an initial multi-source model of the radiation source, which includes an initial phase space file that includes information of a plurality of simulated particles of a plurality of energy levels. The systems may estimate, based on the initial phase space file, a plurality of component PDD curves corresponding to the plurality of energy levels. The systems may obtain a measured PDD curve corresponding to radiation of the energy spectrum. For each energy level, the systems may determine, based on the plurality of component PDD curves and the measured PDD curve, a weight for the each energy level. The systems may further determine the target multi-source model of the radiation source based at least in part on the initial multi-source model and the weights.

An ion-based radiotherapy plan for passive delivery of one or more beams (7) uses an optimization problem set up to allow variation in settings of the range modulating device, and/or settings of the aperture element during the delivery of the first beam, so that said plan will include modulation of the fluence of the beam during the delivery of the beam. The optimization problem is set up to allow variation of the settings of an aperture element (11), a range modulating device (9) during delivery of each beam, so that said plan will include modulation in depth of the beam during the delivery of the beam.

A method for generating a radiation treatment plan is provided. The method may include determining a set of one or more optimization goals for radiation delivery by a therapeutic radiation delivery apparatus. The method may also include determining a plan for radiation delivery from a radiation source of the therapeutic radiation delivery apparatus. The radiation source may be capable of continuously rotating around a subject. The plan may include a plurality of radiation segments. Each radiation segment may be characterized by at least one parameter selected from a start angle, a stop angle, a two-dimensional segment shape, or a segment MU value such that the plurality of radiation segments satisfy the set of one or more optimization goals by superimposing at least two radiation segments from at least two different rotations into a target volume of the subject.