Methods of beam angle optimization for intensity modulated radiotherapy (IMRT) treatment include determining beam's eye view (BEV) regions and a BEV region connectivity manifold by evaluating dose response of each region of interest for each vertex in a delivery coordinate space (DCS). The information contained in the BEV regions and the BEV region connectivity manifold is used to guide an optimizer to find optimal field geometries in the IMRT treatment. To improve the visibility of insufficiently exposed voxels of planning target volumes (PTVs), a post-processing step may be performed to enlarge certain BEV regions, which are considered for exposing during treatment trajectory optimization.

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.

Presented systems and methods enable efficient and effective robust radiation treatment planning and treatment, including analysis of dose rate robustness. In one embodiment, a method comprising accessing treatment plan information, accessing information corresponding to an uncertainty associated with implementation of the radiation treatment plan, and generating a histogram, wherein the histogram conveys a characteristic of the treatment plan including an impact of the uncertainty on the characteristic. The histogram can be a dose rate volume histogram and can be utilized to test a degree of robustness of a treatment plan (e.g., including allowance for uncertainty scenarios, etc.). The uncertainty can be associated with potential variation associated with tolerances (e.g., radiation system/machine performance tolerance, patient characteristic tolerances, etc.) and set up issues (e.g., variation in initial system/machine set up, variation patient setup/position, etc.)

The dose rate of voxels within a particle beam (e.g., proton beam) treatment field delivered using pencil beam scanning (PBS) is calculated, and a representative dose rate for the particle beam treatment field is reported. The calculations account for a dose accumulation in a local region or a sub-volume (e.g., a voxel) as a function of time.

A memory has a fluence map that corresponds to a particular patient stored therein. This memory also has at least one deep learning model stored therein trained to deduce a leaf sequence for a multi-leaf collimator from a fluence map. A control circuit operably coupled to that memory iteratively optimizes a radiation treatment plan to administer therapeutic radiation to that patient by, at least in part, generating a leaf sequence as a function of the at least one deep learning model and the fluence map that corresponds to the patient.

Information associated with a radiation treatment plan includes, for example, values of dose per voxel in a target volume, values of dose rate per voxel in the target volume, and values of parameters used when generating the values of dose per voxel and the values of dose rate per voxel. Renderings that include, for example, a rendering of an image of or including the target volume, and a rendering of selected values of the radiation treatment plan, are displayed. When a selection of a region of one of the renderings is received, a displayed characteristic of another one of the renderings is changed based on the selection.

Methods of and devices for detecting a measurable characteristic of the gas sample. The methods and devices are able to detect a value of or a change of measurable characteristic (e.g., such as chemical concentrations), a change of chemical compositions and/or biological responses of a living organism that are induced by a stressor. The biological responses are able to include cellular stress, damage, and immune responses. The stressor is able to include an exposure to ionizing radiation. The effects of the stressors are able to be monitored in terms of changes in the chemical concentrations and chemical compositions in an exhaled breath. The chemicals are able to function as bio-markers. The chemicals that are to be monitored are able to include nitric oxide, carbon monoxide, carbon dioxide, ethane, and other molecules related to specific disease resulting from the stressor.

The aim of the invention is to provide a planner with the opportunity to effect local improvement of an IMRT treatment plan which is available to him. To this end, a method for customizing a dose distribution setting for a technical appliance in tumor therapy is proposed.

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.

Nominal values of parameters, and perturbations of the nominal values, that are associated with previously defined radiation treatment plans are accessed. For each treatment field of the treatment plans, a field-specific planning target volume (fsPTV) is determined based on those perturbations. At least one clinical target volume (CTV) and at least one organ-at-risk (OAR) volume are also delineated. Each OAR includes at least one sub-volume that is delineated based on spatial relationships between each OAR and the CTV and the fsPTV for each treatment field. Dose distributions for the sub-volumes are determined based on the nominal values and the perturbations. One or more dose prediction models are generated for each sub-volume. The dose prediction model(s) are trained using the dose distributions.