Siemens Healthineers International Ag

Petri Hirvonen

Matti Ropo

Timo K Koponen

Perttu Niemela

Pierre Lansonneur

Michiko Rossi

Viljo Petaja

Douglas Allen Barnett

Pavel Falkovskiy

An initial, relatively coarse arrangement of spots in a target volume and a respective dose distribution per spot are accessed from memory or determined. If the dose distributions of neighboring spots do not satisfy a similarity criterion, then a new set of spots with finer spacing is determined for the regions that include dissimilar spots (e.g., spots are added between the dissimilar spots), and spot dose distributions are determined for the new spot arrangement. The process is repeated until the similarity criterion is satisfied for all or a threshold number of spots or until a minimum spot spacing is reached. The final arrangement of spots and dose distributions for the spots can be stored. During subsequent optimization of a treatment plan based on the final arrangement of spots, a dose distribution for a point that is between the spots can be determined by interpolating the dose distributions of nearby spots.

Radiation treatment planning systems and methods with interpolable spot placements and dose distributions

A radiation treatment plan for a particular patient is optimized that provides corresponding resultant radiation dosing information. Such optimization can include, by one approach, calculating a corresponding influence matrix. Upon detecting at least one manual edit to at least one spot weight that corresponds to the radiation treatment plan, these teachings can provide for responsively generating new radiation dosing information in at least near real-time as a function of a corresponding influence matrix.

Method and apparatus to detect and respond to radiation treatment plan spot weight edits

A crystalline structure modeling methodology that is conventionally used to model crystalline matter down to the atomic level is instead used to determine spot placement for radiation treatment. The cross-sectional shape of a treatment target is specified; locations (peaks) in a density field inside the shape are determined using the crystalline structure model; locations of spots in the treatment target for spot scanning are determined, where the locations correspond to the locations (peaks) inside the shape determined using the crystalline structure model; and the locations of the spots are stored as candidates for potential inclusion in a radiation treatment plan.

Methods and systems using modeling of crystalline materials for spot placement for radiation therapy

These teachings provide for quickly yet accurately forming an influence matrix by generating the influence matrix via integration with a Monte Carlo particle transport simulation. The resultant influence matrix can then be utilized in an ordinary manner when optimizing a radiation treatment plan. By one approach, the foregoing comprises generating the influence matrix via integration with a Monte Carlo particle transport simulation on a particle-by-particle basis. For example, for each particle, these teachings can provide for identifying a spot to which the particle belongs and then adding a dose deposited by the particle during transport to an influence matrix element that corresponds to a spot to which the particle belongs and a voxel to where the dose was deposited.

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Espoo, Finland

Petri Hirvonen