Abstract: Solutions are provided herein that specifically accounts for biological effects of tissue during radiation planning (such as treatment planning). In one or more embodiments, the biological effects may be calculated by accessing a knowledge base to determine reference data comprising at least one biological characteristic corresponding to the at least one organ, predicting a biological effect for the plurality of identified structures based on the biological characteristic corresponding to the at least one organ, and generating or modifying a radiation plan based on the biological effect. By incorporating biological data and fraction dose information, dose-estimation models can be created and trained to more accurately estimate dose absorption and effectiveness. Moreover, existing estimation models may be adapted to create dose estimations that account for the biological efficiency of target structures.

Abstract: A radiation-treatment plan that comprises a plurality of dose-delivery fractions can be optimized by using fraction dose objectives and at least one other, different dose objective. This use of fraction dose objectives can comprise accumulating doses delivered in previous dose-delivery fractions. The other, different dose objective can comprise a remaining total dose objective, a predictive dose objective, or some other dose objective of choice. An existing radiation-treatment plan having a corresponding resultant quality and that is defined, at least in part, by at least one delivery parameter can be re-optimized by specifying at least one constraint as regards that delivery parameter as a function, at least in part, of that resultant quality and then applying that constraint when re-optimizing the existing radiation-treatment plan.

Abstract: A control circuit forms a radiation therapy treatment plan. By one approach this comprises displaying a structure dose volume histogram on a display and detecting when a user directly manipulates the displayed structure dose volume histogram. In response to detecting that manipulation the control circuit uses a corresponding virtual set of optimization objectives to optimize a radiation therapy treatment plan. If desired, the control circuit can also use weighted optimization objectives when optimizing the radiation therapy treatment plan. Also if desired, the control circuit can use only a low-resolution approximate geometry to represent a particular trajectory as corresponds to different exposure fields for the radiation therapy to be administered when initially optimizing the radiation therapy treatment plan. The control circuit can then subsequently use a high-resolution geometry to represent that trajectory to further optimize the radiation therapy treatment plan.

Abstract: A control circuit administers a radiation treatment plan that specifies a planned total radiation dose for a radiation treatment session for a given patient by modulating a radiation beam with at least one high-resolution aperture that is formed using one of a plurality of linearly-sequential high-resolution aperture possibilities. By one approach the foregoing comprises modulating the radiation beam using at least substantially only high-resolution apertures that are formed using a plurality of the linearly-sequential high-resolution aperture possibilities. In some cases the foregoing can comprise administering the radiation treatment plan using at least two separate radiation exposures for only a single treatment field, in which case, by one approach, each of the separate radiation exposures for the single treatment field can comprise modulating the radiation beam using at least substantially only high-resolution apertures.

Abstract: A multi-layer multi-leaf collimation system includes at least a first layer of collimation leaves that are vertically offset with respect to a second layer of collimation leaves. A control circuit generates a preliminary radiation treatment plan using a model of a radiation therapy treatment platform using a single-layer multi-leaf collimation system following which the control circuit generates a final radiation treatment plan that takes into account at least a second layer of collimation leaves. The resultant final radiation treatment plan can then be used to administer radiation to a patient using the aforementioned multi-layer multi-leaf collimation system.

Abstract: System and method for automatically generate therapy plan parameters by use of an integrate model with extended applicable regions. The integrated model integrates multiple predictive models from which a suitable predictive model can be selected automatically to perform prediction for a new patient case. The integrated model may operate to evaluate prediction results generated by each predictive model and the associated prediction reliabilities and selectively output a satisfactory prediction. Alternatively, the integrated model may select a suitable predictive model by a decision hierarchy in which each level corresponds to divisions of a patient data feature set and divisions on a subordinate level are nested with divisions on a superordinate level.

Abstract: A treatment planning method and system for optimizing a treatment plan used to irradiate a treatment volume including a target volume, such as a tumor, is disclosed. In accordance with the present invention, gradients of a cost function that defines a treatment volume are back projected to a surface of interest. The method and system of preferred embodiments of the present invention calculate the gradients with respect to the dose received by the treatment volume. Machine parameters that are associated with the surface of interest may then be optimized based on the back projected gradients.