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: The present invention proposes a method for automatically creating a dose prediction model based on existing clinical knowledge that is accumulated from multiple sources without collaborators establishing communication links between each other. According to embodiments of the claimed subject matter, clinics can collaborate in creating a dose prediction model by submitting their treatment plans into a remote computer system (such as a cloud-based system) which aggregates information from various collaborators and produces a model that captures clinical information from all submitted treatment plans. According to further embodiments, the method may contain a step where all patient data submitted by a clinic is made anonymous or the relevant parameters are extracted and condensed prior to submitting them over the communications link in order to comply with local regulations.

Abstract: A control circuit optimizes a radiation-treatment plan (as regards treating at least one target volume for a given patient) by automatically determining a spatially-variant normal tissue constraint as a function, at least in part, of dose distribution for normal tissue that is proximal to the target volume. If desired, the control circuit can repeatedly determine spatially-variant normal tissue constraints while optimizing the radiation-treatment plan. This automatic determination can comprise evaluating dose distributions at specific different distances from the target volume. So configured, the control circuit can effect such evaluation by penalizing, during the optimization of the radiation-treatment plan, dose distribution levels that exceed a predetermined distribution property (such as an aggregation value for the dose values including, but not limited to, an average value of dose values for each of the given specific different distances) at a given one of the specific different distances.

Abstract: A patient support system includes a patient support having a surface for supporting a patient and a longitudinal axis, and a positioner coupled to the patient support for positioning the patient support, wherein the positioner is configured to move the patient support along a path that has an arc, circular, or zig-zag shape, and wherein the path lies within a plane that forms an angle with the surface of the patient support.

Abstract: Determine first information regarding physical-movement limitations pertaining to at least one multi-leaf collimator and also determine second information regarding movement of the treatment target with respect to the given patient. Then, while optimizing a radiation-treatment leaf-sequence plan, constrain individually-planned leaf positions as a function, at least in part, of the first information, the second information, and planned positions of adjacent leaves. By one approach, the first information can comprise information regarding a speed (such as a maximum speed) at which individual leaves of the multi-leaf collimator are able to move during a treatment session. By one approach, the second information can comprise information regarding a distance (such as a maximum distance) that one or more parts of the treatment target may possibly move as compared to a presumed position used during the optimizing of the radiation-treatment leaf-sequence plan.

Abstract: A patient support system includes a patient support having a surface for supporting a patient and a longitudinal axis, and a positioner coupled to the patient support for positioning the patient support, wherein the positioner is configured to move the patient support along a path that has an arc, circular, or zig-zag shape, and wherein the path lies within a plane that forms an angle with the surface of the patient support.

Abstract: The present invention proposes a method for automatically creating a dose prediction model based on existing clinical knowledge that is accumulated from multiple sources without collaborators establishing communication links between each other. According to embodiments of the claimed subject matter, clinics can collaborate in creating a dose prediction model by submitting their treatment plans into a remote computer system (such as a cloud-based system) which aggregates information from various collaborators and produces a model that captures clinical information from all submitted treatment plans. According to further embodiments, the method may contain a step where all patient data submitted by a clinic is made anonymous or the relevant parameters are extracted and condensed prior to submitting them over the communications link in order to comply with local regulations.

Abstract: A control circuit provides a user with an opportunity to designate one or more patient structures for a particular patient that are to be protected from radiation. When optimizing a radiation-treatment plan for that patient, then, the control circuit uses the designated patient structure(s) as an area to be masked from radiation during administration of the radiation-treatment plan. By one approach the aforementioned opportunity to designate patient structures as being designated patient structures comprises providing the user with an opportunity to so designate patient structures via a display. The aforementioned masking can be accomplished as desired including by appropriate use of a multi-leaf collimator.

Abstract: A control circuit identifies (prior to optimizing a radiation-treatment plan) at least one angle (such as one or more gantry angles as correspond to an arc-therapy treatment platform) to provide one or more identified angles. The control circuit then optimizes a radiation-treatment plan with respect to a particular patient target volume by using the identified angle(s) as preferred angles as regards irradiating the patient target volume. Being “preferred,” the radiation-treatment plan is thereby influenced (without being required) towards changing a rate of moving the gantry when traversing the preferred angle(s). For example, the plan can be biased towards slowing down movement of the gantry at such angles to thereby deliver a relatively greater amount of radiation to the patient target volume at the preferred angle.

Abstract: A control circuit has access to information that correlates a plurality of patient-experience outcomes with corresponding delivered-radiation metrics and uses that plurality of patient-experience outcomes in conjunction with developing a radiation-therapy treatment plan for a particular patient. Those patient-experience outcomes can comprise, for example, information regarding how various patients fared post-radiation treatment as regards such things as post-radiation treatment life expectancy, tumor eradication success, and one or more other quality-of-life metrics. These teachings will accommodate using a particular one of the patient-experience outcomes as an optimization goal when optimizing candidate radiation-therapy treatment plans to develop the radiation-therapy treatment plan. In such a case these teachings will further accommodate, if desired, permitting a user to modify one or more optimization objectives while displaying intermediate optimization results.

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 method of delivering radiation in a session includes delivering radiation towards a patient using a radiation system, wherein the radiation is delivered based at least in part on a physiological phase or a position of the patient, after the radiation is delivered, changing a configuration of the radiation system, wherein the act of changing the configuration is performed independent of at least one motion of the patient, and delivering additional radiation towards the patient after the configuration of the radiation system is changed, wherein the acts of delivering radiation and the act of changing the configuration are performed in response to a processor executing a treatment plan that prescribes a plurality of packages and a transition, the transition prescribing the act of changing the configuration of the radiation system when no radiation is being delivered by the radiation system.

Abstract: A patient support system includes a patient support having a surface for supporting a patient and a longitudinal axis, and a positioner coupled to the patient support for positioning the patient support, wherein the positioner is configured to move the patient support along a path that has an arc, circular, or zig-zag shape, and wherein the path lies within a plane that forms an angle with the surface of the patient support.

Abstract: A control circuit optimizes a radiation-treatment plan (as regards treating at least one target volume for a given patient) by automatically determining a spatially-variant normal tissue constraint as a function, at least in part, of dose distribution for normal tissue that is proximal to the target volume. If desired, the control circuit can repeatedly determine spatially-variant normal tissue constraints while optimizing the radiation-treatment plan. This automatic determination can comprise evaluating dose distributions at specific different distances from the target volume. So configured, the control circuit can effect such evaluation by penalizing, during the optimization of the radiation-treatment plan, dose distribution levels that exceed a predetermined distribution property (such as an aggregation value for the dose values including, but not limited to, an average value of dose values for each of the given specific different distances) at a given one of the specific different distances.

Abstract: A control circuit operably couples to a memory having historical information stored therein. This historical information comprises information regarding delivered radiation doses to non-targeted patient volumes for a plurality of different volume presentations. The control circuit iteratively optimizes a radiation-treatment plan for a specific plan using that historical information. The aforementioned historical information can comprise delivered-dose metrics as correspond to different relative distances within given patients. The control circuit can employ such information to determine, for example, an estimated dosage (including, if desired, a corresponding range of estimated dosages) for at least one volume within the specific patient at a specific distance from a specific point of reference. The control circuit can compare such historical information against radiation-treatment plan optimization results to qualitatively assess the radiation-treatment plan optimization results.

Abstract: A control circuit stores a plurality of radiation treatment plan states as pertain to optimization of a given radiation treatment plan. The control circuit detects a user's selection of a particular one of the plurality of radiation treatment plan states and responsively displays dose distribution information as corresponds to that selected state. The control circuit can automatically store at least some of those states and/or can provide the user with an opportunity to selectively save a particular state. The control circuit can provide the user with an opportunity to modify optimization objectives such that at least two of the states correspond to different optimization objectives for the radiation treatment plan. The control circuit can also display a radiation treatment plan state selector to facilitate the user selecting the particular state. An individual selector for each state can provide a visual indication of merit as pertains to each such state.

Abstract: A patient support system includes a patient support having a surface for supporting a patient and a longitudinal axis, and a positioner coupled to the patient support for positioning the patient support, wherein the positioner is configured to move the patient support along a path that has an arc, circular, or zig-zag shape, and wherein the path lies within a plane that forms an angle with the surface of the patient support.

Abstract: Optimization of a radiation-delivery treatment plan can be facilitated by permitting the making of automatic changes to one or more treatment objectives. This can comprise processing radiation-delivery treatment plan parameters with respect to one or more predetermined treatment objectives and then automatically changing that predetermined treatment objective to provide one or more changed treatment objectives (including altered, deleted, and/or added treatment objectives) that can then be used to at least attempt to optimize a radiation-delivery treatment plan. That predetermined treatment objective can comprise, for example, a treatment objective as regards a given treatment volume. The automatic changing of the predetermined treatment objective can occur in response to a variety of stimuli such as detecting a change with respect to a treatment condition such as a change in the presentation of a patient volume of interest.

Abstract: A radiation-delivery treatment plan includes a first value for a limit as pertains to motion compensation-based adjustment of a radiation-delivery parameter during a first portion of a radiation treatment session as well as a second value for that same limit during a second, different portion of the treatment session. By one approach, the radiation-delivery treatment plan selects between this first and second value as a function of a preselected parameter. Examples of such parameters include, but are not limited to, radiation-beam orientation parameters (such as a gantry-based parameter) and/or any of a variety of external surrogates.

Abstract: A radiation-treatment planning apparatus accesses information regarding a treatment target and at least one operational parameter pertaining to a physical characteristic of a given radiation-treatment platform. The apparatus also accesses information regarding a candidate treatment plan using the given platform. The apparatus then optimizes the candidate treatment plan by permitting, temporarily, discontinuities of the at least one operational parameter as between adjacent ones of a plurality of control points to thereby yield an optimized treatment plan. By one approach, this operational parameter can comprise a speed at which a collimator aperture can be changed. In such a case, the aforementioned discontinuities can comprise discontinuities with respect to the speed at which this aperture can be changed. So configured, these teachings will accommodate temporarily permitting speeds that are too fast to be actually performed by the given radiation-treatment platform.