Abstract: At least one example embodiment provides a method including obtaining a first image, the first image including a light field on a patient, the light field being generated by a treatment system; obtaining a treatment plan outline, the treatment plan outline including an area of the patient for a treatment; determining positioning information based on the first image and the treatment plan outline, the positioning information including an indicator of a position of the treatment system with respect to the patient; and controlling the treatment system based on the positioning information.

Abstract: At least one example embodiment provides a method including obtaining a surface of a patient, obtaining first treatment information for the patient, the first treatment information associated with a treatment for the patient, the first treatment information corresponding to at least one of a treatment intent for the patient, a treatment plan for the patient or a structure of the patient, obtaining at least one model based on the first treatment information for the patient and determining a region of interest of the patient based on the surface of the patient and the at least one model.

Abstract: A three-dimensional model for a patient fixation device that serves to immobilize at least a portion of a particular patient when capturing CT image information of that patient is accessed and then registered with the pixels that correspond to the patient fixation device in the CT image. The model can specify rules of movement for each of a plurality of structural elements that comprise the patient fixation device and that are capable of movement relative to one another. By one approach the aforementioned registration occurs on a part-by-part basis for each of the structural elements. Following registration, the CT image can be automatically segmented.

Abstract: These teachings provide for accessing optimization information comprising at least one isocenter that corresponds to a body outline for a particular patient, field geometry information for a particular radiation treatment platform, and dosimetric data. The optimization information can further comprise a model of a body outline for the patient. A control circuit optimizes a radiation treatment plan as a function of the optimization information to provide an optimized radiation treatment plan where radiation dose levels delivered to the particular patient from a particular field depends on the relative volume magnitude of field path intersections to thereby reduce radiation dose delivery to healthy patient tissue in regions having relatively more overlapping fields.

Abstract: A method of generating a treatment plan for treating a patient with radiotherapy, the method includes obtaining a plurality of sample plans, which are generated by use of a knowledge base comprising historical treatment plans and patient data. The method also includes performing a multi-criteria optimization based on the plurality of sample plans to construct a Pareto frontier, where the plurality of sample plans are evaluated with at least two objectives measuring qualities of the plurality of sample plans such that treatment plans on the constructed Pareto frontier are Pareto optimal with respect to the objectives. The method further includes identifying a treatment plan by use of the constructed Pareto frontier.

Abstract: A method of generating a treatment plan for treating a patient with radiotherapy, the method includes obtaining a plurality of sample plans, which are generated by use of a knowledge base comprising historical treatment plans and patient data. The method also includes performing a multi-criteria optimization based on the plurality of sample plans to construct a Pareto frontier, where the plurality of sample plans are evaluated with at least two objectives measuring qualities of the plurality of sample plans such that treatment plans on the constructed Pareto frontier are Pareto optimal with respect to the objectives. The method further includes identifying a treatment plan by use of the constructed Pareto frontier.

Abstract: A three-dimensional model for a patient fixation device that serves to immobilize at least a portion of a particular patient when capturing CT image information of that patient is accessed and then registered with the pixels that correspond to the patient fixation device in the CT image. The model can specify rules of movement for each of a plurality of structural elements that comprise the patient fixation device and that are capable of movement relative to one another. By one approach the aforementioned registration occurs on a part-by-part basis for each of the structural elements. Following registration, the CT image can be automatically segmented.

Abstract: A three-dimensional model for a patient fixation device that serves to immobilize at least a portion of a particular patient when capturing CT image information of that patient is accessed and then registered with the pixels that correspond to the patient fixation device in the CT image. The model can specify rules of movement for each of a plurality of structural elements that comprise the patient fixation device and that are capable of movement relative to one another. By one approach the aforementioned registration occurs on a part-by-part basis for each of the structural elements. Following registration, the CT image can be automatically segmented.

Abstract: A control circuit accesses topograms of a patient that include patient content that is beyond the portion of the patient that appears in the three-dimensional computed tomography (CT) images for that patient. The control circuit uses those topograms to derive a virtual volumetric structure representing at least some of the patient content that is beyond the aforementioned portion of the patient that appears in the 3D CT images. That virtual volumetric structure can then be used to predict potential collisions when assessing a radiation treatment plan for the patient that utilizes the aforementioned radiation treatment platform. By one approach the topograms include at least two substantially orthographic views of the aforementioned patient content.

Abstract: These teachings provide for accessing optimization information comprising at least one isocenter that corresponds to a body outline for a particular patient, field geometry information for a particular radiation treatment platform, and dosimetric data. The optimization information can further comprise a model of a body outline for the patient. A control circuit optimizes a radiation treatment plan as a function of the optimization information to provide an optimized radiation treatment plan where radiation dose levels delivered to the particular patient from a particular field depends on the relative volume magnitude of field path intersections to thereby reduce radiation dose delivery to healthy patient tissue in regions having relatively more overlapping fields.

Abstract: In the context of a multi-criteria optimization workspace, a control circuit provides a user opportunity to modify radiation treatment plan optimization objective values, wherein the optimization objectives include at least one of a radiation treatment plan complexity optimization objective and a radiation treatment delivery time optimization objective. These teachings then provide for the control circuit receiving input from the user comprising a change to at least one of these optimization objective values. By one approach the control circuit first accesses a prioritized list of clinical goals and automatically generates optimization objectives as a function of the prioritized list of clinical goals.

Abstract: A three-dimensional model for a patient fixation device that serves to immobilize at least a portion of a particular patient when capturing CT image information of that patient is accessed and then registered with the pixels that correspond to the patient fixation device in the CT image. The model can specify rules of movement for each of a plurality of structural elements that comprise the patient fixation device and that are capable of movement relative to one another. By one approach the aforementioned registration occurs on a part-by-part basis for each of the structural elements. Following registration, the CT image can be automatically segmented.

Abstract: A control circuit accesses topograms of a patient that include patient content that is beyond the portion of the patient that appears in the three-dimensional computed tomography (CT) images for that patient. The control circuit uses those topograms to derive a virtual volumetric structure representing at least some of the patient content that is beyond the aforementioned portion of the patient that appears in the 3D CT images. That virtual volumetric structure can then be used to predict potential collisions when assessing a radiation treatment plan for the patient that utilizes the aforementioned radiation treatment platform. By one approach the topograms include at least two substantially orthographic views of the aforementioned patient content.

Abstract: A system generally includes at least one computing device having a user interface and a display interface. The computing device is configured to generate at least one desktop that can be viewed by a user via the display interface and to access a plurality of functionality modules that are each configured to receive at least one radiotherapy parameter. The computing device is configured to enable the user, via the user interface, to place the functionality modules onto the desktop. The computing device is configured to enable the user, via the user interface, to connect one of the placed functionality modules to at least another one to commence the generation of at least one workflow output. The computing device is also configured to enable the user, via the user interface, to connect a plurality of input components to the placed functionality modules to finalize the generation of the workflow output.

Abstract: A system generally includes at least one computing device having a user interface and a display interface. The computing device is configured to generate at least one desktop that can be viewed by a user via the display interface and to access a plurality of functionality modules that are each configured to receive at least one radiotherapy parameter. The computing device is configured to enable the user, via the user interface, to place the functionality modules onto the desktop. The computing device is configured to enable the user, via the user interface, to connect one of the placed functionality modules to at least another one to commence the generation of at least one workflow output. The computing device is also configured to enable the user, via the user interface, to connect a plurality of input components to the placed functionality modules to finalize the generation of the workflow output.

Abstract: A method of generating a treatment plan for treating a patient with radiotherapy, the method includes obtaining a plurality of sample plans, which are generated by use of a knowledge base comprising historical treatment plans and patient data. The method also includes performing a multi-criteria optimization based on the plurality of sample plans to construct a Pareto frontier, where the plurality of sample plans are evaluated with at least two objectives measuring qualities of the plurality of sample plans such that treatment plans on the constructed Pareto frontier are Pareto optimal with respect to the objectives. The method further includes identifying a treatment plan by use of the constructed Pareto frontier.