Abstract: In a radiation treatment plan that includes a plurality of treatment fields of multiple treatment modalities, such as IMRT modality and dynamic treatment path modality (e.g., VMAT and conformal arc therapy), an optimized spatial point sequence may be determined that optimizes the total treatment time, which includes both the beam-on time (i.e., during the delivery of radiation dose) and the beam-off time (i.e., during transitions between consecutive treatment fields). The result is a time-ordered field trajectory that intermixes and interleaves different treatment fields. In one embodiment, a dynamic treatment path may be cut into a plurality of sections, and one or more IMRT fields may be inserted between the plurality of sections.

Abstract: After accessing optimization information for a particular patient and for a particular radiation treatment platform, a control circuit generates an optimized radiation treatment plan by processing the optimization information using direct-aperture-optimization that includes fluence-based sub-optimization. By one approach, the control circuit includes the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization. By one approach, the control circuit is configured to include only a few iterations of the fluence-based sub-optimization when including the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization.

Abstract: After accessing optimization information for a particular patient and for a particular radiation treatment platform, a control circuit generates an optimized radiation treatment plan by processing the optimization information using direct-aperture-optimization that includes fluence-based sub-optimization. By one approach, the control circuit includes the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization. By one approach, the control circuit is configured to include only a few iterations of the fluence-based sub-optimization when including the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization.

Abstract: After accessing optimization information for a particular patient and for a particular radiation treatment platform, a control circuit generates an optimized radiation treatment plan by processing the optimization information using direct-aperture-optimization that includes fluence-based sub-optimization. By one approach, the control circuit includes the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization. By one approach, the control circuit is configured to include only a few iterations of the fluence-based sub-optimization when including the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization.

Abstract: New techniques are described herein for providing a user-friendly interface for adjusting dose distribution values during optimization of a radiation application plan. In an embodiment, a graphical user interface is provided that provides an image of a target area for a radiation application, and a graphical overlay of a dose distribution disposed over the target area that visually represents the optimized dose distribution according to the input dose parameters. In one or more embodiments, the dose distribution may be automatically calculated from input parameters supplied by a user through the graphical user interface prior to optimization. A user (such as a clinician, radiation oncologist, or radiation therapy operator, etc.) is able to modify the visualization of the dose distribution volume during optimization via a user input device in conjunction with the graphical user interface and have the modification adjusted in real-time.

Abstract: After accessing optimization information for a particular patient and for a particular radiation treatment platform, a control circuit generates an optimized radiation treatment plan by processing the optimization information using direct-aperture-optimization that includes fluence-based sub-optimization. By one approach, the control circuit includes the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization. By one approach, the control circuit is configured to include only a few iterations of the fluence-based sub-optimization when including the fluence-based sub-optimization in at least some, but not necessarily all, iterations of the direct-aperture-optimization.

Abstract: New techniques are described herein for providing a user-friendly interface for adjusting dose distribution values during optimization of a radiation application plan. In an embodiment, a graphical user interface is provided that provides an image of a target area for a radiation application, and a graphical overlay of a dose distribution disposed over the target area that visually represents the optimized dose distribution according to the input dose parameters. In one or more embodiments, the dose distribution may be automatically calculated from input parameters supplied by a user through the graphical user interface prior to optimization. A user (such as a clinician, radiation oncologist, or radiation therapy operator, etc.) is able to modify the visualization of the dose distribution volume during optimization via a user input device in conjunction with the graphical user interface and have the modification adjusted in real-time.

Abstract: In a radiation treatment plan that includes a plurality of treatment fields of multiple treatment modalities, such as IMRT modality and dynamic treatment path modality (e.g., VMAT and conformal arc therapy), an optimized spatial point sequence may be determined that optimizes the total treatment time, which includes both the beam-on time (i.e., during the delivery of radiation dose) and the beam-off time (i.e., during transitions between consecutive treatment fields). The result is a time-ordered field trajectory that intermixes and interleaves different treatment fields. In one embodiment, a dynamic treatment path may be cut into a plurality of sections, and one or more IMRT fields may be inserted between the plurality of sections.

Abstract: In a radiation treatment plan that includes a plurality of treatment fields of multiple treatment modalities, such as IMRT modality and dynamic treatment path modality (e.g., VMAT and conformal arc therapy), an optimized spatial point sequence may be determined that optimizes the total treatment time, which includes both the beam-on time (i.e., during the delivery of radiation dose) and the beam-off time (i.e., during transitions between consecutive treatment fields). The result is a time-ordered field trajectory that intermixes and interleaves different treatment fields. In one embodiment, a dynamic treatment path may be cut into a plurality of sections, and one or more IMRT fields may be inserted between the plurality of sections.

Abstract: Methods and systems are provided for developing radiation therapy treatment plans. A treatment template with radiation fields can be chosen for a patient based on a tumor location. Static radiation field positions can be adjusted for the patient, while arc radiation fields may remain the same. Static radiation field positions can be adjusted using dose gradient, historical patient data, and other techniques.

Abstract: Streamlined and partially automated methods of setting normal tissue objectives in radiation treatment planning are provided. These methods may be applied to multiple-target cases as well as single-target cases. The methods can impose one or more target-specific dose falloff constraints around each target, taking into account geometric characteristics of each target such as target volume and shape. In some embodiments, methods can also take into account a planner's preferences for target dose homogeneity. In some embodiments, methods can generate additional dose falloff constraints in locations between two targets where dose bridging is likely to occur.

Abstract: Methods and systems are provided for developing radiation therapy treatment plans. A treatment template with radiation fields can be chosen for a patient based on a tumor location. Static radiation field positions can be adjusted for the patient, while arc radiation fields may remain the same. Static radiation field positions can be adjusted using dose gradient, historical patient data, and other techniques.

Abstract: Methods and systems are provided for developing radiation therapy treatment plans. A treatment template with radiation fields can be chosen for a patient based on a tumor location. Static radiation field positions can be adjusted for the patient, while arc radiation fields may remain the same. Static radiation field positions can be adjusted using dose gradient, historical patient data, and other techniques.

Abstract: A method for determining MLC leaf sequences for radiation treatment includes obtaining BEV projections of a first target volume and a second target volume along one or more treatment paths of a radiation treatment plan, analyzing the BEV projections to determine one or more contiguous ranges of spatial points where there exists an interstitial region between the first target volume and the second target volume in the direction of MLC leaf motion, and determining a first set of MLC leaf sequences such that an aperture formed by the MLC in a first portion of the one or more contiguous ranges of spatial points exposes radiation to the first target volume but not the second target volume, and an aperture formed by the MLC in a second portion of the one or more contiguous ranges of spatial points exposes radiation to the second target volume but not the first target volume.

Abstract: In a radiation treatment plan that includes a plurality of treatment fields of multiple treatment modalities, such as IMRT modality and dynamic treatment path modality (e.g., VMAT and conformal arc therapy), an optimized spatial point sequence may be determined that optimizes the total treatment time, which includes both the beam-on time (i.e., during the delivery of radiation dose) and the beam-off time (i.e., during transitions between consecutive treatment fields). The result is a time-ordered field trajectory that intermixes and interleaves different treatment fields. In one embodiment, a dynamic treatment path may be cut into a plurality of sections, and one or more IMRT fields may be inserted between the plurality of sections.

Abstract: An optimized radiation treatment plan may be developed in which the total monitor unit (MU) count is taken into account. A planner may specify a maximum treatment time. An optimization algorithm may convert the specified maximum treatment time to a maximum total MU count, which is then used as a constraint in the optimization process. A cost function for the optimization algorithm may include a term that penalizes any violation of the upper constraint for the MU count.

Abstract: In a radiation treatment plan that includes a plurality of treatment fields of multiple treatment modalities, such as IMRT modality and dynamic treatment path modality (e.g., VMAT and conformal arc therapy), an optimized spatial point sequence may be determined that optimizes the total treatment time, which includes both the beam-on time (i.e., during the delivery of radiation dose) and the beam-off time (i.e., during transitions between consecutive treatment fields). The result is a time-ordered field trajectory that intermixes and interleaves different treatment fields. In one embodiment, a dynamic treatment path may be cut into a plurality of sections, and one or more IMRT fields may be inserted between the plurality of sections.

Abstract: Streamlined and partially automated methods of setting normal tissue objectives in radiation treatment planning are provided. These methods may be applied to multiple-target cases as well as single-target cases. The methods can impose one or more target-specific dose falloff constraints around each target, taking into account geometric characteristics of each target such as target volume and shape. In some embodiments, methods can also take into account a planner's preferences for target dose homogeneity. In some embodiments, methods can generate additional dose falloff constraints in locations between two targets where dose bridging is likely to occur.

Abstract: New techniques are described herein for providing a user-friendly interface for adjusting dose distribution values during optimization of a radiation application plan. In an embodiment, a graphical user interface is provided that provides an image of a target area for a radiation application, and a graphical overlay of a dose distribution disposed over the target area that visually represents the optimized dose distribution according to the input dose parameters. In one or more embodiments, the dose distribution may be automatically calculated from input parameters supplied by a user through the graphical user interface prior to optimization. A user (such as a clinician, radiation oncologist, or radiation therapy operator, etc.) is able to modify the visualization of the dose distribution volume during optimization via a user input device in conjunction with the graphical user interface and have the modification adjusted in real-time.

Abstract: Streamlined and partially automated methods of setting normal tissue objectives in radiation treatment planning are provided. These methods may be applied to multiple-target cases as well as single-target cases. The methods can impose one or more target-specific dose falloff constraints around each target, taking into account geometric characteristics of each target such as target volume and shape. In some embodiments, methods can also take into account a planner's preferences for target dose homogeneity. In some embodiments, methods can generate additional dose falloff constraints in locations between two targets where dose bridging is likely to occur.