Abstract: Patient data can be used to determine input values to different estimation functions for different treatment types. The estimation functions can each be used to estimate one or more outcome values for the respective treatment. A quality score can be determined using the outcome value(s). A first treatment plan having an optimal quality score can be identified, e.g., by displaying the treatment plans with the quality scores, which may correspond to the outcome values.

Abstract: A dose prediction model can be determined for generating a dose distribution of a treatment plan for irradiating a target structure within a patient. Treatment plans from previous patients can be analyzed to determine D characteristic values to obtain a D dimensional point for each treatment plan. The treatment plans can be clustered based on the D dimensional points. The treatment plans of a cluster can then be used to determine a dose prediction model. A dose prediction model for patient can be selected from among multiple models. Characteristics about the patient can be used to determine a D dimensional point corresponding to the patient. The D-dimensional point can be used to select a model in comparison to D dimensional points of the models.

Abstract: Patient data can be used to determine input values to different estimation functions for different treatment types. The estimation functions can each be used to estimate one or more outcome values for the respective treatment. A quality score can be determined using the outcome value(s). A first treatment plan having an optimal quality score can be identified, e.g., by displaying the treatment plans with the quality scores, which may correspond to the outcome values.

Abstract: A dose prediction model can be determined for generating a dose distribution of a treatment plan for irradiating a target structure within a patient. Treatment plans from previous patients can be analyzed to determine D characteristic values to obtain a D dimensional point for each treatment plan. The treatment plans can be clustered based on the D dimensional points. The treatment plans of a cluster can then be used to determine a dose prediction model. A dose prediction model for patient can be selected from among multiple models. Characteristics about the patient can be used to determine a D dimensional point corresponding to the patient. The D-dimensional point can be used to select a model in comparison to D dimensional points of the models.

Abstract: Systems and methods for generating a movement model that requires less storage space than movement models of the prior art are disclosed. This movement model may be based on x-ray images of a patient and may be configured for estimating movement of organs within the patient during medical treatment. The movement model comprises at least two deformation fields associated with strong time points and a plurality of interpolation parameters associated with weak time points. In contrast with the prior art, the stored movement model does not include deformation fields associated with all time points. Because interpolation parameters rather than deformation fields are associated with the weak time points, the movement model requires less storage than movement models of the prior art. The stored movement model is optionally used to calculate interpolation fields that can be used to model movement of a patient.

Abstract: Various embodiments of the invention include systems and methods for adapting a movement model based on an image captured during radiation treatment of a patient. The movement model may, for example, be used in radiotherapy to treat lung cancer. The movement model is typically based on a series of images of a patient captured over a period of time. The movement model and/or one or images included therein may be used to generate a reference image of the patient. The reference image is compared with an image of the patient optionally captured during treatment. The result of this comparison is used to adapt the movement model to conditions during the treatment.

Abstract: A method includes obtaining a first image, obtaining a second image, determining a deformation field using the first and second images, and determining a transformation matrix using the deformation field. A computer product having a set of instruction, an execution of which causes a process to be performed, the process comprising determining a deformation field using first and second images, and determining a transformation matrix using the deformation field. A system includes a computer-readable medium for storing a first image and a second image, and a processor configured to determine a deformation field using the first and second images, and determine a transformation matrix using the deformation field.

Abstract: An interactive method for radiation treatment planning is disclosed. The method applies to staged treatment planning algorithms, as used, for example, with arc therapy. It allows the user to hold the optimization algorithm at a stage in order to make adjustments to the objective function before advancing to the next stage. If adjustments are made, the user can revert to an earlier stage and re-run the optimization process using the adjusted objective function. While a hold is imposed, the treatment planning software may continue optimization at the current stage.

Abstract: Methods for developing and using treatment plans with improved modulation for radiation therapy are disclosed. The methods involve adding an extra component to the patient-related objective function in order to make the optimization algorithm used to develop the treatment plan arrive at a solution with increased modulation. The extra component may take many forms. For example, the user may specify that the treatment plan favor solutions using a range of monitor units. The present invention is particularly useful in conjunction with radiotherapy systems having multileaf collimators for beam shaping, and in connection with advanced radiotherapy techniques, such as IMRT and arc therapy.

Abstract: An interactive method for radiation treatment planning is disclosed. The method applies to staged treatment planning algorithms, as used, for example, with arc therapy. It allows the user to hold the optimization algorithm at a stage in order to make adjustments to the objective function before advancing to the next stage. If adjustments are made, the user can revert to an earlier stage and re-run the optimization process using the adjusted objective function. While a hold is imposed, the treatment planning software may continue optimization at the current stage.

Abstract: Methods for developing and using treatment plans with improved modulation for radiation therapy are disclosed. The methods involve adding an extra component to the patient-related objective function in order to make the optimization algorithm used to develop the treatment plan arrive at a solution with increased modulation. The extra component may take many forms. For example, the user may specify that the treatment plan favor solutions using a range of monitor units. The present invention is particularly useful in conjunction with radiotherapy systems having multileaf collimators for beam shaping, and in connection with advanced radiotherapy techniques, such as IMRT and arc therapy.

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.

Abstract: A method includes obtaining a first image, obtaining a second image, determining a deformation field using the first and second images, and determining a transformation matrix using the deformation field. A computer product having a set of instruction, an execution of which causes a process to be performed, the process comprising determining a deformation field using first and second images, and determining a transformation matrix using the deformation field. A system includes a computer-readable medium for storing a first image and a second image, and a processor configured to determine a deformation field using the first and second images, and determine a transformation matrix using the deformation field.

Abstract: Various embodiments of the invention include systems and methods for adapting a movement model based on an image captured during radiation treatment of a patient. The movement model may, for example, be used in radiotherapy to treat lung cancer. The movement model is typically based on a series of images of a patient captured over a period of time. The movement model and/or one or images included therein may be used to generate a reference image of the patient. The reference image is compared with an image of the patient optionally captured during treatment. The result of this comparison is used to adapt the movement model to conditions during the treatment.