Abstract: In cases where material properties of a structure within or outside a patient receiving radiotherapy treatment, robust planning can be used, based on different scenarios with different material property values using a material override function present in the treatment planning system. A computer-based method of generating a radiotherapy treatment plan for a patient, based on an image of the patient and a desired dose. In cases where material properties of a structure within or outside a patient receiving radiotherapy treatment, robust planning can be used, based on different scenarios with different material property values using a material override function present in the treatment planning system. Robust planning is performed based on the at least two scenarios to provide robust evaluation data for each of the at least two scenarios and/or a robust optimized treatment plan with respect to all values in the set of material override values.

Abstract: A radiotherapy treatment plan for grid therapy in which a patient is radiated from a source of radiation with a set of spatially fractionated beams of charged particles such as protons, including varying the direction of each beam in the set of beams. Generating the plan comprises the steps of determining a first path through the patient to a first Bragg peak position and determining a second path through the patient, at least a part of the second path being directed at an angle from the first path to a first deflected Bragg peak position. The beam directions may be varied by means of magnetic fields or by varying the relative angle between the gantry and the patient.

Abstract: A method for generating data representing the volume of part of a body, the method comprising generating a point distribution model “PDM” based on an input dataset comprising data representing at least one surface of part of a body, the PDM defining a surface model dataset based on an average dataset and one or more weight-eigenvector pairs, generating a first surface model dataset based on the PDM by modifying at least one weight of the one or more weight-eigenvector pairs, wherein the first surface model dataset is different from the average dataset, and generating an output volume dataset based on the first surface model dataset and a first reference dataset, the first reference dataset comprising data representing the volume of a corresponding part of a body, the output volume dataset comprising data representing a deformed volume of the corresponding part of the body.

Abstract: It is provided a method for checking quality of a treatment plan, wherein a treatment plan specifies a distribution of radiation to thereby provide radiation to a planning target volume. The method is performed by a quality assurance device and comprises the steps of: obtaining a treatment plan and a corresponding first dose, the treatment plan having been calculated in a treatment planning system, the first dose being a predicted dose to be deposited in the patient using the treatment plan; initiating a calculation of a secondary dose, being a dose deposited by the treatment plan, using a secondary dose calculation algorithm; repeatedly calculating a confidence interval of a comparative statistical measurement by comparing the first dose and the secondary dose over a defined geometric volume; and interrupting the calculation of the secondary dose when the confidence interval is better than at least one predefined criterion.

Abstract: A method (100) for generating a treatment plan specifying an irradiation of a patient, the method comprising: a dose inference stage (112), including using a model to infer a spatial dose from patient data; a dose mimicking stage (116), including executing a robust optimization process to generate a deliverable treatment plan which is consistent with the inferred spatial dose, wherein the robust optimization considers a plurality of scenarios relating to patient data uncertainty.

Abstract: A method of optimizing the use of resources in treatment planning involving more than one radiation set delivered to one or more patients, the radiation sets requiring different resources, respectively, wherein the optimization is performed using an optimization problem comprising an optimization function related to the first and second sets of resources. The method may be used for optimizing one plan for one patient, or a number of plans for different patients, in such a way that the available resources are used in the best possible way.

Abstract: It is provided a method for providing a treatment plan for radiotherapy when the delivery is interrupted, the method being performed by a treatment planning system. The method comprises the steps of: detecting that delivery of a first treatment plan has been interrupted; obtaining an indication of delivery of a partial dose, representing the part of the first treatment plan that was delivered prior to the interruption; generating a second treatment plan, wherein the partial dose delivery forms an input to the second treatment plan generation as a background dose; and optimizing the second treatment plan while considering a plurality of scenarios.

Abstract: A compensating device for use in ion-based radiotherapy may comprise a disk with a number of protrusions may be placed in a radiation beam to affect the ions in the beam in different ways to create an irradiation field from a broad beam. This is particularly useful in FLASH therapy because of the limited time available or modulating the beam. A method of designing such a compensating device is proposed, comprising the steps of obtaining characteristics of an actual treatment plan comprising at least one beam, determining at least one parameter characteristic of the desired energy modulation of the actual plan by performing a dose calculation of the initial plan and, based on the at least one parameter, computing a shape for each of the plurality of elongated elements to modulate the dose of the delivery beam to mimic the dose of the initial plan per beam.

Abstract: A method and apparatus for generating a radiation treatment plan for a volume comprising: receiving a first treatment plan upon which to base a second treatment plan, the first treatment plan indicative of a dose distribution; receiving at least one dose-distribution-derived function configured to provide a value based on at least part of the dose distribution; receiving a target for the respective value of each dose-distribution-derived function comprising receiving a probability distribution; determining an optimization problem, wherein the or each objective function is a function of the dose-distribution-derived function, the respective probability distribution and a respective loss function; performing the optimization process based on said optimization problem; and determining said second treatment plan.

Abstract: A computer-based method of optimizing a radiotherapy treatment plan for a patient is proposed, wherein a treatment plan to be provided by one radiation set is optimized taking into account a previously delivered dose delivered by a different radiation set. One of the radiation sets is external beam radiotherapy and the other is brachytherapy.

Abstract: A deep learning model may be trained to provide an estimated image of the interior of a patient, based on a number of image sets, each image set comprising an interior image of the interior of a person and a contour image of the person's outer contour at a specific point in time. The model is trained to establish an optimized parametrized conversion function G specifying the correlation between the interior of the person and the persons outer contour based on the image sets. The conversion function G can then be used to provide estimated images of patient's interior based on their contours.

Abstract: A method of optimizing a radiotherapy treatment plan for delivering charged particles to a patient by pencil beam scanning, involves optimizing the treatment plan using an optimization problem that is designed to allow spots to differ in at least one of shape and orientation, and optionally also in size. This enables the optimization spots so as to cover the target in the best possible way and with a sharp penumbra along the outer edges of the target. The invention also relates to a computer program product and a computer system for use in such planning and a treatment delivery system for delivering such a plan.

Abstract: Generating a robust radiotherapy treatment plan for a treatment volume, defined using a plurality of voxels, of a subject. A first and at least one second image of the treatment volume are received. A distribution of mapped doses in the first image is generated by mapping a dose defined in the at least one second image to the first image using image registration. An optimization problem is defined using at least one optimization function for a total dose, related to the radiotherapy treatment. At least one optimization function value is calculated based on at least two mapped doses in the distribution of mapped doses in the first image. A radiotherapy treatment plan is generated by optimizing the at least one optimization function value evaluated by taking into account the at least two mapped doses in the distribution of mapped doses.

Abstract: A method for generating a robust radiotherapy treatment plan for a treatment volume of a subject, the treatment volume being defined using a plurality of voxels, the method comprising the steps of defining (S100) an optimization problem using at least one optimization function for a biological endpoint related to the radiotherapy treatment; defining (S102) a set of scenarios comprising at least a first scenario and a second scenario, wherein at least two of the scenarios in the set of scenarios represent different biological models to quantify the same biological endpoint; calculating (S104) an optimization function value for each scenario in the set of scenarios; generating (S106) a radiotherapy treatment plan by robustly optimizing the optimization function value evaluated over the set of scenarios.

Abstract: Automatic radiation therapy treatment planning for generating a plan to be delivered from at least one beam angle, using a collimator having a variable collimator angle. Delivery times are determined for a number of possible collimator angles, and the optimization problem is defined to take the delivery times into account when selecting the collimator angles to be used when delivering the radiation.

Abstract: A computer-based method of providing a set of selected spots for use in ion radiotherapy optimization is proposed, the method comprising the steps of defining a number of positions in the volume, each position corresponding to a possible Bragg peak location, the positions being defined to provide coverage of the volume, for each position, for at least one beam direction, performing a ray trace to determine characteristics of a potential spot in the beam that will place its Bragg peak in the position and for each position, selecting zero, one or more of the potential spots, based on the characteristics, and including the one or more selected spots in the set of selected spots. The set of selected spots may be used in treatment planning. The invention also relates to computer program products and a computer system for performing the methods.

Abstract: A method of radiotherapy treatment planning for particle-based arc treatment comprises the steps of determining (S11; S21) an initial set of candidate energy layers, performing a calculation on the initial set, determining (S13; S23), based on the outcome of said calculation, at least one additional energy layer to produce an expanded candidate layer set, wherein the at least one additional energy layer involves an energy level that has not previously been used adding (S14; S24) the at least one additional energy to the initial set, to produce an expanded candidate energy layer set optimizing (S16; S26) a radiotherapy treatment plan based on the expanded candidate layer set.

Abstract: A method of generating a radiotherapy plan for ion therapy, wherein the beam (6) is shaped by means of passive devices is arranged to allow variation in settings of at least one of the passive devices and/or the MU during the delivery of the beam and to control the movement of the patient and/or the beam in such a way as to create an arc. The arc is preferably a continuous arc or includes at least one continuous sub-arc. The method may include forward planning or optimization. In the latter case, the optimization uses an optimization problem set up to allow variation in settings of at least one of the range modulating device (9), the aperture element (11) and the MU during the delivery of the arc. Computer programs control the planning and the delivery.

Abstract: An estimated or predicted dose for radiotherapy treatment may be generated based on a partial dose map including dose information only for one or more regions of interest within a treatment site, by use of a properly trained machine learning system such as a U-Net or a V-Net. Said partial dose map typically set to fulfil clinical goals. A method of training such a machine learning system is also disclosed.

Abstract: The present disclosure generally relates to the field of radiation treatment. More specifically, the present disclosure generally relates to methods and radiation treatment systems for facilitating a multimodal radiation therapy treatment plan, in particular a multimodal radiation therapy plan employing a combined photon beam and electron beam radiation treatment. According to one example embodiment described in the disclosure, a method may comprise obtaining information related to a set of candidate beam types for the combined photon beam and electron beam radiation treatment; comparing the set of candidate beam types against a selection criterion to establish a subset of beam types from the candidate beam types; and generating the combined photon beam and electron beam radiation treatment plan utilizing the thus established subset of beam types.