Raysearch Laboratories Ab

Raysearch Laboratories Ab (publ)

Albin Fredriksson

Kjell Eriksson

Rasmus Bokrantz

Erik Engwall

Erik Traneus

Martin Janson

Bjorn Andersson

Björn Hårdemark

Lars Glimelius

Henrik Olsson

Sebastian Andersson

Mats Holmstrom

David Andersson

Hanna Gruselius

Johan Sundström

Anton Finnson

Cecilia Batinelli

Rasmus Nilsson

Jakob Ödén

Minna Wedenberg

Ivar Bengtsson

Björn Andersson

Mats Holmström

Mats HOLMSTRÖM

Björn HÅRDEMARK

Marcus Nordström

Disclosed herein is a treatment planning method for generating a treatment plan for radiation therapy where a set of targets (-) are to be treated, the method using a multi-leaf collimator (MLC) () for shaping an arc beam (), a gantry () for holding the MLC, the gantry () capable of rotating at least partially around a patient, a couch () for positioning the patient, the MLC () being movable and defining a collimator angle (), the gantry () being movable and defining a gantry angle () and the couch () optionally being movable thereby defining a couch angle (), the method comprising the steps of:

System and method for automated radiotherapy treatment planning

A computer-based method of optimizing a radiotherapy treatment plan for a patient is proposed, wherein a complete treatment comprising both external beam therapy and brachytherapy is optimized in one procedure using an optimization problem comprising an objective function designed to optimize the total dose distribution as a combination of a first dose distribution to be provided by a first radiation set and a second dose distribution to be provided by a second radiation set. One of the radiation sets is external beam radiotherapy and the other is brachytherapy. The optimization is based on a total desired dose for the whole treatment, images of the patient before the treatment starts and an estimated image of the patient after the first radiation set has been delivered.

Computer-implemented method for radiotherapy treatment planning, computer program product and computer system for performing the method

A method () for generating a treatment plan specifying an irradiation of a patient, the method comprising: a dose inference stage (), including using a model to infer a spatial dose from patient data; a dose mimicking stage (), 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.

Automated treatment planning by dose prediction and robust dose mimicking

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.

Method, a computer program and a computer system for optimization of at least one treatment plan

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.

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.

Method and system for robust radiotherapy treatment planning for dose mapping uncertainties

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.

Method and system for robust radiotherapy treatment planning for biological uncertainties

A method of generating a radiotherapy plan for ion therapy, wherein the beam () 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 (), the aperture element () and the MU during the delivery of the arc. Computer programs control the planning and the delivery.

System and method for passive ion radiotherapy treatment planning and delivery

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.

Method and a corresponding radiation treatment system for facilitating optimization of a multimodal radiation therapy plan

It is provided a method for determining arc costs. The method comprises the steps of: determining a plurality of beam orientations; evaluating a set of at least one cost function comprising an intermediate exposure cost function that is evaluated by performing the substeps of: projecting the at least one target volumes on a beam plane; determining an alignment angle based on a collimator angle value; finding any intermediate area in the beam plane along the alignment angle between areas of the at least one target volume projection; determining a value of the intermediate exposure cost function. The method further comprises the steps of: finding a plurality of arcs, wherein each arc comprises a sequence of a plurality of beam orientations; and calculating, for each arc in the plurality of arcs, at least one arc cost based on the cost function values of the beam orientations of the arc.

Evaluation of arcs for a radiation treatment plan

A method is proposed for evaluating the robustness of a radiotherapy treatment plan. The method comprises, defining a number of scenarios, each comprising one or more errors for each fraction of the plan, including interfractional and/or intrafractional errors, and calculating a dose distribution resulting from the scenario; The robustness of the plan is then evaluated based at least one of the following 

System and method for modelling of dose calculation in radiotherapy treatment planning

A method of radiotherapy treatment planning for creating a plan for delivery of radiation to a patient in at least one particle-based arc is proposed. The delivery time for the plan is reduced by including a penalty in the objective function, designed to limit the number of energy layers and/or the number of energy layer changes.

System and method for radiotherapy treatment planning and delivery

A method of radiotherapy treatment planning comprises optimizing a treatment plan based on at least one proposed dose map according to a set of clinical goals The resulting dose distribution is compared to the at least one clinical goal, and if the optimized dose distribution does not fulfil the at least one clinical goal, continuing with step d the dose map is adjusted before a new treatment plan is optimized. When the optimized dose distribution fulfils the clinical goals, the treatment plan is accepted.

System and method for automatic radiotherapy treatment planning

A system plans a radiation therapy treatment of a target volume based on inputs in the form of: a set of candidate beams (B), where each beam defines an arrangement of a therapeutic beam relative to the target volume; a treatment plan (x) for the radiation therapy treatment that uses a subset of the candidate beams (B); an objective function (F) describing a quality of the treatment plan (x); and a feasible region (X) describing requirements on the treatment plan (x) that must be fulfilled. The objective function (F) and/or the feasible region (X) also reflect a first complexity criterion (&#x3c4;(x)&#x2264;{circumflex over (&#x3c4;)}) limiting a first complexity measure (&#x3c4;(x)) to be less than or equal to a maximum first complexity ({circumflex over (&#x3c4;)}). An optimization step is executed repeatedly; whereby, in each iteration, an updated treatment plan (x') is calculated by optimizing the treatment plan (x) with respect to the objective function (F) and the feasible region (X). Here, if a termination criterion is fulfilled, a set of selected beams (B*) is calculated based on the updated treatment plan (x&#x2032;). The set of selected beams (B*) is a subset of the set of candidate beams (B). Otherwise, the updated treatment plan (x&#x2032;) is set to the treatment plan (x); an updated first complexity criterion (&#x3c4;&#x2032;(x)&#x2264;{circumflex over (&#x3c4;)}&#x2032;) is calculated; the updated first complexity criterion (&#x3c4;&#x2032;(x)&#x2264;{circumflex over (&#x3c4;)}&#x2032;) is set to the first complexity criterion (&#x3c4;(x)&#x2264;{circumflex over (&#x3c4;)}), and another iteration of the optimization step is executed.

System and method for planning a radiation therapy treatment

A scenario-based treatment plan optimization method for radiotherapy treatment is proposed, in which a first and a second possible scenario are defined. Different optimization functions are defined for the scenarios and the treatment plan is optimized applying the first optimization function under the first scenario and the second optimization function under the second scenario, thereby obtaining a first optimized radiotherapy treatment plan.

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Stockholm, Sweden

Albin Fredriksson