Raysearch Laboratories Ab

Raysearch Laboratories Ab (publ)

Rasmus Bokrantz

Albin Fredriksson

Kjell Eriksson

Erik Engwall

Björn Hårdemark

Erik Traneus

Martin Janson

Lars Glimelius

Tianfang Zhang

Bjorn Andersson

Fredrik Löfman

Björn Andersson

Cecilia Battinelli

Cecilia Batinelli

Björn HÅRDEMARK

A method for dynamically estimating a biological effect of a variable combination of non-photon radiation in accordance with a relative biological effectiveness, RBE, model including at least one biological effect multiplier δ(T,E) which depends on particle type T and/or particle energy E, the method comprising:

Dynamic estimation of a biological effect of a variable composition of non-photon radiation

It is provided a method for generating a plurality of potential treatment plans, each treatment plan specifying a distribution of radiation to a target volume, the method being performed by a treatment planning system and comprising the steps of: generating a plurality of potential treatment plans (), for performing multi-criteria optimization (MCO), based on a set of optimization functions. At least one optimization function depends on the distribution of the product of radiation dose and linear energy transfer, LET, in a specified region of the patient, yielding a plurality of treatment plans.

Generating a plurality of potential treatment plans for multi-criteria optimization

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

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.

System and method for radiotherapy treatment planning

A method of radiotherapy treatment planning for particle-based arc treatment comprises the steps of

Method, computer program product and computer system for particle-based radiotherapy treatment planning

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

Better Pareto dose distributions for multi-criteria optimization of treatment plans can be obtained by obtaining at least one reference dose function designed to result in an acceptable reference dose distribution, defining a multi-criteria optimization problem including the at least one reference dose function as at least one optimization function, performing at least two optimization procedures based on the multi-criteria optimization problem to generate a set of at least two possible treatment plans, obtaining a treatment plan to be used for treating the patient, based on the set of possible treatment plans, by selecting one plan or by combining plans.

System, computer program product and method for radiation therapy treatment planning

It is provided a method for optimizing a treatment plan for use in radiation therapy. The method is performed in a treatment planning system and comprises the steps of: obtaining a first quality function of the treatment plan, the first quality function yielding an output value based on an input treatment plan; obtaining a first pair of input values and a slope indicator, the input values associating a value of the first quality function to a value of a score; constructing a score function that maps values of the first quality function to values of the score by fitting a curve to the first pair of input values and the slope indicator; and optimizing the treatment plan with respect to the score function, by varying the treatment plan such that the value of the score function is either improved or constrained to a feasible range of score values.

Optimizing a treatment plan based on a score function depending on a quality function

It is provided a method for generating a plurality of treatment plans for radiation therapy, each treatment plan specifying weights for a plurality of geometrically defined fluence elements. Each weight defines an amount of radiation fluence, to thereby provide radiation dose to a target volume. The method is performed in a treatment planning system and comprises the steps of: generating a first set of treatment plans; determining a subset of the fluence elements, based on the first set of treatment plans; and generating a second set of at least two treatment plans, wherein the treatment plans only contain weights for the subset of fluence elements.

Generating a plurality of treatment plans for radiation therapy

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 obtaining an interpolated treatment plan is based on interpolating between associated dose distributions through optimization with respect to an optimization problem comprising optimization functions based on deviations from clinical goals. The method may suitably be used to improve navigated plans resulting from multi-criteria optimization.

Method, a user interface, a computer program product and a computer system for optimizing a radiation therapy treatment plan

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.

Method, computer program and system for optimizing a radiotherapy treatment plan

Radiation therapy treatment planning methods facilitate predicting achievable dose distributions by training a prediction model for clinical DVH curves based on simplified DVH curves obtained using standardized methods. Machine learning applied on pairs of clinical and simplified DVH curves enables predicting actual clinical DVH curves based on simplified DVH curves.

System and method for radiation therapy treatment planning

A scenario-based radiotherapy treatment plan optimization method is used to define an extended region of interest for treatment planning purposes, based on the union of the positions of a region of interest in a number of different scenarios, each scenario representing a realization of a possible location of the region of interest. Preferably a number of scenarios are defined and some of these scenarios are used to define the extended region.

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Stockholm, Sweden

Rasmus Bokrantz