Patent Description:
The development of surgical techniques has made great progress over the years. For instance, patients in need of brain surgery may instead have non-invasive surgery which drastically reduces the trauma to the patients.

Systems for non-invasive surgery include the Leksell Gamma Knife® Icon™ and the Leksell Gamma Knife® Perfexion, which provide such surgery by means of gamma radiation. The radiation is emitted from a large number of fixed radioactive sources and is focused by means of collimators, i.e. passages or channels for obtaining a beam of limited cross section, towards a defined target or treatment volume. Each of the sources provides a dose of gamma radiation which, by itself, is insufficient to damage intervening tissue. However, tissue destruction occurs where the radiation beams from a plurality of radiation sources intersect or converge, causing the radiation to reach tissue-destructive levels. The point of convergence is hereinafter referred to as the "focus point".

Treatment plan optimization in radiotherapy, including for example gamma knife radiosurgery, aims at delivering sufficiently high dose to the target volume within the patient (e.g. in treatment of tumours) at the same time as the dose delivered to adjacent normal tissue is minimized. In treatment plan optimization, at least three competing factors have to be considered: delivering a sufficiently high dose to the target volume, sparing the surrounding normal or healthy tissue and keeping the treatment time as short as possible.

The treatment plan optimization is a process including optimizing the relative isocenter locations or beam directions, the beam shape settings (e.g. collimator configuration) and the fluences. In, for example, the Leksell Gamma Knife® Icon™ and the Leksell Gamma Knife® Perfexion the treatment plan optimization may include optimizing the number of shots being used, the collimator configuration of each shot, the shot times, and the position of the shot. The irregularity and size of a target volume greatly influence relative isocenter locations or beam directions, the beam shape settings (e.g. collimator configuration) and the fluences used to optimize the treatment.

In treatment planning, inverse treatment planning has gained more and more interest. Inverse planning generally refers to the stage in treatment planning where a deliverable treatment plan is sought, such that a number of criteria are satisfied. Inverse planning can be contrasted to forward planning, where the operator manually places, weights and shapes shots. The promises of inverse planning are shorter planning times and higher quality plans. Inverse planning is sometimes tightly integrated with forward planning, e.g. in the software accompanying the Leksell Gamma Knife: Leksell GammaPlan®. It is based on relative isodoses and uses metrics that are well-known in radiosurgery. This facilitates the transition from forward to inverse planning, and is presumably one of the reasons for the widespread adoption of inverse planning. A downside of relative isodose-based inverse planner and the complexity of the objectives is that the resulting optimization problem is inherently difficult to solve. In realistic cases it requires a compromise between computation time and the risk of ending up in a poor local optimum. This makes it difficult to explore what trade-offs are achievable - especially in complicated cases with multiple conflicting objectives. For example, a multi-metastases case where at least one metastasis is adjacent to an organ at risk. Incidentally, in such a case it might also be desirable to specify some criteria that must be met. In present inverse planners crtiteria for organs at risk (OAR) cannot be set.

Historically in inverse treatment planning for Gamma Knife radiosurgery, the relative isodoses are the fundamental object of interest. This is a heuristic motivated by the dose fall-off being the steepest for a certain isodose level, which should coincide with the target boundary. Incidentally, this is true for a single shot but need not be true when the dose distribution is the sum of contributions from multiple shots. Note that utilizing steep gradients presupposes high positional accuracy. For an isocenter the optimization variables are the position, collimator configuration and beam-on time. The isocenter locations are moved during the optimization and the collimator configuration is treated as a discrete element in the set of all possible collimator configurations. Organs at risk are not handled explicitly in the objective function, which can be a severe limitation. Evidently, tolerance doses for organs at risk are given in absolute dose but in the present mode of planning, absolute dose is assigned only after completing the plan. This results in an optimization problem that is very hard in the sense that any solution method requires either extensive computations or runs the risk of returning unsatisfactory solutions. [Insert page 3a].

In improved inverse treatment planning methods provided by the applicant, a number of objectives reflecting clinical criteria for regions of interest, including one or more targets to be treated during treatment of the patient, one or more organs at risk and/or healthy tissue are set and radiation dose profiles to be delivered to the target or targets are generated. A convex optimization problem that steers the delivered radiation according to the objectives is provided and dose profiles for specific treatment configurations including beam shape settings for the radiation dose profiles are calculated using the convex optimization problem. Thereafter, a treatment plan, including determining the radiation dose profiles to be delivered during treatment based on the treatment configurations are created, wherein each radiation dose profile is modelled by a spatial dose volume distribution of radiation, the shape of the spatial distribution depending on the beam shape settings and an optimal treatment plan that satisfies the clinical criteria is selected.

However, there is still a need of more efficient methods for planning and optimizing the treatment.

<CIT> describes a radiation therapy planning system including a radiation therapy optimization unit that receives at least one target structure and at least one organ at risk structure segmented from a volumetric image. An optimized plan is generated based on at least one modified objective function. The optimized plan includes a planned radiation dose for each voxel.

<CIT> describes therapeutic treatment of a patient using intensity-modulated proton therapy. In one example, a method of creating a proton treatment plan is presented that divides volumes of interest into sub-volumes, applies dose constraints to the sub-volumes, finds one or more feasible configurations of a proton therapy system, and selects a proton beam configuration that improves or optimizes one or more aspects of proton therapy. In some implementations, the method of dividing volumes into sub-volumes includes creating fractional sub-volumes based at least in part on proximity to a target volume boundary. In some implementations, the method of finding an improved or optimal proton beam configuration from a set of feasible configurations includes finding a minimum of a cost function that utilizes weighting factors associated with treatment sites.

An object of the present invention is to provide improved methods and systems for planning and optimizing treatment sessions of a patient in radiotherapy systems.

This and other objects are fulfilled by the present invention as defined by the independent claims.

The term "target" or "target volume" refers to a representation of a target of a patient to be treated during radiotherapy. The target may be a tumour to be treated with radiotherapy. Typically, the representation of the target is obtained by, for example, non-invasive image capturing using X-ray or nuclear magnetic resonance.

The term "shot" refers to a delivery of radiation to a predetermined position within a target volume having a predetermined level of radiation and a spatial distribution. The shot is delivered during a predetermined period of time ("beam-on" time) via at least one sector of the collimator of the therapy system using one of the states of the sector. A "composite shot" refers to the delivery of radiation to a focus point using different collimator sizes for different sectors.

The term "beam-on time" refers to the predetermined period of time during which a shot is delivered to the target volume.

The term "constraint" refers to constraints on the optimization variable, either directly, e.g. enforcing non-negative beam-on times, or indirectly, e.g. enforcing a minimum dose delivery to a certain volume. Also, constraint may refer to constraints that must not be violated (hard constraints) and/or constraints for which violations are allowed but penalized in the objective function (soft constraints).

The term "voxel" is used in the context of this application and refers to volume elements on a grid, which may be anisotropic in a three-dimensional space.

The term "frame description" includes at least an objective function and/or constraint for a set of voxels.

The present invention can, for example, be used in radiotherapy. Radiotherapy is used to treat cancers and other ailments in mammalian (e.g., human and animal) tissue. One such radiotherapy device is a Gamma Knife, which irradiates a patient with a large number of low-intensity gamma rays that converge with high intensity and high precision at a target (e.g., a tumour). Another radiotherapy device uses a linear accelerator, which irradiates a tumour with high-energy particles (e.g., photons, electrons, and the like). Still another radiotherapy device, a cyclotron, uses protons and/or ions. Another form of radiotherapy is brachytherapy, where a radiation source is placed inside or next to the area requiring treatment. The direction and shape of the radiation beam should be accurately controlled to ensure that the tumour receives the prescribed radiation dose, and the radiation from the beam should minimize damage to the surrounding healthy tissue, often called the organ(s) at risk (OARs). Treatment planning can be used to control radiation beam parameters, and a radiotherapy device effectuates a treatment by delivering a spatially varying dose distribution to the patient.

The present invention is for example used in connection with treatment planning of treatment provided by means of a radiotherapy system having a collimator body provided with several groups or sets of collimator passages, each set being designed to provide a radiation beam of a respective specified cross-section toward a fixed focus point. Suitably the inlet of each set of collimator passages has a pattern that essentially corresponds to the pattern of the sources on the source carrier arrangement. These sets of collimator passage inlets may be arranged so that it is possible to change from one set to another, thereby changing the resulting beam cross-section and the spatial dose distribution surrounding the focus point. The number of sets of collimator passages with different diameter may be more than two, such as three or four, or even more. A typical embodiment of the collimator comprises eight sectors each having four different states (beam-off, <NUM>, <NUM>, and <NUM>). The sectors can be adjusted individually, i.e. different states can be selected for each sector, to change the spatial distribution of the radiation about the focus point.

The present invention may also be used in connection with treatment planning in radiotherapy.

The present invention may further be used in brachytherapy. Brachytherapy is a form of radiotherapy where a sealed radiation source is placed inside or next to the area requiring treatment. Brachytherapy involves the precise placement of short-range radiation-sources (radioisotopes, Iodine-<NUM> for instance) directly at the site of the cancerous tumour. Brachytherapy treatment planning often involves optimization methods to calculate the dwell times and dwell positions of the radioactive source along specified applicator paths. Inverse planning methods for brachytherapy aim at obtaining adequate target coverage and maximum sparing of critical structures. In geometric optimization, the relative dwell times are determined by the geometry of the implant by assigning an individual weighting factor for the dwell time at each dwell position that is inversely proportional to the dose contribution from neighboring source locations.

Hence, the optimization problem, which in preferred embodiments is a convex optimization problem, steers the delivered radiation according to the objectives and dose profiles for specific treatment configurations including source strengths and/or dwell times are calculated using the optimization problem. Thereafter, a treatment plan, including determining the radiation dose profiles to be delivered during treatment based on the treatment configurations can be created, wherein each radiation dose profile is modelled by a spatial dose volume distribution of radiation, the shape of the spatial distribution depending on the settings and an optimal treatment plan that satisfies the criteria can be selected.

According to embodiments of the present invention, there is provided a method for dose or treatment planning for a radiotherapy system comprising a radiotherapy unit. A spatial dose delivered can be changed by adjusting beam shape settings, wherein delivered radiation is determined using an optimization problem that steers the delivered radiation according to objectives reflecting criteria for regions of interest including at least one of: targets to be treated during treatment of the patient, organs at risk and/or healthy tissue. The method comprises the steps of determining an inner set of voxels that encompasses the outer surface of a target volume, providing a first frame description, which include at least a first objective function for the inner set of voxels, where the first objective function includes at least one objective reflecting criteria for the inner set of voxels.

Then, at least one outer set of voxels encompassing the target volume and the inner set of voxels is determined and a frame description, including an objective function (or functions) for the outer set of voxels, is provided where each reflecting criteria for the outer set of voxels. The frame descriptions are then used in the optimization problem that steers the delivered radiation.

The optimization problem, which in preferred embodiments is a convex optimization problem, steers the delivered radiation according to the objectives and dose profiles for specific treatment configurations including beam shape settings for the radiation dose profiles are calculated using the optimization problem. Thereafter, a treatment plan, including determining the radiation dose profiles to be delivered during treatment based on the treatment configurations can be created, wherein each radiation dose profile is modelled by a spatial dose volume distribution of radiation, the shape of the spatial distribution depending on the beam shape settings and an optimal treatment plan that satisfies the criteria can be selected.

The method for treatment planning is provided for a radiotherapy system comprising a radiotherapy unit having a fixed radiation focus point. A spatial dose distribution surrounding the focus point can be changed by adjusting beam shape setting, including collimator settings, where the collimator is arranged in sectors and has a plurality of collimator passage inlets directing radiation emanating from radioactive sources of a source carrier arrangement of the therapy system to the focus point.

The optimization problem, which in preferred embodiments is a convex optimization problem, steers the delivered radiation according to the objectives and dose rates are calculated for specific treatment configurations including sector and collimator settings and irradiation time for isocenters using the optimization problem. Then, treatment plans can be created including determining shots to be delivered during treatment based on the treatment configurations, wherein each shot is modelled by a spatial dose volume distribution of radiation represented by a three-dimensional voxel representation, wherein the shape of the spatial distribution depending on the specific sector and collimator setting and irradiation time. Finally, an optimal treatment plan that satisfies the criteria can be selected.

According to embodiments of the present invention, the inner and outer set of voxels are shaped as shells. For example, a distance between an inner surface of each shell and an outer surface of the target may be the same in all directions or depend on direction, for example, it may be different in x- y- and z-directions.

In embodiments of the present invention, the objectives for the inner and/or outer set of voxels include delivered dose to the set of voxels.

According to embodiments of the present invention, the method further comprises setting a weight corresponding to an importance of the objective or objectives of the objective functions for the inner and outer set of voxels, respectively.

In embodiments of the present invention, the method further comprises setting a scalar weight corresponding to an importance of the objective or objectives of an objective function for a target volume.

According to embodiments of the present invention, each weight governs an importance of different objectives.

In embodiments of the present invention, the inner and outer set of voxels may have a uniform thickness measured in number of voxels or in distance, for example, in mm between inner and outer boundary or surface. Furthermore, the inner and outer set of voxels may have a non-uniform thickness measured in voxels or in distance, for example, in mm between inner and outer boundary or surface.

According to embodiments of the present invention, a weight for the inner set of voxels is selected to promote selectivity, and wherein a weight of an outer set of voxels is selected to promote high gradient outside the target/targets.

In embodiments of the present invention, an inner surface of a first outer set of voxels encompasses an outer surface of the inner set of voxels.

According to embodiments of the present invention, at least one frame description comprise an approximation of an integral, over the voxels in the set of voxels, of a function for dose delivery that depends on the distance to an outer surface of the target volume.

The described method may further comprise calculating dose profiles for specific treatment configurations including beam shape settings for the radiation dose profiles using the optimization problem, creating treatment plans including determining the radiation dose profiles to be delivered during treatment based on the treatment configurations, wherein each radiation dose profile is modelled by a spatial dose volume distribution of radiation, the shape of the spatial distribution depending on the beam shape settings, and selecting an optimal treatment plan that satisfies the criteria.

The described method may further comprise calculating dose rates for specific treatment configurations including sector and collimator settings and irradiation time for the isocenters using the optimization problem, creating treatment plans including determining shots to be delivered during treatment based on the treatment configurations, wherein each shot is modelled by a spatial dose volume distribution of radiation, the shape of the spatial distribution depending on the specific sector and collimator setting and irradiation time, and selecting an optimal treatment plan that satisfies the criteria.

The described method may further comprise defining a set of beam directions, modelling radiation dose profiles to be delivered to the target as a plurality of beamlets each having a beamlet intensity, setting a number of objectives reflecting criteria for the target, providing an optimization problem that steers the delivered radiation according to the objectives so as to create fluence maps, wherein the fluence maps define the beamlet intensities for each of the beamlets, creating treatment plans based on fluence maps and criteria for the target, and selecting an optimal treatment plan that satisfies the criteria.

The described method may comprise positioning of radiation source(s) relative to the patient, including generating fixed isocenter positions.

The radiation source positions may be generated as a set of continuous points in the target volume based on basis functions, wherein the points are fixed during the treatment planning.

According to embodiments of the present invention, the objectives include delivered dose to target, delivered dose to a boundary space surrounding the target, delivered dose to regions classified as a risk organ, and/or beam-on time penalization.

Dose rates for specific treatment configurations including sector and collimator settings and irradiation time may be calculated using the convex optimization problem for predetermined isocenters within the volume.

An optimized dose plan determined by means of the present invention, may be transferred to a radiotherapy system for use in the treatment of the patient. The dose plan determined by the invention may also or alternatively be used as input in a treatment optimization procedure where the number of shots, position of the shots and the shot sizes defined during the volume filling according to the invention serves as basis in an optimization of the number of shots, the position and the beam-on time of the respective shots and the shots sizes.

According to still another aspect of the present invention, there is provided a treatment planning computer structure in which the method according to the present invention may be implemented.

In embodiments of the present invention, the treatment plan computer structure may utilize methods according to the present invention and may be integrated into a system for delivering intensity modulated radiation treatment (IMRT) including a radiation source that generates at least one radiation beam. A beam shaping device, e.g. a multi-leaf collimator or a conical collimator, may be disposed between the radiation source and the patient. The collimator is communicatively connected to the treatment planning computer structure and is configured to modify the plurality of beamlets to deliver according to optimal treatment plan, i.e. a fluence map based on the beam shape settings determined, to the patient.

In further embodiments of the present invention, the treatment plan computer structure may utilize methods according to the present invention that may be integrated into a radiotherapy system having a collimator body provided with several groups or sets of collimator passages, each set being designed to provide a radiation beam of a respective specified cross-section toward a fixed focus point. Suitably the inlet of each set of collimator passages has a pattern that essentially corresponds to the pattern of the sources on the source carrier arrangement. These sets of collimator passage inlets may be arranged so that it is possible to change from one set to another, thereby changing the resulting beam cross-section and the spatial dose distribution surrounding the focus point. The collimator body is communicatively connected to the treatment planning computer structure to deliver according to optimal treatment plan to the patient.

As the skilled person realizes, steps of the methods according to the present invention, as well as preferred embodiments thereof, are suitable to realize as computer program or as a computer readable medium.

Further objects and advantages of the present invention will be discussed below by means of exemplifying embodiments.

With reference first to <FIG> and <FIG>, an exemplary radiotherapy device in which a treatment plan developed using the present invention can be used for treatment of a patient.

<FIG> is a perspective view of an assembly comprising a source carrier arrangement <NUM> surrounding a collimator body <NUM>. The source carrier arrangement <NUM> and the collimator body <NUM> both have the shape of a frustum of a cone. The source carrier arrangement <NUM> comprises six segments <NUM> distributed along the annular circumference of the collimator body <NUM>. Each segment <NUM> has a plurality of apertures <NUM> into which containers containing radioactive sources, such as cobalt, are placed. The collimator body <NUM> is provided with collimator passages or channels, internal mouths <NUM> of the channels are shown in the figure.

Each segment <NUM> has two straight sides <NUM> and two curved sides 14a, 14b. One of the curved sides 14a forms a longer arc of a circle, and is located near the base of the cone, while the other curved side 14b forms a shorter arc of a circle. The segments <NUM> are linearly displaceable, that is they are not rotated around the collimator body <NUM>, but are instead movable back and forth along an imaginary line drawn from the center of the shorter curved side 14b to the center of the longer curved side 14a. Such a translation displacement has the effect of a transformation of coordinates in which the new axes are parallel to the old ones.

As can be seen from <FIG> there is a larger number of internal mouths <NUM> or holes of the collimator passages than the number of apertures <NUM> for receiving radioactive sources. In this particular case, there are three times as many collimator passages as there are apertures for receiving radioactive sources, such as e.g. <NUM> apertures and <NUM> collimator passages. The reason for this is that there are three different sizes of collimator passages in the collimator body <NUM>, or rather passages which direct radiation beams with three different diameters, toward the focus point. The diameters may e.g. be <NUM>, <NUM> and <NUM>. The three different types of collimator passages are each arranged in a pattern which corresponds to the pattern of the apertures in the source carrier arrangement. The desired size or type of collimator passage is selected by displacing the segments <NUM> of the source carrier arrangement linearly along the collimator body so as to be in register with the desired collimator passages.

In <FIG>, aradiotherapy system including a radiotherapy device <NUM> having a source carrier arrangement as shown in <FIG>, and a patient positioning unit <NUM> is shown. In the radiotherapy unit <NUM>, there are thus provided radioactive sources, radioactive source holders, a collimator body, and external shielding elements. The collimator body comprises a large number of collimator channels directed towards a common focus point, as shown in <FIG>.

The patient positioning unit <NUM> comprises a rigid framework <NUM>, a slidable or movable carriage <NUM>, and motors (not shown) for moving the carriage <NUM> in relation to the framework <NUM>. The carriage <NUM> is further provided with a patient bed <NUM> for carrying and moving the entire patient. At one end of the carriage <NUM>, there is provided a fixation arrangement <NUM> for receiving and fixing a patient fixation unit or interface unit. The coordinates of the fixation unit are defined by a fixation unit coordinate system, which through the fixed relationship with the treatment volume also is used for defining the outlines of the treatment volume. In operation, the fixation unit, and hence the fixation unit coordinate system, is moved in relation to the fixed radiation focus point such that the focus point is accurately positioned in the intended coordinate of the fixation unit coordinate system.

<FIG> illustrates a radiotherapy device <NUM>, a Gamma Knife in which the present invention can be used. A patient <NUM> may wear a coordinate frame <NUM> to keep stable the patient's body part (e.g. the head) undergoing surgery or radiotherapy. Coordinate frame <NUM> and a patient positioning system <NUM> may establish a spatial coordinate system, which may be used while imaging a patient or during radiosurgery. Radiotherapy device <NUM> may include a protective housing <NUM> to enclose a plurality of radiation sources <NUM> for generation of radiation beams (e.g. beamlets) through beam channels <NUM>. The plurality of beams may be configured to focus on an isocenter <NUM> from different locations. While each individual radiation beam may have relatively low intensity, isocenter <NUM> may receive a relatively high level of radiation when multiple doses from different radiation beams accumulate at isocenter <NUM>. In certain embodiments, isocenter <NUM> may correspond to a target under surgery or treatment, such as a tumour.

<FIG> illustrates another radiotherapy device <NUM>, a linear accelerator <NUM> in which the present invention can be used. Using a linear accelerator <NUM>, a patient <NUM> may be positioned on a patient table <NUM> to receive the radiation dose determined by the treatment plan. Linear accelerator <NUM> may include a radiation head <NUM> that generates a radiation beam <NUM>. The entire radiation head <NUM> may be rotatable around a horizontal axis <NUM>. In addition, below the patient table <NUM> there may be provided a flat panel scintillator detector <NUM>, which may rotate synchronously with radiation head <NUM> around an isocenter <NUM>. The intersection of the axis <NUM> with the center of the beam <NUM>, produced by the radiation head <NUM> is usually referred to as the "isocenter". The patient table <NUM> may be motorized so that the patient <NUM> can be positioned with the tumour site at or close to the isocenter <NUM>. The radiation head <NUM> may rotate about a gantry <NUM>, to provide patient <NUM> with a plurality of varying dosages of radiation according to the treatment plan.

In the following, the present invention will be described in more detail with reference to embodiments. As been discussed above, the inverse planning according to the invention is formulated as optimization problem or problems, which preferably is convex and thereby the solutions is reproducible and can be found quick and efficiently. The clinical criteria that provides basis for the evaluation are inherently non-convex and are therefore translated into convex "surrogates". In the present invention, two or more geometric structures are introduced for each target volume and the target volume is hence encompassed by two set of voxels or shells.

In <FIG>, the geometry of an inverse planning problem in a simplified two-dimensional illustration is shown. The structures are shown as rings but since the target volume is three-dimensional, the rings are consequently sets of voxels, or in other words shells or sphere layers shapes, and encompasses the target volume (or tumour value). The target volume <NUM> is thus encompassed by the inner shell <NUM> and, at least one, outer shell <NUM>. The inner shell <NUM> promotes selectivity and the outer shell <NUM> promotes gradient index, respectively. The inner shell <NUM> encompasses the target volume <NUM> and its inner surface <NUM> may be directly adjacent to the outer surface <NUM> of the target volume <NUM>, as shown in <FIG> while the inner surface <NUM> of the outer shell <NUM> in the example in the <FIG> may be adjacent to outer surface <NUM> of the inner shell <NUM>. However, the outer shell <NUM> or outer shells may be located with a radial distance from the outer surface <NUM> of the inner shell <NUM>, as shown in <FIG>. The radial distance may be different in different directions, for example, the distance may be different in x- y- and z-directions.

Hence, the target volume <NUM> is encompassed by the inner shell <NUM> and, at least one, outer shell <NUM>. The inner shell <NUM> promotes selectivity and the outer shell <NUM> promotes gradient index, respectively. The inner shell <NUM> encompasses the target volume <NUM> and its inner surface <NUM> may be directly adjacent to the outer surface <NUM>. In this embodiment, the inner surface <NUM> of the outer shell <NUM> is located at a distance from the outer surface <NUM> of the inner shell <NUM>.

In <FIG>, the shells are illustrated having regularly shaped inner surfaces, but it is understood that it is only schematic illustration, for example, the inner surfaces and outer surfaces may be irregular for example, due to different distances between inner surface of a shell and outer surface of the target in different directions.

Further, the shells are illustrated as having a uniform thickness measured in number of voxels or in distance, for example, in mm between inner and outer boundary or surface but the inner and outer set of voxels may instead have a non-uniform thickness measured in voxels or in distance, for example, in mm between inner and outer boundary or surface.

The frame description for each shell is formulated so that each voxel can be individually considered. According to an embodiment, the frame description is an approximation of an integral, namely a sum where the terms correspond to the voxels at distance rj from the outer surface <NUM> of the target volume <NUM> and may be given by: <MAT> where x is the irradiation times for each isocenter, sector, and collimator setting, ϕj is the dose rate matrix for voxels at distance rj, D(r) is a function describing the desired dose as a function of the distance from the target surface, Nj is the number of voxels at distance rj, r is the vector of all target distances and wij is a scalar weight, which in embodiments can be varied voxel-by-voxel. In embodiments of the present invention, the term D(r) is used, describing that the desired dose varies in different directions.

According to embodiments, two shells are applied having a size or volume that depend on the volume of the target. Penalizing dose in these two shells will correspond to promoting the two non-convex quantities selectivity and gradient index, respectively. The size or volume of the outer shell is preferably chosen so that a desired gradient index can be achieved.

The objective function may be formulated voxel-by-voxel for the target and the two encompassing shells. According to embodiments of the present invention, a minimal objective function for one target and thus two shells, which easily can be generalized to more than one target, with neither OAR nor beam-on time penalization, can be formulated as follows: <MAT> where x is the irradiation times for each isocenter, sector and collimator setting, w<NUM>, w<NUM>, w<NUM> are the weights for the target, inner and outer ring respectively. DT is the prescription dose, Ni is the number of target voxels in the structure i ∈ {T, IR, OR} and ϕi is the dose rate in the respective structure. The first term penalizes underdosing of the target, the second term penalizes overdosing of the inner shell and the third term penalizes dose in the outer shell that exceeds DT/<NUM>, where the gradient index is defined as the volume with dose exceeding DT/<NUM> over volume of the dose exceeding DT. The three terms are good convex surrogates for coverage, selectivity and gradient index, respectively. The objective function is a weighted sum where the three weights w<NUM>, w<NUM>, w<NUM> governs the relative importance of the different objectives, and thus, the importance of coverage, selectivity and gradient index respectively. With one weight, or at least one weight, corresponding to each clinical metric, the translation of the clinical objectives to the desired plan qualities can be obtained by adjusting weights of the objective function before the optimization is performed. Since the problem is convex, the complete set of weights will span a Pareto surface. Thus, the extension of the current problem to one of multicriteria optimization is straightforward.

Turning now to <FIG>, a general method according to the present invention will be described. The method may be used for treatment planning for a linear accelerator, for example, in intensity modulated radiotherapy as well as in Volumetric Modulated Arc Therapy utilizing multi-leaf collimators. In a linear accelerator, electron beams are generated by an electron accelerator including an electron gun, a wave guide and a guide magnet. The electron beam impinges on a target made of high atomic number materials thereby creating ionizing radiation. Ionizing radiation can be modeled as a plurality of beamlets each having a beamlet intensity that can be modelled according to a fluence map. The fluence map is determined in the optimization. Moreover, the method may also be used in treatment planning for radiotherapy system having a collimator body provided with several groups or sets of collimator passages, each set being designed to provide a radiation beam of a respective specified cross-section toward a fixed focus point. Suitably the inlet of each set of collimator passages has a pattern that essentially corresponds to the pattern of the sources on the source carrier arrangement. These sets of collimator passage inlets may be arranged so that it is possible to change from one set to another, thereby changing the resulting beam cross-section and the spatial dose distribution surrounding the focus point. The number of sets of collimator passages with different diameter may be more than two, such as three or four, or even more. A typical embodiment of the collimator comprises eight sectors each having four different states (beam-off, <NUM>, <NUM>, and <NUM>). The sectors can be adjusted individually, i.e. different states can be selected for each sector, to change the spatial distribution of the radiation about the focus point.

First in the method <NUM>, at step <NUM>, an inner set of voxels that encompasses the outer surface of a target volume is determined.

Then, in step <NUM>, a first frame description for an inner set of voxels is provided, where the first frame description reflecting criteria for the inner set of voxels.

Thereafter, at step <NUM>, at least one outer set of voxels encompassing the target volume and the inner set of voxels is determined.

At step <NUM>, frame description(s) for at least one outer set of voxels is provided, each reflecting criteria for that outer set of voxels.

The frame descriptions are then used in the optimization problem that steers the delivered radiation at step <NUM>.

Turning now to <FIG>, a treatment planning computer structure in which the method according to the present invention may be implemented will be described. The treatment planning computer structure <NUM> may include a modelling module <NUM> configured for modelling a volume of a patient as a three-dimensional voxel representation or for obtaining such a three-dimensional voxel representation, wherein the volume includes a target volume to be treated during a treatment of the patient in a radiotherapy unit. A voxel set calculating module <NUM> calculates or determines an inner set of voxels that encompasses o the outer surface of a target volume based on a first frame description (e.g. including an objective function and/or one or more constraints for an inner set of voxels) for an inner set of voxels, where the first frame description reflecting criteria for the inner set of voxels, and at least one outer set of voxels encompassing the target volume and the inner set of voxels based on frame description(-s), e.g. including an objective function (or functions) and/or one or more constraints for outer set of voxels, where each reflecting criteria for the outer set of voxels. In one example, the objective functions may be formulated voxel-by-voxel for the target and the two encompassing shells or inner and outer set of voxels, as also shown above: <MAT> where x is the irradiation times for each isocenter, sector and collimator setting, w<NUM>, w<NUM>, w<NUM> are the weights for the target, inner and outer ring respectively. DT is the prescription dose, Ni is the number of target voxels in the structure i ∈ {T, IR, OR} and ϕi is the dose rate in the respective structure.

Further, a calculation module <NUM> configured for generating radiation dose profiles to be delivered to the target, for providing the convex optimization problem including, for example, the objective functions for the inner and outer set of voxels shown above, that steers the delivered radiation according to the objectives, and for calculating dose profiles for specific treatment configurations including beam shape settings for the radiation dose profiles are calculated using the convex optimization problem. A treatment plan module <NUM> is configured for creating treatment plans including determining the radiation dose profiles to be delivered during treatment based on the treatment configurations, wherein each radiation dose profile is modelled by a spatial dose volume distribution of radiation represented by a three-dimensional voxel representation, the shape of the spatial distribution depending on the beam shape settings. An optimizing module <NUM> is configured for selecting an optimal treatment plan that satisfies the clinical criteria. In embodiments of the present invention, the optimization, i.e. selecting an optimal treatment plan that satisfies the clinical criteria, is performed and then the treatment plan including determining the radiation dose profiles to be delivered during treatment based on the treatment configurations is created.

In embodiments of the present invention, the treatment plan computer structure <NUM> may utilize a method as described in <FIG> or <FIG> and may be integrated into a system for delivering intensity modulated radiation treatment including a radiation source that generates at least one radiation beam and a structure for generating a plurality of beamlets.

The methods described herein according to the present invention may furthermore be used in combination with a method for providing a low overall dose volume. In <FIG>, this is described in more detail. It should however be noted that <FIG> shows the geometry of in a simplified two-dimensional illustration. The structures are shown as rings but since the target volumes is three-dimensional, the rings are consequently shells or sphere layers shapes and encompasses the target volume (or tumour value).

There is an abundance of clinical data showing that adverse cognitive effects may occur if large volumes, Vad, of normal tissue is irradiated by relatively low dose. In particular, this is the case when multiple targets are close to each other. In <FIG>, three targets T1, T2, T3 are shown being close to each other. Further, inner and outer set of voxels, called rings below but since the targets are three-dimensional they are shells in reality, are denoted by S1T1, S2T1, S1T2, S2T2, S1T3, S2T3.

The main problem is that the set of voxels, with volume equal to Vad, depends on the dose distribution and will change during the optimization, leading to a non-convex optimization problem which is in general difficult to solve. To achieve a convex formulation it is therefore necessary to have a fixed geometry in which dose is penalized.

According to the present invention, a volume filling procedure or fill algorithm is applied, for example, a fill algorithm used in the Leksell Gamma Plan. One example of a suitable fill algorithm is described in a co-pending, not yet published, patent application by the same applicant.

Based on the use of the fill algorithm, a fixed low dose ring, R as shown in <FIG>, of voxels can be created in the volume surrounding at least one target (T1, T2, T3). The voxels of this fixed volume can then be penalized giving an efficient low dose penalization. If there is assumed that there is a pair (Vad,Dad) where Dad is the dose at which adverse effects are significant if the volume is at least Vad, see <FIG>. For instance, there is clinical evidence suggesting an increased risk of radionecrosis if the volume receiving more than <NUM> Gy exceeds <NUM> cc, but the user could specify other values. According to the present invention, such adverse effects can be significantly reduced or elimiated by introducing a penalty term in the optimization problem. As mentioned above, a fill algorithm is used first, which is a pre-step to the optimization. In addition to providing the isocenter locations, the fill algorithm also gives the shot collimator configuration for each isocenter. By setting the prescription dose forcing the weights to be <NUM> for all shots, a realistic dose distribution can be calculated. To suppress doses to large volume a low dose ring is created and the algorithm for creating the low dose ring consists of the following steps. A fill algorithm is thus used to find isocenter locations and to determine shot collimator configurations for all isocenter locations. Prescription doses for the target(s), T1, T2, T3, are set. This gives irradiation times for all shots. Then, the dose distribution is calculated from the above configuration. Thereafter, the voxels, SVad ,in the the 3D isodose volume of the dose distribution having a volume equal to Vad (after having added the target volumes) are identified. Then, a ring of voxels, R, is defined as the set difference between a contraction and an expansion of SVad, see <FIG>, using, for example, a distance model: <MAT> <MAT> <MAT> <MAT> Here DF,ad is the isodose in Gy corresponding to Vad. A "ring size" corresponding to <NUM> Gy is a reasonable choice to include various dose distributions without introducing too many voxels in the optimization. Then, a penalization term is added in the objective function penalizing voxels with dose exceeding a threshold dose. In embodiments of the present invention, it may be in the following form: <MAT> where the sum runs over voxels in the low dose ring and wlr is the optimization weight. This ring is treated in the same way as the outer ring(s) in the optimization.

Claim 1:
A method for treatment planning implemented in a computer structure for use for a radiotherapy system, wherein delivered radiation is determined using an optimization problem that steers the delivered radiation according to objectives reflecting criteria for regions of interest, that includeat least one target volume to be treated during treatment of the patient and at least one of organs at risk and/or healthy tissue,
wherein said at least one target volume, organs at risk and/or healthy tissue are three-dimensional voxel representations, said method comprising the steps of:
determining an inner set of voxels that encompasses the outer surface of a target volume;
providing a first frame description for said inner set of voxels, said first frame description reflecting at least one criterion for the inner set of voxels, wherein said first frame description includes at least an objective function for said inner set of voxels;
determining at least one outer set of voxels encompassing said target volume and said inner set of voxels;
providing a respective frame description for each outer set of voxels, wherein said respective frame description includes at least an objective function for said outer set of voxels, and each respective frame description reflects at least one criterion for that outer set of voxels; setting a weight corresponding to an importance of the objective or objectives of said objective functions for said inner set of voxels and said outer set of voxels; and
using said frame descriptions in the optimization problem that steers the delivered radiation;
wherein said weight for said inner set of voxels is selected to promote selectivity, and wherein said weight for said outer set of voxels is selected to promote high gradient outside the target/targets.