Radiation treatment planning methods, systems and computer program products

Abstract

A method for radiation treatment planning comprises: receiving patient data, including imaging data; identifying contours of structures in the patient, the contours comprising a spatial location of a structure and whether the structure is a metastatic or healthy tissue; calculating a three dimensional (3D) treatment matrix of locations of metastatic tissue; calculating a 3D sparing matrix of location of healthy tissue; modifying the treatment matrix to prioritize certain targets based on their characteristics; modifying the treatment matrix using the sparing matrix to better spare critical structures; identifying treatment clusters based on the treatment matrix; and designating isocenters based on the treatment clusters to thereby formulate a radiation treatment plan for the patient.

Description

Attorney Docket No. 9151.278.WORADIATION TREATMENT PLANNING METHODS, SYSTEMS AND COMPUTER PROGRAM PRODUCTSTECHNICAL FIELD

[0001] The present invention relates to radiation treatment planning, and in particular, methods, systems and computer program products for planning irradiation treatment and avoiding critical anatomical structures.BACKGROUND

[0002] Radiation treatment has been performed by machines such as a medical linear accelerator (LINAC) such as a Varian Truebeam(TM) device or a Gamma Knife(TM) to treat cancerous tumors with radiation. The LINAC devices typically rotate around the tumor at different angles to reduce accumulated radiation exposure in healthy tissue and increase radiation exposure at the treatment or tumor site

[0003] Many cancer patients have multiple metastases or tumors, and treatment planning that avoids healthy tissue remains a challenge. Avoiding critical structures, such as the brain stem or other important anatomical structures, may also present challenges in patients with multiple metastases. The treatment isocenter is a point in space where the axes of rotation for the machine's gantry, collimator, and treatment couch intersect during radiation treatment Selecting the isocenter placement, relative dose during treatment, and overall radiation treatment planning may be challenging for multiple metastases.SUMMARY

[0004] According to some embodiments, a method for radiation treatment planning comprises: receiving patient data, including imaging data; identifying contours of structures in the patient, the contours comprising a spatial location of a structure and whether the structure is a metastatic or healthy tissue; calculating a three dimensional (3D) treatment matrix representing the locations of metastatic tissue; calculating a 3D sparing matrix of location of healthy tissue; modifying the treatment matrix to prioritize certain target regions based on the target region characteristics; modifying the treatment matrix using the sparing matrix to better spare critical structures; identifying treatment clusters based on the treatment matrix; and designating isocenters based on the treatment clusters to thereby formulate a radiation treatment plan for the patient.Attorney Docket No. 9151.278.WO

[0005] Computer program products and a system for implementing the method are provided.BRIEF DESCRIPTION OF THE DRAWINGS

[0006] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain principles of the invention.

[0007] FIG. 1 is a schematic diagram of a radiation treatment planning system according to some embodiments.

[0008] FIG. 2 is a flowchart of operations of a radiation treatment planning system according to some embodiments.

[0009] FIGS. 3A-3C illustrate screen shots of a brain cancer patient from a radiation oncology treatment planning software, including multiple tumors and various critical structures, according to some embodiments.

[0010] FIG. 4 i s a dictionary of targets and structures that are assigned to a treatment matrix according to some embodiments.

[0011] FIG. 5 is a dictionary of critical structures that are assigned to a sparing matrix according to some embodiments.

[0012] FIG. 6 is a DataFrame containing target characteristics and cluster assignments according to some embodiments.

[0013] FIG. 7 is a table of isocenter coordinates for an analyzed patient data set according to some embodiments.

[0014] FIG. 8A is an image of a patient receiving nine arcs of radiation (three isocenters and three arcs per isocenter) in a simulation according to some embodiments

[0015] FIG. 8B is a table of the designated radiation arcs seen in the image of FIG. 8A.

[0016] FIGS. 9A-9B illustrate a visualization in the axial plane of the dose delivered by simulated treatments using a one-isocenter plan (FIG. 9A) and three-isocenter plan (FIG. 9B) according to some embodiments.

[0017] FIG. 10 illustrates a graph of key treatment plan evaluation metrics changing as isocenter quantity varies per a study including ten patients according to some embodiments.

[0018] FIGS. 11A-11F illustrate visualizations in the axial plane of the dose delivered by simulated treatments with varying isocenter configurations to a simulated head phantom containing five tumors according to some embodiments.Attorney Docket No. 9151.278.WODETAILED DESCRIPTION

[0019] The present inventive concepts are described herein with reference to the accompanying drawings and examples, in which embodiments are shown. Additional embodiments may take on many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the inventive concepts to those skilled in the art.

[0020] As illustrated in FIG. 1, a radiation treatment planning system 10 including a control ler / analyzer 100 and a radiation treatment device 120 is shown. The controller 100 includes a processor 110, data 112, and a treatment planning module 114. The treatment planning module 114 is configured to analyze the data 112, which may include patient data such as patient disease information, demographic information, imaging data of the treatment area, critical structures in the treatment area and the like. The treatment planning module 114 analyzes the data 112 and and provides a treatment plan based on patient data to the radiation treatment device 120 as described herein. The radiation treatment device 120 can be a medical linear accelerator (LINAC) for treating patients with cancer using radiation beams. Various types of radiation treatment may be used, including stereotactic radiosurgery or SRS, which is a method for delivering radiation to tumors in the brain, neck, lungs, liver, spine, and other parts of the body, that involves immobilizing the patient. An example of SRS is treatment performed with the Gamma Knife stereotactic radiosurgery device. Accordingly, the radiation treatment device 120 may be a medical linear accelerator (LINAC) device, Proton Therapy Machine, Tomotherapy Machine, Orthovoltage Machine, and sterotactic radiosurgery treatments (e.g. Cyberknife or Gamma Knife).

[0021] As shown in FIG. 2, the treatment planning module 114 receives image data of a treatment area (Block 200). The image data may include standard imaging data, for example, in accordance with the Digital Imaging and Communications in Medicine Standard (DICOM) in radiation therapy. The contours of structures in the image are identified (Block 210). The contours may be isolated and logged by 1) an identifier or name, 2) a type of contour that can identify the nature of the structure (e.g., a tumor and size of metastasis, a critical structures such as the brain stem, and the like), 3) a location, for example, in voxel coordinates, 4) whether the contour is desired to be treated with radiation or spared from treatment, and 5) a prescription (for contours to be treated) or constraint (for contours to be spared).

[0022] A 3D treatment matrix and a 3D sparing matrix are calculated based on the image data and the contours of the structures (Block 220). The 3D treatment matrix includesAttorney Docket No. 9151.278.WOregions of the treatment area in which radiation treatment is desired, as well as information regarding the need to irradiate the targets. The 3D sparing matrix includes regions of the treatment area that includes critical structures or anatomical features in which radiation should be avoided, as well as information regarding the maximum dosimetric constraints.

[0023] The 3D treatment matrix is modified to prioritize certain target regions based on the target, region characteristics and by using the sparing matrix to better spare critical structures (Block 230). The modified 3D treatment matrix is used to determine treatment clusters (Block 240) Targets (or target regions) may be prioritized based on various characteristics. For example, target regions are first characterized based on various geometric and clinical considerations, such as target depth and size. Target prioritization is then calculated based on target characteristics using an equation such as EQUATIONS 1 --3. EQUATIONS 1-3 are as follows:EQ 1. Pt= PD* Pv* PxPtTotal Target PriorityPD: T ar get Depth-Based PriorityPv: Target Volume-Based PriorityPx: Target Priority Contribution by some variable xEQ 2. PD= 1 + kDDt2Dt= Target DepthkD> 0: Depth Control FactorkyEQ 3PF = 1 +_2L_Vt= Target Volumekv> 0: Volume Control Factor

[0024] Prioritized targets are weighted more heavily in algorithms for determining target cluster, such as the modified form of k-means clustering seen in EQUATION 4.K EQ 4. WCSSeff= ^ \\Xi -FkWeff2k = 1 Xi GWCSS-. Within-Cluster Sum of SquaresCkthe k-th clusterAttorney Docket No. 9151.278.WOpkthe k-th cluster centroid coordinatesXi. the coordinates of each data point (i) in CkK\ the number of clusters||... Weff'- the effective euclidian distance

[0025] Critical structure sparing needs are also imposed on the 3D treatment matrix and can be done so either through the modification of the clustering equation (EQUATION 5) or by directly modifying the 3D treatment matrix.EQ 5. WCSSe^f spare K / \2 1 A "’ L efffc=i \ X( e T n ckXjEO n ckip "eff T: Set of TargetsO\ Set of Organsα ≥ 0: Target Weightβ ≥ 0: Organ Weighte > 0: Constant to avoid divison by 0

[0026] For example, the sparing needs may be superimposed from the 3D sparing matrix onto the 3D treatment matrix. Alternatively, the 3D sparing matrix may be used to deform or modify the 3D treatment matrix or contribute to the determination of the target prioritization.

[0027] Each treatment cluster has a centroid, which can be used to identify isocenters for treatment (Block 250) This centroid can be determined either by analyzing the original treatment matrix or a modified treatment matrix that considers any number of potential modifiers, such as target prioritization or organ sparing. The resulting treatment matrix may no longer directly include the data associated with concepts such as sparing critical structures, however, the modified treatment matrix may spatially represent such concepts by shifting the location of the treatment values using the sparing matrix. For example, EQUATION 5 represents the need for sparing through centroid repulsion (pushing the centroid away from organs) as opposed to tumors which exhibit centroid attraction (pulling the centroid towards the tumors).Attorney Docket No. 9151.278.WO

[0028] The modified treatment matrix may be analyzed by a clustering algorithm to determine a number of isocenters and their locations for treatment purposes. The clustering algorithm considers the intensity and the need for treatment of regions in the modified treatment matrix. One way for the clustering algorithm to do so is to inflate the quantity of targets proportionally to the target priority, simulating a greater number of targets and thus increasing the attraction to the center of high-priority targets. After the clusters are determined, each cluster may be evaluated in isolation or with regard to the other clusters. For each cluster of the modified treatment matrix, the centroid may be determined in some manner, such as the one seen in EQUATION 6.EQ 6.|Ck|: the total number data points in Ck

[0029] With target prioritization, the centroid equation can consider the inflated data sets previously described. The clusters may include multiple tumors; however, in some cases, a cluster may only include a single tumor or a portion of a tumor. Treatment clusters can either be “hard” (each target is assigned to exactly one cluster) or “soft” (each target is assigned to at least one cluster).

[0030] The coordinates of each centroid may be used in the treatment planning system as isocenters, and the new isocenters are used for radiation treatment. These isocenters can be utilized generally in the treatment planning process, or isocenters can be specifically designated for partially or fully treating specific targets based on the determined clusters.

[0031] Accordingly, in some embodiments, radiation treatment plans with isocenters that are identified without necessarily including one isocenter for each target or tumor can be formulated. The number and location of isocenters may be optimized such that the location and number of isocenters is calculated based on tumor and critical structure contours instead of identifying one isocenter per target. The selection of isocenters according to some embodim ents may impact the number of treatment arcs, beam modulation, collimator patterns, and the like, and may result in changes that decrease treatment time, decrease integral dose, increase conformity, reduce the magnitude of error, and increase feasibility and efficacy.

[0032] Embodiments according to the present invention are described below'.

[0033] The need for treatment may be based on standard prescription guidelines. For example, a malignant secondary tumor of size 2.1-3 cm can be dosed with 15-18Gy ofAttorney Docket No. 9151.278.WOradiation; voxels the tumor occupies could be assigned a value equivalent to the prescription, or variable values throughout the contoured volume based that respect the prescribed isodose line. Alternatively, tumors could be considered as a point instead of a cloud of voxels and would thus receive a static prescription. Clinical procedures may be different clinic-to-clinic and patient-to-patient, and the prescription is variable and determined by the clinician on a per-treatment basis. Clinical constraints and the weighting of different constraints may also be used, including constraints for sparing or critical structures. The contours may be identified using information in the DICOM-RT file or other patient data including imaging data (and if it is a tumor, the size is measured) and then the needs of the contour (treatment, dose, or avoiding or sparing radiation) is assigned to the voxels associated with the structure.

[0034] Modification of the 3D treatment matrix may be determined by various techniques as would be understood by one of skill in the art of modifying the matrix. The treatment matrix may be modified to avoid the areas identified by the 3D sparing matrix, including but not limited to, the organ repulsion or vector deformation. Modification based on target priority may occur through the multiplicative priority factor as described in EQUATION 1 or other means. This modification can be represented through an inflation of the target data set or other means. Numerous geometric, biological, clinical, and technology factors may be factors may be used to determine target priority, including but not limited to, target depth, volume, and prescription. Clustering may also be performed by various techniques as would be understood by one of skill in the art. Clustering may be performed to cluster together tissue for treatment and / or sparing from treatment, including, but not limited to, k-means clustering or Partitioned Local Depth.

[0035] FIGS. 3A-3C illustrates a screen shot of a brain cancer patient from a radiation oncology treatment planning software, including multiple tumors and various critical structures. The presence of a tumor within a critical structure, such as the brainstem, presents challenges for treatment because critical structures are regions in which radiation should avoid. The relevant structures, including targets for treatment, are contoured in color. Regions of interest may be extracted into other programming languages, such as Python. As shown in FIGS. 4-5, each target and structure, or any combination of them, may be assigned a matrix. These matrices may be combined to yield the 3D treatment matrix and the 3D sparing matrix.

[0036] FIG. 6 is a DataFrame containing target characteristics and cluster assignments. Each color represents a different cluster. Targets are represented by their centers of mass in this instance; however, targets may be represented by point clouds. Proximity to critical structures is used for organ sparing in this instance; however, it may be represented in otherAttorney Docket No. 9151.278.WOways. Target priorities are listed in this DataFrame, though prior to clustering, each row is duplicated a number of times equal to the target priority (rounded to the nearest integer) in this instance; however, target priority can be represented in other ways.

[0037] Following clustering, as shown in FIG. 6, the centroid may be calculated for each cluster, and the resultant isocenter coordinates are noted, as seen in FIG 7. These coordinates may be used to designate isocenters directly in the DICOM-RT file before sending the data to a treatment planning software system (such as RayStation(TM), Eclipse(TM), or Monaco(TM)), or can be manual input into the plan. In systems that have built-in scripting, such as RayStation(TM), all aspects of the workflow can be performed inside the software, and the output would be the direct creation of beams with the corresponding isocenter locations. The remainder of the plan may be generated using constrained planning methodologies.

[0038] As shown in FIGS. 8A-B, beams are assigned to each isocenter (in this case, nine arcs of radiation (three isocenters and three arcs per isocenter). In this case, two 180-degree arcs and one 360-degree arc were used for each isocenter. These beams are planned using methods that may be known to those of skill in the art, and the arcs may revolve around their respective isocenters. Beam arrangements factors may also be adjusted depending on the matrices and clustering, including but not limited to gantry start and stop angles, collimator angle, couch angle, gantry spacing, and maximum delivery time. While the example plan is shown utilizing arc therapy, static beams or other types of therapies can be utilized, including any time of radiation treatment utilizing an isocenter, focus, or other geometric point of focus or rotation.

[0039] FIGS. 9A-9B illustrates a visualization in the axial plane of the dose delivered by simulated treatments using one-and three-isocenter plans, respectively. It can be seen that the plan with three isocenters exhibits substantially less dose to healthy tissue and the brain stem while delivering approximately the same dose to targets. Healthy tissue may include critical structures and / or normal tissue (e.g., tissue that does not exhibit disease characteristics).

[0040] FIG. 10 illustrates a graph of key treatment plan evaluation metrics changing as isocenter quantity varies per a study including ten patients with nine-eleven tumors each. It can be seen that as isocenter quantity increases, plan quality increases, but at a diminishing rate. This is most notably demonstrated by the V8Gy and V12Gy measurements, indicating reduced integral dose.

[0041] FIGS. 11A-11F illustrates a a visualization in the axial plane of the dose delivered by simulated treatments with varying isocenter configurations to a simulated head phantom containing five tumors according to some embodiments. The methods and systems describedAttorney Docket No. 9151.278.WOherein were used to simulate radiation treatment plans with one isocenter, which is the current clinical standard. In addition, plans with between one and five isocenters were simulated. The most clinically acceptable treatment plans included three or four isocenters. As shown in FIGS.11 A-l IF, too few isocenters (e.g., one isocenter, FIG 1 IB) and too many isocenters (e.g., five isocenters, FIG. 1 IF) can be less accurate for treating the tumor with radiation and avoiding or sparing critical structures than three isocenters (FIG. FIG. 11D). In some embodiments, simulated radiation treatment plans may be calculated with different numbers of isocenters using the methods and systems described herein to determine the best number of isocenters.

[0042] Although in some embodiments, a plurality of treatment plans may be simulated, and the most accurate or “best” treatment plan may be selected to increase the dosage delivered to diseased structures or tumors and to decrease the dosage delivered to healthy tissue or critical structures, it should be understood that it may not be necessary to simulate the treatment plan(s) in order to determine which isocenter quantity / configuration is best. Accordingly, a mathematical analysis of the cluster structure may be used. Accordingly, in some embodiments, a patient may be treated with radiation using the radiation treatment plan that is obtained using the methods described herein, e.g., using a medical linear accelerator (LINAC) device, a Proton Therapy Machine, a Tomotherapy Machine, Orthovoltage Machine, GammaKnife or CyberKnife device.

[0043] Like numbers refer to like elements throughout. In the figures, the thickness of certain lines, layers, components, elements or features may be exaggerated for clarity.

[0044] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting thereof. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items. As used herein, phrases such as “between X and Y” and “between about X and Y” should be interpreted to include X and Y. As used herein, phrases such as “between about X and Y” mean “between about X and about Y.” As used herein, phrases such as “from about X to Y” mean “from about X to about Y.” The term “about” should be understood to include variations of up to 20%.

[0045] Unless otherwise defined, all terms (including technical and scientific terms) usedAttorney Docket No. 9151.278.WOherein have the same meaning as commonly understood by one of ordinary skill in the art. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and relevant art and should not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Well-known functions or constructions may not be described in detail for brevity and / or clarity.

[0046] It will be understood that when an element is referred to as being “on,” “attached” to, “connected” to, “coupled” with, “contacting,” etc., another element, it may be directly on, attached to, connected to, coupled with or contacting the other element or intervening elements may also be present. In contrast, when an element is referred to as being, for example, “directly on,” “directly attached” to, “directly connected” to, “directly coupled” with or “directly contacting” another element, there are no intervening elements present. It will also be appreciated by those of skill in the art that references to a structure or feature that is disposed “adjacent” another feature may have portions that overlap or underlie the adjacent feature.

[0047] Spatially relative terms, such as “under,” “below,” “lower,” “over,” “upper” and the like, may be used herein for ease of description to describe one element or feature's relationship to another element(s) or feature(s) as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is inverted, elements described as “under” or “beneath” other elements or features would then be oriented “over” the other elements or features. Thus, the exemplary term “under” may encompass both an orientation of “over” and “under.” The device may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly. Similarly, the terms “upwardly,” “downwardly,” “vertical,” “horizontal” and the like are used herein for the purpose of explanation only unless specifically indicated otherwise.

[0048] It will be understood that, although the terms “first,” “second,” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. Thus, a “first” element discussed below could also be termed a “second” element without departing from the teachings of the present disclosure. The sequence of operations (or steps) is not limited to the order presented in the claims or figures unless specifically indicated otherwise.

[0049] The present invention is described below with reference to block diagrams and / or flowchart illustrations of methods, apparatus (systems) and / or computer program productsAttorney Docket No. 9151.278.WOaccording to embodiments of the invention. It is understood that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, and / or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer and / or other programmable data processing apparatus, create means for implementing the functions / acts specified in the block diagrams and / or flowchart block or blocks.

[0050] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function / act specified in the block diagrams and / or flowchart block or blocks.

[0051] The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions / acts specified in the block diagrams and / or flowchart block or blocks.

[0052] Accordingly, the present invention may be embodied in hardware and / or in software (including firmware, resident software, micro-code, etc.). Furthermore, embodiments of the present invention may take the form of a computer program product on a computer-usable or computer-readable storage medium having computer-usable or computer-readable program code embodied in the medium for use by or in connection with an instruction execution system.

[0053] The computer-usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CD-ROM).

[0054] The foregoing is illustrative of the present inventive concept and is not to be construed as limiting thereof. Although a few example embodiments have been described, those skilled in the art will readily appreciate that many modifications are possible in theAttorney Docket No. 9151.278.WOexemplary embodiments without materially departing from the novel teachings of this inventive concept. Accordingly, all such modifications are intended to be included within the scope of this inventive concept as defined in the claims. Therefore, it is to be understood that the foregoing is illustrative of the present inventive concept and is not to be construed as limited to the specific embodiments disclosed, and that modifications to the disclosed embodiments, as well as other embodiments, are intended to be included within the scope of the appended claims.

Claims

Attorney Docket No. 9151.278.WOWHAT IS CLAIMED IS:

1. A method for radiation treatment planning, the method comprising: receiving patient data, including imaging data;identifying contours of structures in the patient, the contours comprising a spatial location of a structure and whether the structure is a metastatic or healthy tissue;calculating a three dimensional (3D) treatment matrix of locations of metastatic tissue; calculating a 3D sparing matrix of location of healthy tissue;modifying the 3D treatment matrix to prioritize certain target regions based on target region characteristics;modifying the 3D treatment matrix using the sparing matrix to better spare critical structures;identifying treatment clusters based on the treatment matrix; anddesignating isocenters based on the treatment clusters to thereby formulate a radiation treatment plan for the patient.

2. The method of Claim 1, further comprising treating the patient with radiation using the radiation treatment plan.

3. The method of any preceding claim, wherein the health tissue comprises critical structures or normal tissue.

4. The method of any preceding claim, wherein designating isocenters is based on a centroid of the treatment clusters in the modified 3D treatment matrix or other similar representations.

5. The method of any preceding claim, wherein each of the treatment clusters includes one or more tumors or a portion of a tumor.

6. The method of any preceding claim, further comprising:identifying a plurality of treatment plans based on different numbers of isocenters; simulating the plurality of treatment plans; andselecting one of the plurality of treatment plans based on the simulating and whether radiation is reduced to critical structures.Attorney Docket No. 9151.278.WO7. The method of any preceding claim, wherein identifying treatment clusters comprises clustering together tissue for treatment.

8. The method of Claim 7, further comprises identifying sparing needs by quantifiably representing critical structure tissue in which radiation is reduced during treatment.

9. The method of any preceding claim, wherein the treatment is performed by a medical linear accelerator (LINAC) device, Proton Therapy Machine, Tomotherapy Machine, Orthovoltage Machine, and sterotactic radiosurgery treatments (e.g. Cyberknife or Gamma Knife).

10. A computer implemented method configured to implement the method of any preceding claim.

11. A computer program product comprising a non-transient computer readable medium, the computer readable medium having computer readable program code embodied therein, the computer readable program code comprising:computer readable program code configured to receive patient data, including imaging data;computer readable program code configured to identify contours of structures in the patient, the contours comprising a spatial location of a structure and whether the structure is a metastatic or healthy tissue;computer readable program code configured to calculate a three dimensional (3D) treatment matrix of locations of metastatic tissue;computer readable program code configured to calculate a 3D sparing matrix of location of healthy tissue;computer readable program code configured to modify the 3D treatment matrix to prioritize certain targets based on their characteristics;computer readable program code configured to modify the 3D treatment matrix using the sparing matrix to better spare critical structures;computer readable program code configured to identify treatment clusters based on the treatment matrix;Attorney Docket No. 9151.278.WOandcomputer readable program code configured to designate isocenters based on the treatment clusters to thereby formulate a radiation treatment plan for the patient.

12. The computer program product of Claim 11, wherein the healthy tissue and diseased but essential tissue comprises critical structures.

13. The computer program product of Claim 11, wherein the computer readable program code is configured to designate isocenters is based on treatment clusters in the modified 3D treatment matrix.

14. The computer program product of Claims 11-13, wherein each of the treatment clusters includes one or more tumors or a portion of a tumor.

15. The computer program product of Claims 11-14, further comprising: computer readable program code configured to identify a plurality of treatment plans based on different numbers of isocenters;computer readable program code configured to simulate the plurality of treatment plans; andcomputer readable program code configured to select one of the plurality of treatment plans based on the simulating and whether radiation is reduced to critical structures.

16. The computer program product of Claim 11-15. wherein the computer readable program code is configured to identify treatment clusters by clustering together tissue for treatment.

17. The computer program product of Claim 16, wherein further comprising computer readable program code configured to identify sparing clusters by clustering together critical structure tissue in which radiation is reduced during treatment.

18. The computer program product of Claims 11-17, wherein the treatment is performed by a medical linear accelerator (LINAC) device.

19. A system for radiation treatment planning, the system comprising:Attorney Docket No. 9151.278.WOa radiation treatment planning module on a processor, the radiation treatment planning module being configured to provide a radiation treatment plan to a radiation treatment device, the radiation treatment planning module being further configured to receive patient data, including imaging data; to identify contours of structures in the patient, the contours comprising a spatial location of a structure and whether the structure is a metastatic or healthy tissue; to calculate a three dimensional (3D) treatment matrix of locations of metastatic tissue; to calculate a 3D sparing matrix of location of healthy tissue; to modify the treatment matrix using the sparing matrix to better spare critical structures; to identify treatment clusters based on the treatment matrix; and to designate isocenters based on the treatment clusters to thereby formulate a radiation treatment plan for the patient.

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