Patient volume segmentation device and method

Abstract

By one method, a control circuit accesses planned computed tomography image information for a particular patient. The control circuitry also accesses two-dimensional digital subtraction angiography image information for a particular patient. The control circuit then fuses the planned computed tomography image information with the two-dimensional digital subtraction angiography image information to provide fused image information of the patient target volume.

Description

Technical Field

[0001] These teachings generally relate to treating a planned target volume of a patient with energy according to an energy-based treatment plan, and more particularly to segmenting one or more patient volumes to support development of an energy-based treatment plan. Background Art

[0002] The use of energy to treat medical conditions comprises a known area of ​​prior art effort. For example, radiation therapy comprises an important component of many treatment plans for reducing or eliminating harmful tumors. Unfortunately, the energy applied by itself cannot distinguish between unwanted material and adjacent tissues, organs, etc. that are desirable or even critical for the continued survival of the patient. As a result, energy such as radiation is usually applied in a carefully administered manner to at least attempt to confine the energy to a given target volume. So-called radiation treatment plans are often used in the above-mentioned aspects.

[0003] A radiation treatment plan typically includes specified values ​​for each of the various treatment platform parameters during each of a plurality of consecutive fields. A treatment plan for a radiation treatment course is typically generated automatically by a so-called optimization process. As used herein, "optimization" will be understood to refer to improving a candidate treatment plan without necessarily ensuring that the optimized result is in fact a single best solution. Such optimization typically includes automatically adjusting one or more physical treatment parameters (typically while observing one or more corresponding constraints on these aspects), and mathematically calculating the possible corresponding treatment results (such as the level of dose) to identify a given set of treatment parameters that represents a good compromise between the desired treatment result and avoiding adverse side effects.

[0004] One or more patient volumes (such as a radiation target and one or more organs at risk) are typically identified to facilitate the aforementioned optimization. Segmentation refers to the identification of separate patient structures, including but not limited to the target treatment volume and the organs at risk. Segmentation is sometimes performed by humans. Although some progress is being made in automated segmentation, certain applications are very challenging even for partial automation. For example, this may be the case when the patient target volume includes an arteriovenous malformation.

[0005] In an AVM, arteries and veins are connected by a cluster of abnormally formed blood vessels. This tangled web of vessels disrupts normal blood flow and oxygen exchange. Arteries within an AVM often deliver high-pressure blood directly into the veins, causing the veins to enlarge and weaken over time. This can lead to various complications, such as bleeding, decreased oxygen supply to tissues, or the formation of blood clots. While radiation can be used to help manage this condition, planning radiation treatment may be hampered, at least in part, by the difficulty in segmenting an AVM. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] The above needs are at least partially met by providing a patient volume segmentation apparatus and method as described in the following detailed description, particularly when studied in conjunction with the accompanying drawings, wherein:

[0007] Figure 1 Includes block diagrams of various embodiment configurations according to these teachings;

[0008] Figure 2 including flow charts configured according to various embodiments of these teachings;

[0009] Figure 3 Includes screen shots of various embodiment configurations according to these teachings;

[0010] Figure 4 Included are graphical depictions of various embodiment configurations according to these teachings;

[0011] Figure 5 includes graphical depictions of various embodiment configurations according to these teachings; and

[0012] Figure 6 Included are graphical depictions of various embodiment configurations according to these teachings.

[0013] The elements in the figure are shown for simplicity and clarity, and do not have to be drawn to scale. For example, the dimensions and / or relative positioning of some elements in the elements in the figure may be exaggerated relative to other elements to help improve the understanding of the various embodiments of this teaching. In addition, common but well-understood elements (which are useful or necessary in commercially feasible embodiments) are often not depicted, so as to contribute to the less obstructed views of these various embodiments of this teaching. Certain actions and / or steps can be described or depicted in a special order of appearance, and those skilled in the art will understand that this particularity about the order is actually not required. The terms and expressions used herein have the common technical meanings consistent with such terms and expressions of the technicians in the aforementioned technical field, unless different specific meanings are set forth in addition herein. Unless otherwise specifically indicated, when used in this article, the word "or" should be interpreted as having a separation grammatical structure rather than a connection grammatical structure. DETAILED DESCRIPTION

[0014] In general, according to these various embodiments, segmentation of various patient target volumes may be facilitated. This may include relatively difficult volumes, including but not limited to arteriovenous malformations located in regions such as within a patient's brain.

[0015] By one approach, control circuitry accesses planning computed tomography image information for a particular patient. The control circuitry also accesses two-dimensional digital subtraction angiography image information for the particular patient. The control circuitry then fuses the planning computed tomography image information with the two-dimensional digital subtraction angiography image information to provide fused image information of a target volume of the patient.

[0016] By one approach, these teachings will adapt control circuitry to generate the aforementioned two-dimensional digital subtraction angiography image information based on at least two x-ray images. The latter may include, for example, two digital subtraction angiography images that are at least substantially orthogonal to each other.

[0017] By one approach, the aforementioned planning computed tomography image information at least partially comprises segmented three-dimensional contours from the corresponding computed tomography image information. In this case, and as an example, the planning computed tomography image information is fused with the two-dimensional digital subtraction angiography image information by at least partially projecting the segmented three-dimensional contours as two-dimensional contours on the two-dimensional digital subtraction angiography image information.

[0018] By one approach, the two-dimensional digital subtraction angiography image information for a particular patient includes at least one closed two-dimensional contour surrounding an image of a target volume of the patient on each of the at least two two-dimensional digital subtraction angiography images.

[0019] By one approach, fusing planning computed tomography image information with two-dimensional digital subtraction angiography image information includes, at least in part, performing a registration between each of the x-ray and planning computed tomography images.

[0020] By one approach, these teachings adapt a control circuit to simultaneously present on an interactive user display: at least two digital subtraction angiography images and at least three computed tomography images, the at least two digital subtraction angiography images each including a pre-delineated two-dimensional guide structure corresponding to a patient target volume and at least one pipeline projection. By one approach, the planning computed tomography images include an axial image, a sagittal image, and a coronal image. By one approach, each of the planning computed tomography images includes a three-dimensional guide frame reconstructed from a two-dimensional guide contour from at least two of the digital subtraction angiography images.

[0021] Digital subtraction angiography has previously been used for AVM target identification because of the unique real-time vascular supply and drainage information it provides in its series of digital subtraction angiography images. Unfortunately, two-dimensional digital subtraction angiography has inherent limitations as a treatment planning procedure. For example, digital subtraction angiography cannot provide accurate three-dimensional target information due to its two-dimensional nature. The three-dimensional target volume calculated using a pair of digital subtraction angiography images is typically the intersection volume of a pair of two-dimensional projections based on a pair of contours depicted on a pair of radiographs. Note that given two projected contours, this defined three-dimensional target volume is only one of the possible volumes corresponding to these two-dimensional projections. Therefore, the resulting three-dimensional target volume often does not represent the true AVM shape, particularly for concave and irregular targets. The resulting errors, including both significant overestimation and underestimation of AVMs, have been reported.

[0022] However, the present teachings provide an effective method for fusing two-dimensional digital subtraction angiography images and planning computed tomography images to interactively and accurately segment the AVM target volume in the planning computed tomography images based on lesion information from the two-dimensional digital subtraction angiography image series. Accurate segmentation in turn helps ensure a more efficient radiation treatment planning optimization process and improved patient outcomes.

[0023] These and other benefits may become more apparent after a thorough review and study of the following detailed description. Referring now to the drawings, and in particular to the Figure 1 , an illustrative device 100 compatible with many of these teachings will first be presented.

[0024] In this particular example, enabling device 100 includes control circuit 101. As a "circuit," control circuit 101 thus includes a structure that includes at least one (and typically many) conductive paths (such as paths composed of a conductive metal such as copper or silver) that carry electrical power in an orderly manner, and that typically also includes corresponding electrical components (both passive (such as resistors and capacitors) and active (such as any of a variety of semiconductor-based devices), as appropriate) to allow the circuit to implement the control aspects of these teachings.

[0025] Such control circuit 101 may include a fixed-purpose hardwired hardware platform (including but not limited to: Application Specific Integrated Circuit (ASIC) (which is an integrated circuit customized for a specific purpose and not intended for general use), Field Programmable Gate Array (FPGA), etc.), or may include a partially or fully programmable hardware platform (including but not limited to: microcontroller, microprocessor, etc.). These architectural choices for such structures are well known and well understood in the art and do not require further description here. The control circuit 101 is configured (e.g., by using corresponding programming that will be fully understood by those skilled in the art) to implement one or more of the steps, actions and / or functions described herein.

[0026] The control circuit 101 is operably coupled to a memory 102. The memory 102 may be integrated with the control circuit 101, or may be physically separate (in whole or in part) from the control circuit 101 as desired. The memory 102 may also be local to the control circuit 101 (where, for example, the two share a common circuit board, chassis, power supply, and / or housing), or may be partially or completely remote to the control circuit 101 (where, for example, the memory 102 is physically located in another facility, another metropolitan area, or even another country than the control circuit 101).

[0027] In addition to information as described herein, such as optimization information for a particular patient (including but not limited to planning computed tomography image information and two-dimensional digital subtraction angiography image information) and information about a particular radiation treatment platform, the memory 102 may also be used, for example, to non-transitory store computer instructions that, when executed by the control circuit 101, cause the control circuit 101 to operate as described herein. (As used herein, this reference to "non-transitory" will be understood to refer to the non-transitory state of the storage content (and, therefore, excludes the case where the storage content merely constitutes a signal or wave), rather than the volatility of the storage medium itself, and therefore includes both non-volatile memory (such as read-only memory (ROM)) and volatile memory (such as dynamic random access memory (DRAM)).

[0028] By an optional approach, the control circuit 101 is also operatively coupled to a user interface 103. The user interface 103 may include any of a variety of user input mechanisms (such as, but not limited to, keyboards and keypads, cursor control devices, touch-sensitive displays, voice recognition interfaces, gesture recognition interfaces, etc.) and / or user output mechanisms (such as, but not limited to, visual displays, audio transducers, printers, etc.) to receive information and / or instructions from a user and / or provide information to a user.

[0029] If desired, the control circuit 101 may also be operably coupled to a network interface (not shown). So configured, the control circuit 101 may communicate with other elements (both within the device 100 and outside the device 100) via the network interface. Network interfaces (including both wireless and non-wireless platforms) are well known in the art and need not be elaborated on here.

[0030] By one approach, a computed tomography device 106 and / or other imaging devices 107 known in the art may acquire some or all of any desired patient-related imaging information, including planning computed tomography image information and other x-ray images, as described herein.

[0031] In this illustrative example, the control circuit 101 is configured to ultimately output an optimized energy-based treatment plan (e.g., such as the optimized radiation treatment plan 113). The energy-based treatment plan typically includes specified values ​​for each of the various treatment platform parameters during each of the plurality of sequential exposure fields. In this case, the energy-based treatment plan is generated by an optimization process, examples of which are further provided herein.

[0032] By one approach, the control circuit 101 may be operably coupled to an energy-based treatment platform 114 configured to deliver therapeutic energy 112 to a corresponding patient 104 having at least one treatment volume 105 and also having one or more organs at risk (at least one of the following: Figure 1 108 and 109 are represented by the first to Nth organs at risk 108 and 109). These teachings are generally applicable to use with any of a wide variety of energy-based treatment platforms / devices. In a typical application setting, the energy-based treatment platform 114 will include an energy source, such as a radiation source 115 of ionizing radiation 116.

[0033] By one approach, the radiation source 115 can be selectively moved along an arcuate path via a gantry (wherein the path at least to some extent surrounds the patient itself during the administration of treatment). The arcuate path can include a complete or nearly complete circle as desired. By one approach, the control circuit 101 controls the movement of the radiation source 115 along the arcuate path and can accordingly control when the radiation source 115 starts moving, stops moving, speeds up, slows down, and / or the speed at which the radiation source 115 travels along the arcuate path.

[0034] As an illustrative example, radiation source 115 may include, for example, an x-ray source based on a radio frequency (RF) linear particle accelerator (linac-based). A linac is a type of particle accelerator that greatly increases the kinetic energy of charged subatomic particles or ions by subjecting the charged particles to a series of oscillating electric potentials along a linear beam line, which can be used to generate ionizing radiation (e.g., x-rays) 116 and high-energy electrons.

[0035] A typical energy-based treatment platform 114 may also include one or more support devices 110 (such as a couch) for supporting the patient 104 during a treatment session, one or more patient fixation devices 111, a gantry or other movable mechanism for allowing selective movement of a radiation source 115, and one or more energy shaping devices (e.g., beam shaping devices 117 such as jaws, multi-leaf collimators, etc.) for providing selective energy shaping and / or energy modulation as needed.

[0036] In a typical application setting, it is assumed herein that during an energy-based treatment session, the patient support device 110 can be selectively controlled by the control circuit 101 to move in any direction (i.e., any X, Y, or Z direction). Because the aforementioned elements and systems are well known in the art, further elaboration of these aspects is not provided herein unless otherwise relevant to the description.

[0037] Reference now Figure 2 , a process 200 will be described, which can be implemented, for example, in conjunction with the above-described application facility (and more particularly, via the aforementioned control circuit 101). Generally speaking, the process 200 is used to facilitate generating an optimized radiation treatment plan 113, thereby facilitating treating a specific patient with therapeutic radiation using a specific radiation treatment platform according to the optimized radiation treatment plan.

[0038] For purposes of illustrative examples, the description provided herein assumes that the patient treatment volume at least partially includes an AVM. External beam radiation therapy is one of the treatment modalities currently available for treating brain AVMs. It should be understood that these teachings are not limited to this application setting.

[0039] At box 201, the process 200 provides: accessing planning computed tomography image information for a particular patient. Those skilled in the art will appreciate that the planning computed tomography image is typically a computed tomography image captured during a pre-processing phase. Such an image is typically used to capture both the target volume and surrounding tissue / structure of the patient. By one approach, the planning computed tomography image information includes, at least in part, a segmented three-dimensional contour from the corresponding computed tomography image information.

[0040] At optional block 202, the process 200 will provide for generating two-dimensional digital subtraction angiography image information based on at least two x-ray images. A digital subtraction angiography will be understood to generally include images of blood vessels in the brain. Such images are generally used to help detect problems with blood flow. The procedure may involve inserting a catheter into an artery in the leg and passing the catheter through a blood vessel in the brain. A contrast dye is injected through the catheter and an x-ray image of the blood vessel is taken. For the purposes of this description, it will be assumed that the digital subtraction angiography image information presents information about the above-mentioned arteriovenous malformation in the patient's brain.

[0041] By one approach, these teachings will accommodate making the two digital subtraction angiography images described above orthogonal to each other (or at least substantially orthogonal to each other - e.g., having a true orthogonality of 0 to 10 degrees).

[0042] At block 203, the control circuit 101 accesses two-dimensional digital subtraction angiography image information for a particular patient. By one approach, the action may include accessing the above-mentioned information generated at optional block 202. By another approach, the action may include accessing such information from another source. By one approach, the accessed two-dimensional digital subtraction angiography image information for a particular patient includes at least one closed two-dimensional contour surrounding an image of a patient target volume (such as the aforementioned arteriovenous malformation in the patient's brain) on each of the at least two two-dimensional digital subtraction angiography images.

[0043] At block 204, the control circuit 101 then fuses the aforementioned planning computed tomography image information with the aforementioned two-dimensional digital subtraction angiography image information to provide fused image information of the patient target volume. By one approach, when the planning computed tomography image information at least partially includes the aforementioned segmented three-dimensional contours from the corresponding computed tomography image information, the fusion of the planning computed tomography image information with the two-dimensional digital subtraction angiography image information may at least partially include: projecting the segmented three-dimensional contours into two-dimensional contours on the two-dimensional digital subtraction angiography image information.

[0044] By one approach, the aforementioned fusion of the planning computed tomography image information with the two-dimensional digital subtraction angiography image information may at least partially comprise, for each image pair of X-ray and planning computed tomography images, performing a registration between the two.

[0045] These teachings are flexible in practice and will accommodate various ways of utilizing the aforementioned findings. As an illustrative optional example of these aspects, and not intended to imply any limitation of these aspects, at optional block 205 and now also referenced Figure 3, the control circuit 101 can simultaneously present two (or more) digital subtraction angiography images 301, 302 and at least three three-dimensional planning computed tomography images 305-307 on an interactive display 300 (e.g., including a portion of the above-mentioned user interface 103), the two (or more) digital subtraction angiography images 301, 302 each including a pre-delineated two-dimensional guide structure 303 corresponding to the patient target volume and at least one pipeline projection 304. Such images can greatly facilitate interaction with the user to best utilize the fused content.

[0046] By one approach, the aforementioned at least three three-dimensional planning computer tomography images may include an axial image 305, a sagittal image 306, and a coronal image 307. In addition, if necessary, the at least three three-dimensional planning computer tomography images may each include a three-dimensional guide frame 308, which is reconstructed based on two-dimensional guide contours from at least two of the digital subtraction angiography images.

[0047] Additional details will now be provided by corresponding examples. Again, it should be understood that these examples are intended for illustrative purposes and are not intended to imply any particular limitations regarding these teachings.

[0048] In this example, to better integrate a 2D digital subtraction angiography image series into a routine workflow when segmenting a 3D AVM target in a planning computed tomography image, these teachings will adapt: ​​interactively segmenting a 3D AVM target from a 3D dataset using a unique visual aid alongside fused 2D digital subtraction angiography images.

[0049] In this example, an arteriovenous malformation target is identified and determined (e.g., by a neurosurgeon) based on temporal blood flow information and vascular structure from frames of a two-dimensional digital subtraction angiography image series (which have been acquired from orthogonal or near-orthogonal x-ray angles). The result is a closed two-dimensional contour on each of the series of digital subtraction angiography images, which can then be used as a two-dimensional guiding structure in subsequent steps.

[0050] The frameless 2D / 3D rigid registration may be performed twice independently, once for each image pair of X-ray / computed tomography images, where the X-ray image has the same geometrical setup as the corresponding series of digital subtraction angiography images. As a result, a geometrical relationship between the series of digital subtraction angiography images and the planning computed tomography images is established. (One skilled in the art will appreciate that a "frame" is a mechanical structure used to hold the patient's head still during image capture. Thus, the foregoing reference to "frameless" will be understood to refer to capturing the reference images without the use of such a frame.)

[0051] When segmenting a 3D AVM target from a planning CT image, the planning CT image can be displayed side-by-side with the 2D DSA image in a previously established registration. The 2D guide structure can be displayed in the 2D DSA image. In order to better integrate the vascular structure of the 2D DSA image into the workflow, the example will be adapted to implement the following visual aids to support interactively (i.e., with the user) segmenting the 3D AVM target.

[0052] In this example, two pipelines can be generated in each of the two-dimensional digital subtraction angiography images to help define the projection range of the two-dimensional guide structure from the first two-dimensional digital subtraction angiography image to the second two-dimensional digital subtraction angiography image, and to indicate the quality of the two-dimensional / three-dimensional registration. By one approach, the calculation of the two projection lines can be based on the epipolar geometry of stereo vision. What is a pipeline? (In this example, the above pipeline can include a display graphic element rendered on the display image. In this example, the pipeline can include a pair of non-parallel lines having an intersection at corresponding sources.)

[0053] Referring to the aforementioned epipolar geometry, given a contour point in a first two-dimensional digital subtraction angiography image, a plane (also referred to as an epipolar plane) can be defined by two X-ray source positions (or camera centers) and the given contour point. The intersection of the epipolar plane and the plane of the second two-dimensional digital subtraction angiography image defines an epipolar line. The projected position of the given contour point from the first two-dimensional digital subtraction angiography image is located on the epipolar line. Iterating over all points in the contour of the guide structure from the first two-dimensional digital subtraction angiography image, these teachings can generate a set of such epipolar lines, all of which intersect at a common point (referred to as an epipolar point).

[0054] The epipolar point is a projection of the first X-ray source position in the second two-dimensional digital subtraction angiography image. The two projection lines of the guide structure from the first two-dimensional digital subtraction angiography image view represent the two outermost epipolar lines found from all epipolar lines intersecting the second two-dimensional digital subtraction angiography image plane, and vice versa.

[0055] By one approach, these teachings are adapted to generate a three-dimensional guide box in a three-dimensional planning computed tomography image to indicate the approximate location and size of an AVM target.

[0056] By a first method in these aspects, two cones may be computed. The first cone connects the sagittal X-ray image source with each point of the sagittal contour of the two-dimensional guide structure. The second cone connects the frontal X-ray image source with each point of the frontal contour of the two-dimensional guide structure. The two cones may then be cut off at the edges of the computed tomography image so that they form two frustums. A bounding box may then be computed around each frustum. Where two frustum bounding boxes intersect, an intersection bounding box may be computed. (For performance reasons, a bounding box may be computed because doing so may reduce the number of candidate voxels for the guide box. However, the present teachings may also be practiced without the use of bounding boxes. For example, all voxels of the computed tomography image may be iterated over instead.)

[0057] Continuing with the foregoing example, for each voxel within the intersecting bounding box within the computed tomography volume, two projection lines may be defined such that one projection line connects the virtual X-ray source position of the frontal two-dimensional digital subtraction angiography image to the voxel, and the other projection line connects the virtual X-ray source position of the sagittal two-dimensional digital subtraction angiography image. Then, the points where the two projection lines intersect the corresponding two-dimensional digital subtraction angiography image planes (frontal or sagittal) may be calculated. If both points of intersection are located inside the contour of the corresponding guide structure, the voxel within the computed tomography volume that is intersected by the two projection lines may be classified as part of the guide frame structure.

[0058] If necessary, these teachings will also support projecting a three-dimensional contour to a two-dimensional contour by using a triangular mesh algorithm. For example, the current three-dimensional target structure volume can be converted to a triangular mesh. The conversion can be based on a marching cube algorithm, which triangulates the isosurface of the volume according to an implicit function (one of the forms of f(x, y, z) = 0). The algorithm advances on a uniform cube (or voxel) grid superimposed on the function area. If all 8 vertices of the cube are positive, or all 8 vertices are negative, the cube is completely above or completely below the surface, and no triangles are emitted. Otherwise, the cube spans the function, and some triangles and vertices are generated. Since each vertex can be positive or negative, there are technically 256 possible configurations. For each cube, an index is calculated by comparing the pixel value at the vertex of the cube with the isosurface value. Using the cube index, a list of cube edges can be looked up from a pre-calculated case table. Then, linear interpolation can be used to determine the points (or triangle vertices) where the isosurfaces along the cube edges intersect. The last step of the method can provide a unit normal for calculating each triangle vertex. The rendering algorithm can then use the unit normal to produce smooth shading.

[0059] As an alternative method to generate a 3D guide frame, and now refer to Figure 4and Figure 5 Both, two three-dimensional projections of the two two-dimensional guide structures can be calculated. The three-dimensional projection 401 of the sagittal two-dimensional guide structure 402 consists of points inside the computed tomography volume 403, which are located inside the projection cone given by projecting the sagittal two-dimensional guide structure 402 (with the sagittal X-ray image source 404 as the center of the projection). Similarly, the three-dimensional projection 501 of the frontal two-dimensional guide structure 502 consists of voxels inside the computed tomography volume 403, which are located inside the projection cone given by projecting the frontal two-dimensional guide structure 502 (with the frontal X-ray image source 503 as the center of the projection).

[0060] Reference now Figure 6 , the corresponding 3D guide frame 601 can then be calculated by performing an intersection of the two 3D projections of the two 2D guide structures. If a point inside the computed tomography volume 403 is in both the sagittal 3D projection and the frontal 3D projection, the point is classified as part of the 3D guide frame.

[0061] After the target is appropriately segmented, information about the segmented target can then be used in a common process to optimize a radiation-based treatment plan, which can then be used to administer therapeutic radiation to a patient using the optimized radiation-based treatment plan and, for example, the radiation treatment platform 114 described above.

[0062] Thus, by one approach, these teachings can successfully utilize one volumetric computed tomography image and two pairs of x-ray images (i.e., four x-ray images total). Each digital subtraction angiography image can be generated from two x-ray images that were taken from the same location at different points in time. One of the two x-ray images can also be used to achieve image fusion with the volumetric computed tomography image. This cannot be done with the digital subtraction angiography image, but the resulting registration can also be applied to the digital subtraction angiography image because it has the same orientation in space as the pair of x-ray images below it. By one approach, the entire process can use two independent image fusions with the volumetric computed tomography image, where the two digital subtraction angiography images (i.e., the underlying related x-ray image pair) are more or less orthogonal to each other.

[0063] Those skilled in the art will appreciate that various modifications, changes and combinations may be made to the above-described embodiments without departing from the scope of the present invention, and such modifications, changes and combinations should be considered to be within the scope of the inventive concept.

Claims

1. A method of facilitating segmentation of a patient target volume to support radiation treatment planning, the method comprising: Through the control circuit: access to patient-specific planning computed tomography image information; accessing two-dimensional digital subtraction angiography image information for the specific patient; The planning computed tomography image information is fused with the two-dimensional digital subtraction angiography image information to provide fused image information of the target volume.

2. The method of claim 1, wherein the patient target volume comprises, at least in part: Arteriovenous malformation.

3. The method of claim 1 , wherein the planning computed tomography image information comprises at least in part: Segmented three-dimensional contours from corresponding computed tomography image information, and wherein fusing the planning computed tomography image information with the two-dimensional digital subtraction angiography image information comprises at least in part: projecting the segmented three-dimensional contours into two-dimensional contours on the two-dimensional digital subtraction angiography image information.

4. The method according to claim 1, further comprising: The two-dimensional digital subtraction angiography image information is generated based on at least two X-ray images.

5. The method of claim 4, wherein the at least two X-ray images comprise: Two images that are at least substantially orthogonal to each other.

6. The method according to claim 1, wherein the two-dimensional digital subtraction angiography image information for the specific patient comprises: At least one closed two-dimensional contour surrounding an image of the patient target volume on each of the at least two two-dimensional digital subtraction angiography images.

7. The method of claim 1 , wherein fusing the planning computed tomography image information with the two-dimensional digital subtraction angiography image information comprises at least in part: For each image pair of an X-ray image and a planning computed tomography image, a registration is performed between the X-ray image and the planning computed tomography image.

8. The method according to claim 1, further comprising: Simultaneously present on the interactive user display: at least two digital subtraction angiography images, each of the at least two digital subtraction angiography images comprising: a pre-delineated two-dimensional guide structure corresponding to the patient target volume, and at least one pipeline projection; At least three three-dimensional planning computed tomography images.

9. The method of claim 8, wherein the at least three three-dimensional planning computed tomography images comprise: Axial, sagittal, and coronal images.

10. The method of claim 8, wherein the at least three three-dimensional planning computed tomography images each comprise: A three-dimensional guide frame is reconstructed based on two-dimensional guide contours from at least two of the digital subtraction angiography images.

11. An apparatus for facilitating segmentation of a patient target volume to support radiation treatment planning, the apparatus comprising: The control circuit is configured as follows: access to patient-specific planning computed tomography image information; accessing two-dimensional digital subtraction angiography image information for the specific patient; The planning computed tomography image information is fused with the two-dimensional digital subtraction angiography image information to provide fused image information of the patient target volume.

12. The apparatus of claim 11, wherein the patient target volume at least partially comprises: Arteriovenous malformation.

13. The apparatus of claim 11, wherein the planning computed tomography image information comprises at least in part: segmented three-dimensional contours from corresponding computed tomography image information, and wherein the control circuit is configured to fuse the planning computed tomography image information with the two-dimensional digital subtraction angiography image information at least in part by projecting the segmented three-dimensional contours as two-dimensional contours onto the two-dimensional digital subtraction angiography image information.

14. The apparatus according to claim 11, wherein the control circuit is further configured to: The two-dimensional digital subtraction angiography image information is generated based on at least two X-ray images.

15. The apparatus of claim 14, wherein the at least two X-ray images comprise: Two images that are at least substantially orthogonal to each other.

16. The apparatus according to claim 11, wherein the two-dimensional digital subtraction angiography image information for the specific patient comprises: At least one closed two-dimensional contour surrounding an image of the patient target volume on each of the at least two two-dimensional digital subtraction angiography images.

17. The apparatus of claim 11, wherein the control circuit is configured to fuse the planning computed tomography image information with the two-dimensional digital subtraction angiography image information at least in part by achieving registration between the x-ray image and the planning computed tomography image for each image pair of the x-ray image and the planning computed tomography image.

18. The apparatus of claim 11, wherein the control circuit is further configured to: Simultaneously present on the interactive user display: At least two digital subtraction angiography images, each of the at least two digital subtraction angiography images comprising: a pre-rendered two-dimensional guide structure corresponding to the patient target volume, and at least one pipeline projection; At least three three-dimensional planning computed tomography images.

19. The apparatus of claim 18, wherein the at least three three-dimensional planning computed tomography images comprise: Axial, sagittal, and coronal images.

20. The apparatus of claim 18, wherein the at least three three-dimensional planning computed tomography images each comprise: A three-dimensional guide frame is reconstructed based on two-dimensional guide contours from at least two of the digital subtraction angiography images.

Images