WO2010001327A1

WO2010001327A1 - Processing anatomy and associated quantitative analysis data of tissue

Info

Publication number: WO2010001327A1
Application number: PCT/IB2009/052805
Authority: WO
Inventors: Marcel Breeuwer
Original assignee: Koninklijke Philips Electronics N.V.
Priority date: 2008-07-04
Filing date: 2009-06-29
Publication date: 2010-01-07

Abstract

The invention relates to a method of processing anatomy data and associated quantitative analysis data of tissue. The method comprises the step of identifying a coronary arterystructure being closest to a selected tissue area. In a preferred embodiment, the selected tissue area is on an outer surface of a whole-heart surface.

Description

Processing anatomy and associated quantitative analysis data of tissue

FIELD OF THE INVENTION

The invention relates to a method of processing anatomy and associated quantitative analysis data of tissue.

BACKGROUND TO THE INVENTION

Coronary arteries around the heart can be imaged using X-ray angiography, thus providing 2-dimensional (2D) projection images wherein other anatomical structures such as the myocardium are hardly visible. Further, 3-dimensional (3D) imaging techniques for imaging the heart and the coronary arteries are available, e.g. 3D magnetic resonance imaging (MRI) and 3D computed tomography angiography (CTA).

In order to visualize various heart components, such as atria, ventricles, coronary arteries and large vessels, 3D volume rendering based on 3D MRI and/or CTA data can be used.

Recently, automatic segmentation of complete heart image data, including the coronary arteries has been extensively investigated. Consequently, whole-heart segmentation algorithms and algorithms for tracking centerlines of the coronary arteries are available. Based on automatic segmentation techniques, surface renderings of the heart and surrounding vessels can be made, see e.g. the article 'CoViCAD: Comprehensive Visualization of Coronary Artery Disease' by Maurice Termeer e.a. in IEEE Transactions on visualization and computer graphics, Vol. 13, No. 6 November/December 2007 and the patent publication US 2005/0272992.

Further, algorithms for the quantification of myocardial function, perfusion and viability have been developed during the last decades. Myocardial function can be quantified from MRI as well as from CTA images. Perfusion and viability can still only be quantified with MRI. The quantitative analysis results are usually represented in 2D, using so-called Bulls-Eye plots. As such, 2D Bulls-Eye plots are currently most frequently used for the visualization of quantitative functional, perfusion and viability data, whereas coronary arteries, atria and ventricles are usually visualized with volume rendering techniques. A frequently occurring heart disease is coronary artery stenosis, occlusion, which usually results in myocardial ischemia and may result in myocardial infarction. Myocardial ischemia is a reduced contraction due to insufficient oxygen supply, while myocardial infarction is starvation of myocardial tissue due to lack of oxygen. Although reduced myocardial function, insufficient myocardial perfusion and the presence of dead myocardial tissue can arise as a result of one or more occlusions in the coronary arteries, these coronary arteries are not represented in the Bulls-Eye plots. On the other hand, in the volume renderings that do show the coronary arteries, no quantitative data is shown. As a result, the clinician cannot easily relate the position of a diseased myocardial area to the occlusion in the coronary artery that causes the disease. Severe stenosis may be visible in the 3D whole-heart CTA and/or MRI image data, but moderate-to-severe stenosis can easily be missed.

SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a method of processing anatomy data wherein support for a diagnosis of an artery disease is improved.

According to a first aspect of the invention, a method of processing anatomy data is provided, the method comprising identifying a blood vessel structure of a blood vessel system, which blood vessel structure is closest to a selected tissue area. By identifying a blood vessel structure that is closest to a selected tissue area, the selected tissue area, such as a diseased myocardial tissue area, can be associated with a blood vessel structure, such as a coronary artery structure, of a blood vessel system, such as coronary arteries. The coronary artery structure identified on the basis of a selected diseased myocardial tissue area may suffer from arterial stenosis and thus may be the reason for the disease of the myocardial tissue. As a result, a significant improvement is obtained in supporting clinicians deciding which coronary arteries cause the disease and should be treated.

In an implementation, the identifying step comprises determining a distance between the selected tissue area and each location of a plurality of locations defined based on the blood vessel system. The plurality of locations may comprise locations on a centerline of the blood vessel system. A segment of the blood vessel system such that the centerline of this segment comprises a location of the plurality of locations which has the smallest distance value to the selected tissue area may be identified in the identifying step of the method. In an implementation, the method is applied to coronary arteries surrounding a heart muscle. The tissue comprises myocardial tissue and the identified blood vessel structure of a blood vessel system is a coronary artery structure of coronary arteries. The method is very useful for identifying diseased coronary arteries. In an implementation, each location of the plurality of locations is defined by a mapping of a location on a centerline of the coronary arteries onto an outer surface of the myocardial tissue. Typically, coronary arteries are close to the outer surface of the myocardial tissue. The mapping may be a projection of the centerline onto the outer surface of the myocardial tissue. In an implementation, the distance between the selected area of the myocardial tissue and each location of the plurality of locations is defined as the length of the shortest curve on the surface of the myocardial tissue connecting a location in the selected area of the myocardial tissue to the location of the plurality of locations. Using the distance measured along the surface is more appropriate than using the standard 3D Euclidean distance, for example.

In an embodiment, the tissue area is selected by a user using a user interface. The method is arranged to visualize a 3D visualization plot of the tissue computed from the anatomy data, e.g. a 3D whole-heart surface rendering. Using a mouse-controlled cursor, for example, the user may indicate an area of the myocardial tissue to be selected on the 3D visualization plot, such as a 3D whole-heart surface rendering. The indicated tissue area may comprise a suspicious scar tissue, for example.

Alternatively or additionally, the tissue area can be selected on a 2D visualization plot, such as a 2D Bulls-Eye plot. The 2D Bulls-Eye plot may be arranged for displaying quantitative analysis data, e.g. myocardial perfusion data showing blood supply to the myocardial tissue. The method further comprises the step of associating corresponding areas in the 3D visualization plot and the 2D visualization plot. As a consequence, by indicating an area in the 2D visualization plot, an associated area of the tissue is selected. Optionally, the selected area may be displayed in the 3D visualization plot. Based on the selected area of the tissue, a coronary artery structure is identified. According to a second aspect of the present invention, a computer system for processing anatomy data is provided, the system comprising a processor (12) that is arranged to identify a blood vessel structure of a blood vessel system, being closest to a selected tissue area. According to a third aspect of the present invention, a computer program product for processing anatomy data of tissue is provided, which computer program product comprises instructions for causing a processor to perform the step of identifying a blood vessel structure of a blood vessel system, being closest to a selected tissue area. It will be appreciated by those skilled in the art that two or more of the above- mentioned embodiments, implementations, and/or aspects of the invention may be combined in any way deemed useful.

Modifications and variations of the computer system and/or of the computer program product, which correspond to the described modifications and variations of the method, can be carried out by a person skilled in the art on the basis of the present description.

A person skilled in the art will appreciate that the method may be applied to multidimensional image data, e.g., to 3-dimensional (3D) or 4-dimensional (4D) images, acquired by various acquisition modalities such as, but not limited to, standard X-ray Imaging, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound (US), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), and Nuclear Medicine (NM).

BRIEF DESCRIPTION OF THE DRAWINGS In order that the invention may be more fully understood, embodiments thereof will now be described by way of example only, with reference to the Figures, in which:

Fig. 1 shows a whole-heart 3D volume rendering;

Fig. 2 shows a 2D Bulls-Eye plot; Fig. 3a shows a first whole-heart 3D surface rendering;

Fig. 3b shows a second whole-heart 3D surface rendering;

Fig. 3 c shows a third whole-heart 3D surface rendering;

Fig. 3d shows a fourth whole-heart 3D surface rendering;

Fig. 4 shows a combined 3D and 2D plot; Fig. 5 schematically shows an implementation of the method; and

Fig. 6 schematically shows an embodiment of the computer system. The Figures are merely for illustrating implementations and embodiments of the invention. In the Figures, the same reference numbers refer to equal or corresponding parts.

DETAILED DESCRIPTION OF EMBODIMENTS

Figure 1 shows a whole-heart 3D volume rendering 1 of a human heart. The volume rendering 1 is based on CTA and/or MRI data. However, in principle, also other data may serve as a basis for generating the volume rendering, e.g. cine, perfusion and viability CMR. In the volume rendering 1, the shape and size of ventricles, atria, myocardium valves and coronary arteries can be depicted, thus providing a perspective 3D view of the heart anatomy.

Figure 2 shows a 2D Bulls-Eye plot 2 representing quantitative analysis results of e.g. myocardial function, perfusion or viability of the heart. The Bulls-Eye plot 2 comprises a set of concentric circles which are each divided into a number of segments. Inner circles represent a region near the apex, the bottom of the left ventricle, while outer circles represent the area near the top of the left ventricle. The plot 2 is popular in medical practice as it is intuitive and gives a comparable global overview of a property being measured. Similar representations could be generated for other heart components such as the right ventricle and atria. Figures 3a-d show, respectively, a first, second, third and fourth whole-heart

3D surface rendering 3based on CTA and/or MRI data. Here, various components of the heart, such as the myocardium of the atria and ventricles and the surrounding coronary arteries have been segmented using available segmentation techniques. The coronary arteries can e.g. be shown as segmented lumen surfaces, especially if the scanning resolution allows segmentation of the lumen, or schematically by their centerlines. As is the case with 3D volume rendering, a whole-heart 3D surface rendering can be based on CTA, MRI and/or other heart data.

On the outer surface 4 of the whole-heart surface rendering 3, a myocardium tissue area is selected by a cursor 5 controlled e.g. by a mouse, which cursor can be moved by a clinician consulting the 3D surface rendering 3. Alternatively, also another user interface interactively associated with the 3D visualization plot can be used for selecting a tissue area, e.g. a digital pen to be pressed against the screen depicting the surface rendering 3. In an embodiment, the myocardium tissue area can also be selected by a user-controlled cursor in a 2D plot, such as a 2D Bulls-Eye plot. As the cursor 5 is positioned on the whole-heart surface 4, the position of cursor 5 is represented by 3D coordinates. Further, the segmented arteries are modeled as curved lines in a 3D space using segmentation techniques, see e.g. the article 'Automatic whole heart segmentation in CT images: method and validation' by O. Ecabert et al. in PROC of SPIE, VoI 6512, pages 65120G-1 - 65120G-12. Then, a distance between the selected myocardium tissue area and a plurality of locations defined by an artery centerline 6a is determined. The computed values of the distance between the selected myocardium tissue area and the plurality of locations defined based on the coronary arteries are compared with each other so that an artery structure closest to the selected myocardium area can be identified.

The selected myocardium tissue area represents a myocardium volume, which is of interest to a clinician, surrounding a location which is typically indicated by a user on the outer surface of the myocardial tissue of a 3D rendering of the heart. Alternatively, the area may be selected by the user by indicating boundaries of a region of interest. It is noted that arteries having a relatively large cross section are situated mainly on or near to the outer surface 4 of the whole-heart 3. If a specific artery is located off said outer surface 4, as a first step in the distance determining step, locations on the artery or on its centerline are projected onto said outer surface 4. In this way, the distance between the selected area and a location on the artery centerline may be determined along the whole-heart outer surface 4. Preferably, the distance is determined by the shortest path, also called a geodetic path, between a location on the outer surface of the myocardium defined by the selected tissue area, e.g. the user-indicated location or the centre of an area on the outer surface defined by the user- indicated boundaries of a region of interest, and each of the plurality of locations defining the position of the coronary arteries. However, in principle, also other distances could be used for identifying a structure of the coronary arteries closest to the selected area of the myocardial tissue, e.g. the Euclidean distance defined by the length of the interval connecting two 3D positions corresponding to the selected area and a location on the coronary arteries.

The identified artery structure may comprise a single artery or multiple arteries, or segments thereof, as will be explained below in more detail. Further, the identified artery structure can be visualized in a 3D visualization plot, e.g. the surface rendering 3 as shown in Figures 3a-d. Alternatively or additionally, the identified artery structure can be communicated to the clinician in another way, e.g. by describing or naming the identified artery structure in an audio message transmitted by a system implementing the method of the invention.

The identified artery structure in Figure 3a comprises a whole single coronary artery 6b. The whole artery is thus highlighted. Figure 3b shows an identified artery structure wherein only a segment 7 of an artery, extending upstream to a first bifurcation 8, is identified. Further, Figure 3 c shows a selected artery structure comprising an artery segment 9 comprising locations for which the distance to the selected myocardial tissue area is in a predetermined distance range. As an example, the system of the invention may be arranged for identifying and visualizing an artery segment comprising locations connected by one segment of the centerline, for which the distance to the selected myocardial tissue area 5 falls within 10% of the distance from the closest location on the coronary artery to said tissue area 5. In Figure 3d, the identified artery structure comprises two separate artery segments 9, 10 comprising all locations for which the distance to the selected myocardial tissue area 5 falls within 10% of the distance from the closest location on the coronary artery to said tissue area 5. As the selected myocardial tissue area 5 is substantially in the middle between the artery segments 9, 10, the plot shown in Figure 3d depicts a possible most realistic situation wherein both blood vessel segments 9, 10 supply blood to the selected myocardial tissue area 5.

Figure 4 shows combined 3D and 2D plots, wherein the 3D plot is a whole- heart surface rendering 3 and wherein the 2D plot is a Bulls-Eye plot 2. Here, the tissue area in the surface rendering 3 selected by the cursor 5 is associated with a corresponding area 11 in the 2D Bulls-Eye plot 2. As a result, a clinician consulting the combined plot may directly correlate a selected diseased myocardial area with the position of coronary arteries that are supposed to supply blood to the selected area. This further improves the support for diagnosing coronary artery disease. Consequently, function, perfusion and viability image analysis data are linked to the anatomy whole-heart and coronary image data. The association between the cursor 5 in the surface rendering 3 and cursor 11 in the Bulls-Eye plot 2 can be performed using available image registration techniques, e.g. by aligning the slices of the functional, perfusion and/or viability image data with the 3D whole-heart image data. Preferably, the association of the two pointers is performed as an update step after each change of the selected myocardial area, so that a dynamic positional linking between the cursors 5, 11 and hence of the various heart data is obtained. For example, the clinician may watch and change the position of the cursor 5 in the surface rendering 3, thereby also moving the cursor 11 in the Bulls-Eye plot 2. However, the other way around is also possible, i.e. watching and changing the position of the Bulls-Eye plot cursor 11, thereby also moving the surface rendering cursor 5.

Optionally, the cursor 11 can also be shown in original image data from which the quantitative data originates. Figure 5 schematically shows an implementation of the method. The method comprises a step 101 of identifying a blood vessel structure of a blood vessel system, as can be seen in the flow chart in Figure 5. The identifying step 101 may comprise a step 102 of determining a distance between the selected tissue area and each location of a plurality of locations defined based on the blood vessel system. Further, in order to perform the determining step 102, the identifying step 101 may comprise a step 103 of mapping a location on a centerline of the coronary arteries onto an outer surface of the myocardial tissue. The distance determining step 102 may comprise a step 104 of defining the distance between the selected area of the myocardial tissue and the each location of the plurality of locations as the length of the shortest curve on the surface of the myocardial tissue connecting a location in the selected area of the myocardial tissue to the each location of the plurality of locations. Optionally, the method may comprise the step 105 of visualizing a 3D visualization plot for displaying an image of the tissue computed from the anatomy data, wherein the tissue area is selectable by means of a user interface associated with the visualized 3D visualization plot. In addition, the method may comprise the step 106 of visualizing the identified blood vessel structure in the 3D visualization plot. Further, the method may comprise the step 107 of visualizing quantitative analysis data associated with the anatomy data, in a 2D visualization plot, and associating the selected tissue area with a corresponding area in the 2D visualization plot.

Further, Figure 6 schematically shows a computer system 13 for processing anatomy and associated quantitative analysis data of tissue. The system 13 comprises a processor 12 that is arranged to identify an artery structure being closest to a selected tissue area. It is noted that the method for processing anatomy and associated quantitative analysis data of tissue can be performed using dedicated hardware structures, such as FPGA and/or ASIC components. Otherwise, the method can also at least partially be performed using a computer program product comprising instructions for causing the processor 12 to perform the above described steps of the method according to the invention.

The invention is not restricted to the embodiments described herein. It will be understood that many variants are possible. The method may additionally or alternatively include visualizing the quantitative analysis data in the 3D visualization plot, e.g. the surface rendering 3. As an example, quantitative analysis data such as perfusion data might be represented in color on the outer surface 4 of the whole-heart rendering 3, thus allowing a direct identification of diseased areas and the identified coronary structure that is closest to these areas on the whole- heart surface representation 3. Instead of using color data, also other visualization techniques can be applied, e.g. using gray values and/or flashing images.

Further, visualization plots can be shown from a fixed virtual point of view or from a variable point of view. In the latter case, a heart model can e.g. be shown from a virtual circumventing point of view, such that the heart model rotates in the visualization plot.

Instead of using the method for processing heart anatomy data, the method could in principle also be applied to other tissue data, such as lung muscle tissue.

Whilst specific embodiments of the invention have been described above, it will be appreciated that the invention may be practiced otherwise than as described. The description is not intended to limit the invention. Any reference signs in the claims shall not be construed as limiting the scope.

Claims

CLAIMS:

1. A method of processing anatomy data comprising identifying (101) a blood vessel structure of a blood vessel system, which blood vessel structure is closest to a selected tissue area.

2. A method according to claim 1, wherein the identifying step comprises determining (102) a distance between the selected tissue area and each location of a plurality of locations defined based on the blood vessel system (6a).

3. A method according to claim 2, wherein the tissue comprises myocardial tissue and wherein the identified blood vessel structure of a blood vessel system is a coronary artery structure of coronary arteries.

4. A method according to claim 3, wherein the each location of the plurality of locations is defined by a mapping (103) of a location on a centerline of the coronary arteries onto an outer surface of the myocardial tissue.

5. A method according to claim 4, wherein the distance between the selected area of the myocardial tissue and the each location of the plurality of locations is defined (104) as the length of the shortest curve on the surface of the myocardial tissue connecting a location in the selected area of the myocardial tissue to the each location of the plurality of locations.

6. A method according to claim 4 or 5, wherein the identified coronary artery structure comprises an artery segment (9, 10) defined by locations of the plurality of locations having distances to the selected tissue area in a predetermined distance range.

7. A method according to any of the previous claims, wherein the identified blood vessel structure comprises a single blood vessel segment (6b,7) or multiple blood vessel segments (9; 10).

8. A method according to any of the previous claims, wherein the identified blood vessel structure comprises a blood vessel segment (7) extending upstream to a first bifurcation (8).

9. A method according to any of the previous claims, further comprising visualizing (105) a 3D visualization plot (3) for displaying an image of the tissue computed from the anatomy data, wherein the tissue area is selectable by means of a user interface (5) associated with the visualized 3D visualization plot (3).

10. A method according to claim 9, further comprising visualizing 106 the identified blood vessel structure in the 3D visualization plot (3).

11. A method according to any of the previous claims, further comprising visualizing (107) quantitative analysis data associated with the anatomy data, in a 2D visualization plot (2), and associating the selected tissue area with a corresponding area in the 2D visualization plot (2).

12. A method according to claim 11, wherein the 2D visualization plot is a Bulls- Eye plot.

13. A method according to claim 11 or 12, wherein the tissue area is selectable by means of the user interface (5) associated with the visualized 2D visualization plot (2).

14. A computer system (13) for processing anatomy data, comprising a processor (12) that is arranged to identify a blood vessel structure of a blood vessel system, being closest to a selected tissue area.

15. A computer program product for processing anatomy data of tissue, which computer program product comprises instructions for causing a processor to perform the step of identifying a blood vessel structure of a blood vessel system, being closest to a selected tissue area.