Apparatus for determining a functional index for stenosis assessment

Abstract

An apparatus for determining a functional index for stenosis assessment of a vessel is provided. The apparatus comprises an input interface (40) and a processing unit (50). The input interface is configured to obtain image data (30) representing a two-dimensional representation of a vessel (6). The processing unit (50) is configured to determine a course of the vessel (6) and a width (w1, w2) of the vessel along its course in the image data and is further configured to determine the functional index for stenosis assessment of the vessel based on the width of the vessel in the image data.

Claims

1. An apparatus, comprising: an input interface; and a processing unit, wherein the input interface is configured to obtain image data of at least a section of a vessel, wherein the image data comprises a single two-dimensional (2D) representation of at least the section of the vessel, and wherein the processing unit is configured to generate, based on the single 2D representation, a functional index for stenosis assessment corresponding to a fluid flow through at least the section of the vessel, wherein, to generate the functional index for stenosis assessment, the processing unit is configured to: determine a geometric model of at least the section of the vessel based on the image data, wherein the geometric model comprises an inner diameter and a change of the inner diameter along a course of at least the section of the vessel, wherein the functional index for stenosis assessment is distinct from the inner diameter and the change of the inner diameter; determine a resistance value of at least the section of the vessel based on the geometric model; and determine the functional index for stenosis assessment based on: the resistance value; and a boundary condition comprising at least one of: a volumetric flow rate associated with an inlet of at least the section of the vessel; the volumetric flow rate associated with an outlet of at least the section of the vessel; a pressure associated with the inlet; or the pressure associated with the outlet.

2. The apparatus of claim 1, wherein the processing unit is configured to: apply a densitometry method to the image data to compensate for foreshortening effects in the image data when determining a width of the vessel.

3. The apparatus of claim 1, wherein the processing unit is configured to: apply a scaling factor to a width of the vessel in the image data; and determine the functional index for stenosis assessment based on the width multiplied by the scaling factor.

4. The apparatus of claim 3, wherein the processing unit is configured to: receive a distance of the vessel from an image plane of the image data; and determine the scaling factor based on the distance.

5. The apparatus of claim 3, wherein the processing unit is configured to: segment the vessel along a course of the vessel such that there are multiple vessel segments; and apply a specific scaling factor to the width of each one of the multiple vessel segments.

6. The apparatus of claim 5, wherein the processing unit is configured to segment the vessel based on a distance between a vessel segment and a projection surface.

7. The apparatus of claim 3, wherein the processing unit is configured to: detect a reference element within the image data; and determine the scaling factor based on a known size of the reference element and the size of the reference element in the image data.

8. The apparatus of claim 1, wherein the processing unit is configured to: independently derive a respective functional index for stenosis assessment from a corresponding one of a plurality of 2D representations.

9. The apparatus of claim 8, wherein the processing unit is configured to: determine a variation between the respective functional indices for stenosis assessment from different ones of the plurality of 2D representations; compare the variation to a predetermined maximal variation; and generate an acceptance criterion based on the comparison.

10. The apparatus of claim 1, wherein the processing unit is configured to calculate a quality score for the single 2D representation.

11. The apparatus of claim 1, wherein the processing unit is configured to determine the functional index for stenosis assessment using a lumped element fluid dynamics model including the resistance value and the boundary condition.

12. The apparatus of claim 1, wherein the single 2D representation comprises a projection image.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) Exemplary embodiments of the invention will be described in the following with reference to the following drawings:

(2) FIG. 1 schematically illustrates an imaging system.

(3) FIG. 2 schematically illustrates two-dimensional image data for being used by an apparatus according to an exemplary embodiment.

(4) FIG. 3 schematically illustrates an apparatus according to an exemplary embodiment.

(5) FIG. 4 schematically illustrates a flow chart of a method according to an exemplary embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

(6) In the following, the invention is exemplarily described as being used in the context of the apparatus for determining a functional index for stenosis assessment. However, the invention can also be used in the context of the method for determining a functional index for stenosis assessment. Thus, all the following examples and/or explanations may also be intended as being implemented by the method of the invention. Features relating to the apparatus are to be understood as to similarly apply to the method, as well, and vice versa.

(7) FIG. 1 schematically illustrates an imaging system 10, for example an X-ray system, for generating image data of a region of interest of an object 5, for example of a part of the human body. The imaging system 10 may emit X-ray radiation towards and through the object such that the composition of the object is projected onto the projection surface 20. Thus, a two-dimensional image is generated which can be used as input data for the apparatus described herein.

(8) However, it should be noted that image data generated by other means or by other processes may be used as input data for the apparatus as long as the image data are a two-dimensional representation of a spatial object like the human body.

(9) FIG. 2 schematically shows an image 30 containing a projection of a section of a vessel 6 in a two-dimensional projection. In this two-dimensional image, the section of the vessel 6 does not have a constant diameter but the diameter changes. In particular, the diameter W1 at the left side is greater than the diameter W2 at the right side of the image 30.

(10) The functional index for stenosis assessment for the shown section of vessel 6 is determined as follows: determining a geometric model of at least a section of a vessel, the model including an inner diameter of a vessel or a section of the vessel and the change of the diameter along the course of the vessel. This may be done, for example, by partitioning the section of vessel 6 as to have multiple partitions and determining a diameter or mean diameter for each partition; the higher the numbers of partitions, the more exact may be the functional index for stenosis assessment; determine at least one resistance value of at least the section of the vessel based on the geometric model. With reference to FIG. 2, a simulated fluid flowing from the left to the right would experience an increasing fluid dynamic resistance if W2 is smaller than W1, for example due to a stenosis. In particular, the vessel or vessel segment may be approximated by at least one linear or non-linear resistor, preferably a series of such resistors. determine a pressure drop of a fluid which flows through said vessel or section of the vessel based on the at least one resistance value. For example, the pressure drop may be determined using a lumped element fluid dynamics model, including the determined resistance value or values and certain boundary conditions. For example, assumptions may be made regarding the (volumetric) flow rate and/or pressure at the inlet and/or outlet of the vessel or vessel section, which assumptions are then used as boundary conditions in the lumped elements model. Alternatively, physical measurement values, such as an aortic pressure measurement, may be used as boundary conditions.

(11) The determined pressure drop, for example over a stenosis in a coronary vessel segment, is an equivalent of the functional index for stenosis assessment.

(12) FIG. 3 shows an apparatus for determining a functional index for stenosis assessment. The apparatus comprises an interface 40 for receiving image data representing a two-dimensional image, a processing unit 50, and an output unit 60. Even though the output unit 60 is shown in FIG. 3, this is not a necessarily required component of the apparatus. The processing unit may determine the functional index for stenosis assessment and may store this value in a memory unit or storage unit such that an external output unit may access said memory unit or storage unit to read out the functional index for stenosis assessment.

(13) The interface 40 is configured for receiving image data 30. The image data may be provided as pictures or projections of body regions or as digital data transmitted to the interface 40 via a suitable data transmission protocol either via a data transmission network or by accessing kind of memory unit which stores the image data.

(14) The output unit may be a device for optically indicating the functional index for stenosis assessment. For example, the output unit may be a monitor or any other kind of display.

(15) According to an aspect of the invention, the input interface is configured to obtain image data representing a two-dimensional representation of a vessel and the processing unit is configured to determine a course of the vessel and a width of the vessel along its course in the image data and is further configured to determine the functional index for stenosis assessment of the vessel based on the width of the vessel in the image data.

(16) The input interface may receive image data in any format. The input interface is adapted to receive two-dimensional image data, in particular. Especially, only a single two-dimensional representation (a projection, for example) of a vessel is used for determining the functional index for stenosis assessment, for example a fractional flow reserve.

(17) According to an embodiment, the two-dimensional image data of the vessel represents a two-dimensional image of a blood vessel of a human.

(18) According to an embodiment, the two-dimensional image is a projection of the vessel.

(19) According to an embodiment, the width of the vessel corresponds to a diameter of the vessel in an image plane or projection plane.

(20) As an effect, coronary lesion hemodynamic significance may be estimated based on fractional flow reserve, for example.

(21) According to an embodiment, the processing unit is configured to apply a densitometry method to the image data as to compensate for foreshortening effects in the image data when determining the width of the vessel.

(22) Densitometry is used for quantitative measurement of optical density. By means of the densitometry method, it may be determined if the distance of the vessel from the image plane or projection plane varies along the course of the vessel and this may be additionally considered when determining the width of the vessel. This may be done as to not adulterate the determined width value of the vessel as a result of the varying distance from the image plane or projection plane. In other words, the measured width may be corrected based on the results of the densitometry method.

(23) The densitometry may be used to compensate for foreshortening in the projection/two-dimensional image and the width may be determined based on both the diameter in the projection and the result of the densitometry measurement by accumulating the results of these approaches.

(24) According to an embodiment, the processing unit is configured to apply a scaling factor to the width of the vessel in the image and to determine the functional index for stenosis assessment based on the width multiplied by the scaling factor.

(25) Thus, a non-magnified size of the vessel may be determined and the functional index for stenosis assessment is determined based on this corrected vessel diameter.

(26) According to an embodiment, the processing unit is configured to receive the distance of the projected vessel from a projection plane of the projected image data and to determine the scaling factor based on said distance.

(27) The magnification of the vessel width in the image or projection is dependent on the distance of the vessel from the image or projection surface, respectively. This distance may be considered when determining the scaling factor to get a more accurate result.

(28) According to an embodiment, the processing unit is configured to segment the vessel along its course such that there are multiple vessel segments or partitions and to apply a specific scaling factor to the width of each one of the multiple vessel segments or partitions.

(29) As a projection of the vessel or a two-dimensional image of the vessel are used, the width along the course of the vessel in the projection or image may not be true to scale. Therefore, it may be necessary to apply different scaling factors to the width of the segments of the vessel in order to determine the non-magnified width.

(30) According to an embodiment, the processing unit is configured to segment the vessel such that one segment of the vessel has substantially the same distance from the projection surface.

(31) Thus, there is an appropriate segmentation such that there is almost the same magnification of the diameter within one segment and it may be ensured that the scaling factor is applicable to the entire segment without artificially adding distortion or bias to the width of the vessel.

(32) The segmentation may be done such that the distance of the vessel within one segment is within a corridor of a predetermined width around the medium distance of the segment, for example within 5% or 10% around the medium distance.

(33) According to an embodiment, the processing unit is configured to detect a reference element within the image data and to determine the scaling factor based on a known size of the reference element and the size of the reference element in the image data.

(34) Thus, the scaling factor of the vessel may be determined based on the known dimensions of the reference element in a more accurate manner.

(35) According to an embodiment, the processing unit is configured to determine a functional index for stenosis assessment based on the width of the vessel in the image data, wherein the functional index is one of: a pressure drop along a centreline of the vessel, a virtual fractional flow reserve, a curve of the pressure drop as a function of the blood flow through the vessel, a fluid-dynamic resistance value, a blood velocity profile, a blood velocity distribution.

(36) In general, any parameter or any functional index that can be derived from hemodynamic parameters (e.g. coronary flow reserve, CFR, instant flow reserve, iFR) may be used individually or in combination with any one or multiple of the abovementioned indicators.

(37) According to an embodiment, the vessel is an artery of a human body.

(38) FIG. 4 schematically illustrates a flow chart 100 of a method for determining a functional index for stenosis assessment. The method comprises the following steps:

(39) In a first step 110, also referred to as step a), image data corresponding to two-dimensional image data of a vessel are obtained.

(40) In a second step 120, also referred to as step b), a course of the vessel and a width of the vessel along its course in the image data is determined.

(41) In a third step 130, also referred to as step c), a functional index for stenosis assessment of the vessel is determined based on the width of the vessel in the image data. It is understood that, without repeating here all the explanations, examples, features and/or advantages provided with reference to the apparatus for determining a functional index for stenosis assessment, the method of the invention is intended to be configured to carry out the method steps 110 to 130 for which the apparatus is configured to. Thus, all the above examples, explanations, features and/or advantages, although provided previously with reference to the apparatus for determining a functional index for stenosis assessment, are also intended to apply in a similar manner to the method and to, in particular for the following exemplary embodiments of the method.

(42) According to an exemplary embodiment of the method, the step of obtaining image data comprises obtaining a projection of the vessel, wherein the width of the vessel is determined based on the projection.

(43) According to an exemplary embodiment, the method further comprises the steps of: determining a length of the vessel in the image; determining a scaling factor based on a densitometry approach; applying the scaling factor to the determined width of the vessel.

(44) According to a further example of the present invention, a computer program element is provided, which, when being executed by a processing unit is adapted to carry out the method described above.

(45) According to further example of the present invention, a computer readable medium having stored thereon a program element is provided, which, when being executed by a processing unit is adapted to carry out the method described above.

(46) In other words, the approach described above relating to the apparatus and method for determining a functional index for stenosis assessment may be summed up as follows and it is proposed here to approximate this by one or more of the following:

(47) Apply 2D QCA methods to obtain a 2D segmentation and a vessel centerline of the culprit vessel segments. In order to estimate the non-magnified size of the vessel diameter and length, the scaling factor due to magnification can be estimated from either of the known system geometry and an estimate of the position of the heart inside the X-ray system, the known size of the catheter at the ostium of the contrary artery tree, or a phantom/reference element placed on the chest wall of the patient.

(48) Thus, a geometric model including a centerline and the local vessel radius r.sub.i for each centerline point are determined. This may include branching points.

(49) The geometric model further includes cross-sectional areas that are estimated for one or more of the centerline points. For example, such estimate is made for each centerline point. In a first approximation, this is A.sub.i=π*r.sub.i.sup.2.

(50) Thus, a simple geometric model of the segmented vessel is generated, which is used as a basis for a subsequent calculation of a functional index.

(51) In one embodiment, densitometric information is used to estimate the vessel diameter in the through-plane direction. This may be based on cardiac digital subtraction angiography (DSA). Furthermore, this may utilize a time series images over a complete cardiac cycle to improve the robustness of the densitometric measurement. Densitometric evaluation might be limited to a segment of the vessel, e.g. between two bifurcations.

(52) In another embodiment, the projection angle is chosen such that the apparent stenosis diameter is minimized. This choice may be done manually by a human operator of an imaging system by selecting one of multiple acquired projections, or an automatic suggestion is made based on prior-knowledge using a reference database of projection images. This approach may result in a systematic underestimation of the cross-sectional area, and may lead to improved reproducibility as compared to an unguided approach.

(53) In another embodiment, the projection angle is chosen (manually or automated) such that least vessel foreshortening occurs. This may be combined with the diameter minimization.

(54) Based on some or all of the vessel characteristics that are extracted from 2D images (like diameter, length, curvature, through plane diameter, bifurcation number and location), a functional index for stenosis assessment is calculated. This functional index can, for instance, be either of: the pressure drop along the centerline of the vessel, virtual FFR, e.g. based on CFD simulations, a curve of the pressure drop as a function of the blood flow through the stenosis, or a quantity derived thereof, a fluid-dynamic resistance value, simulated average blood velocity profile or velocity distribution, or any other functional index that can be derived from hemodynamic parameters (e.g. CFR, iFR, etc.).

(55) In an embodiment, the functional index for stenosis assessment is derived from a 2D projection image. Preferably, a single angiographic 2D projection image with segmentation and pressure drop profile is used for functional assessment, as it can be obtained from fluid dynamics simulations.

(56) However, additionally, the index may be independently derived from a plurality of 2D images. That is, a functional index being derived “independently” involves deriving separate indices for individual images in a series, for instance carrying out the vessel segmentation, modeling and fluid dynamics simulation for each image of the series.

(57) Different images in the series are for example acquired in different cardiac states. Alternatively or in addition, different projection angles may be used providing different viewing angles on the vasculature.

(58) Optionally, an improved assessment can be based on one or more of the functional indices derived from different images. For example, in this case, it may be helpful to merge the individual numbers into a combined index (e.g. the mean value).

(59) Alternatively or in addition, a variation between the functional indices from different images is determined. For example, such variation can be compared to a predetermined maximal variation (Vmax), based on which an acceptance criterion may be generated, in order to have feedback on the accuracy of the results. If the simulated values from multiple images are within expected or predetermined limits of variation, the acceptance criterion may indicate that the simulated results may be accepted with higher confidence than for a single frame evaluation.

(60) The expected maximal variation (Vmax) may be predetermined taking into account the nature of the different images of the sequence. For example, for multiple images taken at the same projection angle but in different heart phases, Vmax may be lower than for multiple images taken at different projection angles.

(61) Alternatively or in addition, the processing unit may be configured to calculate a quality score for one or more images being used as a basis for calculating the functional index for stenosis assessment.

(62) For example, such quality score may be based on one or more of the following quality parameters: The resolution of the angiographic X-ray image, as may for example be determined from DICOM data associated with the image. The size of the projected vessel tree, e.g. an image area covered by contrast-enhanced vessels. A larger projected vascular tree may represent a higher quality image. The amount of noise in the projection, as may for example be determined by means of a noise measurement in a background area, i.e. a portion of the image outside the vascular tree. A lower amount of noise may represent a higher quality image. A sharpness of projection, as may for example be determined by means of an entropy analysis or gradient measures. The motion of the coronary arteries, as may for example be determined by means of a correspondence analysis with neighbouring images in a sequence. Strong motion may lead to blurred contours and thereby a lower quality image.

(63) Other quality parameters, such as the amount of foreshortening in the projection image for the section of vessel of interest, or the amount of vessel overlap in the projection image, could also be taken into consideration.

(64) In an embodiment, the quality score may be visualized together with the angiographic X-ray image, the calculated functional index and, optionally, the determined segmentation of the vessel segment of interest.

(65) In a further embodiment, if the functional index is independently derived for a plurality of images, the quality score may be calculated for each image together with the functional index. For example, the quality score may then be used as a weighting factor in determining a combined functional index, whereby a functional index derived from a lower quality image is given less weight in the combined index as a functional index derived from a higher quality image.

(66) The approach described herein is applicable for functional assessment of stenosis in all major arteries of the human body (coronaries, iliac, femoral, brachial, hepatic, carotids).

(67) In an embodiment, the functional index may be compared to one or more geometric measures for example obtained by means of QCA. Automatic QCA measurements may be carried out along the centerline of the vessel or vessel section of interest. Likewise, an FFR value may be calculated for the same vessel or vessel section.

(68) For example, a user interface may be provided that enables such comparison. Both the QCA and FFR values can be normalized and overlaid on top of the angiographic X-ray image that was used as a basis for the calculations. In an example, portions of the vessel where a discrepancy between the normalized QCA and FFR values exceeds a predetermined threshold may be determined and visualized on the image, for instance by means of highlighting or color coding. The normalization may be based on standard decision thresholds, e.g. a threshold for a decision whether a stent is to be placed or not. In that case, a QCA value of 0.5 may correspond to an FFR value of 0.8.

(69) It has to be noted that embodiments of the invention are described with reference to different subject matters. In particular, some embodiments are described with reference to a method whereas other embodiments are described with reference to the apparatus. However, a person skilled in the art will gather from the above that, unless otherwise notified, in addition to any combination of features belonging to one subject matter also any combination between features relating to different subject matters is considered to be disclosed with this application. However, all features can be combined providing synergetic effects that are more than the simple summation of the features. While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive. The invention is not limited to the disclosed embodiments. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing a claimed invention, from a study of the drawings, the disclosure, and the dependent claims.

(70) In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single parameter, feature or other element may fulfil the functions of several items re-cited in the claims. The mere fact that certain measures are re-cited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims should not be construed as limiting the scope.