Fractional flow reserve determination

Abstract

The present invention relates to a device (1) for fractional flow reserve determination. The device (1) comprises a model generator (10) configured to generate a three-dimensional model (3DM) of a portion of an imaged vascular vessel tree (VVT) surrounding a stenosed vessel segment (SVS), based on a partial segmentation of the imaged vascular vessel tree (VVT). Further, the device comprises an image processor (20) configured to calculate a blood flow (Q) through the stenosed vessel segment (SVS) based on an analysis of a time-series of X-ray images of the vascular vessel tree (VVT). Still further, the device comprises a fractional-flow-reserve determiner (30) configured to determine a fractional flow reserve (FFR) based on the three-dimensional model (3DM) and the calculated blood flow.

Claims

1. A device for fractional flow reserve determination, the device comprising: a processor configured to: receive a time series of X-ray or CT images of an imaged vascular vessel tree, the imaged vascular vessel tree comprising stenosed vessel segment, a proximal vessel segment proximal to the stenosed vessel segment, and a distal vessel segment distal to the stenosed vessel segment, wherein the proximal vessel segment comprises a diameter; generate a three-dimensional model of a portion of the imaged vascular vessel tree based on a segmentation of only the stenosed vessel segment and the distal vessel segment; calculate a blood flow through the stenosed vessel segment based on an analysis of the time series of X-ray or CT images of the imaged vascular vessel tree; obtain the diameter of the proximal vessel segment, wherein the proximal vessel segment is excluded from the segmentation such that the diameter of the proximal vessel segment is not obtained based on the segmentation; and determine, using a plurality of boundary conditions, a fractional flow reserve based on the three-dimensional model and the calculated blood flow, wherein the plurality of boundary conditions comprises a boundary condition associated with the distal vessel segment, wherein the boundary condition is determined using the diameter of the proximal vessel segment, wherein the diameter of the proximal vessel segment is approximated using a diameter of a catheter.

2. The device of claim 1, wherein the diameter of the proximal vessel segment comprises a coronary ostium diameter.

3. The device of claim 1, wherein the plurality of boundary conditions comprises at least one of: a pressure constraint; a flow constraint; or a lumped element model comprising at least one of a resistor, a varistor, or a capacitor.

4. The device of claim 1, wherein the processor is further configured to determine at least one boundary condition of the plurality of boundary conditions using a pressure constraint derived from an aortic pressure measurement.

5. The device of claim 4, wherein the aortic pressure measurement is an arm cuff pressure measurement or an aortic catheter measurement.

6. The device of claim 1, wherein the three-dimensional model comprises a plurality of tubes each defined by at least one of a diameter, a length, a position, or a direction.

7. The device of claim 1, wherein the processor is further configured to calculate a distal pressure of the stenosed vessel segment using a three-dimensional fluid dynamics simulation or a lumped components model.

8. The device of claim 7, wherein a resistance of the stenosed vessel segment is approximated from a cross-sectional area of the stenosed vessel segment.

9. The device of claim 1, wherein the analysis of the time series of X-ray or CT images has a period of up to 1 second, 5 seconds, or 12 seconds.

10. The device of claim 1, wherein the analysis of the time series of X-ray or CT images includes determining calibrated intensities over a region of interest including the stenosed vessel segment.

11. The device of claim 1, wherein the analysis of the time series of X-ray or CT images includes using densitometry.

12. The device of claim 1, wherein the processor is configured to obtain a measurement of the diameter of the proximal vessel segment on the time series of X-ray or CT images.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) A more complete appreciation of the present invention and the attendant advantages thereof will be more clearly understood with reference to the following schematic drawings, which are not to scale, wherein:

(2) FIG. 1 shows a schematic diagram of region of interest on an image vascular vessel tree for explaining the present invention;

(3) FIG. 2 shows a schematic diagram of an intensity as a function of time plot for explaining the present invention;

(4) FIG. 3 shows a schematic diagram of a simple geometric model of a stenosed vessel segment for explaining the present invention;

(5) FIG. 4 shows a schematic diagram of a coronary vessel tree with typical boundary conditions for explaining the present invention;

(6) FIG. 5 shows a schematic diagram of a complete segmentation of the coronary vessels and the proposed reduced segmentation for explaining the present invention;

(7) FIG. 6 shows a schematic diagram of a flowchart diagram for explaining the present invention;

(8) FIG. 7 shows a schematic diagram of a device for fractional flow reserve determination according to an exemplary embodiment of the present invention;

(9) FIG. 8 shows a schematic diagram of a medical imaging device according to an exemplary embodiment of the present invention; and

(10) FIG. 9 shows a schematic diagram of a flowchart diagram of a method for fractional flow reserve determination according to an exemplary embodiment of the present invention.

DETAILED DESCRIPTION OF EMBODIMENTS

(11) The illustration in the drawings is purely schematic and does not intend to provide scaling relations or size information. In different drawings or figures, similar or identical elements are provided with the same reference numerals. Generally, identical parts, units, entities or steps are provided with the same reference symbols in the description.

(12) FIG. 1 shows a schematic diagram of a region of interest on an image vascular vessel tree for explaining the present invention.

(13) In FIG. 1, an imaged vascular vessel tree VVT is shown and a partial segmentation of the image vascular vessel tree VVT is performed around a stenosed vessel segment SVS of interest.

(14) According to an exemplary embodiment of the present invention, the geometric model of the coronary tree can be obtained by segmentation of cardiac computed tomography, CT, image volumes or from a few preferably two orthogonal X-ray angiography projections.

(15) A quantitative measurement of the blood flow in the stenosed segment may be performed. For example, a densitometric approach may be suited to estimate the flow from a short time-series of X-ray angiography images.

(16) A power injector, or a controllable injector, e.g. an injector module, can be used to minimize the dilution of the contrast agent with blood. For quantitative measurement of the contrast agent inflow, the image may be calibrated properly. To this end, scatter and background structures may be removed (e.g. by top-hat filtering, bone removal or by digital subtraction of a reference image) and the imaged intensity may be calibrated (e.g. using a phantom with known attenuation or using information of the three-dimensional vessel geometry). A region of interest, ROI, may be marked, as illustrated later on in FIG. 3, and tracked over time.

(17) FIG. 2 shows a schematic diagram of an intensity as a function of time plot for explaining the present invention. According to an exemplary embodiment of the present invention, when integrating the calibrated intensities over the ROI, the volumetric blood flow Q can be calculated as the slope of the curve at bolus arrival time as shown in FIG. 2. Contrast transit-time or arrival-time methods for flow quantification might also be used, either as an alternative or in combination with the densitometric approach.

(18) According to an exemplary embodiment of the present invention, as an inlet boundary condition, the aortic pressure can be estimated from arm cuff pressure measurements, or can be measured directly using an aortic catheter, as usually done in interventional cardiology. Using the flow boundary condition, the requirements for geometric modeling are significantly relaxed. A typical fractional flow reserve FFR simulation may be given by a detailed segmentation of the complete coronary tree (including fine distal branches).

(19) FIG. 3 shows a schematic diagram of a simple geometric model of a stenosed vessel segment for explaining the present invention. FIG. 3 shows a partial segmentation of the image vascular vessel tree VVT around the stenosed vessel segment SVS.

(20) According to an exemplary embodiment of the present invention, if the blood flow Q through the stenosis and the aortic pressure p.sub.a are known, a model of the stenosed vessel segment alone (as shown in FIG. 3) is sufficient to calculate the distal pressure p.sub.d. This can be achieved via a full three-dimensional computational fluid dynamics simulation or by a lumped components approach where the segment's resistance is approximated from its cross-sectional areas, considering the Poiseuille effect (or Poiseuille's Law), the Bernoulli principle and others. Then, the fractional flow reserve FFR can be calculated as in the following equation:
FFR=P.sub.d/P.sub.a.

(21) FIG. 3 shows a simple geometric model of a stenosed vessel segment. The inlet and outlet boundary conditions are given by the aortic pressure p.sub.a and the flow Q, respectively.

(22) According to an exemplary embodiment of the present invention, the so-called virtual fractional flow reserve (vFFR) method may be used in combination with invasive pressure measurements by computational fluid dynamics (CFD) simulations. CFD simulations may be based on a geometric model of the coronary tree, which can be obtained either from CT angiography or from X-ray angiography images. A region of interest, ROI, may be marked and tracked over time.

(23) FIG. 4 shows a schematic diagram of a coronary vessel tree with typical boundary conditions for explaining the present invention.

(24) For accurate vFFR simulations, the choice of personalized boundary conditions at the inlets and outlets (as illustrated using FIG. 4) are considered. At each inlet and outlet, boundary conditions are assigned for non-ambiguous definition of all model variables. In general, these boundary conditions are pressure or flow constraints or lumped element models, composed of resistors, non-linear resistors (varistors) and dynamic elements (such as capacitors). For example, one can impose a pressure pin at the inlet (coronary ostium) and a particular resistance going to ground to each of the outlets.

(25) The term “varistor” as used by the present invention refers to an electronic component with a nonlinear current-voltage characteristic, which is therefore also known as a voltage-dependent resistor (VDR).

(26) The error of vFFR simulations depends at least linearly on a correct estimate of the flow value through the stenosis and hence on the correct choice of boundary conditions. If parts of the coronary tree are excluded from the segmentation, the flow through the remaining branches (especially through the stenosed segment) and hence the vFFR prediction would be compromised.

(27) FIG. 5 shows a schematic diagram of a complete segmentation of the coronary vessels and the proposed reduced segmentation.

(28) According to an exemplary embodiment of the present invention, the boundary conditions (pressures or resistances) at each outlet usually depend on the size (e.g. diameter, cross-sectional area) of the out-going vessel relative to the root vessel (e.g. LCA, RCA). Then, scaling laws can be applied to calculate the relative flow or impedance of each outlet. E.g. in case of a simple outlet resistance, resulting in equation 1:

(29) $R_{out}=150\frac{\mathrm{Pa}}{m\text{/}s}.Math.\sqrt[3]{\frac{d_{\mathrm{root}}}{d_{out}}}$

(30) wherein Rout is the outlet resistance, d.sub.out is the diameter of the outlet, droot is the diameter of the root vessel, wherein the expression “Pa” of equation 1 refers to pascal (symbol: Pa) and is the SI derived unit of pressure, internal pressure, stress, Young's modulus and tensile strength, defined as one newton per square meter. The expression “m/s” of equation 1 refers to meter per second. Meter per second is an SI derived unit of speed (scalar) and velocity (vector), defined by distance in meters divided by time in seconds. Calculating the outlet resistance requires knowledge of the diameter droot of the root vessel, which is not available with an incomplete segmentation.

(31) According to an exemplary embodiment of the present invention, it is proposed to calculate vFFR with only a partial segmentation of the vascular tree together with an explicit measurement of the diameter of the coronary ostium. This measure may be then used in a scaling law for the boundary conditions, e.g. as droot in equation 1.

(32) The basic principle is illustrated in FIG. 5. Conventionally, a complete segmentation of the coronary vessel tree is preferred to increase the accuracy of vFFR calculations. A detailed segmentation, however, may be tedious and may hamper clinical workflow, especially during cardiac interventions. As the fractional flow reserve (FFR) value depends mostly on the stenosis geometry and the flow through the stenosed vessel segment, a partial segmentation (e.g. of the branches distal to the stenosis) can be sufficient for vFFR calculations if the ostium diameter is used to calculate peripheral resistance, for example by equation 1.

(33) FIG. 5 shows a complete segmentation of the coronary vessel tree (left) and proposed reduced segmentation (right).

(34) According to an exemplary embodiment of the present invention, the ostium diameter can be obtained (a) by interactive or (semi-)automated measurement on X-ray images or CT-volumes or (b) approximated by the diameter of coronary catheter, which was chosen by the interventional radiologist.

(35) In general, it will often be reasonable to exclude the major branches located proximal to a stenosis from the segmentation (as in FIG. 5) without introducing a large error. This is true if the pressure drop Dp from the inlet to the cropping point is small, i.e. no stenosis is located there. This is not very limiting, because if stenoses were located there, this branches would be included in the segmentation anyway. The blood flow through the stenosis can then still be estimated accurately by flow or impedance boundary conditions with a scaling law using the root diameter information.

(36) FIG. 6 shows a schematic diagram of a flowchart diagram for explaining the present invention.

(37) Initially, a three-dimensional model 3DM of an imaged vascular vessel tree VVT based on a partial segmentation of the imaged vascular vessel tree VVT surrounding a stenosed vessel segment SVS may be calculated.

(38) Then, calculating a blood flow Q through the stenosed vessel segment SVS based on an analysis of a time-series of X-ray images may be performed.

(39) Subsequently, a fractional flow reserve FFR based on the three-dimensional model 3DM and the calculated blood flow Q may be calculated.

(40) FIG. 7 shows a schematic diagram of a device 1 for fractional flow reserve determination.

(41) The device 1 for fractional flow reserve determination may comprise a model generator 10, an image processor 20, and a fractional-flow-reserve determiner 30.

(42) The model generator 10 may be configured to calculate a three-dimensional model 3DM of an imaged vascular vessel tree VVT on a partial segmentation of an image vascular vessel tree VVT surrounding a stenosed vessel segment SVS. The three-dimensional model may be a virtual structure of a vessel structure, a complex branched tree structure, or any other structure as a circuit, wherein the vessel structure is modeled by a plurality of tubes each of which defined by, for instance parameters like size, length, position, and direction.

(43) The image processor 20 may be configured to calculate a blood flow Q through the stenosed vessel segment SVS based on an analysis of a time-series of X-ray images. The analysis may be an image processing analysis, for instance, a brightness analysis or an image contrast analysis.

(44) The fractional-flow-reserve determiner 30 may be configured to determine a fractional flow reserve based on the three-dimensional model of the imaged vascular vessel tree VVT and the calculated blood flow Q.

(45) Further, the distance between the location, at which the diameter of the ostium was measured, and the part, at which the segmentation of the stenosed vessel segment SVS starts, may be used as an input parameter by the model generator 10.

(46) FIG. 8 shows a schematic diagram of a medical imaging system 200 according to an exemplary embodiment of the present invention.

(47) The medical imaging system 200 may comprise an example of the device 1 for fractional flow reserve determination. The medical imaging system 200 may be an X-ray guided cardiac medical intervention device, a CT-imaging system or a magnetic resonance (MR) angiography imaging system.

(48) Further, the medical imaging system 200 may be used for coronary flow reserve determination.

(49) FIG. 9 shows a schematic diagram of a flowchart of a method for fractional flow reserve determination. The method may comprise the following steps:

(50) As a first step a) of the method, generating S1 a three-dimensional model of an imaged vascular vessel tree VVT based on a partial segmentation of the imaged vascular vessel tree VVT surrounding a stenosed vessel segment SVS by a model generator 10 may be conducted.

(51) As a second step b) of the method, calculating S2 a blood flow Q through the stenosed vessel segment SVS based on an analysis of a time-series of X-ray images by image processor 20 may be conducted.

(52) As a third step c) of the method, determining S3 a fractional flow reserve FFR based on the fractional flow reserve FFR and the calculated blood flow Q by a fractional-flow-reserve determiner 30 may be conducted.

(53) According to an example, the step of calculating S2 the blood flow Q through the stenosed vessel segment SVS comprises calculating the blood flow Q using calibrated intensities over a region of interest including the stenosed vessel segment SVS. In an example, the step of determining S3 the fractional flow reserve FFR is performed using at least one boundary condition on an inlet and/or an outlet of the imaged vascular vessel tree VVT.

(54) It has to be noted that embodiments of the present invention are described with reference to different subject-matters. In particular, some embodiments are described with reference to method type claims whereas other embodiments are described with reference to device type claims.

(55) However, a person skilled in the art will gather from the above and the foregoing description that, unless otherwise notified, in addition to any combination of features belonging to one type of the subject-matter also any combination between features relating to different subject-matters is considered to be disclosed with this application.

(56) However, all features can be combined providing synergetic effects that are more than the simple summation of these features.

(57) While the present invention has been illustrated and described in detail in the drawings and the foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the present 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 and practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims.

(58) 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 processor or controller or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited 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.