Method and system for calculating blood vessel pressure difference and fractional flow reserve

Abstract

A method for computing fractional flow reserve (FFR), including receiving geometrical parameters of a blood vessel segment including a proximal end and a distal end, the geometrical parameters including a first geometrical parameter, a second geometrical parameter and a third geometrical parameter; and with the proximal end as a reference point, deriving a reference lumen diameter function and a geometrical parameter difference function based on the geometrical parameters and the distance from the position along the segment of blood vessel to the reference point. Derivatives of the geometrical parameter difference function are calculated in multiple scales. FFR is computed as a ratio of a second blood flow pressure at the first location of the blood vessel to a first blood flow pressure at the proximal end of the segment based on the multiple scales of derivative difference functions and the maximum mean blood flow velocity.

Claims

1. A method of detecting pressure deviation in a blood vessel segment, comprising: receiving geometrical parameters of a blood vessel segment comprising a proximal end and a distal end, wherein the geometrical parameters comprises a first geometrical parameter representing a cross-sectional area or diameter of the proximal end of the segment, a second geometrical parameter representing a cross-sectional area or diameter of the distal end of the segment, and a third geometrical parameter representing a cross-sectional area or diameter of the blood vessel segment at a first location between the proximal end and the distal end; wherein the geometrical parameters are obtained by two-dimensional or three-dimensional coronary angiography, coronary computed tomography angiography (CTA), intravascular ultrasound (IVUS) or optical coherence tomography (OCT); receiving a mean blood flow velocity of the blood vessel segment; with the proximal end point as a reference point, deriving a reference lumen diameter function based on the first geometrical parameter, the second geometrical parameter and a distance x from a certain position along the blood vessel segment to the reference point; wherein the reference lumen diameter function is used to represent reference lumen diameter at different positions along the blood vessel as a function of the distance x from the position to the reference point, and wherein the derivation of the reference lumen diameter function Preferably comprises a linear normalization as a function of location from the proximal end to the distal end of the segment; with the proximal end point as a reference point, deriving a geometrical parameter difference function based on the third geometrical parameter and the reference lumen diameter function; wherein the geometrical parameter difference function indicates a relationship of differences between the reference lumen diameter function and the received geometrical parameters with respect to the distances x from the reference point; calculating derivatives of the geometrical parameter difference function in multiple scales, wherein the scales are resolutions indicative of distances between two adjacent points when calculating derivative numerically, wherein the multiple scales comprise a first greater scale and a second smaller scale, wherein the multiple scales of derivative difference functions comprise a derivative difference function f.sub.1(x) in the first scale and a derivative difference function f.sub.2(x) in the second scale, wherein use of the multiple scales enables manifestation of impacts of different severity of stenosis (focal and diffuse) on the pressure deviation; wherein the derivative difference function f.sub.1(x) in the first scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by stenosis affecting a wide range, with geometrical parameter differences caused by focal stenosis being ignored, wherein the derivative difference function f.sub.2(x) in the second scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a focal lesion; and obtaining a pressure deviation ΔP between a first blood flow pressure at the proximal end and a second blood flow pressure at the first location based on the derivatives of the geometrical parameter difference in multiple scales at the first location, the mean blood flow velocity V and a square of the mean blood flow velocity V.sup.2.

2. The method of claim 1, further comprising: computing the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure by weighting integrals of the first scale of derivative difference function f.sub.1(x) and the second scale of derivative difference function f.sub.2(x) as well as the mean blood flow velocity V and its square V.sup.2.

3. The method of claim 2, further comprising: computing the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure according to
ΔP=α[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.1(x)dx+β[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.2(x)dx where C.sub.1 and C.sub.2 represent coefficients of the mean blood flow velocity V and its square V.sup.2, respectively, and α and β denote weighting coefficients of the derivative difference functions in the first and second scales respectively.

4. The method of claim 1, further comprising: computing derivatives of the geometrical parameter difference function in n scales, wherein the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure is computed based on the n scales of derivative difference functions, wherein the scales are resolutions indicative of distances between two adjacent points when calculating derivative numerically, wherein the n scales consist of a first scale, a second scale, . . . and an n-th scale, wherein the derivative difference function f.sub.1(x) in the first scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a first lesion characteristic, with geometrical parameter differences caused by other lesions being ignored, wherein the derivative difference function f.sub.2(x) in the second scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a second lesion characteristic, wherein the derivative difference function f.sub.n(x) in the n-th scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by an n-th lesion characteristic, and wherein n is a natural number greater than 1.

5. The method of claim 4, further comprising: computing the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure by weighting integrals of the n scales of derivative difference functions f.sub.1(x), . . . , f.sub.n(x) and the mean blood flow velocity V and the square of the mean blood flow velocity V.sup.2.

6. The method of claim 5, further comprising: computing the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure according to
ΔP=α.sub.1[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.1(x)dx+α.sub.2[C.sub.1V+C.sub.2V.sup.2]∫f.sub.2(x)dx+ . . . +α.sub.n[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.n(x)dx where, C.sub.1 and C.sub.2 represent coefficients of the mean blood flow velocity V and its square V.sup.2, respectively, and α.sub.1, α.sub.2, . . . , and α.sub.n denote weighting coefficients for the derivative difference functions f.sub.1(x), f.sub.2(x), . . . , f.sub.n(x) in the n scales, respectively.

7. The method of claim 1, wherein the location data related to the first location is a distance from the first location to the proximal end of the segment, and wherein the mean blood flow velocity is a mean velocity from the proximal end to the distal end.

8. The method of claim 1, further comprising: receiving two-dimensional coronary angiography images under a certain angle; and registering region of interest of the images for different frames, wherein the region of interest of the coronary angiography is from the proximal end point of the segment to the distal end.

9. The method of claim 8, further comprising: plotting a gray-level histogram from the registered region of interest and fitting the gray-level as a function of time within a cardiac cycle.

10. The method of claim 9, further comprising: obtaining a mean flow velocity of contrast medium within the segment from the gray-level fitting function.

11. The method of claim 10, wherein the mean blood flow velocity V of the blood vessel segment is approximately equal to the mean flow velocity of the contrast medium obtained from the gray-level fitting function.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) FIG. 1 schematically illustrates a structural comparison between a stenosed lumen and its reference lumen of the present invention.

(2) FIG. 2 illustrates a difference function depicting difference between the reference lumen and actual lumen of the blood vessel segment.

(3) FIG. 3A is a diagram showing a derivative difference function f.sub.1(x) in a first scale.

(4) FIG. 3B is a diagram showing a derivative difference function f.sub.2(x) in a second scale.

(5) FIG. 4 is a schematic diagram of blood pressure drop system of the present invention.

DETAILED DESCRIPTION

(6) Technical solutions according to embodiments of the present invention will be thoroughly described below with reference to the accompanying drawings so that they will be clearer. Apparently, the embodiments set forth below are only some, but not all embodiments of the inventions. All other embodiments obtained by those of ordinary skill in the art based on the embodiments disclosed herein fall within the scope of the invention.

Embodiment 1

(7) The present invention provides a method for computing a pressure deviation within a segment of a blood vessel, the method comprising: receiving geometrical parameters of the segment having a proximal end point and a distal end point. The geometrical parameters include: a first geometrical parameter representing a cross-sectional area (or diameter) of the segment at the proximal end; a second geometrical parameter representing a cross-sectional area (or diameter) of the segment at the distal end; and a third geometrical parameter representing a cross-sectional area (or diameter) of the first location at a first location between the proximal end point and the distal end point. Based on the first geometrical parameter, the second geometrical parameter, the third geometrical parameter and location data related to the first location, a reference (assuming there was no lesion) lumen diameter of the blood vessel at the first location can be obtained. A geometrical parameter difference between an actual lumen diameter and the reference lumen diameter at the first location is calculated based on the third geometrical parameter and the reference lumen diameter at the first location. Preferably, the geometrical parameter difference is obtained from the division of the actual lumen diameter by the reference lumen diameter.

(8) With the proximal end point as a reference point, based on the first geometrical parameter, the second geometrical parameter and the distance x of a certain position on the segment from the reference point, a reference lumen diameter function is derived, which represents reference lumen diameter at different positions along the blood vessel as a function of the distance x from the position to the reference point. Based on the third geometrical parameter and the reference lumen diameter function, a geometrical parameter difference function is derived, which represents the variation of a difference between the reference lumen diameter function and the received geometrical parameters with respect to the distance x from the reference point.

(9) In a specific embodiment, the derivation of the reference lumen diameter function includes linear normalization of location parameters in the range from the proximal end of the segment to the distal end.

(10) In a specific embodiment, with the proximal end as a reference point, based on the third geometrical parameter and the reference lumen diameter function, a geometrical parameter difference function is derived, which represents a variation of a difference between the reference lumen diameter function and the received geometrical parameters with the distance x from the reference point.

(11) In a specific embodiment, multiple scales of derivative difference functions of the geometrical parameter difference are derived, based on which a pressure deviation ΔP between a first blood flow pressure and a second blood flow pressure is calculated.

(12) Wherein, the scales are resolutions indicative of distances between two adjacent points when calculating the derivative numerically. The multiple scales include a first greater scale and a second smaller scale. Use of the multiple scales allows manifestation of the impacts of different degrees of stenosis (focal and diffuse) on the blood flow pressure deviation.

(13) In a specific embodiment, the different scales include a first greater scale and a second smaller scale, and the multiple scales of derivative difference functions include a derivative difference function f.sub.1(x) in the first scale and a derivative difference function f.sub.2(x) in the second scale. Use of the different scales allows manifestation of impacts of different degrees of stenosis (focal and diffuse) on the blood flow pressure deviation. The first scale of derivative difference function f.sub.1(x) is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by long sever lesion ignoring focal stenosis. The second scale of derivative difference function f.sub.2(x) is utilized to detect a geometrical parameter difference caused by a focal stenosis.

(14) The pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure can be obtained by weighting integrals of the first and the second scale of derivative difference function as well as a mean blood flow velocity V and its square V.sup.2.

(15) Preferably, the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure is obtained according to
ΔP=α[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.1(x)dx+β[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.2(x)dx

(16) where, C.sub.1 and C.sub.2 represent coefficients of the mean blood flow velocity V and its square V.sup.2, respectively, and α and β denote weighting coefficients for the derivative difference functions in the first and second scales, respectively.

(17) Preferably, in order to more accurately compute the pressure deviation within the segment of the vessel under various conditions, it could be contemplated to calculate derivatives of the geometrical parameter difference function in n different scales and calculate the pressure deviation between the first blood flow pressure and the second blood flow pressure based on the n scales of derivative difference functions. That is:

(18) The derivatives of the geometrical parameter difference function in the n scales are derived, and the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure is calculated based on the n scales of derivative difference functions. The scales are implemented as resolutions indicative of distances between two adjacent points when calculating derivative numerically. The n scales are a first scale, a second scale, . . . , and an n-th scale.

(19) The first scale of derivative difference function f.sub.1(x) is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a first lesion characteristic, with geometrical parameter differences attributed to other lesions being ignored.

(20) The second scale of derivative difference function f.sub.2(x) is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a second lesion characteristic, . . . , and the derivative difference function f.sub.n(x) in the n-th scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by an n-th lesion characteristic. n is a natural number greater than 1. The pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure can be obtained by weighting integrals of the n scales of derivative difference functions f.sub.1(x), . . . , f.sub.n(x) as well as a mean blood flow velocity V and its square.

(21) Preferably, the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure is obtained according to:
ΔP=α.sub.1[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.1(x)dx+α.sub.2[C.sub.1V+C.sub.2V.sup.2]∫f.sub.2(x)dx+ . . . +α.sub.n[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.n(x)dx

(22) where, C.sub.1 and C.sub.2 represent coefficients of the mean blood flow velocity V and its square V.sup.2, respectively, and α.sub.1, α.sub.2, . . . , and α.sub.n denote weighting coefficients for the derivative difference functions f.sub.1(x), f.sub.2(x), . . . , f.sub.n(x) in the n scales, respectively.

(23) Preferably, the location data related to the first location indicate the distance from the first location to the proximal end of the segment, and the mean blood flow velocity of the segment is a mean velocity from the proximal end to the distal end.

(24) Preferably, the method further includes: receiving two-dimensional coronary angiography images under a certain angle; and registering a region of interest of the images for different frames. The region of interest of the coronary angiography is from the proximal end to the distal end.

(25) Preferably, the method further includes: plotting a gray-level histogram for the registered region of interest; and fitting the gray value as a function of time within a cardiac cycle.

(26) Preferably, the method further includes: obtaining a mean flow velocity of the contrast medium within the segment of the vessel based on the gray-level fitting function.

(27) Preferably, the mean blood flow velocity V of the segment is approximately equal to the mean contrast medium velocity obtained from the gray-level fitting function.

(28) The method will be described in further detail below with reference to FIGS. 1 and 2. Referring to FIG. 1, the method includes: receiving geometrical parameters of a segment of a blood vessel, including: (a) a geometrical parameter (cross-sectional area or diameter) at a proximal end P of the segment; (b) a geometrical parameter (cross-sectional area or diameter) at a distal point D of the segment; and (c) taking P as a reference point, a geometrical parameter (cross-sectional area or diameter) of the segment between P and D as well as the distance x from the position of the segment to the reference point P are obtained.

(29) The geometrical parameters may be obtained by any of a variety of techniques including two-dimensional or three-dimensional coronary angiography, coronary computed tomography angiography (CTA), intravascular ultrasound (IVUS) or optical coherence tomography (OCT). Generally, the geometrical parameters of the segment may be its cross-sectional areas or diameters. In case of two-dimensional diameters of the blood vessel being received, we can assume the cross-sections of the blood vessel to be circular and thus can obtain its cross-sectional areas.

(30) Based on these data (a), (b) and (c), a reference geometrical parameter of the segment (assuming there was no lesion) can be obtained and represented as a linear function of the distance from the reference point P. In FIG. 1, the solid lines represents an actual lumen of the segment, while the dotted lines represents a reference lumen thereof. A geometrical parameter difference as a function of the distance from the reference point P can be derived from a ratio of the geometrical parameter of the reference lumen to that of the actual lumen.

(31) FIG. 2 is a diagram showing the geometrical parameter difference between the actual lumen and the reference lumen of FIG. 1 as a geometrical parameter difference function F(x). It is noted that, as revealed by an analysis, an accurate pressure deviation between a first blood flow pressure and a second blood flow pressure can be calculated using the geometrical parameter difference function F(x) in a single scale in the case of a single type of lesion. However, when multiple types of lesions, especially including a diffuse lesion, coexist in the blood vessel, the pressure deviation calculated by the method will suffer from a significant error. On the one hand, when the single scale is small, the derivative difference function at severe stenosis will be close to that at mild stenosis. This will lead to underestimation of the impact of the severe stenosis on the pressure deviation. On the other hand, when the single scale is great, the derivative of the difference function at the mild stenosis will be zero, i.e., failure to detect the impact of the mild stenosis on the pressure deviation.

(32) In order to overcome the deficiencies of the conventional methods of a single scale, it is preferred to take derivative of the geometrical parameter difference in n scales for a blood vessel with different degrees of lesions, and calculate the pressure deviation between the first and second blood flow pressures based on derivative difference functions in these scales.

(33) For example, in a preferred embodiment, derivative of the geometrical parameter difference function are derived in two scales, and the pressure deviation between the first and second blood flow pressures is calculated from there two scales of derivatives difference functions (including a first greater scale and a second smaller scale). The derivative difference function f.sub.1(x) in the first scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by long severe lesion, with geometrical parameter differences caused by focal stenosis being ignored. The derivative difference function f.sub.2(x) in the second scale is adapted to detect a geometrical parameter difference caused by a focal change of the segment.

(34) Derivatives of the difference function f(x) of FIG. 2 are taken in these two scales.

(35) The derivative difference function in the greater scale is:

(36) $f_1\left(x\right)=\frac{F\left(X+\Delta h_1/2\right)-F\left(X-\Delta h_1/2\right)}{\Delta h_1},$

(37) and the derivative difference function in the smaller scale is:

(38) $f_2\left(x\right)=\frac{F\left(X+\Delta h_2/2\right)-F\left(X-+\Delta h_2/2\right)}{\Delta h_2}$

(39) where Δh1>Δh2.

(40) As shown in FIGS. 3A and 3B, in the greater scale Δh.sub.1, F(X+Δh.sub.1)−F(X) is nearly zero at focal lesion A, B. Therefore, f.sub.1(x) can reflect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by long severe stenosis, with any geometrical parameter difference caused by focal stenosis being ignored. In the smaller scale Δh.sub.2, geometrical parameter differences attributed to the focal stenosis A, B and the widely-affecting stenosis C can all be identified. However, according to the derivative difference function f.sub.2(x) in the smaller scale, the value of the derivatives for the different severity of stenosis are substantially equal and cannot be used to distinguish the different impacts of the stenosis on the pressure deviation. To achieve this, it is contemplated to weighting the derivative difference functions f.sub.1(x) and f.sub.2(x) in the two scales.

Embodiment 2

(41) The present invention also provides a method for computing fractional flow reserve (FFR) of a segment of a blood vessel, comprising: receiving geometrical parameters of the segment comprising a proximal end and a distal end, the geometrical parameters comprising a first geometrical parameter representing a cross-sectional area (or diameter) of the segment at the proximal end, a second geometrical parameter representing a cross-sectional area (or diameter) of the segment at the distal end and a third geometrical parameter representing cross-sectional area (or diameter) at a first location between the proximal end and the distal end; with the proximal end point as a reference point, deriving a reference lumen diameter function and a geometrical parameter difference function based on the geometrical parameters and the distance from position along the segment to the reference point; obtaining derivatives the geometrical parameter difference function in multiple scales, wherein the scales are resolutions indicative of distances between two adjacent points when calculating derivative numerically; receiving a mean blood flow velocity of the segment obtained by conventional coronary angiography and obtaining a maximum mean blood flow velocity of the segment by looking up a table; and obtaining FFR as a ratio of a second blood flow pressure at the first location of the blood vessel to a first blood flow pressure at the proximal end of the segment, based on the multiple scales of derivative difference functions and the maximum mean blood flow velocity.

(42) In a specific embodiment, the present invention provides a method for computing fractional flow reserve (FFR) of a segment of a blood vessel, comprising: obtaining a mean blood flow velocity V of the segment in a resting state optionally by conventional angiography (without maximum dilation of the microcirculation); calculating a maximum blood flow velocity V.sub.max at maximum dilation of microcirculation based on the mean velocity V; solving for a pressure deviation ΔP.sub.max corresponding to the maximum blood flow velocity; and obtaining FFR according to equation FFR=(P1−ΔP.sub.max)/P1, where P1 represents a first blood flow pressure at the proximal end of the segment, which can be approximately estimated from the cardiac diastolic and systolic pressures or accurately measured using a catheter.

(43) Preferably, the maximum blood flow velocity is obtained by looking up a correspondence table listing mean coronary blood flow velocities under a resting state and the corresponding maximum blood flow velocities at maximum dilation of microcirculation.

(44) Preferably, the pressure deviation ΔP.sub.max corresponding to the maximum blood flow velocity is obtained using the method of Embodiment 1.

(45) Preferably, FFR may be computed for a given fixed maximum blood flow velocity V.sub.max.

Embodiment 3

(46) The present invention provides a system for computing a pressure deviation within a segment of a blood vessel, which can implement the method for computing a pressure deviation set forth in the foregoing embodiment. The system includes: a geometrical parameter data acquisition module, configured to acquire geometrical parameters of the segment, the blood vessel comprising a proximal end and a distal end, the geometrical parameters comprising a first geometrical parameter representing a cross-sectional area or diameter of the segment at the proximal end, a second geometrical parameter representing a cross-sectional area or diameter of the segment at the distal end and a third geometrical parameter representing a cross-sectional area or diameter of the segment at a first location between the proximal end and the distal end of the segment; a location data acquisition module, configured to acquire location data related to the first location; a velocity acquisition module, configured to acquire a mean blood flow velocity of the segment and the square of the mean blood flow velocity; a reference lumen diameter computation module, configured to a compute a reference lumen diameter at the first location of the blood vessel based on the first geometrical parameter, the second geometrical parameter, the third geometrical parameter and the location data related to the first location; a geometrical parameter difference computation module, configured to compute a geometrical parameter difference between the third geometrical parameter and the reference lumen diameter at the first location; and a pressure deviation computation module, configured to obtain the geometrical parameter difference data at the first location output from the geometrical parameter difference computation module and the mean blood flow velocity and its square from the velocity acquisition module and to compute the pressure deviation ΔP between a first blood flow pressure at the proximal end and a second blood flow pressure at the first location.

(47) Preferably, the reference lumen diameter computation module is configured to derive a reference lumen diameter function, based on the first geometrical parameter, the second geometrical parameter and a distance x from a certain position along the segment of vessel to the proximal end as a reference point, wherein the reference lumen diameter function is used to represent reference lumen diameter along different positions along the blood vessel as a function of the distance x between the position and the reference point.

(48) Preferably, the system further comprises a normalization module configured to preform linear normalization as a function of location from the proximal end to the distal end point of the vessel segment.

(49) Preferably, the geometrical parameter difference computation module is configured to derive, with the proximal end point as a reference point, based on the third geometrical parameter and the reference lumen diameter function. The geometrical parameter difference function indicates a relationship of differences between the reference lumen diameter function and the received geometrical parameters with respect to the distances x from the reference point.

(50) Preferably, the system further comprises a multi-scale derivative difference computation module configured to calculate derivatives of the geometrical parameter difference function in multiple scales. The pressure deviation computation module computes the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure by weighting integrals of the derivative difference functions in the multiple scales based on the output of the multi-scale difference derivative computation module as well as the mean blood flow velocity V and its square V.sup.2 output from the velocity acquisition module.

(51) The multiple scales comprise two or more scales implemented as resolutions indicative of distances between two adjacent points when calculating derivative

(52) The pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure is computed based on multiple scales of derivatives difference function. The scales are resolutions indicative of distances between two adjacent points when calculating derivative numerically. The different scales comprise a first greater scale and a second smaller scale. The multiple scales of derivative difference functions comprise a first scale of derivative difference function f.sub.1(x) and a second scale of derivative difference function f.sub.2(x). Use of the multiple scales enables manifestation of different impacts of stenosis of different degrees of severity (focal and diffuse) in the segment on the pressure deviation. The first scale of derivative difference function f.sub.1(x) is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by long severe stenosis, with geometrical parameter differences caused by focal stenosis being ignored. The second scale of derivative difference function f.sub.2(x) is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a focal change occurring in the stenotic segment.

(53) In this case, the pressure deviation computation module computes the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure by weighting integrals of the first scale of derivative difference function f.sub.1(x) and the second scale of derivative difference function f.sub.2(x) output from the multi-scale difference derivative computation module and based on the mean blood flow velocity V and its square V.sup.2 output from the velocity acquisition module.

(54) Preferably, the pressure deviation computation module computes the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure according to
ΔP=α[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.1(x)dx+β[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.2(x)dx

(55) where C.sub.1 and C.sub.2 represent coefficients of the mean blood flow velocity V and its square V.sup.2, respectively, and α and β denote weighting coefficients for the derivative difference functions in the first and second scales, respectively.

(56) Preferably, in order to more accurately compute the pressure deviation in the segment of the blood vessel under various conditions, it is further contemplated to derive derivatives of the geometrical parameter difference function in n multiple scales and compute the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure based on the n scales of derivative difference functions. That is, the derivatives of the geometrical parameter difference function are calculated in the n scales, wherein the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure is computed based on the n scales of derivative difference functions. The scales are implemented as resolutions indicative of distances between two adjacent points when calculating derivative numerically. The n scales are a first scale, a second scale, . . . , and an n-th scale.

(57) The derivative difference function f.sub.1(x) in the first scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a first lesion characteristic, with geometrical parameter differences caused by other lesions being ignored. The derivative difference function f.sub.2(x) in the second scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by a second lesion characteristic, . . . , and the derivative difference function f.sub.n(x) in the n-th scale is adapted to detect a geometrical parameter difference between an actual lumen diameter and a reference lumen diameter caused by an n-th lesion characteristic, wherein n is a natural number greater than 1.

(58) In this case, the pressure deviation computation module computes the pressure deviation ΔP between the first blood flow pressure and the second blood flow pressure according to
ΔP=α.sub.1[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.1(x)dx+α.sub.2[C.sub.1V+C.sub.2V.sup.2]∫f.sub.2(x)dx+ . . . +α.sub.n[C.sub.1V+C.sub.2V.sup.2]*∫f.sub.n(x)dx

(59) where, C.sub.1 and C.sub.2 represent coefficients for the mean blood flow velocity V and its square V.sup.2, respectively, and α.sub.1, α.sub.2, . . . , and α.sub.n denote weighting coefficients for the derivative difference functions f.sub.1(x), f.sub.2(x), . . . , f.sub.n(x) in the n scales, respectively.

(60) The location data related to the first location is a distance from the first location to the proximal end of the segment, and the mean blood flow velocity of the segment is a mean blood flow velocity between the proximal end and the distal end.

(61) Preferably, the system further comprises a two-dimensional coronary angiography module configured to capture two-dimensional coronary angiography images of the segment under a certain angle and register region of interest of the images for different frame counts. The region of interest of the coronary angiography is from the proximal end of the segment to the distal end.

(62) Preferably, the velocity acquisition module is configured to plot a gray-level histogram from the registered region of interest based on the output from the two-dimensional coronary angiography module, and to fit the gray-level histogram as a function of time within a cardiac cycle, based on which a mean flow velocity of contrast medium within the segment of the vessel are obtained.

(63) Preferably, the mean blood flow velocity V within the segment is approximately equal to the mean flow velocity of the contrast medium.

Embodiment 4

(64) The present invention provides a system for computing fractional flow reserve (FFR) of a segment of blood vessel, comprising: a geometrical parameter data acquisition module, configured to acquire geometrical parameters of the segment, the blood vessel comprising a proximal end and a distal end, the geometrical parameters comprising a first geometrical parameter representing a cross-sectional area (or diameter) of the segment at the proximal end, a second geometrical parameter representing a cross-sectional area (or diameter) of the segment at the distal end and a third geometrical parameter representing a cross-sectional area (or diameter) of the segment at a first location between the proximal end and the distal end; a location data acquisition module, configured to acquire location data related to the first location; a reference lumen diameter computation module, configured to derive, a reference lumen diameter function with respect to the distance from a certain position along the segment to the proximal end as a reference point; a geometrical parameter difference computation module, configured to derive a parameter difference function based on the reference lumen diameter function and the third geometrical parameter; a multi-scale computation module, configured to obtain derivatives of the geometrical parameter difference function in multiple scales implemented as resolutions indicative of distances between two adjacent points when calculating derivative numerically; a mean blood flow velocity acquisition module, configured to acquire a mean blood flow velocity of the segment through conventional coronary angiography; a maximum mean blood flow velocity computation module, configured to obtain a maximum mean blood flow velocity of the segment by looking up a correspondence table stored in the module; and an FFR computation module, configured to obtain FFR as ratio of a second blood flow pressure at the first location of the blood vessel to a first blood flow pressure at the proximal end, based on the multiple scales of derivative difference functions and the maximum mean blood flow velocity.

(65) In a specific embodiment, the present invention also provides a system for computing fractional flow reserve (FFR) of a segment of a blood vessel, comprising: a mean blood flow velocity acquisition module, configured to acquire a mean blood flow velocity V of the segment preferably by conventional coronary angiography (without maximum dilation of microcirculation); a maximum blood flow velocity acquisition module, configured to calculate a maximum blood flow velocity V.sub.max under the condition of maximum dilation of microcirculation based on the mean velocity V; a pressure deviation computation module, configured to solve for a pressure deviation ΔP.sub.max corresponding to the maximum blood flow velocity; and an FFR computation module, configured to obtain FFR, based on a first blood flow pressure at the proximal end of the blood vessel and the pressure deviation ΔP.sub.max, according to FFR=(P1−ΔP.sub.max)/P1, wherein P1 can be approximately estimated from the cardiac diastolic and systolic pressures or accurately measured using a catheter.

(66) The maximum blood flow velocity acquisition module may obtain the maximum blood flow velocity by looking up a correspondence table listing mean coronary blood flow velocities in a resting state and the corresponding maximum blood flow velocities under the condition of maximum dilation of myocardial microcirculation. The correspondence table may be stored on the maximum blood flow velocity acquisition module or another separate module of the system.

(67) Preferably, the pressure deviation computation module may have the structure of the system of Embodiment 3 for obtaining the pressure deviation ΔP.sub.max corresponding to the maximum blood flow velocity using the method of Embodiment 1.

(68) Preferably, FFR may be computed for a given fixed maximum blood flow velocity V.sub.max.

(69) It is to be noted that the above systems and functional modules are presented merely as an example to describe a basic, but not the only, structure for implementing the present invention.

(70) While the invention has been described with reference to several preferred embodiments, it is not intended to be limited to these embodiments in any sense. Various changes and modifications may be made by any person of skill in the art without departing from the spirit or scope of the invention. Accordingly, the scope of the invention shall be as defined in the appended claims.