Method and system for determining blood flow in a coronary artery

Abstract

Method for determining a blood flow, Q, in a coronary artery of a patient at a distal position of the coronary artery, the method comprising positioning (1) a guide wire provided with a temperature sensor such that the temperature sensor is positioned at said distal position, positioning (2) an infusion catheter in the coronary artery such that a distal end of the catheter is proximally of the temperature sensor, measuring (3) blood temperature, Tb, using the guide wire temperature sensor, infusing (4) indicator fluid with a known infusion rate, Qi, into the coronary artery using the infusion catheter, measuring (5) a temperature T of a mixture of blood and indicator fluid using the guide wire temperature sensor, predicting (6) a temperature, Ti of the indicator fluid at the distal end of the infusion catheter using a predictive model, and calculating (7) said blood flow as Q=k*(Tb-Ti) / (Tb-T)*Qi. A corresponding system is also provided.

Description

[0001] METHOD AND SYSTEM FOR DETERMINING BLOOD FLOW IN A CORONARY ARTERY

[0002] TECHNICAL FIELD

[0003] The invention relates to measuring blood flow in a coronary artery of a patient and the use of such a blood flow measurement for diagnosing coronary vascular disease.

[0004] BACKGROUND

[0005] Measuring blood flow in a coronary artery is useful for a variety of purposes, for example for use as an input for determining Coronary Flow Resistance (CFR) or Microvascular Resistance Reserve (MRR) for diagnosing coronary vascular disease.

[0006] The continuous thermodilution method for in-vivo measurements of blood flow is known in the art and is disclosed for example in US 7775988B2. In brief, the method comprises infusing an indicator fluid such as saline at room temperature at a constant and known infusion rate in the proximal part of the artery under study, while the temperature of the blood mixed with the infusate is measured in a distal part of the artery. Since the room temperature is lower than the temperature of the blood (body temperature), the temperature of the mixture of blood and indicator fluid will be lower than the body temperature. For a given infusion rate and a given temperature of the indicator fluid when it enters the coronary artery, the difference between the body temperature and the temperature of the mixture in the distal part of the artery will be inversely proportional to the flow.

[0007] In practice, indicator fluid at room temperature is infused at a defined flow rate (Qi) into the proximal artery via a dedicated catheter that ensures instantaneous mixing with blood. The temperature of the blood at the distal part of the coronary artery is recorded continuously using a standard pressure / temperature wire (also referred to as a guide wire) to determine a blood temperature prior to infusion (Tb) and a temperature of the blood / indicator fluid mixture during infusion (T). If the temperature of the indicator fluid at the tip of the catheter (TJ is known, absolute coronary flow (Q) can be calculated using the following equation: wherein k is a constant being the ratio of the specific heat of blood and the specific heat of the indicator fluid,

[0008] As disclosed in US 7775988B2, if the pressure / temperature wire is arranged through the infusion catheter, the temperature of the indicator fluid at the tip of the catheter (Tj) can be measured by means of retracting the guide wire such that the temperature sensor is located inside the infusion catheter followed by measuring the temperature, Tj, of the indicator fluid using the pressure / temperature wire.

[0009] The measurements of coronary flow by the above-described continuous thermodilution method have been shown accurate. Accuracy has been demonstrated by comparing the measurements obtained by continuous coronary thermodilution to myocardial perfusion comparison with PET- derived measurements of Q. One problem with the method is that precision (test-re-test repeatability) in some cases has been lower than expected. Another problem with the method is that T; measurement requires the retraction / pullback of the pressure / temperature sensor in the distal part of the infusion catheter. Pulling back the guide wire in a coronary artery is counterintuitive for most invasive cardiologists. When an additional, hyperemic, measurement must be done, the wire must be re-advanced in the distal part of the artery. These steps add complexity and additional time to the procedure.

[0010] SUMMARY

[0011] An object of the invention is to provide an improved method and an improved system for determining a blood flow in a coronary artery of a patient which overcomes or at least improves on the above-described problems.

[0012] These and other objects are achieved by the present invention by means of a method and a system according to the independent claims.

[0013] According to a first aspect of the invention, there is provided a method for determining a blood flow, Q, in a coronary artery of a patient at a distal position of said coronary artery, the method comprising:

[0014] Positioning a guide wire provided with a temperature sensor such that the temperature sensor is positioned at said distal position in said coronary artery; Positioning an infusion catheter in the coronary artery such that a distal end of the catheter is proximally of the temperature sensor;

[0015] Measuring blood temperature, Tb, using the guide wire temperature sensor;

[0016] Infusing indicator fluid with a known infusion rate, Qi, into the coronary artery using the infusion catheter, said indicator fluid having a temperature being lower than the blood temperature;

[0017] During said infusing, measuring a temperature, T, of a mixture of blood and indicator fluid using the guide wire temperature sensor; Determining a temperature Tj, of the indicator fluid at the distal end (the tip) of the infusion catheter;

[0018] Calculating said blood flow using the following formula: wherein k is a constant, wherein said determining a temperature of the indicator fluid at a distal end of the infusion catheter comprises predicting or calculating said temperature, Tj, of the indicator fluid using a predictive model.

[0019] In other words, the temperature of the indicator fluid at the distal end / tip of the infusion catheter, i.e. the temperature of the indicator fluid when entering from the infusion catheter into the coronary artery, i.e. the temperature of the indicator fluid at the location where it enters the coronary artery, is not measured as in the prior art but is calculated / predicted using a predictive model. As will be described in more detail below with reference to embodiments of the first aspect of the invention, the predictive model can simply be a mean value based on previous patient measurements of Tj, or may be a model such as a regression model by means of which T; is calculated. The indictor fluid is preferably continuously infused such that the temperature, T, of the mixture of blood and indicator fluid can be accurately measured during the infusion.

[0020] It is understood that positioning the infusion catheter in the coronary artery such that a distal end of the catheter is proximally of the temperature sensor refers to that the distal end (tip) of the catheter is positioned upstream of the temperature sensor, i.e. the temperature sensor is arranged more distally than the tip of the catheter. The constant k may be described as the ratio of the specific heat of blood and the specific heat of the indicator fluid. In embodiments where the indicator fluid is saline, k=1.08.

[0021] The invention is based on the insight that although some of the residual variability of the blood flow determination using the thermodilution method is related to variability of T (which can be explained by physiologic variations in Q), a substantial contribution to the variability is due to variations in Tj. Theoretically, Tj would be expected to remain stable for a given infusion rate of room temperature indicator fluid, particularly with repeated measurements taken minutes apart, but the inventors have realized that this is not the case. The invention is further based on the insight that this may be caused due to variations in the exact location of the temperature sensor while retracting / pulling back the guide wire. The invention is further based on the insight that by replacing the measurement of Tj obtained by means of the retraction method by a calculated / predicted value based on one or more other known parameters, the high accuracy of the blood flow determination can be maintained while the precision / repeatability can surprisingly actually be improved. The invention is furthermore based on the insight that such a calculation / prediction of Tj also alleviates the need for the retraction / pullback of the guide wire, which thus greatly simplifies the procedure.

[0022] In embodiments, the predictive model has at least one of the following variables as input: the infusion rate, Qi, of the indicator fluid, the temperature, T, of the mixture of blood and indicator fluid, the blood temperature, Tb, the temperature of the indicator fluid provided to the infusion catheter, a height of the patient, a weight of the patient, BMI of the patient, the temperature of the patient, the length of the catheter within the patient, and room temperature.

[0023] In embodiments, the predictive model is a regression model (such as a linear regression model). The regression model may be based on previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter. The regression model may use the infusion rate, Qi, of the indicator fluid and the temperature, T, of the mixture as regression variables. The indicator fluid as provided to the infusion catheter (from a pump or the like) is normally at room temperature, but if not, the temperature of the indicator fluid may also be a regression variable.

[0024] In embodiments, the predictive model is an average value model based on previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter. In other words, an average value of previous patient measurements of said temperature, Tj, of the indicator fluid is used (with no variables as input).

[0025] In embodiments, the predictive model is an adaptive trained model. The method may comprise training the adaptive trained model using a training system to adapt a predicted temperature of the indicator fluid from said adaptive trained model to previous patient measurements of said temperature of the indicator fluid. The training system may be based on machine-learning models, rule-based systems and / or artificial intelligence.

[0026] In embodiments, where the guide wire is arranged partially in / through the infusion catheter, the previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter may be, or have been, obtained by means of retracting the guide wire such that the temperature sensor is located inside the infusion catheter followed by measuring the temperature, Tj, of the indicator fluid using the temperature sensor. According to a second aspect of the invention, there is provided a method for determining microvascular resistance reserve, MRR, in the myocardium perfused by a normal or a stenotic coronary artery of a human patient, the method comprising the following steps during rest condition of the patient: determining blood flow, Qrest, through the coronary artery using the method according to the first aspect of the invention or embodiments thereof; and measuring blood pressure, Pa, rest, at a position proximal in the coronary artery or proximally of any stenosis if present; further comprising the following steps during maximum hyperemia of the patient: determining blood flow, Qmax, through the coronary artery using the method according to any of the preceding claims; and measuring blood pressure, Pd,hyper, at a position distal in the coronary artery or distally of any stenosis if present, wherein the microvascular resistance reserve is calculated as MRR =Qmax Pa’rest, Qrest ?d, hyper

[0027] In embodiments where the guide wire is furthermore provided with a pressure sensor at its distal end, the blood pressure, Pd,hyper, at a position distal in the coronary artery or distally of any stenosis if present may be measured using said guide wire.

[0028] Pa, rest may be determined by means of any known invasive or non-invasive technique. The general invasive technique to measure Pa, rest, is by means of a guiding catheter arranged in the coronary artery to guide the guide wire or by the guide wire (provided with a pressure sensor as described above). The simplest non-invasive technique comprises measuring the aortic blood pressure using a sphygmomanometer ("cuff measurement”).

[0029] The method for determining MRR is disclosed in detail in applicants co-pending application US2023225622A1 which is hereby incorporated by reference in its entirety.

[0030] According to a third aspect of the invention, there is provided a method for diagnosing microvascular disease, the method comprising determining MRR using the method according to the second aspect of the invention of embodiments thereof, comparing the determined MRR value with a reference value, and, if the determined MRR value is lower than the reference value, determine that the patient has microvascular disease. The reference value may be about 3.0. The extent of microvascular disease may be determined by the determined MRR value in relation to the reference value. According to a fourth aspect of the invention, there is provided a method for determining microvascular resistance, R^, rest, at rest condition of the patient, which method comprises the following steps during rest condition of the patient: determining blood flow, Qrest, through the coronary artery using the method according to the first aspect of the invention or embodiments thereof; and measuring blood pressure, Pa, rest, at a position proximal in the coronary artery or proximally of any stenosis if present, wherein the microvascular resistance is calculated as R^, rest =Pa, rest / Qrest.

[0031] According to a fifth aspect of the invention, there is provided a method for diagnosing microvascular disease, the method comprising: determining microvascular resistance, R^ rest, at rest condition of the patient using the method according to the fourth aspect of the invention; determining microvascular resistance, R^,min, at maximum hyperemia of the patient using the steps of the method according to the fourth aspect of the invention although carried out at maximum hyperemia of the patient; determining MRR by calculating MRR =R^rest;comparing the determined MRR value with a reference value, comparing the determined microvascular resistance, R^ rest, value at rest condition with a reference value, comparing the determined microvascular resistance, R^,min, value at maximum hypermia with a reference value, comparing the determined blood flow, Qrest, value at rest condition with a reference value, comparing the determined blood flow, Qmax, value at maximum hypermia of the patient with a reference value, if the determined MRR value is below said reference value, and the determined microvascular resistance, R^, rest, value is below a reference value, and the determined blood flow, Qrest is above its reference value, determine that the patient has functional microvascular disease; and if the determined MRR value is below said reference value, and the determined microvascular resistance, R^mtm value is above a reference value, and the determined blood flow, Qmax is below its reference value, determine that the patient has structural microvascular disease. According to a sixth aspect of the invention, there is provided a method for determining absolute Coronary Flow Reserve, CFR, which method comprises: determining, at rest condition of the patient, blood flow, Qrest, through the coronary artery using the method according to the first aspect of the invention or embodiments thereof; determining, during maximum hyperemia of the patient, blood flow, Qmax, through the coronary artery using the method according to the first aspect of the invention or embodiments thereof; and calculating the absolute Coronary Flow Reserve as CFR= Qmax / Qrest

[0032] According to a seventh aspect of the invention, there is provided a method for diagnosing coronary artery disease, the method comprising determining CFR using the method according to the fifth aspect of the invention, comparing the determined CFR value with a reference value, and, if the determined CFR value is lower than the reference value, determine that the patient has coronary artery disease. The reference value may be about 2.0. The extent of coronary artery disease may be determined by the determined CFR value in relation to the reference value.

[0033] According to an eighth aspect of the invention, there is provided system for determining a blood flow, Q, in a coronary artery of a patient at a distal position of said coronary artery, the system comprising:

[0034] A guide wire provided with a temperature sensor at a distal end thereof, the guide wire being adapted to be positioned in said coronary artery with its temperature sensor at said distal position;

[0035] An infusion system comprising a catheter arranged with its distal end proximally of the temperature sensor, the infusion system being configured to provide indicator fluid via said catheter, and

[0036] Control means connected to the temperature sensor and to the infusion system, the control means being configured to: i) Obtain, using the temperature sensor, a measurement of blood temperature, Tb; ii) Order the infusion system to infuse indicator fluid at a known infusion rate, Qi, using the infusion catheter; iii) Obtain, using the temperature sensor, a temperature, T, of a mixture of blood and indicator fluid; iv) Predict a temperature, Tj, of the indicator fluid at the distal end of the infusion catheter using a predictive model having at least one of the following variables as input: the infusion rate, Qi, of the indicator fluid, the temperature, T, of the mixture, the blood temperature, Tb, a height of the patient, a weight of the patient, BMI of the patient, the temperature of the patient, the length of the catheter within the patient, and room temperature. v) Calculating said blood flow using the following formula:

[0037] Tb- T;

[0038] Q = k ■ ■ Qi lb- 1wherein k is a constant

[0039] The control means may for example be a computer or an electronic control unit (ECU) provided with, or connected to, an interface connected to said temperature sensor and to said infusion system, where the computer or ECU is provided with software configured to carry out actions i)- v) described above.

[0040] In embodiments of the system, the predictive model has at least one of the following variables as input: the infusion rate, Qi, of the indicator fluid, the temperature, T, of the mixture of blood and indicator fluid, the blood temperature, Tb, a height of the patient, a weight of the patient, BMI of the patient, the temperature of the patient, the length of the catheter within the patient, and room temperature.

[0041] In embodiments of the system, the predictive model is a regression model (such as a linear regression model). The regression model may be based on previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter. The regression model may use the infusion rate, Qi, of the indicator fluid and / or the temperature, T, of the mixture as regression variables.

[0042] In embodiments of the system, the predictive model is an average value model based on previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter.

[0043] In embodiments of the system, the predictive model is an adaptive trained model. The system may further comprise a training system configured to train the adaptive trained model to adapt a predicted temperature of the indicator fluid from said adaptive trained model to previous patient measurements of said temperature of the indicator fluid, said training system being based on machine-learning models, rule-based systems and / or artificial intelligence. In embodiments of the system, the guide wire is furthermore provided with a pressure sensor at its distal end, wherein the control means is furthermore connected to the pressure sensor.

[0044] In embodiments of the system where the guide wire comprises a pressure sensor, the control means may be configured to: carry out actions i) -v) during rest condition of the patient to obtain a blood flow, Qrest, through the coronary artery during rest condition, obtain, from said pressure sensor of the guide wire or from an additional pressure sensor connected to the control means, during rest condition of the patient, a blood pressure, Pa, rest, at a position proximal in the coronary artery or proximally of any stenosis if present; carry out actions i) -v) during maximum hypermia of the patient to obtain a blood flow Qmax through the coronary artery during max hypermia, obtain, from said pressure sensor of the guide wire during maximum hyperemia of the patient a blood pressure, Pd,hyper, at a position distal in the coronary artery or distally of any stenosis if present, calculate microvascular resistance reserve as MRR =pa.rest ,

[0045] Qrest ?d, hyper

[0046] In embodiments of the system where the guide wire comprises a pressure sensor, the control means may be configured to: carry out actions i) -v) during rest condition of the patient to obtain a blood flow, Qrest, through the coronary artery during rest condition, carry out actions i) -v) during maximum hypermia of the patient to obtain a blood flow Qmax through the coronary artery during max hypermia, and calculate Coronary Flow Reserve as CFR= Qmax / Qr st.

[0047] The features of the embodiments described above are combinable in any practically realizable way to form embodiments having combinations of these features. Further, all features and advantages of embodiments described above with reference to the first aspect of the invention may be applied in corresponding embodiments of the second, third, fourth, fifth, sixth, seventh and eighth aspects of the invention and vice versa. Further, all features and advantages of the methods according to the second, third, fourth, fifth, sixth or seventh aspect of the invention or embodiments thereof may be applied in / form embodiments of the system according to the eighth aspect of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Above discussed and other aspects of the present invention will now be described in more detail using the appended drawings, which show presently preferred embodiments of the invention, wherein: fig. 1 is a flowchart illustrating an embodiment of the method according to the first aspect of the invention, fig. 2 illustrates schematically the coronary circulation and also illustrates schematically an embodiment of a system according to the eighth aspect of the invention, fig. 3a-b shows comparisons between coronary artery blood flow (Q) determined using the prior art / standard method (comprising retraction of the guide wire to measure indicator fluid temperature at the distal end of the infusion catheter) and Q determined using an embodiment of the method according to the first aspect of the invention; fig. 4a-b shows the precision (test-re-retest repeatability) of a first measurement of Q (QI) and its repeat measurement (Q2) determined using the prior art / standard method; fig. 4c-d shows the precision (test-re-retest repeatability) of a first measurement of Q (QI) and its repeat measurement (Q2) determined using an embodiment of the method according to the first aspect of the invention.

[0049] DETAILED DESCRIPTION

[0050] Fig. 1 is a flowchart illustrating an embodiment of the method according to the first aspect of the invention. The method comprises positioning 1 a guide wire provided with a temperature sensor such that the temperature sensor is positioned at said distal position in said coronary artery, positioning 2 an infusion catheter in the coronary artery such that a distal end of the catheter is proximally of the temperature sensor, measuring 3 blood temperature, Tb, using the guide wire temperature sensor, infusing 4 indicator fluid (saline) with a known infusion rate, Qi, into the coronary artery using the infusion catheter, said indicator fluid having a temperature being lower than the blood temperature. During said infusing, a temperature, T, of a mixture of blood and indicator fluid is measured 5 using the guide wire temperature sensor, whereafter a temperature Tj, of the indicator fluid at the distal end of the infusion catheter is predicted 6 using a predictive model. Finally, the blood flow is calculated using the following formula: (Equation 1) wherein k=1.08,

[0051] The predictive model is a linear regression model is based on previous patient measurements of the temperature, Tj, of the indicator fluid at the distal end of the infusion catheter and uses the infusion rate, Qi, of the indicator fluid and the temperature, T, of the mixture as regression variables. The predictive model will be described below (see "Derivation of the predictive model”).

[0052] Fig. 2 illustrates schematically the coronary circulation and also illustrates schematically an embodiment of a system according to the seventh aspect of the invention. In Fig. 2, the letter A indicates the aorta, the letter B indicates the epicardial artery, and the letter C indicates the microcirculation. In fig. 2, a stenosis in the epicardial artery is schematically shown in crosssection as two black dots. Pais the pressure proximally of the stenosis in the epicardial artery and Pd is the pressure distally of the stenosis. It is understood that the method and system according to the invention can be used to determine the blood flow Q at the distal position regardless of the presence of a stenosis or not

[0053] The system comprises a sensor guide wire 11 provided with a pressure and temperature sensor 12 near a distal end thereof, the sensor guide wire being positioned in the coronary artery with its temperature sensor at the distal position (downstream of the stenosis, if present). The system further comprises an infusion system comprising an infusion catheter 13 arranged with its distal end 14 proximally of the temperature / pressure sensor 12, the infusion system being configured to provide indicator fluid via said catheter. The guide wire 11 and the infusion catheter are guided by the guide catheter 15. The infusion catheter 13 surrounds the guide wire 11 along part of the length of the guide wire (see fig. 2). The opposite end of the infusion catheter 13 is connected to a source 16 of indicator fluid (incl. a pump or other means to feed indicator fluid to the infusion catheter) which is also part of the infusion system. The guide catheter 15 and the infusion catheter 13 are shown in cross-section such the extension of the infusion catheter and the guide wire are visible.

[0054] Control means in the form of a processing unit 17 such as a computer provided with, an interface 18 connected to the temperature / pressure sensor 12 and to the infusion system 16 such that the processing unit can obtain temperature and pressure data and control a flow of indicator fluid.

[0055] The processing unit is configured to: i) obtain, using the temperature sensor 12, a measurement of blood temperature, Tb; ii) Order the source of indicator fluid 16 of the infusion system to infuse indicator fluid at a known infusion rate, Qi, using the infusion catheter 13; iii) Obtain, while indicator fluid is infused, a temperature, T, of a mixture of blood and indicator fluid using the temperature sensor 12; iv) Predict a temperature, Tj, of the indicator fluid at the distal end of the infusion catheter using a predictive model; v) Calculating said blood flow using the following formula: wherein k =1.08 (the ratio of the specific heat of blood and the specific heat of the indicator fluid being saline).

[0056] The predictive model is a linear regression model is based on previous patient measurements of the temperature, Tj, of the indicator fluid at the distal end of the infusion catheter and uses the infusion rate, Qi, of the indicator fluid and the temperature, T, of the mixture as regression variables. The predictive model will be described below (see "Derivation of the predictive model”).

[0057] The system illustrated in fig. 2 and described above can be used to carry out one or more of the methods according to the first, second, third, fourth, fifth, sixth or seventh aspects of the invention or embodiments thereof. In particular, the system can be used to determine MRR and / or CFR by means of the processing unit carrying out the steps defined by the second and / or sixth aspects of the invention or embodiments thereof. The system can optionally also be used to diagnose vascular disease by means of the processing unit carrying out the steps defined by the third and / or seventh aspects of the invention or embodiments thereof.

[0058] Derivation of the predictive model

[0059] A total of 371 patients with angina and nonobstructive coronary arteries (ANOCA), defined as the absence of an angiographically significant epicardial stenosis (diameter stenosis (DS) >50%) by visual estimate, were included in a derivation cohort All patients underwent continuous thermodilution measurements in a single coronary artery during both resting and hyperaemic conditions, and thus 742 measurements were available in total. Multivariate linear regression testing a range of covariates found that only T and Q, were significant predictors of T, (both p<0.0001), with all other covariates having p values > 0.500. The final bivariate model with just T and Qi as covariates was strongly predictive of T, (R2=0.811). Standardisation of the model coefficients using the z-score demonstrated that Q, (standardised coefficient 1.39) was a significantly stronger contributor to the prediction of T, than T (standardised coefficient 0.28). The final equation for T, derived from the multivariate regression model was:

[0060] Tj = 0.98T — 0.28Qj + 0.90 (Equation 2) For simplicity and to improve readability of the results, values of Q calculated with measured T, will be referred to as standard 0, and values of Q calculated with predicted T, will be referred to as simplified 0.

[0061] Validation of the predictive model

[0062] A validation cohort consisted of 120 patients that underwent repeat absolute coronary flow measurements during both resting (Qresu and Qrest2) and hyperaemic (Qhyperi and Qhyperz) conditions, corresponding to 480 separate measurements. Using the 480 thermodilution measurements of the validation cohort, Q was calculated with Equation 1 using measured T, (standard Q) and with predicted T, (simplified Q) calculated using Equation 2. Simplified Q exhibited a strong correlation with standard Q (r=0.94 [CI 0.93-0.95], p<0.001) as well as excellent absolute agreement (ICC 0.94 [0.92-0.95], p<0.001) (see fig. 3a-b). Passing-Bablok regression analysis found no significant systematic (intercept A: 3.71 [CI -0.01-7.01]) or proportional (slope B: 0.96 [CI 0.93-1.00]) bias.

[0063] Considering the strong correlation between simplified Q and standard Q it can be concluded that the agreement between the simplified Q calculation (based on predicted T,) and the standard Q calculation is high.

[0064] In the validation cohort, when Q was calculated using measured T,, the first measurement of Q (Qi) and its repeat measurement (Q2) demonstrated a strong correlation (r=0.94 [CI 0.92-0.95], p<0.001) with excellent absolute agreement (ICC=0.94 [CI 0.92-0.95], p<0.001) (see fig. 4a).

[0065] When Q was recalculated with predicted T,, the correlation between Qi and Q2 improved (r=0.95 [CI 0.94-0.96], p<0.001) (see fig. 4c) but with no statistically significant difference between its correlation coefficient and that seen with Q calculated with measured T, (p = 0.115). However, the absolute agreement between Qiand Q2 remained high (ICC=0.95 [CI 0.94-0.96], p<0.001), with a significantly lower SD when compared with the standard calculation of Q (predicted T,: SD 24.05 vs measured T,: SD 29.58, F-testp <0.001), see fig. 4b and 4d.

[0066] Consequently, it can be concluded that the simplified calculation of Q results in improved precision / repeatability.

[0067] CFR calculated using the measured T, (CFR1 and CFR2) demonstrated a moderate correlation (r=0.64 [CI 0.52-0.74], p<0.001) and absolute agreement (ICC=0.64 [CI 0.52-0.74], p<0.001) (see Table 1 below). However, when calculated using predicted T,, the correlation between CFRi and CFR2 was significantly improved (r=0.77 [CI 0.69-0.83], p<0.001) (p value = 0.048) ((see Table 1 below). Furthermore, absolute agreement was improved (ICC=0.77 [CI 0.69-0.83], p<0.001) with a significantly reduced standard deviation (predicted T,: SD 0.48 vs measured T,: SD 0.65, F-test p<0.001). The repeatability coefficient also decreased (predicted T,: 0.94 vs measured T,: 1.27) (see Table 1 below).

[0068] Similarly, the standard deviation of differences between Ri and R2, and between MRRi and MRR2 were significantly reduced with the use of predicted T, (see Table 1 below). Furthermore, the use of predicted T, resulted in statistically significant improvement in the correlation between Ri and R2 (see Table 1 below).

[0069] Table 1. Summary of metrics of correlation and absolute agreement between repeat measurements in the validation cohort ICC: intraclass correlation coefficient, SD: standard deviation. RC: repeatability coefficient * indicates a statistically significant difference between simplified (predicted T,) and standard (measured T,) calculations. A p value <0.05 was considered significant

[0070] The description above and the appended drawings are to be considered as non-limiting examples of the invention. The person skilled in the art realizes that several changes and modifications may be made within the scope of the invention. For example, the predictive model does not necessarily need to be a linear function / regression model but can be any other type of model such as a mean value model or an adaptive model. Furthermore, additional variables may be used as inputs to the predictive model such as blood temperature, the temperature of the patient or room temperature.

Claims

CLAIMS1. Method for determining a blood flow, Q, in a coronary artery of a patient at a distal position of said coronary artery the method comprising:Positioning (1) a guide wire provided with a temperature sensor such that the temperature sensor is positioned at said distal position in said coronary artery;Positioning (2) an infusion catheter in the coronary artery such that a distal end of the catheter is proximally of the temperature sensor;Measuring (3) blood temperature, Tb, using the guide wire temperature sensor;Infusing (4) indicator fluid with a known infusion rate, Qi, into the coronary artery using the infusion catheter, said indicator fluid having a temperature being lower than the blood temperature;During said infusing, measuring (5) a temperature, T, of a mixture of blood and indicator fluid using the guide wire temperature sensor;Determining (6) a temperature Tj, of the indicator fluid at the distal end of the infusion catheter;Calculating (7) said blood flow using the following formula:wherein k is a constant being the ratio of the specific heat of blood and the specific heat of the indicator fluid, wherein said determining (6) a temperature of the indicator fluid at the distal end of the infusion catheter comprises predicting said temperature, Tj, of the indicator fluid using a predictive model.

2. Method according to claim 1, wherein said predictive model has at least one of the following variables as input: the infusion rate, Qi, of the indicator fluid, the temperature, T, of the mixture of blood and indicator fluid, the blood temperature, Tb, a height of the patient, a weight of the patient, BMI of the patient, the temperature of the patient, the length of the catheter within the patient, the temperature of the indicator fluid as provided to the infusion catheter, and room temperature.

3. Method according to claim 2, wherein said predictive model is a regression model based on previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter using the infusion rate, Qi, of the indicator fluid and the temperature, T, of the mixture as regression variables.

4. Method according to claim 2, wherein said predictive model is an adaptive trained model.

5. Method according to claim 4, further comprising training said adaptive trained model using a training system to adapt a predicted temperature of the indicator fluid at the distal end of the infusion catheter from said adaptive trained model to previous patient measurements of said temperature of the indicator fluid at the distal end of the infusion catheter, said training system being based on machine-learning models, rule-based systems and / or artificial intelligence.

6. Method according to claim 1, wherein said predictive model is an average value model based on previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter.

7. Method according to claim 3, 5 or 6, wherein said guide wire is arranged through said infusion catheter, and wherein said previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter have been obtained by means of retracting the guide wire such that the temperature sensor is located inside the infusion catheter followed by measuring the temperature, Tj, of the indicator fluid using the temperature sensor.

8. A method for determining microvascular resistance reserve, MRR, in the myocardium perfused by a normal or a stenotic coronary artery of a human patient, said method comprising the following steps during rest condition of the patient: determining blood flow, Qrest, through the coronary artery using the method according to any of the preceding claims; and measuring blood pressure, Pa, rest, at a position proximal in the coronary artery or proximally of any stenosis if present; further comprising the following steps during maximum hyperemia of the patient: determining blood flow, Qmax, through the coronary artery using the method according to any of the preceding claims; and measuring blood pressure, Pd,hyper, at a position distal in the coronary artery or distally of any stenosis if present, wherein the microvascular resistance reserve is calculated as MRR =Qmax Pa’rest,Qrest ?d, hyper9. A method for diagnosing microvascular disease, the method comprising determining MRR using the method according to claim 8, the method for diagnosing comprising comparingthe determined MRR value with a predetermined reference value, and, if the determined MRR value is lower than the reference value, determine that the patient has microvascular disease.

10. A method for determining microvascular resistance, Rmtcro, rest, at rest condition of the patient, which method comprises the following steps during rest condition of the patient: determining blood flow, Qrest, through the coronary artery using the method according to any of claims 1-7; and measuring blood pressure, Pa, rest, at a position proximal in the coronary artery or proximally of any stenosis if present; wherein the microvascular resistance is calculated as R^, rest =Pa, rest / Qrest.

11. A method for determining Coronary Flow Reserve, CFR, which method comprises: determining, at rest condition of the patient, blood flow, Qrest, through the coronary artery using the method according to any claims 1-7; determining, during maximum hyperemia of the patient, blood flow, Qmax, through the coronary artery using the method according to any claims 1-7; and calculating the Coronary Flow Reserve as CFR= Qmax / Qrest12. A method for diagnosing vascular disease, the method comprising determining CFR using the method according to claim 11, the method for diagnosing comprising comparing the determined CFR value with a predetermined reference value, and, if the determined CFR value is lower than the reference value, determine that the patient has vascular disease.

13. System for determining a blood flow, Q, in a coronary artery of a patient at a distal position of said coronary artery, the system comprising:A guide wire (11) provided with a temperature sensor (12) at a distal end thereof, the guide wire being adapted to be positioned in said coronary artery with its temperature sensor at said distal position;An infusion system (13, 14, 16) comprising a catheter (13) arranged with its distal end (14) proximally of the temperature sensor (12), the infusion system being configured to provide indicator fluid via said catheter, andControl means (17) connected to the temperature sensor (12) and to the infusion system (16), the control means being configured to: i) Obtain, using the temperature sensor (12), a measurement of blood temperature, Tb;ii) Order the infusion system (16) to infuse indicator fluid at a known infusion rate, Qi, using the infusion catheter (13); iii) While indicator fluid is infused, obtain, using the temperature sensor (12), a temperature, T, of a mixture of blood and indicator fluid; iv) Predict a temperature, Tj, of the indicator fluid at the distal end of the infusion catheter using a predictive model having at least one of the following variables as input: the infusion rate, Qi, of the indicator fluid, the temperature, T, of the mixture, the blood temperature, Tb, a height of the patient, a weight of the patient, BMI of the patient, the temperature of the patient, the length of the catheter within the patient, and room temperature; v) Calculating said blood flow using the following formula:wherein k is a constant being the ratio of the specific heat of blood and the specific heat of the indicator fluid.

14. System according to claim 13, wherein said predictive model has at least one of the following variables as input: the infusion rate, Qi, of the indicator fluid, the temperature, T, of the mixture of blood and indicator fluid, the blood temperature, Tb, a height of the patient, a weight of the patient, BMI of the patient, the temperature of the patient, the length of the catheter within the patient, the temperature of the indicator fluid as provided to the infusion catheter, and room temperature.

15. System according to claim 14, wherein said predictive model is a regression model based on previous patient measurements of said temperature, Tj, of the indicator fluid at the distal end of the infusion catheter using the infusion rate, Qi, of the indicator fluid and the temperature, T, of the mixture as regression variables.

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