Method for predicting cardiovascular risk
The present invention describes a new functional biomarker of vascular inflammation and its use in predicting all-cause or cardiac mortality. The invention also provides a method for stratifying patients according to their risk of all-cause or cardiac mortality using data gathered from a computer tomography scans of a blood vessel to determine a specific combination of structural and functional biomarkers of vascular inflammation and disease.
1 . A method of predicting cardiac mortality risk or risk of a patient suffering a cardiovascular event, wherein the method is performed by a processing system, said method comprising:
receiving image data gathered from a computer tomography (CT) scan along a length of a blood vessel;
determining from the image data (i) fat attenuation index (FAI) of epicardial adipose tissue (FAI EpAT ) to provide an average attenuation of voxels corresponding to epicardial adipose tissue (EpAT);
determining from the image data at least one of
(ii) calcium index (Calcium-i) to provide a total volume of voxels corresponding to local calcium within a wall of a vascular segment, divided by a total volume of the respective vascular segment; and/or
(iii) fibrous plaque index (FPi) to provide a total volume of voxels corresponding to fibrous tissue within a wall of a vascular segment, divided by a total volume of the respective vascular segment; and
generating an output value based at least in part on the value of (i) and (ii) and/or (iii) compared to a pre-determined cut-off value or based at least in part on the absolute value of (i) and (ii) and/or (iii), wherein the output value indicates the patient's cardiac mortality risk or risk of suffering a cardiovascular event.
2 . The method according to claim 1 , wherein the output value is used to quantify vascular inflammation.
3 . The method according to claim 1 , wherein the output value is used to guide pharmacological treatment decisions and/or monitor responses to medical treatments.
4 . The method according to claim 1 , further comprising determining from the image data (iv) volumetric perivascular characterization index (VPCI), and wherein generating the output value comprises generating the output value based at least in part on the value of (iv).
5 . The method according to claim 1 , further comprising determining (v) epicardial adipose tissue volume (EpAT-vol), wherein generating the output value comprises generating the output value based at least in part on the value of (v).
6 . The method according to claim 1 , further comprising determining (vi) fat attenuation index of the perivascular adipose tissue (FAI PVAT ), wherein generating the output value comprises generating the output value based at least in part on the value of (vi).
7 . The method according to claim 1 , further comprising determining (vii) perivascular water index (PVWi), wherein generating the output value comprises generating the output value based at least in part on the value of (vii).
8 . The method according to claim 1 , further comprising determining one or more of (viii) the age and (ix) gender of the patient and wherein generating the output value comprises generating the output value based at least in part on the value of (viii) and/or (ix).
9 . The method according to claim 1 , further comprising determining one or more of:
(xi) the presence of chronically expanding plaque;
(xii) the presence of soft atherosclerotic plaque;
(xiii) the presence of plaque with a large necrotic core; and
(xiv) the total plaque volume;
and wherein generating the output value comprises generating the output value based at least in part on the value of one or more of (xi)-(xiv).
10 . The method according to claim 1 , further comprising determining one or more of:
(XV) coronary calcium volume,
(xvi) hypertension,
(xvii) hyperlipidemia/hypercholesterolemia;
(xviii) diabetes mellitus;
(xix) presence of coronary artery disease;
(xx) smoking; and
(xxi) family history of heart disease;
and wherein generating the output value comprises generating the output value based at least in part on the value of one or more of (xv)-(xxi).
11 . The method according to claim 1 , wherein coefficients for each of (i) to (iii) are derived from Cox hazard or logistic regression models.
12 . The method according to claim 1 , wherein the cut-off points for each of (i) to (iii) are derived from receiver operating characteristic (ROC) curves.
13 . The method according to claim 1 , wherein the output value is a continuous single value function or a value that falls within one of three discrete brackets corresponding to low, medium and high risk of a cardiovascular event, cardiac death or all-cause mortality.
14 . The method according to claim 1 , wherein the method is used to stratify patients according to their risk of cardiac mortality or risk of suffering a cardiovascular event.
15 . The method according to claim 1 , wherein the patient has been diagnosed with vascular inflammation or a condition known to be associated with vascular inflammation.