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 a mortality risk or risk of a patient suffering a cardiovascular event, said method comprising:
(a) determining:
(i) epicardial adipose tissue volume (EpAT-vol);
and at least one of
(ii) fat attenuation index of epicardial adipose tissue (FAI EpAT ); and
(iii) fat attenuation index of perivascular adipose tissue (FAI PVAT );
wherein FAI PVAT is determined using data gathered from a computer tomography (CT) scan along a length of a blood vessel; and
(b) comparing each of the values determined in (a) to a pre-determined cut-off value or using the absolute value of each variable determined in (a) in order to generate an output value that indicates the patient's mortality risk or risk of suffering a cardiovascular event.
2. The method according to claim 1 , wherein step (a) further comprises using the data gathered from a computer tomography scan along a length of a blood vessel to determine (iv) calcium index (Calcium-i) and/or (v) fibrous plaque index (FPi); wherein the value of (iv) and/or (v) is included in step (b) of claim 1 .
3. The method according to claim 1 , wherein step (a) further comprises using the data gathered from a computer tomography scan along a length of a blood vessel to determine (vi) perivascular water index (PVWi) and/or (vii) volumetric perivascular characterisation index (VPCI); wherein the value of (vi) and/or (vii) is included in step (b) of claim 1 .
4. The method according to claim 1 , further comprising determining one or more of (viii) age and (ix) gender of the patient and wherein the value of (viii) and/or (ix) is included in step (b) of claim 1 .
5. The method according to claim 1 , further comprising determining one or more of:
(x) coronary calcium;
(xi) hypertension;
(xii) hyperlipidemia/hypercholesterolemia;
(xiii) diabetes mellitus;
(xiv) presence of coronary artery disease;
(xv) smoking; and
(xvi) family history of heart disease;
and wherein the value of one or more of (x)-(xvi) is included in step (b) of claim 1 .
6. The method according to claim 1 , further comprising determining one or more of:
(iv) calcium index (Calcium-i);
(v) fibrous plaque index (FPi);
(vi) perivascular water index (PVWi);
(vii) volumetric perivascular characterisation index (VPCI);
(viii) age of the patient;
(ix) gender of the patient;
(x) coronary calcium;
(xi) hypertension;
(xii) hyperlipidemia/hypercholesterolemia;
(xiii) diabetes mellitus;
(xiv) presence of coronary artery disease;
(xv) smoking; and
(xvi) family history of heart disease;
and wherein the value of one or more of (iv)-(xvi) is included in step (b) of claim 1 .
7. The method according to claim 1 , wherein coefficients for each of (i) to (iii) are derived from Cox hazard or logistic regression models.
8. The method according to claim 1 , wherein the cut-off points for each of (i) to (v) are derived from receiver operating characteristic (ROC) curves.
9. The method according to claim 1 , wherein the output value is a continuous single valued function or a value that falls within one of three discrete brackets corresponding to low, medium and high risk of a cardiac event, cardiac death or all-cause mortality.
10. The method according to claim 1 , wherein the method is used to stratify patients according to their risk of all-cause or cardiac mortality.
11. 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.