Table 2 Characteristics of noninvasive imaging techniques and scoring systems

TE

uses shear waves induces by an external push to measure liver stiffness. Simultaneous measurement of steatosis due to the CAP technology which is based on the ultrasound beam attenuation.

Assessment of liver stiffness and liver fat

Fast and easy to perform

Non-invasive, rapid, reproducible, and highly accurate

Limited sensitivity in mild liver fibrosis due to obesity and active phase of inflammation

Increased liver stiffness and higher CAP values are associated with a metabolic dysfunction which is a risk factor for CVD.

ARFI + FAT QUANTIFICATION

ultrasound technology measures shear wave velocity generated by tissue displacement to determine the stiffness of the liver and the ultrasound beam attenuation and or the backscattering to quantify the steatosis

Evaluation of liver stiffness and fatty liver

Mounted on conventional ultrasound equipment

Requires high operator skills

Increased liver stiffness and higher value of ultrasound beam attenuation and or backscattering are associated with a risk of CVD. At the same time the application of this technology in the carotid artery evaluation can predict ASCVD risk

MRE

Uses mechanical waves to quantitatively measure tissue elasticity

Evaluation of liver fibrosis and cirrhosis

High-resolution imaging with high accuracy

Higher cost and high equipment requirements

Early identification and surveillance of CV risk through the quantification of myocardial and vascular stiffness

MRS

Utilizes chemical shift imaging to distinguish hydrogen atoms in different molecular environments

Quantification of liver fat content

Accurate quantification of liver fat

High cost, not suitable for routine clinical use

identifies metabolic derangements and delineate lipid-rich atherosclerotic plaques in the arterial vasculature

APRI

assesses liver fibrosis risk based on the ratio of serum AST and platelets

Screening for liver fibrosis

Noninvasive, easy to perform

Accuracy influenced by liver inflammation and platelet disease

Fluctuations in AST and platelet levels may lead to increased inflammation and thrombotic risk

FIB-4

based on age, ALT, platelets and AST

Assessment of liver fibrosis risk

Simple, based on routine blood tests

May not be accurate enough in early stages of disease

Score of ≥ 2.67 was a significant predictor of MACEs

A valuable predictor for AVS

NFS

combines multiple serum markers and demographic characteristics

Assessment of liver fibrosis risk

Noninvasive and multifactorial

Further validation is needed to improve accuracy

Higher NFS values are associated with an increased risk of MACEs

Forns index

utilizes serum cholesterol levels, platelet count, age, and GGT levels to estimate fibrosis stage

identifying patients with significant or advanced liver fibrosis

accurately exclude advanced fibrosis, demonstrated by high NPVs

may be less reliable in the presence of certain liver conditions that affect cholesterol metabolism

significant correlations with various CV risk scores

HFS

incorporates age, sex, AST levels, albumin, HOMA-IR, and platelet count in its algorithm, adjusting for confounding variables like diabetes status

Identifying individuals presenting with substantial or progressive hepatic fibrosis

Accurately discerning the absence of advanced fibrosis, as evidenced by elevated NPVs

requires validation in diverse populations and may be influenced by factors such as age and diabetes

Exhibiting substantial associations with a spectrum of CV risk scores

Pericoronary FAI

Measures attenuation of pericoronary fat by CT scan

Assessment of cardiovascular disease risk

Noninvasive, quantifiable

Requires CT scan, radiation exposure

Greater FAI have worse cardiovascular outcomes

CCTA

Uses X-rays and computer processing to create 3D images of the coronary arteries

Assessment of coronary artery disease

High-resolution imaging that can detect early lesions

Radiation exposure, requires the use of contrast agents

Identify ASCVD