Quantification of Epicardial Adipose Tissue on CT

Purpose

Automatically quantify and segment a patient’s epicardial adipose tissue on CT.

Tag(s)

 

Panel

Cardiac

Define-AI ID

19040036

Originator

Caterina Monti
Lead
Caterina Monti

Panel Chair

Carlo De Cecco

Panel Reviewers

Cardiac Panel

License

Creative Commons 4.0 
Status Public Comment
RadElement Set RDES85 
                         

Clinical Implementation


Value Proposition


Recently, research has reinforced the idea that epicardial adipose tissue (EAT) volume and density are associated with coronary artery disease (CAD), atrial fibrillation, and other adverse cardiovascular events. However segmenting the EAT on CT and measuring its volume and attenuation is a tedious and time-consuming task especially given the average slice thickness. This would be an excellent opportunity for an AI algorithm to assist clinicians and track EAT measurements that are otherwise left unreported. These data could help clinicians more appropriately identify and follow up patients at higher risk for adverse cardiovascular events from increased EAT. EAT could be assessed on noncontrast scans obtained for calcium scoring, thus effectively providing an additional biomarker for more accurate risk assessment.

Narrative(s)


Patient with intermediate cardiovascular risk according to the Framingham risk score undergoes CT comprising noncontrast images for evaluation of calcium scoring. Algorithm analyzes images and segments the EAT. With these measurements, potentially combined with calcium scoring, the clinician is able to establish a tailored follow-up scheme, based on individual cardiovascular risk.

Workflow Description


The image is obtained from modality and sent to PACS and the AI engine. The image is analyzed by the engine. The system then detects and estimates EAT volume and mean attenuation values. An alert message is sent to PACS from the engine with the information, identification, and graphic highlighting the EAT.

Considerations for Dataset Development



EAT Location



surrounding the heart, more prominent at base and the apex, in the atrioventricular sulci, on the entire surface of the right ventricle, and around the great coronary vessels with their origins

EAT size

varied

Age

[18,100]

Sex at birth

Male, female

BMI

Varied

Ethnicity

varied

Arterial hypertension

Absent, present

Active smoking

Yes, No

Diabetes

Absent, present

Hypercholesterolemia

Absent, present

Cardiac height

varied

Arrhythmias

Absent, present

Framingham risk score

Any

Slice thickness

possibly lower than 1 mm

Technical Specifications


Inputs

DICOM Study 

Procedure

CT (Calcium Scoring scans)

Views

Axial, coronal

Data Type

DICOM

Modality

CT

Body Region

Chest

Anatomic Focus

Heart


Primary Outputs


EAT Volume

RadElement ID

RDE483

Definition

Volume of the epicardial adipose tissue

Data Type

Numeric

Value Set

N/A

Units

cm3


EAT Average Attenuation

RadElement ID

RDE484

Definition

Average attenuation of the epicardial adipose tissue

Data Type

Numeric

Value Set

N/A

Units

HU

EAT Segmentation

RadElement ID

RDE485

Definition

Segmentation of the epicardial adipose tissue

Data Type

Coordinate

Value Set

N/A

Units

N/A

Future Development Ideas


  • The algorithm might compare patients’ EAT data over time, and provide an estimate of the variations in EAT.
  • An algorithm for magnetic resonance segmentation might also be implemented, so that values can be compared between different techniques when patients undergo different examinations according to clinical indications.
  • Additional measures such as EAT thickness estimated in a position equivalent to that commonly used for ultrasound could be implemented.