Quantitative Detection of Pericardial Adhesions Using Four-Dimensional Computed Tomography: A Novel Motion-Based...

Area of Science:

• Cardiovascular Imaging
• Medical Physics
• Computational Anatomy

Background:

• Pericardial adhesions can complicate cardiac procedures, increasing risks.
• Current detection methods are limited, especially in patients without known risk factors.

Purpose of the Study:

• To develop and validate a novel, quantitative, noninvasive method for detecting pericardial adhesions using 4D CT.
• To assess the clinical utility of this framework in surgical planning.

Main Methods:

• Utilized preoperative 4D CT datasets from 20 cardiac surgery patients.
• Integrated expert-guided pericardial segmentation, symmetric diffeomorphic registration, and motion disparity analysis.
• Quantified tissue motion differences by analyzing displacement fields between pericardium and epicardial adipose tissue (EAT), focusing on the LAD region.

Main Results:

• Significant differences (p < 0.01) were found between adhesion and non-adhesion groups using peak ratio (PR) and distribution width index (DWI).
• Adhesion cases showed high PR (>100) and low DWI (<0.3).
• Non-adhesion cases exhibited moderate PR (<50) and higher DWI (>0.4).

Conclusions:

• Validated a novel quantitative framework for assessing pericardial adhesions with 4D CT.
• Provides an objective and computationally efficient tool for preoperative assessment.
• Demonstrates potential clinical utility for surgical planning and risk assessment.