Non-Invasive Assessment of Coronary Microvascular Dysfunction Using Vascular Deformation-Based Flow Estimation

Area of Science:

• Cardiovascular Imaging
• Biomedical Engineering
• Computational Physiology

Background:

• Non-invasive computation of the index of microcirculatory resistance (IMR) from coronary computed tomography angiography (CTA) is crucial for assessing coronary microvascular dysfunction (CMD).
• Existing CTA-based methods for estimating coronary blood flow lack personalization due to reliance on physiological assumption models.
• Inaccurate coronary blood flow estimation hinders reliable IMR computation.

Purpose of the Study:

• To develop a novel vascular deformation-based flow estimation (VDFE) model for direct and personalized coronary blood flow estimation.
• To enable accurate non-invasive computation of IMR for improved CMD assessment.
• To overcome the limitations of existing methods in IMR calculation.

Main Methods:

• Vascular deformation was extracted from multi-phase CTA data for each vascular segment.
• An inverse problem-solving approach was applied to derive coronary blood flow based on blood flow-vascular deformation relationships.
• Vascular deformation constraints ensured individualized coronary blood flow estimation.

Main Results:

• The VDFE model demonstrated validity in experimental studies involving 106 vessels from 89 subjects.
• The computed IMR achieved an accuracy of 82.08%.
• VDFE-estimated coronary blood flow showed superior reliability compared to four existing methods.

Conclusions:

• The proposed VDFE model is an effective approach for non-invasive IMR computation with excellent diagnostic performance.
• VDFE offers a promising solution for accurate assessment of coronary microvascular dysfunction.
• This method has the potential to become a valuable clinical tool for CMD management and prognosis.