Abstract

Objective: Non-invasive computation of the index of microcirculatory resistance from coronary computed tomography angiography (CTA), referred to as IMR $_\text{CT}$ , is a promising approach for quantitative assessment of coronary microvascular dysfunction (CMD). However, the computation of IMR $_\text{CT}$ remains an important unresolved problem due to its high requirement for the accuracy of coronary blood flow. Existing CTA-based methods for estimating coronary blood flow rely on physiological assumption models to indirectly identify, which leads to inadequate personalization of total and vessel-specific flow. Methods: To overcome this challenge, we propose a vascular deformation-based flow estimation (VDFE) model to directly estimate coronary blood flow for reliable IMR $_\text{CT}$ computation. Specifically, we extract the vascular deformation of each vascular segment from multi-phase CTA. The concept of inverse problem solving is applied to implicitly derive coronary blood flow based on the physical constraint relationship between blood flow and vascular deformation. The vascular deformation constraints imposed on each segment within the vascular structure ensure sufficient individualization of coronary blood flow. Results: Experimental studies on 106 vessels collected from 89 subjects demonstrate the validity of our VDFE, achieving an IMR $_\text{CT}$ accuracy of 82.08 $\%$ . The coronary blood flow estimated by VDFE has better reliability than the other four existing methods. Conclusion: Our proposed VDFE is an effective approach to non-invasively compute IMR $_\text{CT}$ with excellent diagnostic performance. Significance: The VDFE has the potential to serve as a safe, effective, and cost-effective clinical tool for guiding CMD clinical treatment and assessing prognosis.