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Interventional Diagnostic Procedure: A Practical Guide for the Assessment of Coronary Vascular Function
Published on: March 15, 2022
Defining Metrics and the Framework for the Invasive Assessment of Patients With Presumed Coronary Microvascular and
Laurie-Anne Boivin-Proulx1, Erick Schampaert2, Kevin Bainey3
1Department of Cardiology, University of Ottawa Heart Institute, Ottawa, Canada.
Insights
This study defines metrics for assessing coronary function, aiming to improve diagnosis of coronary microvascular and vasomotor dysfunction. Machine learning aids in analyzing complex data for better patient stratification and treatment guidance.
Area of Science:
- Cardiology
- Physiology
- Medical Diagnostics
Background:
- Coronary microvascular and vasomotor dysfunction diagnosis is complex.
- Inconsistent diagnostic pathways and unclear results hinder progress.
- Lack of established therapeutic benefits complicates patient management.
Purpose of the Study:
- To define metrics for invasive coronary function assessment.
- To evaluate the value and limitations of singular versus combined metrics.
- To propose a flexible interpretative framework for coronary function diagnostics.
Main Methods:
- Analysis of invasive coronary function data from the Canadian Coronary Physiology Registry.
- Evaluation of singular and combined metric utility.
- Early phenomapping analysis of non-invasive data using machine learning.
Main Results:
- Defined metrics for invasive coronary function assessment.
- Demonstrated the complexity of coronary dysfunction through phenomapping.
- Showcased machine learning's potential in unraveling diagnostic challenges.
Conclusions:
- A flexible interpretative framework is proposed for coronary function assessment.
- Combining invasive metrics with clinical data is crucial for determining pathophysiologic relevance.
- Further research is guided by the phenotypic and pathophysiologic relevance of these metrics.
Abstract:
The objective of diagnostic investigations should be to confirm or refute the presence of abnormal coronary function and to identify patients who might benefit from specific therapeutic interventions. In the field of coronary microvascular and vasomotor dysfunction, progress toward this goal is hampered if diagnostic pathways differ among sites, the meaning of the results are unclear, or the potential benefits of current therapies are not well established. In this second companion paper, we define the metrics that can be derived from the invasive assessment of the coronary function assessed in the Canadian Coronary Physiology Registry, discuss the theoretical and practical value and limitations of singular vs multiple combined metrics, and propose a flexible interpretative framework. We also provide early phenomapping analysis of the noninvasive data, which both confirm the complexity and demonstrate the power of machine learning to unravel this problem. The combination of the multiple invasive metrics with the comprehensive clinical assessment will determine the phenotypic and pathophysiological relevance of these metrics that will guide further research efforts.
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