ABSTRACT
BACKGROUND: Dark rim artifacts in first-pass cardiovascular magnetic resonance (CMR) perfusion images can mimic perfusion defects and affect diagnostic accuracy for coronary artery disease (CAD). We evaluated whether quantitative myocardial blood flow (MBF) can differentiate dark rim artifacts from true perfusion defects in CMR perfusion. METHODS: Regadenoson perfusion CMR was performed at 1.5 T in 76 patients. Significant CAD was defined by quantitative invasive coronary angiography (QCA) ≥ 50% diameter stenosis. Non-significant CAD (NonCAD) was defined as stenosis by QCA < 50% diameter stenosis or computed tomographic coronary angiography (CTA) < 30% in all major epicardial arteries. Dark rim artifacts had study specific and guideline-based definitions for comparison purposes. MBF was quantified at the pixel-level and sector-level. RESULTS: In a NonCAD subgroup with dark rim artifacts, stress MBF was lower in the subendocardial than midmyocardial and epicardial layers (2.17 ± 0.61 vs. 3.06 ± 0.75 vs. 3.24 ± 0.80 mL/min/g, both p < 0.001) and was also 30% lower than in remote regions (2.17 ± 0.61 vs. 2.83 ± 0.67 mL/min/g, p < 0.001). However, subendocardial stress MBF in dark rim artifacts was 37-56% higher than in true perfusion defects (2.17 ± 0.61 vs. 0.95 ± 0.43 mL/min/g, p < 0.001). Absolute stress MBF differentiated CAD from NonCAD with an accuracy ranging from 86 to 89% (all p < 0.001) using pixel-level analyses. Similar results were seen at a sector level. CONCLUSION: Quantitative stress MBF is lower in dark rim artifacts than remote myocardium but significantly higher than in true perfusion defects. If confirmed in larger series, this approach may aid the interpretation of clinical stress perfusion exams. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00027170 ; first posted 11/28/2001; updated 11/27/2017.
Subject(s)
Artifacts , Coronary Artery Disease/diagnostic imaging , Coronary Circulation , Coronary Stenosis/diagnostic imaging , Coronary Vessels/diagnostic imaging , Image Interpretation, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Myocardial Perfusion Imaging/methods , Adult , Aged , Blood Flow Velocity , Coronary Angiography , Coronary Artery Disease/physiopathology , Coronary Stenosis/physiopathology , Coronary Vessels/physiopathology , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Purines/administration & dosage , Pyrazoles/administration & dosage , Reproducibility of Results , Retrospective Studies , Severity of Illness Index , Vasodilator Agents/administration & dosageABSTRACT
OBJECTIVES: The authors developed a fully automated framework to quantify myocardial blood flow (MBF) from contrast-enhanced cardiac magnetic resonance (CMR) perfusion imaging and evaluated its diagnostic performance in patients. BACKGROUND: Fully quantitative CMR perfusion pixel maps were previously validated with microsphere MBF measurements and showed potential in clinical applications, but the methods required laborious manual processes and were excessively time-consuming. METHODS: CMR perfusion imaging was performed on 80 patients with known or suspected coronary artery disease (CAD) and 17 healthy volunteers. Significant CAD was defined by quantitative coronary angiography (QCA) as ≥70% stenosis. Nonsignificant CAD was defined by: 1) QCA as <70% stenosis; or 2) coronary computed tomography angiography as <30% stenosis and a calcium score of 0 in all vessels. Automatically generated MBF maps were compared with manual quantification on healthy volunteers. Diagnostic performance of the automated MBF pixel maps was analyzed on patients using absolute MBF, myocardial perfusion reserve (MPR), and relative measurements of MBF and MPR. RESULTS: The correlation between automated and manual quantification was excellent (r = 0.96). Stress MBF and MPR in the ischemic zone were lower than those in the remote myocardium in patients with significant CAD (both p < 0.001). Stress MBF and MPR in the remote zone of the patients were lower than those in the normal volunteers (both p < 0.001). All quantitative metrics had good area under the curve (0.864 to 0.926), sensitivity (82.9% to 91.4%), and specificity (75.6% to 91.1%) on per-patient analysis. On a per-vessel analysis of the quantitative metrics, area under the curve (0.837 to 0.864), sensitivity (75.0% to 82.7%), and specificity (71.8% to 80.9%) were good. CONCLUSIONS: Fully quantitative CMR MBF pixel maps can be generated automatically, and the results agree well with manual quantification. These methods can discriminate regional perfusion variations and have high diagnostic performance for detecting significant CAD. (Technical Development of Cardiovascular Magnetic Resonance Imaging; NCT00027170).
