Abstract

PurposeTraditionally, interpretation of myocardial perfusion imaging (MPI) is based on visual assessment. Computer-based automated analysis might be a simple alternative obviating the need for extensive reading experience. Therefore, the aim of the present study was to compare the diagnostic performance of automated analysis with that of expert visual reading for the detection of obstructive coronary artery disease (CAD).Methods206 Patients (64% men, age 58.2 ± 8.7 years) with suspected CAD were included prospectively. All patients underwent 99mTc-tetrofosmin single-photon emission computed tomography (SPECT) and invasive coronary angiography with fractional flow reserve (FFR) measurements. Non-corrected (NC) and attenuation-corrected (AC) SPECT images were analyzed both visually as well as automatically by commercially available SPECT software. Automated analysis comprised a segmental summed stress score (SSS), summed difference score (SDS), stress total perfusion deficit (S-TPD), and ischemic total perfusion deficit (I-TPD), representing the extent and severity of hypoperfused myocardium. Subsequently, software was optimized with an institutional normal database and thresholds. Diagnostic performances of automated and visual analysis were compared taking FFR as a reference.ResultsSensitivity did not differ significantly between visual reading and most automated scoring parameters, except for SDS, which was significantly higher than visual assessment (p < 0.001). Specificity, however, was significantly higher for visual reading than for any of the automated scores (p < 0.001 for all). Diagnostic accuracy was significantly higher for visual scoring (77.2%) than for all NC images scores (p < 0.05), but not compared with SSS AC and S-TPD AC (69.8% and 71.2%, p = 0.063 and p = 0.134). After optimization of the automated software, diagnostic accuracies were similar for visual (73.8%) and automated analysis. Among the automated parameters, S-TPD AC showed the highest accuracy (73.5%).ConclusionAutomated analysis of myocardial perfusion SPECT can be as accurate as visual interpretation by an expert reader in detecting significant CAD defined by FFR.

Highlights

  • Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is widely used for non-invasive diagnosis of obstructive coronary artery disease (CAD) [1]

  • The current sub-analysis of the PACIFIC trial aims to compare the diagnostic accuracy of expert core laboratory reading of SPECT MPI against automated software package grading with and without CT-based attenuation correction (AC), for the detection of obstructive CAD with fractional flow reserve (FFR) as a reference

  • FFR was measured in 548 vessels, but not in 61 due to complete (n = 24) and sub-total (n = 34) occlusions, or severe coronary tortuosity (n = 3, no stenosis ≥30%, considered not hemodynamically significant CAD)

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Summary

Introduction

Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is widely used for non-invasive diagnosis of obstructive coronary artery disease (CAD) [1]. Predominantly invasive coronary angiography (ICA) is used, despite the fact that only fractional flow reserve (FFR) guided treatment has shown improvement in event-free survival and its frequent discrepancy with angiography is increasingly acknowledged [10,11,12]. It remains unclear how automated scoring systems compare with expert human visual grading and what the potential impact is of CT-based AC. The current sub-analysis of the PACIFIC trial aims to compare the diagnostic accuracy of expert core laboratory reading of SPECT MPI against automated software package grading with and without CT-based AC, for the detection of obstructive CAD with FFR as a reference

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