Published in:
01-08-2018 | Original Article
Diagnostic performance of the quantification of myocardium at risk from MPI SPECT/CTA 2G fusion for detecting obstructive coronary disease: A multicenter trial
Authors:
Marina Piccinelli, PhD, Cesar Santana, MD, Gopi Kiran R. Sirineni, MD, Russell D. Folks, CNMT, RT(N), C. David Cooke, MSEE, Chesnal D. Arepalli, MD, Santiago Aguade-Bruix, MD, Zohar Keidar, MD, Alex Frenkel, MD, Ora Israel, MD, Jaume Candell-Riera, MD, Ernest V. Garcia, PhD
Published in:
Journal of Nuclear Cardiology
|
Issue 4/2018
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Abstract
Background
The effective non-invasive identification of coronary artery disease (CAD) and its proper referral for invasive treatment are still unresolved issues. We evaluated our quantification of myocardium at risk (MAR) from our second generation 3D MPI/CTA fusion framework for the detection and localization of obstructive coronary disease.
Methods
Studies from 48 patients who had rest/stress MPI, CTA, and ICA were analyzed from 3 different institutions. From the CTA, a 3D biventricular surface of the myocardium with superimposed coronaries was extracted and fused to the perfusion distribution. Significant lesions were identified from CTA readings and positioned on the fused display. Three estimates of MAR were computed on the 3D LV surface on the basis of the MPI alone (MARp), the CTA alone (MARa), and the fused information (MARf). The extents of areas at risk were used to generate ROC curves using ICA anatomical findings as reference standard.
Results
Areas under the ROC curve (AUC) for CAD detection using MARf was 0.88 (CI = 0.75-0.95) and for MARp and MARa were, respectively 0.82 (CI = 0.69-0.92) and 0.75 (CI = 0.60-0.86) using the ≥70% stenosis criterion. AUCs for CAD localization (all vessels) using MARf showed significantly higher performance than either MARa or MARp or both.
Conclusions
Using ICA as the reference standard, MAR as the quantitative parameter, and AUC to measure diagnostic performance, MPI-CTA fusion imaging provided incremental diagnostic information compared to MPI or CTA alone for the diagnosis and localization of CAD.