Zampella, Emilia (2017) Combined assessment of coronary artery calcium and myocardial perfusion by hybrid Rb-82 PET/CT imaging in the identification of obstructive coronary artery disease. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Lingua: English
Title: Combined assessment of coronary artery calcium and myocardial perfusion by hybrid Rb-82 PET/CT imaging in the identification of obstructive coronary artery disease
Creators:
CreatorsEmail
Zampella, Emiliaemilia.zampella@gmail.com
Date: 6 April 2017
Number of Pages: 25
Institution: Università degli Studi di Napoli Federico II
Department: Scienze Biomediche Avanzate
Dottorato: Scienze biomorfologiche e chirurgiche
Ciclo di dottorato: 29
Coordinatore del Corso di dottorato:
nomeemail
Cuocolo, Albertocuocolo@unina.it
Tutor:
nomeemail
Acampa, WandaUNSPECIFIED
Date: 6 April 2017
Number of Pages: 25
Uncontrolled Keywords: Coronary flow reserve; Calcium score
Settori scientifico-disciplinari del MIUR: Area 06 - Scienze mediche > MED/36 - Diagnostica per immagini e radioterapia
Date Deposited: 18 Apr 2017 11:43
Last Modified: 14 Mar 2018 09:53
URI: http://www.fedoa.unina.it/id/eprint/11554
DOI: 10.6093/UNINA/FEDOA/11554

Abstract

Introduction: Myocardial perfusion imaging (MPI) with positron emission tomography (PET)/computed tomography (CT) allows accurate measurements of coronary artery calcium (CAC), myocardial perfusion and coronary flow reserve (CFR). Aim: We sought to determine whether the combined assessment of CAC score, ischemic total perfusion defect (ITPD) and CFR improves the diagnostic accuracy of PET/CT in predicting obstructive CAD. Methods: We analyzed 93 patients with suspected CAD referred to 82Rb PET/CT MPI and available coronary angiography. Obstructive CAD was defined as a ≥75% stenosis. Regional CAC score was categorized into 2 groups: <300 and ≥300. Regional ITPD was categorized into 3 groups 0%, ≥1 to <5% and ≥5%. CFR was defined as the ratio between hyperemic and baseline myocardial blood flow (MBF). ROC curves were used to obtain the best cutoff value for regional CFR in identifying obstructive CAD. Regression analyses were used to identify variables associated with obstructive CAD. The incremental value of CAC score, ITPD and CFR was assessed. The continuous net reclassification improvement (NRI) was used to evaluate whether a reduced regional CFR was additive in the prediction of severe CAD Results: Vessels with obstructive CAD (n=54) had higher ITPD (P<.001) and lower hyperemic MBF (P<.001) and CFR (P<.001) values compared to those without. The prevalence of ITPD 0% was significantly higher in vessels with CAC score <300 (P<.001) compared to vessels with CAC score ≥300; differently, the prevalence of ITPD <5% was higher in vessels with CAC score ≥300 compared to those with CAC score <300. ROC curves showed that a CFR value of 1.64 was the trade-off between sensitivity and specificity in identifying obstructive CAD. In vessels with CAC score <300, both in non-ischemic (P<.001) as well in vessels with ITPD <5% (P<.05) the prevalence of obstructive CAD was higher in the presence of a reduced regional CFR. In vessels with CAC score ≥300 the prevalence of obstructive CAD was comparable among ITPD and CFR groups. At univariable analysis age (P <.001), male gender (P <.01), CAC score ≥300 (P <.01), regional ITPD (P <.001) and CFR <1.64 (P <.001) were significant predictors of severe CAD. At multivariable analysis CAC score ≥300 (P<.05), regional ITPD (P<.001) and CFR <1.64 (P <.001) were independent predictors of severe CAD. The addition of ITPD to a model including clinical data and a CAC score ≥300 increased the global chi-square in predicting obstructive CAD (29.91 to 72.72; P <0.001). The addition of regional CFR<1.64 further increased the global chi-square (72.72 to 91.97; P <0.001). The continuous NRI by adding CFR to clinical data, CAC score and ITPD was 0.682 Conclusions: CFR provides incremental information about the presence of obstructive CAD over established cardiac risk factors, CAC score and MPI parameters. A combined use of CAC score, MPI and CFR can help to predict more accurately the presence of obstructive CAD.

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