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In Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology

BACKGROUND : We evaluated the performance of conventional (C) single-photon emission computed tomography (SPECT) and cadmium-zinc-telluride (CZT)-SPECT in a large cohort of patients with suspected or known coronary artery disease (CAD) and compared the diagnostic accuracy of the two systems using machine learning (ML) algorithms.

METHODS AND RESULTS : A total of 517 consecutive patients underwent stress myocardial perfusion imaging (MPI) by both C-SPECT and CZT-SPECT. In the overall population, an excellent correlation between stress MPI data and left ventricular (LV) functional parameters measured by C-SPECT and by CZT-SPECT was observed (all P < .001). ML analysis performed through the implementation of random forest (RF) and k-nearest neighbors (NN) algorithms proved that CZT-SPECT has greater accuracy than C-SPECT in detecting CAD. For both algorithms, the sensitivity of CZT-SPECT (96% for RF and 60% for k-NN) was greater than that of C-SPECT (88% for RF and 53% for k-NN).

CONCLUSIONS : MPI data and LV functional parameters obtained by CZT-SPECT are highly reproducible and provide good correlation with those obtained by C-SPECT. ML approach showed that the accuracy and sensitivity of CZT-SPECT is greater than C-SPECT in detecting CAD.

Cantoni Valeria, Green Roberta, Ricciardi Carlo, Assante Roberta, Zampella Emilia, Nappi Carmela, Gaudieri Valeria, Mannarino Teresa, Genova Andrea, De Simini Giovanni, Giordano Alessia, D’Antonio Adriana, Acampa Wanda, Petretta Mario, Cuocolo Alberto


CAD, MPI, SPECT, diagnostic and prognostic application