Gianluca Pontone1, Giuseppe Muscogiuri2, Daniele Andreini3, Andrea I Guaricci4, Marco Guglielmo2, Andrea Baggiano2, Fabio Fazzari5, Saima Mushtaq2, Edoardo Conte2, Andrea Annoni2, Alberto Formenti2, Elisabetta Mancini2, Massimo Verdecchia2, Alessandro Campari2, Chiara Martini6, Marco Gatti7, Laura Fusini2, Lorenzo Bonfanti2, Elisa Consiglio2, Mark G Rabbat8, Antonio L Bartorelli9, Mauro Pepi2. 1. Centro Cardiologico Monzino, IRCCS, Via C. Parea 4, 20138, Milan, Italy. Electronic address: gianluca.pontone@ccfm.it. 2. Centro Cardiologico Monzino, IRCCS, Via C. Parea 4, 20138, Milan, Italy. 3. Centro Cardiologico Monzino, IRCCS, Via C. Parea 4, 20138, Milan, Italy; Department of Cardiovascular Sciences and Community Health, University of Milan, Milan, Italy. 4. Institute of Cardiovascular Disease, Department of Emergency and Organ Transplantation, University Hospital "Policlinico Consorziale" of Bari, Bari, Italy; Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy. 5. Department of Cardiology, University Hospital P. Giaccone, Palermo, Italy. 6. Diagnostic Department, Azienda Ospedaliero-Universitaria, Parma, Italy. 7. Department of Surgical Sciences, Radiology Institute, University of Turin, Turin, Italy. 8. Division of Cardiology, Loyola University of Chicago, Chicago, Illinois; Loyola University Chicago, Edward Hines Jr. VA Hospital, Hines, Illinois. 9. Centro Cardiologico Monzino, IRCCS, Via C. Parea 4, 20138, Milan, Italy; Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, Italy.
Abstract
RATIONALE AND OBJECTIVES: A new postprocessing algorithm named adaptive statistical iterative reconstruction (ASIR)-V has been recently introduced. The aim of this article was to analyze the impact of ASIR-V algorithm on signal, noise, and image quality of coronary computed tomography angiography. MATERIALS AND METHODS: Fifty consecutive patients underwent clinically indicated coronary computed tomography angiography (Revolution CT; GE Healthcare, Milwaukee, WI). Images were reconstructed using filtered back projection and ASIR-V 0%, and a combination of filtered back projection and ASIR-V 20%-80% and ASIR-V 100%. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for left main coronary artery (LM), left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) and were compared between the different postprocessing algorithms used. Similarly a four-point Likert image quality score of coronary segments was graded for each dataset and compared. A cutoff value of P < .05 was considered statistically significant. RESULTS: Compared to ASIR-V 0%, ASIR-V 100% demonstrated a significant reduction of image noise in all coronaries (P < .01). Compared to ASIR-V 0%, SNR was significantly higher with ASIR-V 60% in LM (P < .01), LAD (P < .05), LCX (P < .05), and RCA (P < .01). Compared to ASIR-V 0%, CNR for ASIR-V ≥60% was significantly improved in LM (P < .01), LAD (P < .05), and RCA (P < .01), whereas LCX demonstrated a significant improvement with ASIR-V ≥80%. ASIR-V 60% had significantly better Likert image quality scores compared to ASIR-V 0% in segment-, vessel-, and patient-based analyses (P < .01). CONCLUSIONS: Reconstruction with ASIR-V 60% provides the optimal balance between image noise, SNR, CNR, and image quality.
RATIONALE AND OBJECTIVES: A new postprocessing algorithm named adaptive statistical iterative reconstruction (ASIR)-V has been recently introduced. The aim of this article was to analyze the impact of ASIR-V algorithm on signal, noise, and image quality of coronary computed tomography angiography. MATERIALS AND METHODS: Fifty consecutive patients underwent clinically indicated coronary computed tomography angiography (Revolution CT; GE Healthcare, Milwaukee, WI). Images were reconstructed using filtered back projection and ASIR-V 0%, and a combination of filtered back projection and ASIR-V 20%-80% and ASIR-V 100%. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for left main coronary artery (LM), left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) and were compared between the different postprocessing algorithms used. Similarly a four-point Likert image quality score of coronary segments was graded for each dataset and compared. A cutoff value of P < .05 was considered statistically significant. RESULTS: Compared to ASIR-V 0%, ASIR-V 100% demonstrated a significant reduction of image noise in all coronaries (P < .01). Compared to ASIR-V 0%, SNR was significantly higher with ASIR-V 60% in LM (P < .01), LAD (P < .05), LCX (P < .05), and RCA (P < .01). Compared to ASIR-V 0%, CNR for ASIR-V ≥60% was significantly improved in LM (P < .01), LAD (P < .05), and RCA (P < .01), whereas LCX demonstrated a significant improvement with ASIR-V ≥80%. ASIR-V 60% had significantly better Likert image quality scores compared to ASIR-V 0% in segment-, vessel-, and patient-based analyses (P < .01). CONCLUSIONS: Reconstruction with ASIR-V 60% provides the optimal balance between image noise, SNR, CNR, and image quality.
Authors: Adriana Argentiero; Giuseppe Muscogiuri; Mark G Rabbat; Chiara Martini; Nicolò Soldato; Paolo Basile; Andrea Baggiano; Saima Mushtaq; Laura Fusini; Maria Elisabetta Mancini; Nicola Gaibazzi; Vincenzo Ezio Santobuono; Sandro Sironi; Gianluca Pontone; Andrea Igoren Guaricci Journal: J Clin Med Date: 2022-05-19 Impact factor: 4.964
Authors: Alberico Del Torto; Andrea Igoren Guaricci; Francesca Pomarico; Marco Guglielmo; Laura Fusini; Francesco Monitillo; Daniela Santoro; Monica Vannini; Alexia Rossi; Giuseppe Muscogiuri; Andrea Baggiano; Gianluca Pontone Journal: Front Cardiovasc Med Date: 2022-03-09
Authors: Denisa Muraru; Mara Gavazzoni; Francesca Heilbron; Diana J Mihalcea; Andrada C Guta; Noela Radu; Giuseppe Muscogiuri; Michele Tomaselli; Sandro Sironi; Gianfranco Parati; Luigi P Badano Journal: Front Cardiovasc Med Date: 2022-09-13