Akos Varga-Szemes1, Giuseppe Muscogiuri1,2, U Joseph Schoepf3, Julian L Wichmann1,4, Pal Suranyi1, Carlo N De Cecco1, Paola M Cannaò1,5, Matthias Renker1,6, Stefanie Mangold1,7, Mary A Fox1, Balazs Ruzsics8. 1. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Drive, Charleston, SC, 29425-2260, USA. 2. Department of Medical-Surgical Sciences and Translational Medicine, University of Rome "Sapienza", Rome, Italy. 3. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Drive, Charleston, SC, 29425-2260, USA. schoepf@musc.edu. 4. Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany. 5. Scuola di Specializzazione in Radiodiagnostica, University of Milan, Milan, Italy. 6. Kerckhoff Heart and Thorax Center, Bad Nauheim, Germany. 7. Department of Diagnostic and Interventional Radiology, Eberhard-Karls University Tuebingen, Tuebingen, Germany. 8. Department of Cardiology, Royal Liverpool and Broadgreen University Hospitals, Liverpool, UK.
Abstract
OBJECTIVES: To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements. METHODS: Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers. RESULTS: Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17%; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P > 0.05) but were significantly different from conventional analysis (P < 0.05). Excellent inter-observer agreement was observed. CONCLUSIONS: Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods. KEY POINTS: • Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference.
OBJECTIVES: To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements. METHODS: Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers. RESULTS: Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17%; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P > 0.05) but were significantly different from conventional analysis (P < 0.05). Excellent inter-observer agreement was observed. CONCLUSIONS: Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods. KEY POINTS: • Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference.
Entities:
Keywords:
Aortic flow; Cine magnetic resonance imaging; Left ventricular function; Left ventricular mass; Semi-automated segmentation
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