Clinical feasibility of a myocardial signal intensity threshold-based semi-automated cardiac magnetic resonance segmentation method
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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.
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.
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.
Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods.
• 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
KeywordsLeft ventricular function Left ventricular mass Aortic flow Cine magnetic resonance imaging Semi-automated segmentation
The scientific guarantor of this publication is UJS. The authors of this manuscript declare relationships with the following companies: UJS is a consultant for and/or receives research support from Bayer, Bracco, GE Healthcare, Medrad, and Siemens Healthcare. The other authors declare that they have no competing interests. The authors state that this work has not received any funding. No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Written informed consent was waived by the institutional review board. None of the study subjects or cohorts have been previously reported. Methodology: retrospective, diagnostic/experimental study, performed at one institution.
Conflict of interest
U.J.S. is a consultant for and/or receives research support from Bayer (Wayne/NJ, USA), Bracco (Princeton/NJ, USA), GE Healthcare (Little Chalfont, UK), Medrad (Warrendale/PA, USA), and Siemens Healthcare (Malvern/PA, USA).
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