Clinical feasibility of a myocardial signal intensity threshold-based semi-automated cardiac magnetic resonance segmentation method
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 evalua...
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| Vydané v: | European radiology Ročník 26; číslo 5; s. 1503 - 1511 |
|---|---|
| Hlavní autori: | , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.05.2016
Springer Nature B.V |
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| ISSN: | 0938-7994, 1432-1084, 1432-1084 |
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| 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 |
|---|---|
| AbstractList | 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 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.OBJECTIVESTo 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.METHODSShort-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.RESULTSEvaluation 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.CONCLUSIONSThreshold-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.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. 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. 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 |
| Author | De Cecco, Carlo N. Varga-Szemes, Akos Wichmann, Julian L. Suranyi, Pal Schoepf, U. Joseph Mangold, Stefanie Ruzsics, Balazs Fox, Mary A. Renker, Matthias Cannaò, Paola M. Muscogiuri, Giuseppe |
| Author_xml | – sequence: 1 givenname: Akos surname: Varga-Szemes fullname: Varga-Szemes, Akos organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina – sequence: 2 givenname: Giuseppe surname: Muscogiuri fullname: Muscogiuri, Giuseppe organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Department of Medical-Surgical Sciences and Translational Medicine, University of Rome “Sapienza” – sequence: 3 givenname: U. Joseph surname: Schoepf fullname: Schoepf, U. Joseph email: schoepf@musc.edu organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina – sequence: 4 givenname: Julian L. surname: Wichmann fullname: Wichmann, Julian L. organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt – sequence: 5 givenname: Pal surname: Suranyi fullname: Suranyi, Pal organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina – sequence: 6 givenname: Carlo N. surname: De Cecco fullname: De Cecco, Carlo N. organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina – sequence: 7 givenname: Paola M. surname: Cannaò fullname: Cannaò, Paola M. organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Scuola di Specializzazione in Radiodiagnostica, University of Milan – sequence: 8 givenname: Matthias surname: Renker fullname: Renker, Matthias organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Kerckhoff Heart and Thorax Center – sequence: 9 givenname: Stefanie surname: Mangold fullname: Mangold, Stefanie organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Department of Diagnostic and Interventional Radiology, Eberhard-Karls University Tuebingen – sequence: 10 givenname: Mary A. surname: Fox fullname: Fox, Mary A. organization: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina – sequence: 11 givenname: Balazs surname: Ruzsics fullname: Ruzsics, Balazs organization: Department of Cardiology, Royal Liverpool and Broadgreen University Hospitals |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26267520$$D View this record in MEDLINE/PubMed |
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| Copyright | European Society of Radiology 2015 European Society of Radiology 2016 |
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| Keywords | Aortic flow Cine magnetic resonance imaging Left ventricular mass Left ventricular function Semi-automated segmentation |
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To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional... To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based... Objectives To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional... |
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| SubjectTerms | Accuracy Algorithms Automation Cardiac Diagnostic Radiology Feasibility Studies Female Heart Ventricles - pathology Humans Imaging Internal Medicine Interventional Radiology Magnetic Resonance Angiography - methods Magnetic resonance imaging Magnetic Resonance Imaging, Cine Magnetic Resonance Spectroscopy Male Medicine Medicine & Public Health Methods Middle Aged Myocardium - pathology Neuroradiology Observer Variation Radiology Reproducibility of Results Stroke Volume - physiology Ultrasound Ventricular Dysfunction, Left - pathology Ventricular Dysfunction, Left - physiopathology |
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