| Left ventricle: automated segmentation by using myocardial effusion threshold reduction and intravoxel computation at MR imaging. | |
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MedLine Citation:
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PMID: 18710989 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This retrospective analysis of existing patient data had institutional review board approval and was performed in compliance with HIPAA. No informed consent was required. The purpose of the study was to develop and validate an algorithm for automated segmentation of the left ventricular (LV) cavity that accounts for papillary and/or trabecular muscles and partial voxels in cine magnetic resonance (MR) images, an algorithm called LV Myocardial Effusion Threshold Reduction with Intravoxel Computation (LV-METRIC). The algorithm was validated in biologic phantoms, and its results were compared with those of manual tracing, as well as those of a commercial automated segmentation software (MASS [MR Analytical Software System]), in 38 subjects. LV-METRIC accuracy in vitro was 98.7%. Among the 38 subjects studied, LV-METRIC and MASS ejection fraction estimations were highly correlated with manual tracing (R(2) = 0.97 and R(2) = 0.95, respectively). Ventricular volume estimations were smaller with LV-METRIC and larger with MASS than those calculated by using manual tracing, though all results were well correlated (R(2) = 0.99). LV-METRIC volume measurements without partial voxel interpolation were statistically equivalent to manual tracing results (P > .05). LV-METRIC had reduced intraobserver and interobserver variability compared with other methods. MASS required additional manual intervention in 58% of cases, whereas LV-METRIC required no additional corrections. LV-METRIC reliably and reproducibly measured LV volumes. Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/248/3/1004/DC1. |
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Authors:
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Noel C F Codella; Jonathan W Weinsaft; Matthew D Cham; Matthew Janik; Martin R Prince; Yi Wang |
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Publication Detail:
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Type: Evaluation Studies; Journal Article |
Journal Detail:
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Title: Radiology Volume: 248 ISSN: 1527-1315 ISO Abbreviation: Radiology Publication Date: 2008 Sep |
Date Detail:
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Created Date: 2008-08-19 Completed Date: 2008-09-15 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0401260 Medline TA: Radiology Country: United States |
Other Details:
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Languages: eng Pagination: 1004-12 Citation Subset: AIM; IM |
Copyright Information:
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RSNA, 2008 |
Affiliation:
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Department of Physiology, Biophysics, and Systems Biology, Weill Medical College of Cornell University, 575 Lexington Ave, 3rd Floor, New York, NY, USA. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Artificial Intelligence Female Heart Ventricles / pathology* Humans Image Enhancement / methods* Image Interpretation, Computer-Assisted / methods* Imaging, Three-Dimensional / methods* Magnetic Resonance Imaging / methods* Male Pattern Recognition, Automated / methods* Reproducibility of Results Sensitivity and Specificity Ventricular Dysfunction, Left / diagnosis* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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