1097 Automated frame-by-frame endocardial border detection from cardiac magnetic resonance images for quantitative asses
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BioMed Central
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Meeting abstract
1097 Automated frame-by-frame endocardial border detection from cardiac magnetic resonance images for quantitative assessment of left ventricular function: validation and clinical feasibility Cristiana Corsi*1, Federico Veronesi1, Claudio Lamberti1, Dianna ME Bardo2, Ernest B Jamison2, Roberto M Lang2 and Victor Mor-Avi2 Address: 1University of Bologna, Bologna, Italy and 2University of Chicago, Chicago, IL, USA * Corresponding author
from 11th Annual SCMR Scientific Sessions Los Angeles, CA, USA. 1–3 February 2008 Published: 22 October 2008 Journal of Cardiovascular Magnetic Resonance 2008, 10(Suppl 1):A222
doi:10.1186/1532-429X-10-S1-A222
Abstracts of the 11th Annual SCMR Scientific Sessions - 2008
Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/pdf/1532-429X-10-S1-info.pdfThis abstract is available from: http://jcmr-online.com/content/10/S1/A222 © 2008 Corsi et al; licensee BioMed Central Ltd.
Introduction Cardiac magnetic resonance (CMR) quantification of left ventricular (LV) size and function requires detection of endocardial boundaries. Most current techniques use image intensity gradients that require manual corrections and are thus subjective and time-consuming. As a result, clinically, CMR has been mostly used to measure only end-systolic and end-diastolic volumes (ESV, EDV) and calculate ejection fraction (EF).
Purpose Our aims were: (1) to determine to what extent the lack of dynamic information affect LV volume and EF measurements, (2) to develop and test a technique for dynamic endocardial border detection independent of intensity gradients, as a basis for automated volume measurements throughout the cardiac cycle; (3) to validate this approach against manually traced endocardial boundaries, and test its clinical feasibility in patients with abnormal systolic and diastolic function.
Methods 35 patients (age 53 ± 16 yrs; 19 males) with a wide range of LV volumes (39÷420 ml) and EF (20÷79%) were studied in two separate protocols. LV short-axis images (Philips 1.5 T) were obtained from base to apex (30 frames/cardiac cycle) and analyzed using custom soft-
ware. For each frame, 2D slices were stacked and endocardial boundaries automatically detected throughout the cardiac cycle in all slices simultaneously to preserve spatial continuity by using a modified 3D region-based model based on the probability of density distribution of gray levels. In protocol 1, we studied 19 patients. In addition to the automated analysis, endocardial contours were semi-automatically traced using commercial software (Philips ViewForum) as a reference for comparison. For both techniques, cross-sectional LV cavity area was calculated for each slice, and LV volume calculated throughout the cardiac cycle. Validation included inter-technique comparisons of LV volumes and EF. Border positions were compared by calculating mean radial distance between the automatically detected and the t
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