Title | |
Publication Type | Journal Article |
Year of Publication | 2012 |
Authors | Codella NCF, Lee HYeoun, Fieno DS, Chen DW, Hurtado-Rua S, Kochar M, Finn JPaul, Judd R, Goyal P, Schenendorf J, Cham MD, Devereux RB, Prince M, Wang Y, Weinsaft JW |
Journal | Circ Cardiovasc Imaging |
Volume | 5 |
Issue | 1 |
Pagination | 137-46 |
Date Published | 2012 Jan |
ISSN | 1942-0080 |
Keywords | Algorithms, Animals, Dogs, Female, Heart Ventricles, Humans, Hypertrophy, Left Ventricular, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Observer Variation, Reproducibility of Results, Swine, Ultrasonography, Ventricular Function, Left, Ventricular Remodeling |
Abstract | BACKGROUND: Cardiac magnetic resonance (CMR) typically quantifies LV mass (LVM) by means of manual planimetry (MP), but this approach is time-consuming and does not account for partial voxel components--myocardium admixed with blood in a single voxel. Automated segmentation (AS) can account for partial voxels, but this has not been used for LVM quantification. This study used automated CMR segmentation to test the influence of partial voxels on quantification of LVM. METHODS AND RESULTS: LVM was quantified by AS and MP in 126 consecutive patients and 10 laboratory animals undergoing CMR. AS yielded both partial voxel (AS(PV)) and full voxel (AS(FV)) measurements. Methods were independently compared with LVM quantified on echocardiography (echo) and an ex vivo standard of LVM at necropsy. AS quantified LVM in all patients, yielding a 12-fold decrease in processing time versus MP (0:21±0:04 versus 4:18±1:02 minutes; P CONCLUSIONS: Automated segmentation of myocardial partial voxels yields a 14-17% increase in LVM versus full voxel segmentation, with increased differences correlated with lower spatial resolution. Partial voxel segmentation yields improved CMR agreement with echo and necropsy-verified LVM. |
DOI | 10.1161/CIRCIMAGING.111.966754 |
Alternate Journal | Circ Cardiovasc Imaging |
PubMed ID | 22104165 |
PubMed Central ID | PMC3658317 |
Grant List | K23 HL102249 / HL / NHLBI NIH HHS / United States K23 HL102249-01 / HL / NHLBI NIH HHS / United States |