Key result
Automated segmentation of myocardial partial voxels yielded a 14-17% increase in left ventricular mass versus full voxel segmentation (P<0.001), improving agreement with echo and necropsy.
Why the study?
Does automated CMR segmentation with partial voxel interpolation improve left ventricular mass quantification compared to manual planimetry and full voxel segmentation?
Observational (n=136)
Does automated CMR segmentation with partial voxel interpolation improve left ventricular mass quantification compared to manual planimetry and full voxel segmentation?
Effect estimate: 14-17% increase
Absolute Event Rate: 159% vs 139%
p-value: p=<0.001
Automated segmentation of myocardial partial voxels improves CMR agreement with echocardiography and necropsy-verified left ventricular mass while significantly reducing processing time.
May refine CMR LV mass accuracy; leaves open need for outcome validation before clinical adoption.
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<0.001). AS(FV) mass (136±35 g) was slightly lower than MP (139±35; Δ=3±9 g, P<0.001). Both methods yielded similar proportions of patients with LV remodeling (P=0.73) and hypertrophy (P=1.00). Regarding partial voxel segmentation, AS(PV) yielded higher LVM (159±38 g) than MP (Δ=20±10 g) and AS(FV) (Δ=23±6 g, both P<0.001), corresponding to relative increases of 14% and 17%. In multivariable analysis, magnitude of difference between AS(PV) and AS(FV) correlated with larger voxel size (partial r=0.37, P<0.001) even after controlling for LV chamber volume (r=0.28, P=0.002) and total LVM (r=0.19, P=0.03). Among patients, AS(PV) yielded better agreement with echo (Δ=20±25 g) than did AS(FV) (Δ=43±24 g) or MP (Δ=40±22 g, both P<0.001). Among laboratory animals, AS(PV) and ex vivo results were similar (Δ=1±3 g, P=0.3), whereas AS(FV) (6±3 g, P<0.001) and MP (4±5 g, P=0.02) yielded small but significant differences with LVM at necropsy. 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.
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Codella et al. (2011) conducted an observational in Left ventricular mass quantification (n=136). Automated segmentation with partial voxel interpolation (AS(PV)) vs. Manual planimetry (MP) and full voxel automated segmentation (AS(FV)) was evaluated on Left ventricular mass (LVM) (14-17% increase, p=<0.001). Automated segmentation of myocardial partial voxels yielded a 14-17% increase in left ventricular mass versus full voxel segmentation (P<0.001), improving agreement with echo and necropsy.
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