Hyun Woo Goo1. 1. Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea. ghw68@hanmail.net.
Abstract
BACKGROUND: Semiautomatic three-dimensional (3-D) threshold-based cardiac computed tomography (CT) quantification has not been attempted for left ventricular mass. OBJECTIVE: To evaluate the technical feasibility of semiautomatic 3-D threshold-based cardiac CT quantification of left ventricular mass in patients with various degrees of left ventricular hypertrophy. MATERIALS AND METHODS: In 99 patients, cardiac CT was utilized to quantify ventricular volume and mass by using a semiautomatic 3-D threshold-based method. Left ventricular mass values were compared between the end-systole and the end-diastole. Volumetric parameters were compared among three left ventricular hypertrophy groups (definite, borderline, none). The reproducibility was assessed. The t-test, one-way analysis of variance and Pearson correlation were used. RESULTS: There were no technical failures. The left ventricular mass between the two sessions exhibited a small mean difference of 2.3±1.1% (mean±standard deviation). The indexed mass values were significantly higher at the end-systole than at the end-diastole (71.4±42.9 g/m2 vs. 65.9±43.3 g/m2, P<0.001), with significant correlation (R=0.99, P<0.001). The definite group (83.5±41.3 g/m2) showed statistically significantly higher indexed mass values than the borderline and none groups (64.7±26.9 and 55.6±23.9 g/m2, respectively; P<0.03), while demonstrating no statistically significant difference between the latter two groups (P>0.05). Left ventricular volume-mass and mass-volume ratios could be calculated in all three groups. CONCLUSION: CT quantification of left ventricular mass using semiautomatic 3-D threshold-based segmentation is feasible with high reproducibility and the mass values and its ratios with ventricular volumes may be used in patients with various degrees of left ventricular hypertrophy.
BACKGROUND: Semiautomatic three-dimensional (3-D) threshold-based cardiac computed tomography (CT) quantification has not been attempted for left ventricular mass. OBJECTIVE: To evaluate the technical feasibility of semiautomatic 3-D threshold-based cardiac CT quantification of left ventricular mass in patients with various degrees of left ventricular hypertrophy. MATERIALS AND METHODS: In 99 patients, cardiac CT was utilized to quantify ventricular volume and mass by using a semiautomatic 3-D threshold-based method. Left ventricular mass values were compared between the end-systole and the end-diastole. Volumetric parameters were compared among three left ventricular hypertrophy groups (definite, borderline, none). The reproducibility was assessed. The t-test, one-way analysis of variance and Pearson correlation were used. RESULTS: There were no technical failures. The left ventricular mass between the two sessions exhibited a small mean difference of 2.3±1.1% (mean±standard deviation). The indexed mass values were significantly higher at the end-systole than at the end-diastole (71.4±42.9 g/m2 vs. 65.9±43.3 g/m2, P<0.001), with significant correlation (R=0.99, P<0.001). The definite group (83.5±41.3 g/m2) showed statistically significantly higher indexed mass values than the borderline and none groups (64.7±26.9 and 55.6±23.9 g/m2, respectively; P<0.03), while demonstrating no statistically significant difference between the latter two groups (P>0.05). Left ventricular volume-mass and mass-volume ratios could be calculated in all three groups. CONCLUSION: CT quantification of left ventricular mass using semiautomatic 3-D threshold-based segmentation is feasible with high reproducibility and the mass values and its ratios with ventricular volumes may be used in patients with various degrees of left ventricular hypertrophy.
Entities:
Keywords:
Children; Computed tomography; Heart; Image post processing; Left ventricular hypertrophy; Left ventricular mass; Repeatability; Threshold-based segmentation; Young adults
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