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Synergy of MDCT and Cine MRI for the Evaluation of Cardiac Motility

Daniel T. Boll1,2, Andrea S. Bossert2, Andrik J. Aschoff2, Martin H. Hoffmann2 and Robert C. Gilkeson1

1 Department of Radiology, University Hospitals of Cleveland, 11100 Euclid Ave., Cleveland, OH 44106.
2 Department of Radiology, University Hospitals of Ulm, Ulm, Germany.


Figure 1
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Fig. 1A —Schematic visualization of segmentation of left ventricle in 42-year-old man with aortic valve disease. Ventricular levels were localized perpendicular to long axis as even-parity regions and described as basal, mid cavity, and apical.

 

Figure 2
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Fig. 1B —Schematic visualization of segmentation of left ventricle in 42-year-old man with aortic valve disease. Circumferential locations within each level were located perpendicular to short axis and described as anterior, anteroseptal, and inferoseptal segments and posteriorly as inferior, inferolateral, and anterolateral segments, for a total of 18 segments per ventricle.

 

Figure 3
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Fig. 2A —Schematic visualization of measurement variability of ventricular wall thickening (inner numbers) and motion analysis (outer numbers) expressed as coefficients of variance based on CT (A) and MRI (B) ventricular short-axis imaging data sets. Patient is 72-year-old man with aortic valve disease; mean heart rate was 110 beats per minute. Note asterisks emphasizing areas with significant variation of automatically detected myocardial border at measurement repetitions. All asterisks aligned along endothelial interface.

 

Figure 4
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Fig. 2B —Schematic visualization of measurement variability of ventricular wall thickening (inner numbers) and motion analysis (outer numbers) expressed as coefficients of variance based on CT (A) and MRI (B) ventricular short-axis imaging data sets. Patient is 72-year-old man with aortic valve disease; mean heart rate was 110 beats per minute. Note asterisks emphasizing areas with significant variation of automatically detected pericardial and myocardial borders at measurement repetitions. Asterisks aligned along pericardial-endothelial interface.

 

Figure 5
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Fig. 3A —Increasing heart rates proved existence of exponential error propagation, thus emphasizing necessity of reporting ventricular motility results in combination with underlying heart frequency. bpm = beats per minute. Curve estimation procedure produced quadratic curve estimation regression plots while statistically evaluating measurement differences obtained when determining ventricular wall thickening (A) (correlation, 0.971; significance, p < 0.001) and ventricular wall motion (B) (correlation, 0.975; significance, p < 0.001) based on CT and MR data sets in correlation with underlying heart rates.

 

Figure 6
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Fig. 3B —Increasing heart rates proved existence of exponential error propagation, thus emphasizing necessity of reporting ventricular motility results in combination with underlying heart frequency. bpm = beats per minute. Curve estimation procedure produced quadratic curve estimation regression plots while statistically evaluating measurement differences obtained when determining ventricular wall thickening (A) (correlation, 0.971; significance, p < 0.001) and ventricular wall motion (B) (correlation, 0.975; significance, p < 0.001) based on CT and MR data sets in correlation with underlying heart rates.

 

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