Assessment of regional left ventricular function by dual source computed tomography: interobserver variability and...

Assessment of left ventricular function is possible in contrast-enhanced cardiac CT data sets. However, rapid ventricular motion especially in systole can lead to artifacts. Dual Source Computed Tomography (DSCT) has high temporal resolution which effectively limits motion artifact. We therefore assessed the accuracy of DSCT to detect regional left ventricular wall motion abnormalities in comparison to invasive cine angiocardiography.

We analyzed DSCT data sets of 50 patients (39 male, 11 female, mean age: 61+/-10 years) which were acquired after intravenous injection of 55-70 mL contrast agent (rotation time: 330 ms, collimation: 2 mm x 64 mm x 0.6 mm, 120 kV, 380 mAs, ECG-correlated tube current modulation). 10 data sets consisting of transaxial slices with a slice thickness of 1.5 mm, an increment of 1.0 mm and a matrix of 256 x 256 pixels were reconstructed at 10 time instants during the cardiac cycle (0-90% in 10% increments). The data sets were analyzed visually by two independent readers, using standard left ventricular planes, concerning regional wall motion abnormalities. DSCT was verified in a blinded fashion against cine ventriculography performed during cardiac catheterization (RAO and LAO projection), using a 7-segment model. Analysis was performed on a per-patient (presence of at least one hypo-, a- or dyskinetic segment) and on a per-segment basis.

Concerning the presence of a wall motion abnormality, the two observers agreed in 340/350 segments (97%) and 48/50 patients (96%). In invasive cine angiocardiography, 22 of 50 patients displayed at least one segment with abnormal contraction. To detect these patients, DSCT showed a sensitivity of 95% (21/22), specificity of 96% (27/28), positive predictive value of 95% and negative predictive value of 96%. Out of a total of 350 left ventricular segments, 66 segments had abnormal contraction in cine angiocardiography (34 hypokinetic, 26 akinetic, 6 dyskinetic). For detection of these segments, DSCT had a sensitivity of 88% (58/66), specificity of 98% (278/284), positive predictive value of 91% (58/64) and negative predictive value of 97% (278/286).

DSCT allows the detection of regional wall motion abnormalities with high interobserver agreement as well as high sensitivity and specificity. Whereas sensitivity and positive predictive value were higher in a per-patient- in comparison to a per-segment-based analysis, specificity, negative predictive value and interobserver agreement did not differ considerably between both analyzing methods.