Flat-panel detector volumetric CT for visualization of subarachnoid hemorrhage and ventricles: preliminary results compared to conventional CT
- 11 March 2008
- journal article
- research article
- Published by Springer Nature in Neuroradiology
- Vol. 50 (6), 517-523
- https://doi.org/10.1007/s00234-008-0372-z
Abstract
The aim of this study was to compare flat-panel volumetric CT (VCT) to conventional CT (cCT) in the visualization of the extent of subarachnoid hemorrhage (SAH) and the width of the ventricles in patients with acute SAH. Included in the study were 22 patients with an acutely ruptured cerebral aneurysm who received VCT during coil embolization. VCT image quality, the extent of SAH (using a modified Fisher score and total slice number with SAH visible) and the width of the ventricles (Evans index) were evaluated by two experienced neuroradiologists (RAD1 and RAD2) and compared to the findings on cCT. Ten patients undergoing VCT for reasons other than SAH served as negative controls. Interobserver agreement in rating image quality was excellent for cCT (Kendall W value 0.94) and good for VCT (0.74). SAH was identified by RAD1 and RAD2 on VCT images in all patients. The modified Fisher scores underestimated the extent of SAH on VCT images in comparison with cCT images. Pearson’s correlation coefficient (r) regarding the number of image slices with SAH visible on cCT images compared with the number on VCT images was 0.85 for RAD1 and 0.84 for RAD2. The r value for the degree of interobserver agreement for the number of slices with SAH visible was 0.99 for cCT, and 0.95 for VCT images (n = 19), respectively. The width of the ventricles measured in terms of the Evans Index showed excellent concordance between the modalities (r = 0.81 vs. 0.82). Our preliminary results indicate that VCT is helpful in evaluating SAH in the angiography suite. Additionally, reliable evaluation of ventricle width is feasible. However, there are limitations with regard to the visibility of SAH on VCT images in comparison to cCT images.Keywords
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