Research: Noise-Optimized Virtual Monoenergetic Dual-Energy CT Improves Diagnostic Accuracy for the Detection of Active Arterial Bleeding of the Abdomen.

 2017 Sep;28(9):1257-1266. doi: 10.1016/j.jvir.2017.06.011. Epub 2017 Jul 19.

Noise-Optimized Virtual Monoenergetic Dual-Energy CT Improves Diagnostic Accuracy for the Detection of Active Arterial Bleeding of the Abdomen.

Abstract

PURPOSE:

To evaluate diagnostic accuracy of a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique for detection of active arterial abdominal bleeding on dual-energy (DE) CT angiography compared with standard image reconstruction.

MATERIALS AND METHODS:

DE CT angiography data sets of 71 patients (46 men; age 63.6 y ± 13.3) with suspected arterial bleeding of the abdomen or pelvis were reconstructed with standard linearly blended (F_0.5), VMI+, and traditional virtual monoenergetic imaging (VMI) algorithms in 10-keV increments from 40 to 100 keV. Attenuation measurements were performed in the descending aorta, area of hemorrhage, and feeding artery to calculate contrast-to-noise ratios (CNRs) in patients with active arterial bleeding. Based on quantitative image quality results, the best series for each reconstruction technique were chosen to analyze the diagnostic performance of 3 blinded radiologists.

RESULTS:

DE CT angiography showed acute arterial bleeding in 36 patients. Mean CNR was superior in 40-keV VMI+ compared with VMI series (all P < .001), which showed highest CNRs in 70-keV VMI and F_0.5 (21.6 ± 7.9, 12.9 ± 4.7, and 10.4 ± 3.6) images. Area under the curve analysis for detection of arterial bleeding showed significantly superior (P < .001) results for 40-keV VMI+ (0.963) compared with 70-keV VMI (0.775) and F_0.5 (0.817) series.

CONCLUSIONS:

Diagnostic accuracy in patients with active arterial bleeding of the abdomen can be significantly improved using VMI+ reconstructions at 40 keV compared with standard linearly blended and traditional VMI series in DE CT angiography.

https://www.ncbi.nlm.nih.gov/pubmed/28734847

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