High-definition multidetector computed tomography for evaluation of coronary artery stents: Comparison to standard-definition 64-detector row computed tomography

Background

The assessment of coronary stents with present-generation 64-detector row computed tomography scanners that use filtered backprojection and operating at standard definition of 0.5–0.75mm (standard definition, SDCT) is limited by imaging artifacts and noise.

Objectives

We evaluated the performance of a novel, high-definition 64-slice CT scanner (HDCT), with improved spatial resolution (0.23mm) and applied statistical iterative reconstruction (ASIR) for evaluation of coronary artery stents.

Methods

HDCT and SDCT stent imaging was performed with the use of an ex vivo phantom. HDCT was compared with SDCT with both smooth and sharp kernels for stent intraluminal diameter, intraluminal area, and image noise. Intrastent visualization was assessed with an ASIR algorithm on HDCT scans, compared with the filtered backprojection algorithms by SDCT.

Results

Six coronary stents (2.5, 2.5, 2.75, 3.0, 3.5, 4.0mm) were analyzed by 2 independent readers. Interobserver correlation was high for both HDCT and SDCT. HDCT yielded substantially larger luminal area visualization compared with SDCT, both for smooth (29.4±14.5 versus 20.1±13.0; P<0.001) and sharp (32.0±15.2 versus 25.5±12.0; P<0.001) kernels. Stent diameter was higher with HDCT compared with SDCT, for both smooth (1.54±0.59 versus1.00±0.50; P<0.0001) and detailed (1.47±0.65 versus 1.08±0.54; P<0.0001) kernels. With detailed kernels, HDCT scans that used algorithms showed a trend toward decreased image noise compared with SDCT-filtered backprojection algorithms.

Conclusions

On the basis of this ex vivo study, HDCT provides superior detection of intrastent luminal area and diameter visualization, compared with SDCT. ASIR image reconstruction techniques for HDCT scans enhance the in-stent assessment while decreasing image noise.

Keywords: Computed tomography, Iterative reconstruction, Spatial resolution