Image quality evaluation of iterative model reconstruction on low tube voltage (80 kVp) coronary CT angiography in an animal study

Coronary CT Angiography with Knowledge-Based Iterative Model Reconstruction for Assessing Coronary Arteries and Non-Calcified Predominant Plaques

Objective

To assess the effects of iterative model reconstruction (IMR) on image quality for demonstrating non-calcific high-risk plaque characteristics of coronary arteries.

Materials and Methods

This study included 66 patients (53 men and 13 women; aged 39–76 years; mean age, 55 ± 13 years) having single-vessel disease with predominantly non-calcified plaques evaluated using prospective electrocardiogram-gated 256-slice CT angiography. Paired image sets were created using two types of reconstruction: hybrid iterative reconstruction (HIR) and IMR. Plaque characteristics were compared using the two algorithms. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the images and the CNR between the plaque and adjacent adipose tissue were also compared between the two reformatted methods.

Results

Seventy-seven predominantly non-calcified plaques were detected. Forty plaques showed napkin-ring sign with the IMR reformatted method, while nineteen plaques demonstrated napkin-ring sign with HIR. There was no statistically significant difference in the presentation of positive remodeling, low attenuation plaque, and spotty calcification between the HIR and IMR reconstructed methods (all p > 0.5); however, there was a statistically significant difference in the ability to discern the napkin-ring sign between the two algorithms (χ² = 12.12, p < 0.001). The image noise of IMR was lower than that of HIR (10 ± 2 HU versus 12 ± 2 HU; p < 0.01), and the SNR and CNR of the images and the CNR between plaques and surrounding adipose tissues on IMR were better than those on HIR (p < 0.01).

Conclusion

IMR can significantly improve image quality compared with HIR for the demonstration of coronary artery and atherosclerotic plaques using a 256-slice CT.

CT reconstruction algorithms affect histogram and texture analysis: evidence for liver parenchyma, focal solid liver lesions, and renal cysts

PURPOSE

To determine the effects of different reconstruction algorithms on histogram and texture features in different targets.

MATERIALS AND METHODS

Among 3620 patients, 480 had normal liver parenchyma, 494 had focal solid liver lesions (metastases = 259; hepatocellular carcinoma = 99; hemangioma = 78; abscess = 32; and cholangiocarcinoma = 26), and 488 had renal cysts. CT images were reconstructed with filtered back-projection (FBP), hybrid iterative reconstruction (HIR), and iterative model reconstruction (IMR) algorithms. Computerized histogram and texture analyses were performed by extracting 11 features.

RESULTS

Different reconstruction algorithms had distinct, significant effects. IMR had a greater effect than HIR. For instance, IMR had a significant effect on five features of liver parenchyma, nine features of focal liver lesions, and four features of renal cysts on portal-phase scans and four, eight, and four features, respectively, on precontrast scans (p < 0.05). Meanwhile, different algorithms had a greater effect on focal liver lesions (six in HIR and nine in IMR on portal-phase, three in HIR, and eight in IMR on precontrast scans) than on liver parenchyma or cysts. The mean attenuation and standard deviation were not affected by the reconstruction algorithm (p > .05). Most parameters showed good or excellent intra- and interobserver agreement, with intraclass correlation coefficients ranging from 0.634 to 0.972.

CONCLUSIONS

Different reconstruction algorithms affect histogram and texture features. Reconstruction algorithms showed stronger effects in focal liver lesions than in liver parenchyma or renal cysts.

KEY POINTS

• Imaging heterogeneities influenced the quantification of image features. • Different reconstruction algorithms had a significant effect on histogram and texture features. • Solid liver lesions were more affected than liver parenchyma or cysts.

Editor's Highlight: Pulmonary Vascular Thrombosis in Rats Exposed to Inhaled Sulfur Mustard

Sulfur mustard (SM) is a chemical warfare agent. When inhaled, SM causes significant injury to the respiratory tract. Although the mechanism involved in acute airway injury after SM inhalation has been well described previously, the mechanism of SM's contribution to distal lung vascular injury is not well understood. We hypothesized that acute inhalation of vaporized SM causes activated systemic coagulation with subsequent pulmonary vascular thrombi formation after SM inhalation exposure. Sprague Dawley rats inhaled SM ethanolic vapor (3.8 mg/kg). Barium/gelatin CT pulmonary angiograms were performed to assess for pulmonary vascular thrombi burden. Lung immunohistochemistry was performed for common procoagulant markers including fibrin(ogen), von Willebrand factor, and CD42d in control and SM-exposed lungs. Additionally, systemic levels of d-dimer and platelet aggregometry after adenosine diphosphate- and thrombin-stimulation were measured in plasma after SM exposure. In SM-exposed lungs, chest CT angiography demonstrated a significant decrease in the distal pulmonary vessel density assessed at 6 h postexposure. Immunohistochemistry also demonstrated increased intravascular fibrin(ogen), vascular von Willebrand factor, and platelet CD42d in the distal pulmonary vessels (<200 µm diameter). Circulating d-dimer levels were significantly increased (p < .001) at 6, 9, and 12 h after SM inhalation versus controls. Platelet aggregation was also increased in both adenosine diphosphate - (p < .01) and thrombin- (p < .001) stimulated platelet-rich plasma after SM inhalation. Significant pulmonary vascular thrombi formation was evident in distal pulmonary arterioles following SM inhalation in rats assessed by CT angiography and immunohistochemistry. Enhanced systemic platelet aggregation and activated systemic coagulation with subsequent thrombi formation likely contributed to pulmonary vessel occlusion.

Knowledge-based iterative model reconstruction in coronary computed tomography angiography: comparison with hybrid iterative reconstruction and filtered back projection

Background Knowledge-based iterative model reconstruction (IMR) is known to allow radiation dose reduction while preserving image quality. Purpose To investigate the effect of IMR on coronary computed tomography angiography (CCTA) by comparing it with filtered back projection (FBP) and hybrid iterative reconstruction (HIR). Material and Methods Forty-five patients (group A) who underwent CCTA with prospective electrocardiogram (ECG) triggering at 80 kVp were included. All images were reconstructed using three algorithms: FBP, HIR, and IMR. The control group comprised 45 patients (group B) who underwent CCTA at 100 kVp; their images were reconstructed with HIR alone. Objective and subjective image quality was assessed by two radiologists. Results In group A, the signal-to-noise and contrast-to-noise ratios were significantly higher for images reconstructed with IMR than with HIR or FBP ( P < 0.001). IMR was also superior to HIR and FBP in subjective image quality analyses, including image noise, vessel sharpness, beam-hardening artifact, and overall quality ( P < 0.001). Moreover, the images reconstructed using IMR in group A had superior image quality with less radiation exposure than those reconstructed using HIR in group B on both objective and subjective analyses ( P < 0.001). The mean attenuation values were also significantly higher in group A than in group B ( P < 0.001). Conclusion Compared with HIR and FBP, IMR provided higher quality images with less radiation exposure in CCTA, using low kilovoltage and prospective ECG triggering.