Dual Energy CT With Nonlinear Image Blending Improves Visualization of Delayed Myocardial Contrast Enhancement in Acute Myocardial Infarction:

Image quality enhancement of CT hepatic portal venography using dual energy blending with computer determined parameters

BACKGROUND

Previous studies have shown that using some post-processing methods, such as nonlinear-blending and linear blending techniques, has potential to improve dual-energy computed (DECT) image quality.

OBJECTIVE

To improve DECT image quality of hepatic portal venography (CTPV) using a new non-linear blending method with computer-determined parameters, and to compare the results to additional linear and non-linear blending techniques.

METHODS

DECT images of 60 patients who were clinically diagnosed with liver cirrhosis were selected and studied. Dual-energy scanning (80 kVp and Sn140 kVp) of CTPV was utilized in the portal venous phase through a dual-source CT scanner. For image processing, four protocols were utilized including linear blending with a weighing factor of 0.3 (protocol A) and 1.0 (protocol B), non-linear blending with fixed blending width of 200 HU and set blending center of 150HU (protocol C), and computer-based blending (protocol D). Several image quality indicators, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and contrast of hepatic portal vein and hepatic parenchyma, were evaluated using the paired-sample t-test. A 5-grade scale scoring system was also utilized for subjective analysis.

RESULTS

SNR of protocols A-D were 9.1±2.1, 12.1±3.0, 11.6±2.8 and 14.4±3.2, respectively. CNR of protocols A-D were 4.6±1.3, 8.0±2.3, 7.0±2.0 and 9.8±2.4, respectively. The contrast of protocols A-D were 37.7±11.6, 91.9±21.0, 66.2±19.0 and 107.7±21.3, respectively. The differences between protocol D and other three protocols were significant (P < 0.01). In subjective evaluation, the modes of protocols A, B, C, and D were rated poor, good, generally acceptable, and excellent, respectively.

CONCLUSION

The non-linear blending technique of protocol D with computer-determined blending parameters can help improve imaging quality of CTPV and contribute to a diagnosis of liver disease.

Accuracy of Pulmonary Nodule Volumetry Using Noise-Optimized Virtual Monoenergetic Image and Nonlinear Blending Image Algorithms in Dual-Energy Computed Tomography: A Phantom Study

OBJECTIVE

The aim of the study was to assess accuracy of pulmonary nodule volumetry using noise-optimized virtual monoenergetic image (VMI+) and nonlinear blending image (NBI) algorithms in dual-energy computed tomography (DECT).

METHODS

An anthropomorphic chest phantom with 10 simulated nodules (5 solid nodules and 5 ground-glass opacities) was scanned using DECT80/Sn140kV, DECT100/Sn140kV, and single-energy CT (SECT120kV/200mAs), respectively. The dual-energy images were reconstructed using VMI+ (70 keV) and NBI algorithms. The contrast-to-noise ratio and absolute percentage error (APE) of nodule volume were measured to assess image quality and accuracy of nodule volumetry. The radiation dose was also estimated.

RESULTS

The contrast-to-noise ratio of SECT120kV/200mAs was significantly higher than that of NBI80/Sn140kV and VMI+80/Sn140kV (both corrected P < 0.05), whereas there were no significant differences between NBI100/sn140kV and SECT120kV/200mAs and between VMI+100/sn140kV and SECT120kV/200mAs (both corrected P > 0.05). The APE of SECT120kV/200mAs was significantly lower than that of NBI80/Sn140kV and VMI+80/Sn140kV in both types of nodules (all corrected P < 0.05), whereas there were no significant differences between VMI+100/sn140kV and SECT120kV/200mAs in solid nodules and between NBI100/Sn140kV and SECT120kV/200mAs in ground-glass opacities (both corrected P > 0.05). The radiation dose of DECT100/Sn140kV and DECT80/Sn140kV were significantly lower than that of SECT120kV/200mAs (both corrected P < 0.05).

CONCLUSIONS

The DECT100/sn140kV can ensure image quality and nodule volumetry accuracy with lower radiation dose compared with SECT120kV/200mAs. Specifically, the VMI+ algorithm could be used in solid nodules and NBI algorithm in ground-glass opacities.

Dual-Energy Computed Tomography in Cardiothoracic Vascular Imaging

Dual energy computed tomography is becoming increasingly widespread in clinical practice. It can expand on the traditional density-based data achievable with single energy computed tomography by adding novel applications to help reach a more accurate diagnosis. The implementation of this technology in cardiothoracic vascular imaging allows for improved image contrast, metal artifact reduction, generation of virtual unenhanced images, virtual calcium subtraction techniques, cardiac and pulmonary perfusion evaluation, and plaque characterization. The improved diagnostic performance afforded by dual energy computed tomography is not associated with an increased radiation dose. This review provides an overview of dual energy computed tomography cardiothoracic vascular applications.

Assessment of myocardial viability based on dual-energy computed tomography in patients with chronic myocardial infarction: comparison with magnetic resonance imaging

PURPOSE

To evaluate the diagnostic performance of dual-energy computed tomography (DECT) for the assessment of myocardial viability compared with magnetic resonance imaging (MRI) in patients with chronic myocardial infarction (CMI).

METHODS AND MATERIAL

Twenty-six patients were prospectively enrolled, who underwent DECT and MRI at delayed phase. The infarct volumes for DECT and MRI were measured.

RESULTS

In per-segment and per-vessel analysis, DECT showed excellent diagnostic performance compared with MRI (diagnostic accuracy: 86.2%, 81.2% respectively). In volume analysis, DECT correlated well with MRI (r=0.966, p<0.0001).

CONCLUSIONS

DECT has excellent diagnostic performance for detecting CMI.

Delayed enhancement cardiac computed tomography for the assessment of myocardial infarction: from bench to bedside

A large number of studies support the increasingly relevant prognostic value of the presence and extent of delayed enhancement (DE), a surrogate marker of fibrosis, in diverse etiologies. Gadolinium and iodinated based contrast agents share similar kinetics, thus leading to comparable myocardial characterization with cardiac magnetic resonance (CMR) and cardiac computed tomography (CT) at both first-pass perfusion and DE imaging. We review the available evidence of DE imaging for the assessment of myocardial infarction (MI) using cardiac CT (CTDE), from animal to clinical studies, and from 16-slice CT to dual-energy CT systems (DECT). Although both CMR and gadolinium agents have been originally deemed innocuous, a number of concerns (though inconclusive and very rare) have been recently issued regarding safety issues, including DNA double-strand breaks related to CMR, and gadolinium-associated nephrogenic systemic fibrosis and deposition in the skin and certain brain structures. These concerns have to be considered in the context of non-negligible rates of claustrophobia, increasing rates of patients with implantable cardiac devices, and a number of logistic drawbacks compared with CTDE, such as higher costs, longer scanning times, and difficulties to scan patients with impaired breath-holding capabilities. Overall, these issues might encourage the role of CTDE as an alternative for DE-CMR in selected populations.

Optimized energy of spectral CT for infarct imaging: Experimental validation with human validation

OBJECTIVES

Late contrast enhancement visualizes myocardial infarction, but the contrast to noise ratio (CNR) is low using conventional CT. The aim of this study was to determine if spectral CT can improve imaging of myocardial infarction.

MATERIALS AND METHODS

A canine model of myocardial infarction was produced in 8 animals (90-min occlusion, reperfusion). Later, imaging was performed after contrast injection using CT at 90 kVp/150 kVpSn. The following reconstructions were evaluated: Single energy 90 kVp, mixed, iodine map, multiple monoenergetic conventional and monoenergetic noise optimized reconstructions. Regions of interest were measured in infarct and remote regions to calculate contrast to noise ratio (CNR) and Bhattacharya distance (a metric of the differentiation between regions). Blinded assessment of image quality was performed. The same reconstruction methods were applied to CT scans of four patients with known infarcts.

RESULTS

For animal studies, the highest CNR for infarct vs. myocardium was achieved in the lowest keV (40 keV) VMo images (CNR 4.42, IQR 3.64-5.53), which was superior to 90 kVp, mixed and iodine map (p = 0.008, p = 0.002, p < 0.001, respectively). Compared to 90 kVp and iodine map, the 40 keV VMo reconstructions showed significantly higher histogram separation (p = 0.042 and p < 0.0001, respectively). The VMo reconstructions showed the highest rate of excellent quality scores. A similar pattern was seen in human studies, with CNRs for infarct maximized at the lowest keV optimized reconstruction (CNR 4.44, IQR 2.86-5.94).

CONCLUSIONS

Dual energy in conjunction with noise-optimized monoenergetic post-processing improves CNR of myocardial infarct delineation by approximately 20-25%.

Optimal Contrast of Cerebral Dual-Energy Computed Tomography Angiography in Patients With Spontaneous Subarachnoid Hemorrhage

Objective

The aim of this study was to investigate the image quality of cerebral dual-energy computed tomography (CT) angiography using a nonlinear image blending technique as compared with the conventional linear blending method in patients with spontaneous subarachnoid hemorrhage (SAH).

Methods

A retrospective review of 30 consecutive spontaneous SAH patients who underwent a dual-source, dual-energy (80 kV and Sn140 kV mode) cerebral CT angiography was performed with permission from hospital ethical committee. Optimized images using nonlinear blending method were generated and compared with the 0.6 linear blending images by evaluating cerebral artery enhancement, attenuation of SAH, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR), respectively. Two neuroradiologists independently assessed subjective vessel visualization per segment using a 5-point scale.

Results

The nonlinear blending images showed higher cerebral artery enhancement (307.24 ± 58.04 Hounsfield unit [HU]), lower attenuation of SAH (67.07 ± 6.79 HU), and image noise (7.18 ± 1.20 HU), thus achieving better SNR (43.92 ± 11.14) and CNR (34.34 ± 10.25), compared with those of linear blending images (235.47 ± 46.45 HU for cerebral artery enhancement, 70.00 ± 6.41 HU for attenuation of SAH, 8.39 ± 1.25 HU for image noise, 28.86 ± 8.43 for SNR, and 20.37 ± 7.74 for CNR) (all P < 0.01). The segmental scorings of the nonlinear blending image (31.6% segments with a score of 5, 57.4% segments with a score of 4, 11% segments with a score of 3) ranged significantly higher than those of linear blending images (11.5% segments with a score of 5, 77.5% segments with a score of 4, 11% segments with a score of 3) (P < 0.01). The interobserver agreement was good (κ = 0.762), and intraobserver agreement was excellent for both observers (κ = 0.844 and 0.858, respectively).

Conclusions

The nonlinear image blending technique improved vessel visualization of cerebral dual-energy CT angiography by optimizing contrast enhancement in spontaneous SAH patients.

Virtual monoenergetic dual-energy computed tomography: optimization of kiloelectron volt settings in head and neck cancer

OBJECTIVES

The aim of this study was to evaluate the effects on objective and subjective image quality of virtual monoenergetic reconstructions at various energy levels of dual-energy computed tomography (DECT) in patients with head and neck cancer.

MATERIALS AND METHODS

We included 71 (53 men, 18 women; age, 59.3 ± 12.0 years; range, 33-90 years) patients with biopsy-proven untreated primary (n = 55) or recurrent (n = 16) squamous cell carcinoma who underwent head and neck DECT. Images were reconstructed with a linear blending setting emulating 120 kV acquisition (M_0.3; 30% of 80 kV, 70% of 140 kV spectrum) and as virtual monoenergetic images with photon energies of 40, 60, 80, and 100 keV. Attenuation of lesion, various anatomic landmarks, and image noise were objectively measured, and lesion contrast-to-noise ratio (CNR) was calculated. Two independent blinded radiologists subjectively rated each image series using a 5-point grading scale regarding overall image quality, lesion delineation, image sharpness, and image noise.

RESULTS

Tumor attenuation peaked at 40 keV (140.2 ± 42.6 HU) followed by the 60 keV (121.7 ± 25.5 HU) and M_0.3 series (102.7 ± 22.3; all P < 0.001). However, the calculated lesion CNR was highest in the 60 keV reconstructions (12.45 ± 7.17), 80 keV reconstructions (8.66 ± 6.58), and M_0.3 series (5.21 ± 3.15; all P < 0.001) and superior to the other monoenergetic series (all P < 0.001). Subjective image analysis was highest for the 60 keV series regarding overall image quality (4.22; κ = 0.411) and lesion delineation (4.35; κ = 0.459) followed by the M_0.3 series (3.81; κ = 0.394; 3.77; κ = 0.451; all P < 0.001). Image sharpness showed no significant difference between both series (3.81 vs 3.79; P = 0.78). Image noise was rated superior in the 80 and 100 keV series (4.31 vs 4.34; P = 0.522).

CONCLUSIONS

Compared with linearly blended images, virtual monoenergetic reconstructions of DECT data at 60 keV significantly improve lesion enhancement and CNR, subjective overall image quality, and tumor delineation of head and neck squamous cell carcinoma.

Comparison of the sensitivity and specificity of 5 image sets of dual-energy computed tomography for detecting first-pass myocardial perfusion defects compared with positron emission tomography

The sensitivity and specificity of 5 different image sets of dual-energy computed tomography (DECT) for the detection of first-pass myocardial perfusion defects have not systematically been compared using positron emission tomography (PET) as a reference standard. Forty-nine consecutive patients, with known or strongly suspected of coronary artery disease, were prospectively enrolled in our study. Cardiac DECT was performed at rest state using a second-generation 128-slice dual-source CT. The DECT data were reconstructed to iodine maps, monoenergetic images, 100 kV images, nonlinearly blended images, and linearly blended images by different postprocessing techniques. The myocardial perfusion defects on DECT images were visually assessed by 5 observers, using standard 17-segment model. Diagnostic accuracy of 5 image sets was assessed using nitrogen-13 ammonia PET as the gold standard. Discrimination was quantified using the area under the receiver operating characteristic curve (AUC), and AUCs were compared using the method of DeLong. The DECT and PET examinations were successfully completed in 30 patients and a total of 90 territories and 510 segments were analyzed. Cardiac PET revealed myocardial perfusion defects in 56 territories (62%) and 209 segments (41%). The AUC of iodine maps, monoenergetic images, 100 kV images, nonlinearly blended images, and linearly blended images were 0.986, 0.934, 0.913, 0.881, and 0.871, respectively, on a per-territory basis. These values were 0.922, 0.813, 0.779, 0.763, and 0.728, respectively, on a per-segment basis. DECT iodine maps shows high sensitivity and specificity, and is superior to other DECT image sets for the detection of myocardial perfusion defects in the first-pass myocardial perfusion.

Effects of dual-energy CT with non-linear blending on abdominal CT angiography

Objective

To determine whether non-linear blending technique for arterial-phase dual-energy abdominal CT angiography (CTA) could improve image quality compared to the linear blending technique and conventional 120 kVp imaging.

Materials and Methods

This study included 118 patients who had accepted dual-energy abdominal CTA in the arterial phase. They were assigned to Sn140/80 kVp protocol (protocol A, n = 40) if body mass index (BMI) < 25 or Sn140/100 kVp protocol (protocol B, n = 41) if BMI ≥ 25. Non-linear blending images and linear blending images with a weighting factor of 0.5 in each protocol were generated and compared with the conventional 120 kVp images (protocol C, n = 37). The abdominal vascular enhancements, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and radiation dose were assessed. Statistical analysis was performed using one-way analysis of variance test, independent t test, Mann-Whitney U test, and Kruskal-Wallis test.

Results

Mean vascular attenuation, CNR, SNR and subjective image quality score for the non-linear blending images in each protocol were all higher compared to the corresponding linear blending images and 120 kVp images (p values ranging from < 0.001 to 0.007) except for when compared to non-linear blending images for protocol B and 120 kVp images in CNR and SNR. No significant differences were found in image noise among the three kinds of images and the same kind of images in different protocols, but the lowest radiation dose was shown in protocol A.

Conclusion

Non-linear blending technique of dual-energy CT can improve the image quality of arterial-phase abdominal CTA, especially with the Sn140/80 kVp scanning.

Diagnostic accuracy of late iodine-enhancement dual-energy computed tomography for the detection of chronic myocardial infarction compared with late gadolinium-enhancement 3-T magnetic resonance imaging

OBJECTIVES

The purpose of the study was to compare the performance of late iodine-enhancement (LIE) dual-energy computed tomography (DECT) linear blending and selective myocardial iodine mapping for the detection of chronic myocardial infarction (CMI) with late gadolinium-enhancement (LGE) 3-T magnetic resonance imaging.

MATERIALS AND METHODS

This study was approved by the institutional review board, and the patients gave informed consent. A total of 20 patients with a history of CMI underwent cardiac LIE-DECT and LGE-MRI. Images of the LIE-DECT were reconstructed as 100 kilovolt (peak) (kV[p]), 140 kV(p), and weighted-average (WA; linear blending) images from low- and high-kilovoltage peak data using 3 different weighting factors (0.8, 0.6, 0.3). Additional color-coded myocardial iodine distribution maps were calculated. The images were reviewed for the presence of late enhancement, transmural extent, signal characteristics, infarct volume, and subjective image quality.

RESULTS

Segmental analysis of LIE-DECT data from 100 kV(p), WA of 0.8, and WA of 0.6 showed identical results for the identification of CMI (89% sensitivity, 98% specificity, 96% accuracy) and correctly identified all segments with transmural scarring detected through LGE-MRI. Weighted average of 0.6 received the best subjective image quality rating (15/20 votes) and average measured infarct size correlated best with LGE-MRI (5.7% difference). In comparison with LGE-MRI, iodine distribution maps were susceptible to false-positive and false-negative findings (52% sensitivity, 88% specificity, 81% accuracy), overestimating quantity of transmural scars by 78% while underestimating infarct volume by 55%.

CONCLUSIONS

Late iodine enhancement cardiac dual-energy computed tomography correlates well with LGE-MRI for detecting CMI, whereas iodine distribution analysis provides inferior accuracy. Linear blending further improves image quality and enables more precise estimation of scar volume.