Noise characteristics of virtual monoenergetic images from a novel detector-based spectral CT scanner

Virtual Monoenergetic Images for Diagnostic Assessment of Hypodense Lesions Within the Liver: Semiautomatic Estimation of Window Settings Using Linear Models

OBJECTIVE

The aim of the study was to establish the reference window settings for display of virtual monoenergetic images (VMIs) from spectral detector computed tomography when assessing hypodense liver lesions.

METHODS

In patients with cysts (n = 24) or metastases (n = 26), objective (HU, signal-to-noise ratio [SNR]) and subjective (overall image quality, lesion conspicuity and noise) were assessed. Furthermore, 2 readers determined optimal window center/width (C/W) for conventional images (CIs) and VMIs of 40 to 120 keV. Center/width were modeled against HUliv with and without respect to the keV level (models A and B).

RESULTS

Attenuation and SNR were significantly higher in low-keV VMIs and improved overall image quality and lesion conspicuity (P ≤ 0.05). Model B provided valid estimations of C/W, whereas model A was slightly less accurate.

CONCLUSIONS

The increase in attenuation and SNR on low-keV VMIs requires adjustment of C/W, and they can be estimated in dependency of HUliv using linear models. Reference values for standard display of VMIs of 40 to 120 keV are reported.

Improved visualization of hypodense liver lesions in virtual monoenergetic images from spectral detector CT: Proof of concept in a 3D-printed phantom and evaluation in 74 patients

OBJECTIVES

The well-known boost of iodine associated-attenuation in low-keV virtual monoenergetic images (VMI_low) is frequently used to improve visualization of lesions and structures taking up contrast media. This study aimed to evaluate this concept in reverse. Hence to investigate if increased attenuation within the liver allows for improved visualization of little or not-enhancing lesions.

METHODS

A 3D-printed phantom mimicking the shape of a human liver exhibiting a lesion in its center was designed and printed. Both, parenchyma- and lesion-mimic were filled with different solutions exhibiting 80/100/120HU and 0/15/40/60HU, respectively. Further, a total of 74 contrast-enhanced studies performed on a spectral detector CT scanner (SDCT) were included in this retrospective study. Patients had MRI or follow-up proven cysts and/or hypodense metastases. VMI of 40-200 keV as well as conventional images (CI) were reconstructed. ROI were placed in lesion and parenchyma(-mimics) on CI and transferred to VMI. Signal- and contrast-to-noise ratio were calculated (S-/CNR). Further, two radiologists independently evaluated image quality. Data was statistically assessed using ANOVA or Wilcoxon-test.

RESULTS

In phantoms, S/CNR was significantly higher in VMI_low. The cyst-mimic in highly attenuating parenchyma-mimic on CI yielded a CNR of 6.4 ± 0.8; using VMI_40 keV, mildly hypodense lesion-mimic in poorly attenuating parenchyma-mimic exhibited a similar CNR (5.8 ± 0.9; p ≤ 0.05). The same tendency was observed in patients (cyst in CI/metastasis in VMI_40 keV: 4.4 ± 1.2/3.9 ± 1.8; p ≤ 0.05). Qualitative analysis indicated a benefit of VMI_40 keV (p ≤ 0.05).

CONCLUSIONS

VMI_low from SDCT allow for an improved visualization of hypodense focal liver lesions exploiting the concept of contrast blooming in reverse.

Dual-layer dual-energy computed tomography for the assessment of hypovascular hepatic metastases: impact of closing k-edge on image quality and lesion detectability

OBJECTIVES

To evaluate the image quality of virtual-monoenergetic-imaging (VMI) from dual-layer dual-energy CT (DLCT) for the assessment of hypovascular liver metastases and its effect on lesion detectability.

METHODS

Eighty-one patients with hypovascular-liver-metastases undergoing portal-venous-phase abdominal DLCT were included. Polyenergetic-images (PEI) and VMI at 40-200 keV (VMI_40-200, 10-keV interval) were reconstructed. Image noise, tumor-to-liver contrast, and contrast-to-noise ratio (CNR) of hepatic parenchyma and metastatic nodules (n = 288) were measured to determine the optimal monoenergetic levels. Two radiologists independently and subjectively assessed the image quality (image contrast, image noise, and diagnostic confidence) of PEI and optimal VMI on 5-point scales to determine the best energy. For 38 patients having up to 10 metastases each with diameters < 25 mm (153 lesions), we compared blindly assessed lesion detectability and conspicuity between PEI and VMI at the best energy.

RESULTS

Image noise of VMI_40-200 was consistently lower than that of PEI (p < 0.01). Tumor-to-liver contrast and CNR increased as the energy decreased with CNR at VMI_40-70 being higher than that observed on PEI (p < 0.01). The highest subjective score for diagnostic confidence was assigned at VMI₄₀ followed by VMI_50-70, all of which were significantly better than that of PEI (p < 0.01, kappa = 0.75). Lesion detectability at VMI₄₀ was significantly superior to PEI, especially for lesions with diameters of < 10 mm (p < 0.01, kappa ≥ 0.6).

CONCLUSIONS

VMI_40-70 provided a better subjective and objective image quality for the evaluation of hypovascular liver metastases, and the lesion detectability was improved with use of VMI₄₀ compared with conventional PEI.

KEY POINTS

• DLCT-VMI at 40-70 keV provides a superior subjective and objective image quality compared with conventional PEI for the assessment of hypovascular hepatic metastases during portal venous phase. • Tumor-to-liver contrast and CNR of hypovascular hepatic metastases was maximized at 40 keV without a relevant increase in the image noise. • VMI at 40 keV yields a superior lesion detectability, especially for small (< 1 cm) metastatic nodules compared with conventional PEI.

Utility of virtual monoenergetic images derived from a dual-layer detector-based spectral CT in the assessment of aortic anatomy and pathology: A retrospective case control study

OBJECTIVES

To evaluate the ability of the retrospectively generated virtual monoenergetic images (VMIs) from a dual-layer detector-based spectral computed tomography (SDCT) to augment aortic enhancement for the evaluation of aortic anatomy and pathology.

METHODS

98 patients with suboptimal aortic enhancement (≤200 HU) were retrospectively identified from SDCT scans. VMI from 40 to 80 keV were generated. Attenuation, noise, SNR, and CNR were measured at seven levels in the aorta. Image quality was graded on a 5-point scale, 5 being the best. From the VMI, an ideal set was chosen with mean vascular attenuation above 200 HU while maintaining diagnostic quality. Image parameters and quality of this ideal-set were compared to the standard 120-kVp images.

RESULTS

The mean attenuation of all seven measured anatomical regions was 156.6 ± 61.7 HU in the 120-kVp images. Attenuation of the VMI from 40 to 70 keV were higher than the 120-kVp image, measuring 439.2 ± 215.3 HU, 298.5 ± 140.6 HU, 213.4 ± 94.3 HU, and 164.7 ± 90.2 HU, for 40 keV, 50 keV, 60 keV, and 70 keV, respectively (p value <0.01 for 40, 50, 60 keV; 0.07 for 70 keV). SNR and CNR showed similar trends. The 50 keV VMI had the best image quality (4.48 ± 0.84 vs. 2.24 ± 0.92 on 120-kVp images, p < 0.001). Attenuation, CNR, and SNR increased by 90.6%, 85.0%, and 108.1% at 50 keV compared to 120-kVp.

CONCLUSIONS

A contrast-enhanced CT study can be optimized for the assessment of the aorta by using low-energy VMI obtained using SDCT. At the optimal monoenergetic level, attenuation, SNR, CNR and image quality were significantly higher than that of conventional polyenergetic images.