Value of virtual monochromatic spectral image of dual-layer spectral detector CT with noise reduction algorithm for image quality improvement in obese simulated body phantom

Halved contrast medium dose coronary dual-layer CT-angiography - phantom study of tube current and patient characteristics

Virtual mono-energetic images (VMI) using dual-layer computed tomography (DLCT) enable substantial contrast medium (CM) reductions. However, the combined impact of patient size, tube voltage, and heart rate (HR) on VMI of coronary CT angiography (CCTA) remains unknown. This phantom study aimed to assess VMI levels achieving comparable contrast-to-noise ratio (CNR) in CCTA at 50% CM dose across varying tube voltages, patient sizes, and HR, compared to the reference protocol (100% CM dose, conventional at 120 kVp). A 5 mm artificial coronary artery with 100% (400 HU) and 50% (200 HU) iodine CM-dose was positioned centrally in an anthropomorphic thorax phantom. Horizontal coronary movement was matched to HR (at 0, < 60, 60-75, > 75 bpm), with varying patient sizes simulated using phantom extension rings. Raw data was acquired using a clinical CCTA protocol at 120 and 140 kVp (five repetitions). VMI images (40-70 keV, 5 keV steps) were then reconstructed; non-overlapping 95% CNR confidence intervals indicated significant differences from the reference. Higher CM-dose, reduced VMI, slower HR, higher tube voltage, and smaller patient sizes demonstrated a trend of higher CNR. Regardless of HR, patient size, and tube voltage, no significant CNR differences were found compared to the reference, with 100% CM dose at 60 keV, or 50% CM dose at 40 keV. DLCT reconstructions at 40 keV from 120 to 140 kVp acquisitions facilitate 50% CM dose reduction for various patient sizes and HR with equivalent CNR to conventional CCTA at 100% CM dose, although clinical validation is needed.

Benefits of Dual-Layer Spectral CT Imaging in Staging and Preoperative Evaluation of Pancreatic Ductal Adenocarcinoma

Imaging of pancreatic malignancies is challenging but has a major impact on the patients therapeutic approach and outcome. In particular with pancreatic ductal adenocarcinoma (PDAC), usually a hypovascularized tumor, conventional CT imaging can be prone to errors in determining tumor extent and presence of metastatic disease. Dual-layer spectral detector CT (SDCT) is an emerging technique for acquiring spectral information without the need for prospective patient selection or specific protocols, with a detector capable of differentiating high- and low-energy photons to acquire full spectral images. In this review, we present the diagnostic benefits and capabilities of modern SDCT imaging with a focus on PDAC. We highlight the most useful virtual reconstructions in oncologic imaging and their benefits in staging and assessment of resectability in PDAC, including the assessment of tumor extent, vascular infiltration, and metastatic disease. We present imaging examples on a latest-generation SDCT scanner.

Comparative analysis of automatic segmentation of esophageal cancer using 3D Res-UNet on conventional and 40-keV virtual mono-energetic CT Images: a retrospective study

Objectives

To assess the performance of 3D Res-UNet for fully automated segmentation of esophageal cancer (EC) and compare the segmentation accuracy between conventional images (CI) and 40-keV virtual mono-energetic images (VMI_40 kev).

Methods

Patients underwent spectral CT scanning and diagnosed of EC by operation or gastroscope biopsy in our hospital from 2019 to 2020 were analyzed retrospectively. All artery spectral base images were transferred to the dedicated workstation to generate VMI_40 kev and CI. The segmentation model of EC was constructed by 3D Res-UNet neural network in VMI_40 kev and CI, respectively. After optimization training, the Dice similarity coefficient (DSC), overlap (IOU), average symmetrical surface distance (ASSD) and 95% Hausdorff distance (HD_95) of EC at pixel level were tested and calculated in the test set. The paired rank sum test was used to compare the results of VMI_40 kev and CI.

Results

A total of 160 patients were included in the analysis and randomly divided into the training dataset (104 patients), validation dataset (26 patients) and test dataset (30 patients). VMI_40 kevas input data in the training dataset resulted in higher model performance in the test dataset in comparison with using CI as input data (DSC:0.875 vs 0.859, IOU: 0.777 vs 0.755, ASSD:0.911 vs 0.981, HD_95: 4.41 vs 6.23, all p-value <0.05).

Conclusion

Fully automated segmentation of EC with 3D Res-UNet has high accuracy and clinically feasibility for both CI and VMI_40 kev. Compared with CI, VMI_40 kev indicated slightly higher accuracy in this test dataset.

Low dose of contrast agent and low radiation liver computed tomography with deep-learning-based contrast boosting model in participants at high-risk for hepatocellular carcinoma: prospective, randomized, double-blind study

OBJECTIVE

To investigate the image quality and lesion conspicuity of a deep-learning-based contrast-boosting (DL-CB) algorithm on double-low-dose (DLD) CT of simultaneous reduction of radiation and contrast doses in participants at high-risk for hepatocellular carcinoma (HCC).

METHODS

Participants were recruited and underwent four-phase dynamic CT (NCT04722120). They were randomly assigned to either standard-dose (SD) or DLD protocol. All CT images were initially reconstructed using iterative reconstruction, and the images of the DLD protocol were further processed using the DL-CB algorithm (DLD-DL). The primary endpoint was the contrast-to-noise ratio (CNR), the secondary endpoint was qualitative image quality (noise, hepatic lesion, and vessel conspicuity), and the tertiary endpoint was lesion detection rate. The t-test or repeated measures analysis of variance was used for analysis.

RESULTS

Sixty-eight participants with 57 focal liver lesions were enrolled (20 with HCC and 37 with benign findings). The DLD protocol had a 19.8% lower radiation dose (DLP, 855.1 ± 254.8 mGy·cm vs. 713.3 ± 94.6 mGy·cm, p = .003) and 27% lower contrast dose (106.9 ± 15.0 mL vs. 77.9 ± 9.4 mL, p < .001) than the SD protocol. The comparative analysis demonstrated that CNR (p < .001) and portal vein conspicuity (p = .002) were significantly higher in the DLD-DL than in the SD protocol. There was no significant difference in lesion detection rate for all lesions (82.7% vs. 73.3%, p = .140) and HCCs (75.7% vs. 70.4%, p = .644) between the SD protocol and DLD-DL.

CONCLUSIONS

DL-CB on double-low-dose CT provided improved CNR of the aorta and portal vein without significant impairment of the detection rate of HCC compared to the standard-dose acquisition, even in participants at high risk for HCC.

KEY POINTS

• Deep-learning-based contrast-boosting algorithm on double-low-dose CT provided an improved contrast-to-noise ratio compared to standard-dose CT. • The detection rate of focal liver lesions was not significantly differed between standard-dose CT and a deep-learning-based contrast-boosting algorithm on double-low-dose CT. • Double-low-dose CT without a deep-learning algorithm presented lower CNR and worse image quality.

The new fast kilovoltage-switching dual-energy computed tomography for measuring bone mineral density

Background

The update in technology may impact the accuracy in measuring bone mineral density (BMD). However, the application of the new fast kilovoltage (kV)-switching dual-energy computed tomography (DECT) for BMD measurement has not yet been reported. This study aimed to examine the accuracy and precision of the new fast kV-switching DECT in measuring BMD and to evaluate its applicability in clinical BMD measurement.

Methods

Forty sets of the new fast kV-switching DECT scans and one quantitative computed tomography (QCT) scan were performed on the European Spine Phantom. Their relative errors and relative standard deviations were compared. A retrospective analysis was performed on patients who underwent chest plain DECT and abdominal monoenergetic plain CT at the same time. The relationship between hydroxyapatite-water and hydroxyapatite-fat measured using DECT and BMD measured using QCT was analyzed by multivariate regression analysis.

Results

The relative errors of the new fast kV-switching DECT with low tube speeds (0.8 and 1.0 s/r) were all less than 6% and were less than those of QCT, except for those at 515 mA. The relative standard deviation values with high tube rotation speeds (0.5 and 0.6 s/r) were higher than those with low tube speeds (0.8 and 1.0 s/r) under most tube current conditions. The new fast kV-switching DECT-derived BMD values corrected by multiple linear regression (predicted hydroxyapatite) were significantly positively correlated with the QCT-based BMD values (R²=0.912; P<0.001). The results of the Bland-Altman analysis demonstrated high consistency between the 2 measurement methods.

Conclusions

Results of the phantom measurements indicated that the new fast kV-switching DECT could measure BMD with relatively high accuracy and precision. The results of a subsequent clinical in vivo experiment demonstrated that vertebral BMD measurements derived from DECT and QCT were mostly consistent and highly accurate. Therefore, patients who undergo DECT for other clinical indications can simultaneously have their BMD determined.

Diagnostic performance of dual-energy computed tomography for HCC after transarterial chemoembolization: Utility of virtual unenhanced and low keV virtual monochromatic images

The purpose of this study is to evaluate the usefulness of virtual unenhanced (VUE) and low keV virtual monochromatic images (VMI) for diagnosing viable hepatocellular carcinomas (HCC) after transarterial chemoembolization (TACE). This retrospective study included 53 patients with suspected viable HCC after TACE who underwent multiphasic liver computed tomography including true unenhanced (TUE) phase and conventional (CV) enhanced phases on a dual-energy scanner. VUE images, 40 keV and 55 keV VMIs of enhanced phases were reconstructed using dual-energy computed tomography data. For every patient, six combination image sets (TUE-CV; TUE-55; TUE-40; VUE-CV; VUE-55; VUE-40) were evaluated by two readers and compared with the reference standard.There was no statistically significant difference (P > .05) in sensitivity or specificity among all image combinations. In most combinations, interobserver agreements were almost perfect. The diagnostic odds ratio showed a higher trend in combinations with conventional images. Currently, with regards to diagnostic performance, liver computed tomography including TUE and CV enhanced phases is recommended for tumor surveillance after TACE because VUE and VMIs do not have a distinct advantage compared to conventional images.

Dual-Energy CT of the Heart: A Review

Dual-energy computed tomography (DECT) represents an emerging imaging technique which consists of the acquisition of two separate datasets utilizing two different X-ray spectra energies. Several cardiac DECT applications have been assessed, such as virtual monoenergetic images, virtual non-contrast reconstructions, and iodine myocardial perfusion maps, which are demonstrated to improve diagnostic accuracy and image quality while reducing both radiation and contrast media administration. This review will summarize the technical basis of DECT and review the principal cardiac applications currently adopted in clinical practice, exploring possible future applications.

Deep learning-based reconstruction of virtual monoenergetic images of kVp-switching dual energy CT for evaluation of hypervascular liver lesions: Comparison with standard reconstruction technique

OBJECTIVE

To investigate clinical applicability of deep learning(DL)-based reconstruction of virtual monoenergetic images(VMIs) of arterial phase liver CT obtained by rapid kVp-switching dual-energy CT for evaluation of hypervascular liver lesions.

MATERIALS AND METHODS

We retrospectively included 109 patients who had available late arterial phase liver CT images of the liver obtained with a rapid switching kVp DECT scanner for suspicious intra-abdominal malignancies. Two VMIs of 70 keV and 40 keV were reconstructed using adaptive statistical iterative reconstruction (ASiR-V) for arterial phase scans. VMIs at 40 keV were additionally reconstructed with a vendor-agnostic DL-based reconstruction technique (ClariCT.AI, ClariPi, DL 40 keV). Qualitative, quantitative image quality and subjective diagnostic acceptability were compared according to reconstruction techniques.

RESULTS

In qualitative analysis, DL 40 keV images showed less image noise (4.55 vs 3.11 vs 3.95, p < 0.001), better image sharpness (4.75 vs 4.16 vs 4.3, p < 0.001), better image contrast (4.98 vs 4.72 vs 4.19, p < 0.017), better lesion conspicuity (4.61 vs 4.23 vs 3.4, p < 0.001) and diagnostic acceptability (4.59 vs 3.88 vs 4.09, p < 0.001) compared with ASiR-V 40 keV or 70 keV image sets. In quantitative analysis, DL 40 keV significantly reduced image noise relative to ASiR-V 40 keV images (49.9%, p < 0.001) and ASiR-V 70 keV images (85.2%, p = 0.012). DL 40 keV images showed significantly higher CNR_{lesion to the liver} and SNR_liver than ASiR-V 40 keV image and 70 keV images (p < 0.001).

CONCLUSION

DL-based reconstruction of 40 keV images using vendor-agnostic software showed greater noise reduction, better lesion conspicuity, image contrast, image sharpness, and higher overall image diagnostic acceptability than ASiR for 40 keV or 70 keV images in patients with hypervascular liver lesions.

Virtual noncontrast images derived from dual-energy CT for assessment of hepatic steatosis in living liver donors

PURPOSE

This study aimed to investigate the correlation of attenuation between virtual noncontrast (VNC) and true noncontrast (TNC) CT images and compare the diagnostic performance for hepatic steatosis using MR spectroscopy (MRS) as the reference standard.

METHODS

A total of 131 consecutive hepatic donor candidates who underwent dual-source dual-energy CT and MRS within one month from January 2018 to April 2019 were included. An MRS value > 5.8 % was regarded as substantial hepatic steatosis. The correlation of attenuation between TNC and VNC in the liver and spleen, and liver attenuation index (LAI), defined as hepatic minus splenic attenuation, was evaluated using Spearman's rank correlation. The diagnostic performance of the LAI for hepatic steatosis was compared using receiver operating characteristic analyses.

RESULTS

Twenty-three candidates (17.6 %) had substantial hepatic steatosis. The median liver attenuation (66.7 [IQR, 63.5-70.9] vs. 63.5 [IQR, 60.3-66.9], p < .001) and LAI (12.9 [9.3-16.7] vs. 7.4 [3.9-11.9], p < .001) in the VNC were higher than those in the TNC. Hepatic attenuation (r = 0.93, p < .001), splenic attenuation (r = 0.55, p < .001), and LAI (r = 0.87, p < .001) were significantly correlated between TNC and VNC. Area under the curve of LAI in TNC and VNC were 0.88 (cutoff, LAI < 3.1) and 0.84 (cutoff, LAI < 10.1), respectively, indicating no statistically significant difference (p = 0.11).

CONCLUSION

The LAI of VNC is significantly correlated with that of TNC and might be feasible for diagnosing substantial hepatic steatosis in living liver donor candidates using different cutoff values of LAI.

Towards Personalised Contrast Injection: Artificial-Intelligence-Derived Body Composition and Liver Enhancement in Computed Tomography

In contrast-enhanced computed tomography, total body weight adapted contrast injection protocols have proven successful in achieving a homogeneous enhancement of vascular structures and liver parenchyma. However, because solid organs have greater perfusion than adipose tissue, the lean body weight (fat-free mass) rather than the total body weight is theorised to cause even more homogeneous enhancement. We included 102 consecutive patients who underwent a multiphase abdominal computed tomography between March 2016 and October 2019. Patients received contrast media (300 mgI/mL) according to bodyweight categories. Using regions of interest, we measured the Hounsfield unit (HU) increase in liver attenuation from unenhanced to contrast-enhanced computed tomography. Furthermore, subjective image quality was graded using a four-point Likert scale. An artificial intelligence algorithm automatically segmented and determined the body compositions and calculated the percentages of lean body weight. The hepatic enhancements were adjusted for iodine dose and iodine dose per total body weight, as well as percentage lean body weight. The associations between enhancement and total body weight, body mass index, and lean body weight were analysed using linear regression. Patients had a median age of 68 years (IQR: 58–74), a total body weight of 81 kg (IQR: 73–90), a body mass index of 26 kg/m² (SD: ±4.2), and a lean body weight percentage of 50% (IQR: 36–55). Mean liver enhancements in the portal venous phase were 61 ± 12 HU (≤70 kg), 53 ± 10 HU (70–90 kg), and 53 ± 7 HU (≥90 kg). The majority (93%) of scans were rated as good or excellent. Regression analysis showed significant correlations between liver enhancement corrected for injected total iodine and total body weight (r = 0.53; p < 0.001) and between liver enhancement corrected for lean body weight and the percentage of lean body weight (r = 0.73; p < 0.001). Most benefits from personalising iodine injection using %LBW additive to total body weight would be achieved in patients under 90 kg. Liver enhancement is more strongly associated with the percentage of lean body weight than with the total body weight or body mass index. The observed variation in liver enhancement might be reduced by a personalised injection based on the artificial-intelligence-determined percentage of lean body weight.

Use of dual-energy CT for renal mass assessment

Although dual-energy CT (DECT) may prove useful in a variety of abdominal imaging tasks, renal mass evaluation represents the area where this technology can be most impactful in abdominal imaging compared to routinely performed contrast-enhanced-only single-energy CT exams. DECT post-processing techniques, such as creation of virtual unenhanced and iodine density images, can help in the characterization of incidentally discovered renal masses that would otherwise remain indeterminate based on post-contrast imaging only. The purpose of this article is to review the use of DECT for renal mass assessment, including its benefits and existing limitations. KEY POINTS: • If DECT is selected as the scanning mode for most common abdominal protocols, many incidentally found renal masses can be fully triaged within the same exam. • Virtual unenhanced and iodine density DECT images can provide additional information when renal masses are discovered in the post-contrast-only setting. • For renal mass evaluation, virtual unenhanced and iodine density DECT images should be interpreted side-by-side to troubleshoot pitfalls that can potentially lead to erroneous interpretation.