Dual-Energy Computed Tomography in Patients With Small Hepatocellular Carcinoma: Utility of Noise-Reduced Monoenergetic Images for the Evaluation of Washout and Image Quality in the Equilibrium Phase

Spectral CT: Current Liver Applications

Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.

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.

Iodine maps derived from sparse-view kV-switching dual-energy CT equipped with a deep learning reconstruction for diagnosis of hepatocellular carcinoma

Deep learning-based spectral CT imaging (DL-SCTI) is a novel type of fast kilovolt-switching dual-energy CT equipped with a cascaded deep-learning reconstruction which completes the views missing in the sinogram space and improves the image quality in the image space because it uses deep convolutional neural networks trained on fully sampled dual-energy data acquired via dual kV rotations. We investigated the clinical utility of iodine maps generated from DL-SCTI scans for assessing hepatocellular carcinoma (HCC). In the clinical study, dynamic DL-SCTI scans (tube voltage 135 and 80 kV) were acquired in 52 patients with hypervascular HCCs whose vascularity was confirmed by CT during hepatic arteriography. Virtual monochromatic 70 keV images served as the reference images. Iodine maps were reconstructed using three-material decomposition (fat, healthy liver tissue, iodine). A radiologist calculated the contrast-to-noise ratio (CNR) during the hepatic arterial phase (CNRa) and the equilibrium phase (CNRe). In the phantom study, DL-SCTI scans (tube voltage 135 and 80 kV) were acquired to assess the accuracy of iodine maps; the iodine concentration was known. The CNRa was significantly higher on the iodine maps than on 70 keV images (p < 0.01). The CNRe was significantly higher on 70 keV images than on iodine maps (p < 0.01). The estimated iodine concentration derived from DL-SCTI scans in the phantom study was highly correlated with the known iodine concentration. It was underestimated in small-diameter modules and in large-diameter modules with an iodine concentration of less than 2.0 mgI/ml. Iodine maps generated from DL-SCTI scans can improve the CNR for HCCs during hepatic arterial phase but not during equilibrium phase in comparison with virtual monochromatic 70 keV images. Also, when the lesion is small or the iodine concentration is low, iodine quantification may result in underestimation.

Added value of contrast enhancement boost images in routine multiphasic contrast-enhanced CT for the diagnosis of small (<20 mm) hypervascular hepatocellular carcinoma

PURPOSE

To investigate the added value of contrast enhancement boost (CE-boost) images in multiphasic contrast-enhanced CT (CE-CT) for diagnosing small (<20 mm) hypervascular hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

This retrospective study included 69 patients (age, 74 ± 8 years; 52 men) with 70 hypervascular HCCs (<20 mm) who underwent multiphasic CE-CT (pre-contrast, late arterial phase [LAP], portal venous phase [PVP], and equilibrium phase). Two types of CE-boost images were generated by subtracting PVP from LAP (LA-PV) images and LAP from PVP (PV-LA) images to enhance the contrast effect of hepatic arterial and portal venous perfusion more selectively. Tumor-to-liver contrast-to-noise ratios (CNRs) in CE-boost images were compared with those in CE-CT images using the Wilcoxon signed-rank test. Two independent readers reviewed the imaging datasets: CE-CT alone and CE-CT with CE-boost images. The diagnostic performance of each dataset was compared using jackknife alternative free-response receiver operating characteristics (JAFROC-1).

RESULTS

The tumor-to-liver CNRs in the LA-PV (6.4 ± 3.0) and PV-LA (-3.3 ± 2.1) images were greater than those in the LAP (3.2 ± 1.7) and PVP images (-1.1 ± 1.4) (p <.001 for both). The reader-averaged figures of merit were 0.751 for CE-CT alone and 0.807 for CE-CT with CE-boost images (p <.001). Sensitivities increased by adding CE-boost images for both readers (p <.001 and = 0.03), while positive predictive values were equivalent (p >.99).

CONCLUSION

Adding CE-boost images to multiphasic CE-CT can improve the diagnostic accuracy and sensitivity for small hypervascular HCC by increasing the tumor-to-liver CNR.

The clinical value of dual-energy computed tomography and diffusion-weighted imaging in the context of liver cancer: A narrative review

The dual-energy computed tomography (DECT) and diffusion-weighted magnetic resonance imaging (DWI-MRI) are used to diagnose liver cancer. The clinical value of these two examination methods needs to be further summarized. We collected and summarized relevant literature published from 2011 to 2021. The diagnostic performance of DECT was assessed between conventional computed tomography and DWI-MRI. DWI-MRI had a 69% sensitivity for detecting small hepatocellular carcinoma (HCC) lesions and a 60% diagnostic specificity for differentiating between types of HCC lesions. DECT had a sensitivity to small liver lesions (<1 cm) of 69%, and the diagnostic specificity for HCC and metastasis was about 60%. DWI was more sensitive (90.3% vs. 74.9%) and accurate (91.9% vs. 76.9%) in diagnosing HCC compared with conventional MRI sequencing. With the aid of contrast media, DWI-MRI had 90.0% specificity for detecting small HCCs (smaller than 1 cm). Furthermore, DWI-MRI not only provided physicians with valuable diagnostic information but also delivered histological grading information, with 78% accuracy for all benign lesions and 71% for solid lesions. DECT had relatively high sensitivity and required a lower contrast medium dose. With standardized quantitative parameters, it can be an extremely useful tool for HCC surveillance. DWI-MRI is the preferred imaging process as it produces high-contrast images for supporting an early diagnosis (high sensitivity and specificity) and provides histological information using non-ionizing radiation.

Impact of dual-energy 50-keV virtual monoenergetic images on radiologist confidence in detection of key imaging findings of small hepatocellular carcinomas using multiphase liver CT

BACKGROUND

Dual-energy virtual monoenergetic images can increase iodine signal, potentially increasing the conspicuity of hepatic masses.

PURPOSE

To determine if dual-energy 50-keV virtual monoenergetic images improve visualization of key imaging findings or diagnostic confidence for small (≤2 cm) hepatocellular carcinomas (HCC) at multiphase, contrast-enhanced liver computed tomography (CT).

MATERIAL AND METHODS

Patients with chronic liver disease underwent multiphase dual-energy CT imaging for HCC, with late arterial and delayed phase dual-energy 50-keV images reconstructed. Two non-reader subspecialized gastrointestinal (GI) radiologists established the reference standard, determining the location and diagnosis of all hepatic lesions using predetermined criteria. Three GI radiologists interpreted mixed kV CT images without or with dual-energy 50-keV images. Radiologists identified potential HCCs and rated their confidence (0-100 scales) in imaging findings of arterial enhancement, enhancing capsule, tumor washout, and LI-RADS 5 (2018) category.

RESULTS

In total, 45 patients (14 women; mean age = 59.5 ± 10.9 years) with chronic liver disease were included. Of them, 19 patients had 25 HCCs ≤2 cm (mean size = 1.5 ± 0.4 cm). There were 17 LI-RADS 3 and 4 lesions and 19 benign lesions. Reader confidence in imaging findings of arterial enhancement, enhancing capsule, and non-peripheral washout significantly increased with dual-energy images (P ≤ 0.022). Overall confidence in HCC diagnosis increased significantly with dual-energy 50-keV images (52.4 vs. 68.8; P = 0.001). Dual-energy images demonstrated a slight but significant decrease in overall image quality.

CONCLUSION

Radiologist confidence in key imaging features of small HCCs and confidence in imaging diagnosis increases with use of dual-energy 50-keV images at multiphase, contrast-enhanced liver CT.

Value of spectral detector computed tomography for the early assessment of technique efficacy after microwave ablation of hepatocellular carcinoma

OBJECTIVES

To investigate whether virtual monoenergetic images (VMI) and iodine maps derived from spectral detector computed tomography (SDCT) improve early assessment of technique efficacy in patients who underwent microwave ablation (MWA) for hepatocellular carcinoma (HCC) in liver cirrhosis.

METHODS

This retrospective study comprised 39 patients with 49 HCC lesions treated with MWA. Biphasic SDCT was performed 7.7±4.0 days after ablation. Conventional images (CI), VMI and IM were reconstructed. Signal- and contrast-to-noise ratio (SNR, CNR) in the ablation zone (AZ), hyperemic rim (HR) and liver parenchyma were calculated using regions-of-interest analysis and compared between CI and VMI between 40-100 keV. Iodine concentration and perfusion ratio of HR and residual tumor (RT) were measured. Two readers evaluated subjective contrast of AZ and HR, technique efficacy (complete vs. incomplete ablation) and diagnostic confidence at determining technique efficacy.

RESULTS

Attenuation of liver parenchyma, HR and RT, SNR of liver parenchyma and HR, CNR of AZ and HR were significantly higher in low-keV VMI compared to CI (all p<0.05). Iodine concentration and perfusion ratio differed significantly between HR and RT (all p<0.05; e.g. iodine concentration, 1.6±0.5 vs. 2.7±1.3 mg/ml). VMI50keV improved subjective AZ-to-liver contrast, HR-to-liver contrast, visualization of AZ margin and vessels adjacent to AZ compared to CI (all p<0.05). Diagnostic accuracy for detection of incomplete ablation was slightly higher in VMI50keV compared to CI (0.92 vs. 0.89), while diagnostic confidence was significantly higher in VMI50keV (p<0.05).

CONCLUSIONS

Spectral detector computed tomography derived low-keV virtual monoenergetic images and iodine maps provide superior early assessment of technique efficacy of MWA in HCC compared to CI.

Advanced CT techniques for assessing hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the sixth-most common cancer in the world, and hepatic dynamic CT studies are routinely performed for its evaluation. Ongoing studies are examining advanced imaging techniques that may yield better findings than are obtained with conventional hepatic dynamic CT scanning. Dual-energy CT-, perfusion CT-, and artificial intelligence-based methods can be used for the precise characterization of liver tumors, the quantification of treatment responses, and for predicting the overall survival rate of patients. In this review, the advantages and disadvantages of conventional hepatic dynamic CT imaging are reviewed and the general principles of dual-energy- and perfusion CT, and the clinical applications and limitations of these technologies are discussed with respect to HCC. Finally, we address the utility of artificial intelligence-based methods for diagnosing HCC.

Triple-Phase Computed Tomography May Replace Dual-Energy X-ray Absorptiometry Scan for Evaluation of Osteoporosis in Liver Transplant Candidates

Assessment of bone density is an important part of liver transplantation (LT) evaluation for early identification and treatment of osteoporosis. Dual-energy X-ray absorptiometry (DXA) is currently the standard clinical test for osteoporosis; however, it may contribute to the appointment burden on LT candidates during the cumbersome evaluation process, and there are limitations affecting its accuracy. In this study, we evaluate the utility of biomechanical analysis of vertebral images obtained during dual-energy abdominal triple-phase computed tomography (TPCT) in diagnosing osteoporosis among LT candidates. We retrospectively reviewed cases evaluated for LT between January 2017 and March 2018. All patients who underwent TPCT within 3 months of DXA were included. The biomechanical computed tomography (BCT) analysis was performed at a centralized laboratory (O.N. Diagnostics, Berkeley, CA) by 2 trained analysts blinded to the DXA data. DXA-based osteoporosis was defined as a T score ≤-2.5 at the hip or spine. BCT-based osteoporosis was defined as vertebral strength ≤4500 N for women or ≤6500 N for men or trabecular volumetric bone mineral density ≤80 mg/cm³ . Comparative data were available for 91 patients who had complete data for both DXA and BCT: 31 women and 60 men, age 54 ± 11 years (mean ± standard deviation), mean body mass index 28 ± 6 kg/m² . Using DXA as the clinical reference, sensitivity of BCT to detect DXA-defined osteoporosis was 83.3% (20/24 patients) and negative predictive value was 91.7%; specificity and positive predictive value were 65.7% and 46.5%, respectively. BCT analysis of vertebral images on triple-phase computed tomography, routinely obtained during transplant evaluation, can reliably rule out osteoporosis in LT candidates. Patients with suspicion of osteoporosis on TPCT may need further evaluation by DXA.

Virtual monoenergetic images from spectral detector computed tomography facilitate washout assessment in arterially hyper-enhancing liver lesions

Objectives

To investigate whether the increased soft tissue contrast of virtual monoenergetic images (VMIs) obtained from a spectral detector computed tomography (SDCT) system improves washout assessment of arterially hyper-enhancing liver lesions.

Methods

Fifty-nine arterially hyper-enhancing lesions in 31 patients (age 65 ± 9 years, M/W 20/11) were included in this IRB-approved study. All patients underwent multi-phase SDCT for HCC screening. MRI, CEUS or biopsy within 3 months served as standard of reference to classify lesions as LiRADS 3 or 4/5. VMIs and conventional images (CIs) were reconstructed. Visual analysis was performed on 40, 60, and 80 kiloelectronvolt (keV) and CIs by 3 radiologists. Presence and visibility of washout were assessed; image quality and confidence of washout evaluation were evaluated on 5-point Likert scales. Signal-to-noise ratio (SNR), lesion-to-liver contrast-to-noise ratio (CNR) (|HU_lesion–HU_liver|/SD_liver) and washout (|HU_lesion–HU_liver|) were calculated. Statistical assessment was performed using ANOVA and Wilcoxon test.

Results

On subjective lesion analysis, the highest level of diagnostic confidence and highest sensitivity for the detection of lesion washout were found for 40-keV VMIs (40 keV vs. CI, 81.3 vs. 71.3%). Image quality parameters were significantly better in low-kiloelectronvolt VMIs than in CIs (p < 0.05; e.g. SNR_liver: 40 keV vs. CIs, 12.5 ± 4.1 vs. 5.6 ± 1.6). In LiRADS 4/5 lesions, CNR and quantitative washout values were significantly higher in 40-keV VMIs compared to CIs (p < 0.05; e.g. CNR and washout in 40 keV vs. CIs, 2.3 ± 1.6 vs. 0.8 ± 0.5 and 29.0 ± 19.1 vs. 12.9 ± 6.9 HU, respectively).

Conclusion

By increasing lesion contrast, low-kiloelectronvolt VMIs obtained from SDCT improve washout assessment of hyper-enhancing liver lesions with respect to washout visibility and diagnostic confidence.

Key Points

• Low-kiloelectronvolt virtual monoenergetic images from spectral detector CT facilitate washout assessment in arterially hyper-enhancing liver lesions.

• Image quality and quantitative washout parameters as well as subjective washout visibility and diagnostic confidence benefit from low-kiloelectronvolt virtual monoenergetic images.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07379-3) contains supplementary material, which is available to authorized users.

Dual-energy CT in diffuse liver disease: is there a role?

Dual-energy CT (DECT) can be defined as the use of two different energy levels to identify and quantify material composition. Since its inception, DECT has benefited from remarkable improvements in hardware and clinical applications. DECT enables accurate identification and quantification of multiple materials, including fat, iron, and iodine. As a consequence, multiple studies have investigated the potential role of DECT in the assessment of diffuse liver diseases. While this role is evolving, this article aims to review the most relevant literature on use of DECT for assessment of diffuse liver diseases. Moreover, the basic concepts on DECT techniques, types of image reconstruction, and DECT-dedicated software will be described, focusing on the areas that are most relevant for the evaluation of diffuse liver diseases. Also, we will review the evidence of added value of DECT in detection and assessment of hepatocellular carcinoma which is a known risk in patients with diffuse liver disease.

Deep learning reconstruction of equilibrium phase CT images in obese patients

PURPOSE

To compare abdominal equilibrium phase (EP) CT images of obese and non-obese patients to identify the reconstruction method that preserves the diagnostic value of images obtained in obese patients.

METHODS

We compared EP images of 50 obese patients whose body mass index (BMI) exceeded 25 (group 1) with EP images of 50 non-obese patients (BMI < 25, group 2). Group 1 images were subjected to deep learning reconstruction (DLR), hybrid iterative reconstruction (hybrid-IR), and model-based IR (MBIR), group 2 images to hybrid-IR; group 2 hybrid-IR images served as the reference standard. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise. The overall image quality was assessed by 3 other radiologists; they used a confidence scale ranging from 1 (unacceptable) to 5 (excellent). Non-inferiority and potential superiority were assessed.

RESULTS

With respect to the image noise, group 1 DLR- were superior to group 2 hybrid-IR images; group 1 hybrid-IR- and MBIR images were neither superior nor non-inferior to group 2 hybrid-IR images. The quality scores of only DLR images in group 1 were superior to hybrid-IR images of group 2 while the quality scores of group 1 hybrid-IR- and MBIR images were neither superior nor non-inferior to group 2 hybrid-IR images.

CONCLUSIONS

DLR preserved the quality of EP images obtained in obese patients.

Advances in the early diagnosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers globally. In contrast to the declining death rates observed for all other common cancers such as breast, lung, and prostate cancers, the death rates for HCC continue to increase by ~2–3% per year because HCC is frequently diagnosed late and there is no curative therapy for an advanced HCC. The early diagnosis of HCC is truly a big challenge. Over the past years, the early diagnosis of HCC has relied on surveillance with ultrasonography (US) and serological assessments of alpha-fetoprotein (AFP). However, the specificity and sensitivity of US/AFP is not satisfactory enough to detect early onset HCC. Recent technological advancements offer hope for early HCC diagnosis. Herein, we review the progress made in HCC diagnostics, with a focus on emerging imaging techniques and biomarkers for early disease diagnosis.

Dual-energy computed tomography for evaluation of breast cancer: value of virtual monoenergetic images reconstructed with a noise-reduced monoenergetic reconstruction algorithm

PURPOSE

To evaluate the image quality and lesion visibility of virtual monoenergetic images (VMIs) reconstructed using a new monoenergetic reconstruction algorithm (nMERA) for evaluation of breast cancer.

MATERIALS AND METHODS

Forty-two patients with 46 breast cancers who underwent 4-phasic breast contrast-enhanced computed tomography (CT) using dual-energy CT (DECT) were enrolled. We selected the peak enhancement phase of the lesion in each patient. The selected phase images were generated by 120-kVp-equivalent linear blended (M120) and monoenergetic reconstructions from 40 to 80 keV using the standard reconstruction algorithm (sMERA: 40, 50, 60, 70, 80) and nMERA (40 +, 50 +, 60 +, 70 +, 80 +). The contrast-to-noise ratio (CNR) was calculated and objectively analyzed. Two independent readers subjectively scored tumor visibility and image quality each on a 5-point scale.

RESULTS

The CNR at 40 + and tumor visibility scores at 40 + and 50 + were significantly higher than those on M120. The CNR at 50 + was not significantly different from that on M120. However, the overall image quality score at 40 + was significantly lower than that at 50 + and on M120 (40 + vs M120, P < 0.0001 and 40 + vs 50 +, P = 0.0001).

CONCLUSIONS

VMI reconstructed with nMERA at 50 keV is preferable for evaluation of patients with breast cancer.