A noise-optimized virtual monoenergetic reconstruction algorithm improves the diagnostic accuracy of late hepatic arterial phase dual-energy CT for the detection of hypervascular liver lesions

Lean body weight-based contrast injection protocol in liver CT: optimization of contrast medium dose

OBJECTIVES

To evaluate liver enhancement and image quality of abdominal CECT examinations acquired with multiple LBW-based contrast medium injection protocols.

MATERIAL & METHODS

One hundred fifty patients who underwent a clinically indicated CECT examination were prospectively and randomly assigned to one of the following contrast medium injection protocol groups: A, 700 mg iodine(I)/kg of LBW; B, 650 mgI/kg of LBW; and C, 600 mgI/kg of LBW. Liver signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and magnitude of contrast enhancement (ΔHU) were calculated. Subjective image quality was assessed with 5-point Likert scale.

RESULTS

The final population included 145 patients (64 females), with 50, 48, and 47 in group A, B, and C, respectively. Group A showed significantly higher SNR, CNR and ΔHU than group B (p = .018, p = .004, and p = .031, respectively) and group C (p = .024, p = .043, and p = .004). Group B had similar SNR, CNR, and ΔHU to group C (all p = 1). ΔHU was < 50 HU in 2, 7, and 11 patients in group A (48.2 ± 0.1), B (43.7 ± 5), and C (44.4 ± 5), respectively. Group A achieved the highest scores in terms of overall image quality, artifacts, and diagnostic confidence (both scores: 4; IQRs: 4-5) compared to group B (both scores: 3; IQRs: 3-5; p ≥ .037) and group C (overall image quality score: 3; IQR: 2-5; p = .011. Artifact and diagnostic confidence score: 3; IQR: 1-4; p ≥ .009).

CONCLUSIONS

A dosage of 700 mgI/kg of LBW yields optimal liver enhancement and grants higher image quality compared to lower contrast medium dosages.

Predicting High-Risk Esophageal Varices in Cirrhosis: A Multi-Parameter Splenic CT Study

RATIONALE AND OBJECTIVES

To explore the value of splenic hemodynamic parameters from low-dose one-stop dual-energy and perfusion CT (LD-DE&PCT) in non-invasively predicting high-risk esophageal varices (HREV) in cirrhotic patients.

METHODS

We retrospectively analyzed cirrhotic patients diagnosed with esophageal varices (EV) through clinical, laboratory, imaging, and endoscopic examinations from September 2021 to December 2023 in our hospital. All patients underwent LD-DE&PCT to acquire splenic iodine concentration and perfusion parameters. Radiation dose was recorded. Patients were classified into non-HREV and HREV groups based on endoscopy. Univariate and multivariate logistic regression analysis were performed, and the prediction model for HREV was constructed. P < 0.05 was considered statistically significant.

RESULTS

Univariate analysis revealed that significant differences were found in portal iodine concentration (PIC), blood flow (BF), permeability surface (PS), spleen volume (V-S), total iodine concentration (TIC), and total blood volume of the spleen (BV-S) between groups. TIC demonstrated the highest predictive value with an area under the curve (AUC) value of 0.87. Multivariate analysis showed that PIC, PS, and BV-S were independent risk factors for HREV. The logistic regression model for predicting HREV had an AUC of 0.93. The total radiation dose was 20.66 ± 4.07 mSv.

CONCLUSION

Splenic hemodynamic parameters obtained from LD-DE&PCT can non-invasively and accurately assess the hemodynamic status of the spleen in cirrhotic patients with EV and predict the occurrence of HREV. Despite the retrospective study design and limited sample size of this study, these findings deserve further validation through prospective studies with larger cohorts.

Impact of deep Learning-enhanced contrast on diagnostic accuracy in stroke CT angiography

PURPOSE

To examine the impact of deep learning-augmented contrast enhancement on image quality and diagnostic accuracy of poorly contrasted CT angiography in patients with suspected stroke.

METHODS

This retrospective single-centre study included 102 consecutive patients who underwent CT imaging for suspected stroke between 01/2021 and 12/2022, including whole brain volume perfusion CT (VPCT) and, specifically, a poorly contrasted CT angiography (defined as < 350HU in the proximal MCA). CT angiography imaging data was reconstructed using i.) an iterative reconstruction kernel (conventional CTA, c-CTA) as well as ii.) an iodine-based contrast boosting deep learning model (Deep Learning-enhanced CTA, DLe-CTA). For quantitative analysis, the slope, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were determined. Qualitative image analysis was conducted by three readers, rating image quality and vessel-specific parameters on a 4-point Likert scale. Readers evaluated both datasets for cerebral vessel occlusion presence. VPCT served as the reference standard for calculating sensitivity and specificity.

RESULTS

102 patients were evaluated (mean age 69 ± 13 years; 70 men). DLe-CTA outperformed c-CTA in quantitative (all items p < 0.001) and qualitative image analysis (all items p < 0.05). VPCT revealed 58/102 patients with vascular occlusion. DLe-CTA resulted in significantly higher sensitivity compared to c-CTA (p < 0.001); (all readers put together: c-CTA: 142/174 [81.6 %; 95 % CI: 75.0 %-87.1 %] vs. DLe-CTA 163/174 [94 %; 95 % CI: 89.0 %-96.8 %]). One false positive finding occurred on DLe-CTA (specificity 1/132) [99.2 %; 95 % CI: 95.9 %-100 %].

CONCLUSIONS

Deep learning-augmented contrast enhancement improves the image quality and increases the sensitivity of detection vessel occlusions in poorly contrasted CTA.

Diagnostic Imaging Performance of Dual-Energy Computed Tomography Compared with Conventional Computed Tomography and Magnetic Resonance Imaging for Uterine Cervical Cancer

Objective  This article evaluates the ability of low-energy (40 keV) virtual monoenergetic images (VMIs) in the local diagnosis of cervical cancer compared with that of conventional computed tomography (C-CT) and magnetic resonance imaging (MRI), using clinicopathologic staging as a reference. Methods  This prospective study included 33 patients with pathologically confirmed cervical cancer who underwent dual-energy CT and MRI between 2021 and 2022. The contrast-to-noise ratio (CNR) of the tumor-to-myometrium was compared between C-CT and VMI. Additionally, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) for each local diagnostic parameter were compared between C-CT, VMI, and MRI. Interradiologist agreement was also assessed. Results  The mean CNR was significantly higher on VMI ( p  = 0.002). No significant difference in AUC was found between C-CT and VMI for all local diagnostic parameters, and the specificity of VMI was often significantly less than that of MRI. For parametrial invasion, mean sensitivity, specificity, and AUC for C-CT, VMI, and MRI were 0.81, 0.99, 0.93; 0.64, 0.35, 0.79; and 0.73, 0.67, 0.86, respectively, and MRI had significantly higher specificity and AUC than that of VMI ( p  = 0.013 and 0.008, respectively). Interradiologist agreement was higher for VMI than C-CT and for MRI than VMI. Conclusion  The CNR of VMI was significantly higher than C-CT and interradiologist agreement was better than with C-CT; however, the overall diagnostic performance of VMI did not significantly differ from C-CT and was inferior to MRI. VMI was characterized by low specificity, which should be understood and used for reading.

Low energy virtual monochromatic CT with deep learning image reconstruction to improve delineation of endoleaks

AIM

This study aimed to investigate the utility of low-energy virtual monochromatic imaging (VMI) combined with deep-learning image reconstruction (DLIR) in improving the delineation of endoleaks (ELs) after endovascular aortic repair (EVAR) in contrast-enhanced dual-energy CT (DECT).

METHODS

A total of 61 consecutive patients (mean age, 77 years; 46 men) after EVAR who underwent contrast-enhanced DECT were enrolled. Virtual monochromatic 40- and 70-keV images were reconstructed using DLIR (TrueFidelity-H) and conventional hybrid iterative reconstruction (IR). Contrast-to-noise ratio (CNR) of the EL on the venous-phase CT was calculated. Four different reconstructed image series (hybrid IR and DLIR at two energy levels, 40- and 70-keV) were displayed side-by-side and visually assessed for EL conspicuity on a 5-point comparative scale from 0 (best) to -4 (significantly inferior). Two experienced radiologists independently conducted a qualitative evaluation of the CT images.

RESULTS

A total of 30 out of 61 patients presented with an EL. On both 40- and 70-keV images, the CNR of the EL was significantly higher in DLIR than in hybrid IR (40-keV, 14.5 ± 7.3 vs 8.6 ± 4.2, P<0.001; 70-keV, 8.7 ± 4.5 vs 5.5 ± 2.6, P<0.001). The comparative scale of EL conspicuity in the 40-keV DLIR images (Observer1, -0.2 ± 0.4; Observer2, 0.0 ± 0.0) was significantly higher than 40-keV hybrid IR (Observer1, -0.5 ± 0.5; Observer2, -1.0 ± 0.0; P<0.05), 70-keV DLIR (Observer1, -1.8 ± 0.4; Observer2, -2.0 ± 0.0; P<0.001) and 70-keV hybrid IR images (Observer1, -1.8 ± 0.4; Observer2, -2.4 ± 0.5; P<0.001), respectively.

CONCLUSIONS

Using 40-keV VMI in combination with DLIR improves EL delineation after EVAR compared with the 70-keV VMI with hybrid IR or DLIR.

Dual-Energy and Photon-Counting Computed Tomography in Vascular Applications-Technical Background and Post-Processing Techniques

The field of computed tomography (CT), which is a basic diagnostic tool in clinical practice, has recently undergone rapid technological advances. These include the evolution of dual-energy CT (DECT) and development of photon-counting computed tomography (PCCT). DECT enables the acquisition of CT images at two different energy spectra, which allows for the differentiation of certain materials, mainly calcium and iodine. PCCT is a recent technology that enables a scanner to quantify the energy of each photon gathered by the detector. This method gives the possibility to decrease the radiation dose and increase the spatial and temporal resolutions of scans. Both of these techniques have found a wide range of applications in radiology, including vascular studies. In this narrative review, the authors present the principles of DECT and PCCT, outline their advantages and drawbacks, and briefly discuss the application of these methods in vascular radiology.

Low-dose liver CT: image quality and diagnostic accuracy of deep learning image reconstruction algorithm

OBJECTIVES

To perform a comprehensive within-subject image quality analysis of abdominal CT examinations reconstructed with DLIR and to evaluate diagnostic accuracy compared to the routinely applied adaptive statistical iterative reconstruction (ASiR-V) algorithm.

MATERIALS AND METHODS

Oncologic patients were prospectively enrolled and underwent contrast-enhanced CT. Images were reconstructed with DLIR with three intensity levels of reconstruction (high, medium, and low) and ASiR-V at strength levels from 10 to 100% with a 10% interval. Three radiologists characterized the lesions and two readers assessed diagnostic accuracy and calculated signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), figure of merit (FOM), and subjective image quality, the latter with a 5-point Likert scale.

RESULTS

Fifty patients (mean age: 70 ± 10 years, 23 men) were enrolled and 130 liver lesions (105 benign lesions, 25 metastases) were identified. DLIR_H achieved the highest SNR and CNR, comparable to ASiR-V 100% (p ≥ .051). DLIR_M returned the highest subjective image quality (score: 5; IQR: 4-5; p ≤ .001) and significant median increase (29%) in FOM (p < .001). Differences in detection were identified only for lesions ≤ 0.5 cm: 32/33 lesions were detected with DLIR_M and 26 lesions were detected with ASiR-V 50% (p = .031). Lesion accuracy of was 93.8% (95% CI: 88.1, 97.3; 122 of 130 lesions) for DLIR and 87.7% (95% CI: 80.8, 92.8; 114 of 130 lesions) for ASiR-V 50%.

CONCLUSIONS

DLIR yields superior image quality and provides higher diagnostic accuracy compared to ASiR-V in the assessment of hypovascular liver lesions, in particular for lesions ≤ 0.5 cm.

CLINICAL RELEVANCE STATEMENT

Deep learning image reconstruction algorithm demonstrates higher diagnostic accuracy compared to iterative reconstruction in the identification of hypovascular liver lesions, especially for lesions ≤ 0.5 cm.

KEY POINTS

• Iterative reconstruction algorithm impacts image texture, with negative effects on diagnostic capabilities. • Medium-strength deep learning image reconstruction algorithm outperforms iterative reconstruction in the diagnostic accuracy of ≤ 0.5 cm hypovascular liver lesions (93.9% vs 78.8%), also granting higher objective and subjective image quality. • Deep learning image reconstruction algorithm can be safely implemented in routine abdominal CT protocols in place of iterative reconstruction.

Dual-Energy CT in Oncologic Imaging

Dual-energy CT (DECT) is an innovative technology that is increasingly widespread in clinical practice. DECT allows for tissue characterization beyond that of conventional CT as imaging is performed using different energy spectra that can help differentiate tissues based on their specific attenuation properties at different X-ray energies. The most employed post-processing applications of DECT include virtual monoenergetic images (VMIs), iodine density maps, virtual non-contrast images (VNC), and virtual non-calcium (VNCa) for bone marrow edema (BME) detection. The diverse array of images obtained through DECT acquisitions offers numerous benefits, including enhanced lesion detection and characterization, precise determination of material composition, decreased iodine dose, and reduced artifacts. These versatile applications play an increasingly significant role in tumor assessment and oncologic imaging, encompassing the diagnosis of primary tumors, local and metastatic staging, post-therapy evaluation, and complication management. This article provides a comprehensive review of the principal applications and post-processing techniques of DECT, with a specific focus on its utility in managing oncologic patients.

Review of Clinical Applications of Dual-Energy CT in Patients after Endovascular Aortic Repair

Abdominal aortic aneurysms (AAAs) are a significant cause of mortality in developed countries. Endovascular aneurysm repair (EVAR) is currently the leading treatment method for AAAs. Due to the high sensitivity and specificity of post-EVAR complication detection, CT angiography (CTA) is the reference method for imaging surveillance in patients after EVAR. Many studies have shown the advantages of dual-energy CT (DECT) over standard polyenergetic CTA in vascular applications. In this article, the authors briefly discuss the technical principles and summarize the current body of literature regarding dual-energy computed tomography angiography (DECTA) in patients after EVAR. The authors point out the most useful applications of DECTA in this group of patients and its advantages over conventional CTA. To conduct this review, a search was performed using the PubMed, Google Scholar, and Web of Science databases.

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.

Photon-Counting Detector CT With Quantum Iterative Reconstruction: Impact on Liver Lesion Detection and Radiation Dose Reduction

OBJECTIVES

To assess image noise, diagnostic performance, and potential for radiation dose reduction of photon-counting detector (PCD) computed tomography (CT) with quantum iterative reconstruction (QIR) in the detection of hypoattenuating and hyperattenuating focal liver lesions compared with energy-integrating detector (EID) CT.

MATERIALS AND METHODS

A medium-sized anthropomorphic abdominal phantom with liver parenchyma and lesions (diameter, 5-10 mm; hypoattenuating and hyperattenuating from -30 HU to +90 HU at 120 kVp) was used. The phantom was imaged on ( a ) a third-generation dual-source EID-CT (SOMATOM Force, Siemens Healthineers) in the dual-energy mode at 100 and 150 kVp with tin filtration and ( b ) a clinical dual-source PCD-CT at 120 kVp (NAEOTOM Alpha, Siemens). Scans were repeated 10 times for each of 3 different radiation doses of 5, 2.5, and 1.25 mGy. Datasets were reconstructed as virtual monoenergetic images (VMIs) at 60 keV for both scanners and as linear-blended images (LBIs) for EID-CT. For PCD-CT, VMIs were reconstructed with different strength levels of QIR (QIR 1-4) and without QIR (QIR-off). For EID-CT, VMIs and LBIs were reconstructed using advanced modeled iterative reconstruction at a strength level of 3. Noise power spectrum was measured to compare image noise magnitude and texture. A channelized Hotelling model observer was used to assess diagnostic accuracy for lesion detection. The potential for radiation dose reduction using PCD-CT was estimated for the QIR strength level with the highest area under the curve compared with EID-CT for each radiation dose.

RESULTS

Image noise decreased with increasing QIR level at all radiation doses. Using QIR-4, noise reduction was 41%, 45%, and 59% compared with EID-CT VMIs and 12%, 18%, and 33% compared with EID-CT LBIs at 5, 2.5, and 1.25 mGy, respectively. The peak spatial frequency shifted slightly to lower frequencies at higher QIR levels. Lesion detection accuracy increased at higher QIR levels and was higher for PCD-CT compared with EID-CT VMIs. The improvement in detection with PCD-CT was strongest at the lowest radiation dose, with an area under the receiver operating curve of 0.917 for QIR-4 versus 0.677 for EID-CT VMIs for hyperattenuating lesions, and 0.900 for QIR-4 versus 0.726 for EID-CT VMIs for hypoattenuating lesions. Compared with EID-CT LBIs, detection was higher for QIR 1-4 at 2.5 mGy and for QIR 2-4 at 1.25 mGy (eg, 0.900 for QIR-4 compared with 0.854 for EID-CT LBIs at 1.25 mGy). Radiation dose reduction potential of PCD-CT with QIR-4 was 54% at 5 mGy compared with VMIs and 39% at 2.5 mGy compared with LBIs.

CONCLUSIONS

Compared with EID-CT, PCD-CT with QIR substantially improved focal liver lesion detection, especially at low radiation dose. This enables substantial radiation dose reduction while maintaining diagnostic accuracy.

Abdominal peer learning: advantages and lessons learned

In 2017, our tertiary hospital-based imaging practice transitioned from score-based peer review to the peer learning methodology for learning and improvement. In our subspecialized practice, peer learning submissions are reviewed by domain experts, who then provide feedback to individual radiologists, curate cases for group learning sessions, and develop associated improvement initiatives. In this paper, we share lessons learned from our abdominal imaging peer learning submissions with the assumption that trends in our practice likely mimic others', and hope that other practices can avoid future errors and elevate the level of the quality of their own performance. Adoption of a nonjudgmental and efficient method to share peer "learning opportunities" and "great calls" has increased participation in this activity and increased transparency into our practice, thus allowing for visualization of trends in performance. Peer learning allows us to bring our own individual knowledge and practices together for group review in a collegial and safe environment. We learn from each other and decide how to improve together.

Use of dual-layer spectral detector computed tomography in the diagnosis of pancreatic neuroendocrine neoplasms

PURPOSE

To explore the optimal energy level of dual-layer spectral detector computed tomography (DLCT) images of pancreatic neuroendocrine neoplasms (pNENs) and investigate the value in their detection.

METHODS

This retrospective analysis included 134 pNEN patients with 136 lesions; they underwent contrast-enhanced DLCT scanning with histopathological confirmation of pNENs. Virtual monoenergetic images (VMI) of 40-100 keV, iodine concentration map (IC map), Z-effective atomic number map (Zeff map), and conventional images were analysed. The optimal energy level was obtained by comparing the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The lesion detection rates of DLCT and conventional images were compared. Subjective image analysis was performed by two readers who assessed the image quality and lesion conspicuity on a 5-point scale.

RESULTS

The SNR of VMIs from 40 to 80 keV (arterial phase, P < 0.001; venous phase, P < 0.05) and CNR from 40 to 60 keV (arterial and venous phases, each P < 0.05) were higher than that of conventional images; VMI_40keV showed the highest SNR and CNR. There was a good inter-reader agreement between the two reviewers (Kappa values > 0.61); the scores of Zeff and IC maps were higher than those of conventional images and VMI_40keV (P < 0.05). The detection performance of DLCT images was better than conventional images.

CONCLUSIONS

The VMI_40keV demonstrated the best CNR and SNR of pNENs compared to other VMIs. Zeff and IC maps improve objective image quality and reader preference compared to conventional images. These findings could possess important clinical implications in formulating treatment strategies.

Low-contrast-dose liver CT using low monoenergetic images with deep learning-based denoising for assessing hepatocellular carcinoma: a randomized controlled noninferiority trial

OBJECTIVE

Low monoenergetic images obtained using noise-reduction techniques may reduce CT contrast media requirements. We aimed to investigate the effectiveness of low-contrast-dose CT using dual-energy CT and deep learning-based denoising (DLD) techniques in patients at high risk of hepatocellular carcinoma (HCC).

METHODS

We performed a prospective, randomized controlled noninferiority trial at a tertiary hospital between June 2019 and August 2020 (NCT04027556). Patients at high risk of HCC were randomly assigned (1:1) to the standard-contrast-dose group or low-contrast-dose group, which targeted a 40% reduction in contrast medium dose based on lean body weight. HCC conspicuity on arterial phase images was the primary endpoint with a noninferiority margin of 0.2. Images were independently assessed by three radiologists; model-based iterative reconstruction (MBIR) images of the standard-contrast-dose group and low monoenergetic (50-keV) DLD images of the low-contrast-dose group were compared using a generalized estimating equation.

RESULTS

Ninety participants (age 59 ± 10 years; 68 men) were analyzed. Compared with the standard-contrast-dose group (n = 47), 40% less contrast media was used in the low-contrast-dose group (n = 43) (107.0 ± 17.1 mL vs. 64.5 ± 11.3 mL, p < 0.001). In the arterial phase, HCC conspicuity on 50-keV DLD images in the low-contrast-dose group was noninferior to that of MBIR images in the standard-contrast-dose group (2.92 vs. 2.56; difference, 0.36; 95% confidence interval, -0.13 to ∞; p = 0.013).

CONCLUSIONS

The contrast dose in liver CT can be reduced by 40% without impairing HCC conspicuity when using 50-keV and DLD techniques.

KEY POINTS

• In the arterial phase, hepatocellular carcinoma conspicuity on 50-keV deep learning-based denoising images in the low-contrast-dose group was noninferior to that of model-based iterative reconstruction images in the standard-contrast-dose group. • HCC detection was comparable between 50-keV deep learning-based denoising images in the low-contrast-dose group and model-based iterative reconstruction images in the standard-contrast-dose group.

Photon-counting detector CT improves quality of arterial phase abdominal scans: A head-to-head comparison with energy-integrating CT

PURPOSE

Photon-counting detector (PCD)-CT is expected to have a substantial impact on oncologic abdominal imaging. We compared subjective and objective image quality between PCD-CT and conventional energy-integrating detector (EID-)CT arterial phase abdominal scans.

METHODS

This study included 84 patients undergoing both types of abdominal CT. EID-CT scans were acquired with a tube voltage of 100 kVp. With PCD-CT, acquired with 120-kVp, we reconstructed polychromatic T3D images and virtual monoenergetic images (VMIs) in 10-keV intervals from 40 to 90 keV. Quantitative image analysis included noise and contrast-to-noise ratio (CNR) of hepatic vessels, kidney cortex, and hypervascular liver lesions to liver parenchyma. Three raters used a 5-point Likert scale for qualitative image analysis of image noise and contrast, lesion conspicuity, and overall image quality. Radiation dose exposure (CT dose index) was compared between the two CT types.

RESULTS

Mean CT dose index and effective dose were respectively 18 % and 26 % lower with PCD-CT versus EID-CT. Compared with EID-CT, CNRs of kidney cortex and vessel to liver parenchyma were significantly higher in PCD-CT VMIs at energies ≤ 60 keV and in polychromatic T3D images (p < 0.004). Overall image quality of PCD-CT VMIs at 50 and 60 keV was rated as significantly better (p < 0.01) than the EID-CT images (inter-reader agreement alpha = 0.80). Lesion conspicuity was significantly better in low-keV VMIs (p < 0.03) and worse in > 70-keV VMIs.

CONCLUSIONS

With low-keV VMI, PCD-CT yields significantly improved objective and subjective quality of arterial phase oncological imaging compared with EID-CT. This advantage may translate into higher diagnostic confidence and lower radiation dose protocols.

Diagnostic value of dual-energy CT and clinicopathological and imaging feature analysis of mixed endometrial stromal and smooth muscle tumors with intracardiac extension

Objective

To describe the clinicopathological and imaging features of mixed endometrial stromal and smooth muscle tumors with intracardiac extension and to explore the diagnostic value of dual-energy computed tomography (DECT) for this rare entity.

Materials and methods

This retrospective study analyzed the clinicopathological data and images of a 41-year-old female patient with pathologically documented mixed endometrial stromal and smooth muscle tumors with intracardiac extension who had undergone DECT examination. Seven virtual monoenergetic images (VMIs) in 10-kiloelectron volt (keV) intervals (range = 40–100 keV), iodine density (ID) maps, and Z effective (Zeff) maps were reconstructed, and lesion conspicuity was assessed. Tumor homology was analyzed using quantitative DECT parameters and energy spectrum attenuation curve.

Results

The patient complained of a 10-day history of bilateral lower extremity edema. Computed tomography showed a hypoattenuating filling defect located within the paracervical vein that extended into the right atrium to the ventricle through the right iliac veins and inferior vena cava (IVC). Intracardiac and intravenous lesions mainly demonstrated moderate progressive enhancement, with localized non-enhancing necrotic areas on contrast-enhanced CT. Multiple nodules showing progressive enhancement (long-T1 signal, long-T2 signal) were observed at the fundus of the uterus on dynamic contrast-enhanced magnetic resonance imaging (MRI), which were deemed the primary lesions of the tumor. Overall, the tumor was characterized by a small primary lesion with extensive vascular extension. In addition, the 40 keV VMIs reconstructions were found to provide best visualization for the early detection of tumors.

Conclusion

Although a definitive diagnosis of MESSMT with intracardiac extension requires confirmation by histopathological examination, imaging examination can be used to characterize the extent of the lesion. The dual-energy dataset facilitates tumor visualization and homology evaluation.

Dual energy CT applications in oncological imaging

Cancer is the second leading cause of death in the United States, killing more than 600.000 people each year.¹ Despite several screening programs available, cancer diagnosis is often made incidentally during imaging studies performed for other reasons. Once the diagnosis is made, treatment assessment and surveillance of these patients heavily rely on radiological tools. Computed tomography (CT) in particular is one of the most commonly ordered modalities due to wide availability even in the most remote locations, and fast results. However, conventional CT often cannot definitively characterize a neoplastic lesion unless it was tailored toward answering a specific question. Furthermore, characterizing small lesions can be difficult with CT. An innovative technique called dual-energy CT (DECT) offers solutions to some of the challenges of conventional CT in oncological imaging.

Quantitative and qualitative assessments of deep learning image reconstruction in low-keV virtual monoenergetic dual-energy CT

OBJECTIVES

To evaluate a novel deep learning image reconstruction (DLIR) technique for dual-energy CT (DECT) derived virtual monoenergetic (VM) images compared to adaptive statistical iterative reconstruction (ASIR-V) in low kiloelectron volt (keV) images.

METHODS

We analyzed 30 venous phase acute abdominal DECT (80/140 kVp) scans. Data were reconstructed to ASIR-V and DLIR-High at four different keV levels (40, 50, 74, and 100) with 1- and 3-mm slice thickness. Quantitative Hounsfield unit (HU) and noise assessment were measured within the liver, aorta, fat, and muscle. Subjective assessment of image noise, sharpness, texture, and overall quality was performed by two board-certified radiologists.

RESULTS

DLIR reduced image noise by 19.9-35.5% (p < 0.001) compared to ASIR-V in all reconstructions at identical keV levels. Contrast-to-noise ratio (CNR) increased by 49.2-53.2% (p < 0.001) in DLIR 40-keV images compared to ASIR-V 50 keV, while no significant difference in noise was identified except for 1 and 3 mm in aorta and for 1-mm liver measurements, where ASIR-V 50 keV showed 5.5-6.8% (p < 0.002) lower noise levels. Qualitative assessment demonstrated significant improvement particularly in 1-mm reconstructions (p < 0.001). Lastly, DLIR 40 keV demonstrated comparable or improved image quality ratings when compared to ASIR-V 50 keV (p < 0.001 to 0.22).

CONCLUSION

DLIR significantly reduced image noise compared to ASIR-V. Qualitative assessment showed that DLIR significantly improved image quality particularly in thin sliced images. DLIR may facilitate 40 keV as a new standard for routine low-keV VM reconstruction in contrast-enhanced abdominal DECT.

KEY POINTS

• DLIR enables 40 keV as the routine low-keV VM reconstruction. • DLIR significantly reduced image noise compared to ASIR-V, across a wide range of keV levels in VM DECT images. • In low-keV VM reconstructions, improvements in image quality using DLIR were most evident and consistent in 1-mm sliced images.

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.

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.

Salvaging low contrast abdominal CT studies using noise-optimised virtual monoenergetic image reconstruction

Objectives

To assess the impact of noise-optimised virtual monoenergetic imaging (VMI+) on image quality and diagnostic evaluation in abdominal dual-energy CT scans with impaired portal-venous contrast.

Methods

We screened 11,746 patients who underwent portal-venous abdominal dual-energy CT for cancer staging between 08/2014 and 11/2019 and identified those with poor portal-venous contrast.Standard linearly-blended image series and VMI+ image series at 40, 50, and 60 keV were reconstructed. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of abdominal organs and vascular structures were calculated. Image noise, image contrast and overall image quality were rated by three radiologists using 5-point Likert scale.

Results

452 of 11,746 (4%) exams were poorly opacified. We excluded 190 cases due to incomplete datasets or multiple exams of the same patient with a final study group of 262. Highest CNR values in all abdominal organs (liver, 6.4 ± 3.0; kidney, 17.4 ± 7.5; spleen, 8.0 ± 3.5) and vascular structures (aorta, 16.0 ± 7.3; intrahepatic vein, 11.3 ± 4.7; portal vein, 15.5 ± 6.7) were measured at 40 keV VMI+ with significantly superior values compared to all other series. In subjective analysis, highest image contrast was seen at 40 keV VMI+ (4.8 ± 0.4), whereas overall image quality peaked at 50 keV VMI+ (4.2 ± 0.5) with significantly superior results compared to all other series (p < 0.001).

Conclusions

Image reconstruction using VMI+ algorithm at 50 keV significantly improves image contrast and image quality of originally poorly opacified abdominal CT scans and reduces the number of non-diagnostic scans.

Advances in knowledge

We validated the impact of VMI+ reconstructions in poorly attenuated DECT studies of the abdomen in a big data cohort.

Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis

OBJECTIVES

To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases.

METHODS

This retrospective study included 131 patients who underwent contrast-enhanced DECT (80-kVp and 150-kVp with a tin filter) in the portal venous phase for hepatic metastasis surveillance. Linearly blended images simulating 100-kVp images (100-kVp), standard 40-keV VMI images (40-keV VMI), and post-processed 40-keV VMI using a vendor-agnostic DLM (i.e., DLM 40-keV VMI) were reconstructed. Lesion conspicuity and diagnostic acceptability were assessed by three independent reviewers and compared using the Wilcoxon signed-rank test. The contrast-to-noise ratios (CNRs) were also measured placing ROIs in metastatic lesions and liver parenchyma. The detection performance of hepatic metastases was assessed by using a jackknife alternative free-response ROC method. The consensus by two independent radiologists was used as the reference standard.

RESULTS

DLM 40-keV VMI, compared to 40-keV VMI and 100-kVp, showed a higher lesion-to-liver CNR (8.25 ± 3.23 vs. 6.05 ± 2.38 vs. 5.99 ± 2.00), better lesion conspicuity (4.3 (4.0-4.7) vs. 3.7 (3.7-4.0) vs. 3.7 (3.3-4.0)), and better diagnostic acceptability (4.3 (4.0-4.3) vs. 3.0 (2.7-3.3) vs. 4.0 (4.0-4.3)) (p < 0.001 for all). For lesion detection (246 hepatic metastases in 68 patients), the figure of merit was significantly higher with DLM 40-keV VMI than with 40-keV VMI (0.852 vs. 0.822, p = 0.012), whereas no significant difference existed between DLM 40-keV VMI and 100-kVp (0.852 vs. 0.842, p = 0.31).

CONCLUSIONS

DLM 40-keV VMI provided better image quality and comparable diagnostic performance for detecting hypoenhancing hepatic metastases compared to linearly blended images.

KEY POINTS

• DLM 40-keV VMI provides a superior image quality compared with 40-keV or 100-kVp for assessing hypoenhancing hepatic metastasis. • DLM 40-keV VMI has the highest CNR and lesion conspicuity score for hypoenhancing hepatic metastasis due to noise reduction and structural preservation. • DLM 40-keV VMI provides higher lesion detectability than standard 40-keV VMI (p = 0.012).

A study on spinal level, length, and branch type of the inferior mesenteric artery and the position relationship between the inferior mesenteric artery, left colic artery, and inferior mesenteric vein

Background

This study was aimed to explore the clinical application of dual-energy computed tomography (DECT) monoenergetic plus (mono+) imaging to evaluate anatomical variations in the inferior mesenteric artery (IMA).

Methods

The clinical and imaging data of 212 patients who had undergone total abdominal DECT were retrospectively analyzed. The post-processing mono+ technique was used to obtain 40-keV single-level images in the arterial phase. Three-dimensional reconstruction was performed to evaluate the relationship between the IMA root position and the spinal level, IMA length, and IMA branch type, as well as the position of the left colic artery (LCA) and inferior mesenteric vein (IMV) at the IMA root level.

Results

The IMA root was located at the L3 level in 78.3% of cases and at the L2/L3 level in 3.3%. The highest vertebral level of IMA origin was L2 (4.2%), and the lowest was L4 (7.1%). The distance from the IMA root to the level of the sacral promontory was 99.58 ± 13.07 mm, which increased with the elevation of the IMA root at the spinal level. Of the patients, 53.8% demonstrated Type I IMA, 23.1% Type II, 20.7% Type III, and 2.4% Type IV. The length of the IMA varied from 13.6 to 66.0 mm. 77.3% of the IMAs belonged to Type A, the adjacent type, and 22.7% to Type B, the distant type.

Conclusion

DECT mono+ can preoperatively evaluate the anatomical characteristics of the IMA and the positional relationship between the LCA and IMV at the IMA root level, which would help clinicians plan individualized surgery for patients.

DECT mono+ optimal energy level can preoperatively determine the position of the IMA root.

DECT mono+ can preoperatively evaluate the anatomical characteristics of the IMA.

DECT mono+ can preoperatively determine the positional relationship between the LCA and IMV at the IMA root level.

Evaluation of Hypervascular Focal Liver Lesions Utilizing Virtual Monoenergetic Images from Third-Generation Dual-Source Dual-Energy Computed Tomography

Objectives The purpose of our study was to evaluate the virtual monochromatic imaging in detecting hypervascular focal liver lesions in the late arterial phase with third-generation dual-source dual-energy computed tomography and to assess its image quality.

Materials and Methods In our study, 80 patients were included. Contrast-enhanced images in the late arterial phase (in the dual-energy mode) were acquired and were post-processed in Syngo, via workstation, using Monoenergetic + software. Five sets of images, one polychromatic energy image (corresponding to 120 kVp single-energy image) and four virtual monoenergetic image (VMI) sets at 40, 50, 60, and 70 keV levels, were generated. All these images were analyzed both objectively and subjectively. The attenuation values were measured, and the contrast-to-noise ratio (CNR) of liver and tumor were measured and compared objectively in each dataset. Image noise, image contrast, and diagnostic confidence for liver lesion detection were analyzed subjectively using a five-point scale system. Statistical analysis was performed using Kolmogorov–Smirnov, analysis of variance, and Kruskal–Wallis tests.

Results Among the VMI, maximum image noise was observed in the 40 keV image, with a gradual reduction in the image noise being noted with an increase in the VMI energy. The CNR of the hepatic parenchyma and the tumor gradually increased with a reduction in VMI energy from 70 to 40 keV. On subjective analysis, image contrast and image noise were observed to be more in low VMI datasets. In lesion detection, diagnostic confidence with an excellent confidence level was observed with a decrease in VMI energy.

Conclusion VMI datasets of 40 to 70 keV from third-generation dual-source DECT provide superior diagnostic accuracy for detecting hypervascular liver lesions. Considering the image noise and lesion detection rate among the VMI datasets, 60 keV VMI is the most helpful dataset for increased liver lesion detection with good image quality.

Noise-optimized virtual monoenergetic imaging technology of the third-generation dual-source computed tomography and its clinical applications

The third-generation dual-source computed tomography (DSCT) is among the most advanced imaging methods. It employs noise-optimized virtual monoenergetic imaging (VMI+) technology. It uses the frequency-split method to extract high-contrast image information from low-energy images and low-noise information from images reconstructed at an optimal energy level, combining them to obtain the final image with improved quality. This review is the first to summarize the results of clinical studies that primarily and recently evaluated the VMI+ technique based on tumor, blood vessel, and other lesion classification. We aim to assist radiologists in quickly selecting the appropriate energy level when performing image reconstruction for superior image quality in clinical work and providing several ideas for future scientific research of the VMI+ technique. Presently, VMI+ reconstruction is mostly used for images of various tumors or blood vessels, including coronary plaques, coronary stents, deep vein thromboses, pulmonary embolisms (PEs), active arterial hemorrhages, and endoleaks after endovascular aneurysm repair. In addition, VMI+ has been used for imaging children's heads, liver lesions, pancreatic lacerations, and reducing metal artifacts. Regarding the reconstruction at the optimal energy level, the VMI+ technique yielded a higher image quality than the pre-optimized virtual monoenergetic imaging (VMI) technique and single-energy CT. Moreover, either low concentrations of contrast medium or low iodine injection rates can be applied before VMI+ reconstruction at a low-energy level to reduce contrast agent-related kidney injury risk. After reconstructing an image at the optimal energy level, both the image's window width and level can also be adjusted to improve the image effect's reach and diagnosis suitability. To improve image quality and lesion-imaging clarity and reduce the use of contrast agents, VMI+ reconstruction technology has been applied clinically, in which the selection of energy level is the key to the whole reconstruction process. Our review summarizes these optimal levels for radiologists' reference and suggests new ideas for the direction of future VMI+ research.

Multiparametric dual-energy CT to differentiate stage T1 nasopharyngeal carcinoma from benign hyperplasia

Background

Stage T1 nasopharyngeal carcinoma (NPC_T1) and benign hyperplasia (BH) are 2 common causes of nasopharyngeal mucosa/submucosa thickening without specific clinical symptoms. The treatment management of these 2 entities is significantly different. Reliable differentiation between the 2 entities is critical for the treatment decision and prognosis of patients. Therefore, our study aims to explore the optimal energy level of noise-optimized virtual monoenergetic images [VMI (+)] derived from dual-energy computed tomography (DECT) to display NPC_T1 and BH and to explore the clinical value of DECT for differentiating these 2 diseases.

Methods

A total of 91 patients (44 NPC_T1, 47 BH) were enrolled. The demarcation of the lesion margins and overall image quality, noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were evaluated for 40-80 kiloelectron volts (keV) VMIs (+) and polyenergetic images in the contrast-enhanced phase. Image features were assessed in the contrast-enhanced images with optimal visualization of NPC_T1 and BH. The demarcation of NPC_T1 and BH in iodine-water maps was also assessed. The contrast-enhanced images were used to calculate the slope of the spectral Hounsfield unit curve (λ_HU) and normalized iodine concentration (NIC). The nonenhanced phase images were used to calculate the normalized effective atomic number (NZ_eff). The attenuation values on 40-80 keV VMIs (+) in the contrast-enhanced phase were recorded. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis.

Results

The 40 keV VMI (+) in the enhanced phase yielded higher demarcation of the lesion margins scores, overall image quality scores, noise, SNR, and CNR values than 50-80 keV VMIs (+) and polyenergetic images. NPC_T1 yielded higher attenuation values on VMI (+) at 40 keV (A₄₀), NIC, λ_HU, and NZ_eff values than BH. The multivariate logistic regression model combining image features (tumor symmetry) with quantitative parameters (A₄₀, NIC, λ_HU, and NZ_eff) yielded the best performance for differentiating the 2 diseases (AUC: 0.963, sensitivity: 89.4%, specificity: 93.2%).

Conclusions

The combination of DECT-derived image features and quantitative parameters contributed to the differentiation between NPC_T1 and BH.

Spectral CT Hybrid Images in the Diagnostic Evaluation of Hypervascular Abdominal Tumors-Potential Advantages in Clinical Routine

Background: This study aimed to investigate the use of spectral computed tomography (SCT) hybrid images combining virtual monoenergetic images (VMIs) and iodine maps (IMs) as a potentially efficient search series for routine clinical imaging in patients with hypervascular abdominal tumors. Methods: A total of 69 patients with hypervascular abdominal tumors including neuroendocrine neoplasms (NENs, n = 48), renal cell carcinoma (RCC, n = 10), and primary hepatocellular carcinoma (HCC, n = 11) were analyzed retrospectively. Two radiological readers (blinded to clinical data) read three CT image sets (1st a reference set with 70 keV; 2nd a 50:50 hybrid 140 keV/40 keV set; 3rd a 50:50 hybrid 140 keV/IM set). They assessed images subjectively by rating several parameters including image contrast, visibility of suspicious lesions, and diagnostic confidence on five-point Likert scales. In addition, reading time was estimated. Results: Median subjective Likert scores were highest for the 1st set, except for image contrast, for which the 2nd set was rated highest. Scores for diagnostic confidence, artifacts, noise, and visibility of suspicious lesions or small structures were significantly higher for the 1st set than for the 2nd or 3rd set (p < 0.001). Regarding image contrast, the 2nd set was rated significantly higher than the 3rd set (p < 0.001), while the median did not differ significantly compared with the 1st set. Agreement between the two readers was high for all sets. Estimated potential reading time was the same for hybrid and reference sets. Conclusions: Hybrid images have the potential to efficiently exploit the additional information provided by SCT in patients with hypervascular abdominal tumors. However, the use of rigid weighting did not significantly improve diagnostic performance in this study.

Effect of energy level on the spatial resolution and noise frequency characteristics of virtual monochromatic images: a phantom experiment using four types of CT scanners

PURPOSE

The purpose of the study is to evaluate the effect of energy level on the modulation transfer functions (MTF) and noise power spectra (NPS) of virtual monochromatic images (VMIs) obtained using four types of computed-tomographic (CT) scanners: Revolution, SOMATOM, IQon, and Aquilion.

MATERIALS AND METHODS

VMIs were obtained at 70, 60, and 50 kiloelectron volts (keV), and also at the lowest keV available in each scanner. We evaluated the MTF and NPS in the VMIs obtained at each keV.

RESULTS

No significant effect of the energy level on the MTF was observed in IQon, whereas the spatial resolution decreased as the energy level decreased in the other types of scanners. The NPS curves tended to increase as the energy levels decreased with three types of scanners other than Aquilion.

CONCLUSION

The spatial resolution and noise frequency characteristics of VMIs may be affected by the energy level, and the effects of energy level on these characteristics differ depending on the type of CT scanners.

Improvement of image quality of laryngeal squamous cell carcinoma using noise-optimized virtual monoenergetic image and nonlinear blending image algorithms in dual-energy computed tomography

BACKGROUND

Dual-energy computed tomography (DECT) has been used to improve image quality of head and neck squamous cell carcinoma (SCC). This study aimed to assess image quality of laryngeal SCC using linear blending image (LBI), nonlinear blending image (NBI), and noise-optimized virtual monoenergetic image (VMI+) algorithms.

METHODS

Thirty-four patients with laryngeal SCC were retrospectively enrolled between June 2019 and December 2020. DECT images were reconstructed using LBI (80 kV and M_0.6), NBI, and VMI+ (40 and 55 keV) algorithms. Contrast-to-noise ratio (CNR), tumor delineation, and overall image quality were assessed and compared.

RESULTS

VMI+ (40 keV) had the highest CNR and provided better tumor delineation than VMI+ (55 keV), LBI, and NBI, while NBI provided better overall image quality than VMI+ and LBI (all corrected p < 0.05).

CONCLUSIONS

VMI+ (40 keV) and NBI improve image quality of laryngeal SCC and may be preferable in DECT examination.

Can Dual-energy CT-based Virtual Monoenergetic Imaging Improve the Assessment of Hypodense Liver Metastases in Patients With Hepatic Steatosis?

RATIONALE AND OBJECTIVES

To evaluate the impact of noise-optimized virtual monoenergetic imaging (VMI) on lesion demarcation and measuring accuracy of hypoattenuating liver metastases in patients with fatty liver disease compared to standard reconstructions.

MATERIALS AND METHODS

Twenty-eight patients (mean age 62.2 ± 7.7 years) with fatty liver disease and hypoattenuating liver metastases who underwent unenhanced and contrast-enhanced portal-venous dual-energy CT (DECT) were enrolled. Standard linearly blended and VMI series were reconstructed in 10-keV intervals. Lesion-to-parenchyma contrast-to-noise ratio (CNR) was calculated and the best VMI series was further investigated in a subjective evaluation of overall image quality and lesion demarcation. Size measurements were performed independently by measuring all hypodense lesions (n = 58) twice in a predefined sequence. Inter- and intra-rater agreement was assessed using intra-class correlation coefficient (ICC) statistics.

RESULTS

The calculated CNR was greatest at 40-keV VMI (4.3 ± 2.6), significantly higher compared to standard reconstructions (2.9 ± 1.9; p < 0.001). Subjective ratings for overall image quality showed no significant difference between the 2 reconstruction techniques (both medians 4; p = 0.147), while lesion margin demarcation was found to be superior for 40-keV VMI (median 5; p ≤ 0.001). Inter- (ICC, 0.98 for 40-keV VMI; ICC, 0.93 for standard reconstruction) and intra-rater (ICC, 0.99 for 40-keV VMI; ICC, 0.94 for standard image series) analysis showed an excellent agreement for lesion measurements in both reconstruction techniques.

CONCLUSION

Noise-optimized VMI reconstructions significantly improve contrast and lesion demarcation of hypoattenuating liver metastases in patients with the fatty liver disease compared to standard reconstruction.

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.

Subjective and Objective Assessment of Monoenergetic and Polyenergetic Images Acquired by Dual-Energy CT in Breast Cancer

Objective

To objectively and subjectively assess and compare the characteristics of monoenergetic images [MEI (+)] and polyenergetic images (PEI) acquired by dual-energy CT (DECT) of patients with breast cancer.

Materials and Methods

This retrospective study evaluated the images and data of 42 patients with breast cancer who had undergone dual-phase contrast-enhanced DECT from June to September 2019. One standard PEI, five MEI (+) in 10-kiloelectron volt (keV) intervals (range, 40–80 keV), iodine density (ID) maps, iodine overlay images, and Z effective (Z_eff) maps were reconstructed. The contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) were calculated. Multiple quantitative parameters of the malignant breast lesions were compared between the arterial and the venous phase images. Two readers independently assessed lesion conspicuity and performed a morphology analysis.

Results

Low keV MEI (+) at 40–50 keV showed increased CNR and SNR_{breast lesion} compared with PEI, especially in the venous phase ([CNR: 40 keV, 20.10; 50 keV, 14.45; vs. PEI, 7.27; p < 0.001], [SNR_{breast lesion}: 40 keV, 21.01; 50 keV, 16.28; vs. PEI, 10.77; p < 0.001]). Multiple quantitative DECT parameters of malignant breast lesions were higher in the venous phase images than in the arterial phase images (p < 0.001). MEI (+) at 40 keV, ID, and Z_eff reconstructions yielded the highest Likert scores for lesion conspicuity. The conspicuity of the mass margin and the visual enhancement were significantly better in 40-keV MEI (+) than in the PEI (p = 0.022, p = 0.033, respectively).

Conclusion

Compared with PEI, MEI (+) reconstructions at low keV in the venous phase acquired by DECT improved the objective and subjective assessment of lesion conspicuity in patients with malignant breast lesions. MEI (+) reconstruction acquired by DECT may be helpful for the preoperative evaluation of breast cancer.

Multiparametric dual-energy CT for distinguishing nasopharyngeal carcinoma from nasopharyngeal lymphoma

OBJECTIVES

To determine the optimal kiloelectron volt of noise-optimized virtual monoenergetic images [VMI (+)] for visualization of nasopharyngeal carcinoma (NPC) and nasopharyngeal lymphoma (NPL), and to explore the clinical value of quantitative parameters derived from dual-energy computed tomography (DECT) for distinguishing the two entities.

MATERIALS AND METHODS

Eighty patients including 51 with NPC and 29 with NPL were enrolled. The VMIs (+) at 40-80 keV with an interval of 10 keV were reconstructed by contrast enhanced images. The overall image quality and demarcation of lesion margins, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed in VMIs (+) and polyenergetic images (PEI). Normalized iodine concentration (NIC), slope of the spectral Hounsfield unit curve (λ_HU) and effective atomic number (Z_eff) were calculated. Diagnostic performance was assessed by receiver operating characteristic (ROC) curve.

RESULTS

The 40 keV VMI (+) yielded highest overall image quality scores, demarcation of lesion margins scores, SNR and CNR. The values of NIC, λ_HU and Z_eff in NPL were higher than those in NPC (P <  0.001). Multivariate logistic regression model combining NIC, λ_HU and Z_eff showed the best performance for distinguishing NPC from NPL (AUC: 0.947, sensitivity: 93.1 % and specificity: 92.2 %).

CONCLUSION

VMI (+) reconstruction at 40 keV was optimal for visualizing NPC and NPL. Quantitative parameters derived from DECT were helpful for differentiating NPC from NPL.

New advances in CT imaging of pancreas diseases: a narrative review

Computed tomography (CT) plays a pivotal role as a diagnostic tool in many diagnostic and diffuse pancreatic diseases. One of the major limits of CT is related to the radiation exposure of young patients undergoing repeated examinations. Besides the standard CT protocol, the most recent technological advances, such as low-voltage acquisitions with high performance X-ray tubes and iterative reconstructions, allow for significant optimization of the protocol with dose reduction. The variety of CT tools are further expanded by the introduction of dual energy: the production of energy-selective images (i.e., virtual monochromatic images) improves the image contrast and lesion detection while the material-selective images (e.g., iodine maps or virtual unenhanced images) are valuable for lesion detection and dose reduction. The perfusion techniques provide diagnostic and prognostic information lesion and parenchymal vascularization and interstitium. Both dual energy and perfusion CT have the potential for pushing the limits of conventional CT from morphological evaluation to quantitative imaging applied to inflammatory and oncological diseases. Advances in post-processing of CT images, such as pancreatic volumetry, texture analysis and radiomics provide relevant information for pancreatic function but also for the diagnosis, management and prognosis of pancreatic neoplasms. Artificial intelligence is promising for optimization of the workflow in qualitative and quantitative analyses. Finally, basic concepts on the role of imaging on screening of pancreatic diseases will be provided.

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.

Gastrointestinal Applications of Iodine Quantification Using Dual-Energy CT: A Systematic Review

Dual-energy computed tomography (DECT) can estimate tissue vascularity and perfusion via iodine quantification. The aim of this systematic review was to outline current and emerging clinical applications of iodine quantification within the gastrointestinal tract using DECT. The search was conducted with three databases: EMBASE, Pubmed and The Cochrane Library. This identified 449 studies after duplicate removal. From a total of 570 selected studies, 30 studies were enrolled for the systematic review. The studies were categorized into four main topics: gastric tumors (12 studies), colorectal tumors (8 studies), Crohn’s disease (4 studies) and miscellaneous applications (6 studies). Findings included a significant difference in iodine concentration (IC) measurements in perigastric fat between T1–3 vs. T4 stage gastric cancer, poorly and well differentiated gastric and colorectal cancer, responders vs. non-responders following chemo- or chemoradiotherapy treatment among cancer patients, and a positive correlation between IC and Crohn’s disease activity. In conclusion, iodine quantification with DECT may be used preoperatively in cancer imaging as well as for monitoring treatment response. Future studies are warranted to evaluate the capabilities and limitations of DECT in splanchnic flow.

Measurement Reliability and Diagnostic Accuracy of Virtual Monoenergetic Dual-Energy CT in Patients with Colorectal Liver Metastases

RATIONALE AND OBJECTIVES

To compare dual-energy CT virtual monoenergetic images (VMI) and standard reconstructions for reliability of quantitative size measurements and diagnostic accuracy for the detection of colorectal liver metastases (CRLM).

MATERIALS AND METHODS

We retrospectively included 98 patients (mean age, 61.1±11.5 years) with colorectal cancer, of whom 49 subjects had CRLM. All patients underwent a portal-venous phase dual-energy CT examination. Standard linearly-blended reformats and 40-keV VMI were reconstructed. For both reconstruction techniques, two blinded readers performed measurements of CRLM twice in a preset sequence. Three additional radiologists independently assessed all liver lesions in terms of dignity (benign vs. malignant). Sensitivity, specificity and diagnostic accuracy were calculated on a per-patient basis using MRI as reference standard. Readers scored the suitability for metric measurements and their diagnostic confidence using 5-point Likert scales. Inter-rater agreement was evaluated using intraclass correlation coefficient (ICC).

RESULTS

Inter-rater agreement for lesion size measurements was higher for 40-keV VMI (ICC, 0.88) compared to standard linearly-blended series (ICC, 0.80). Sensitivity and diagnostic accuracy for the detection of CRLM were significantly higher for VMI at 40-keV compared to standard reconstructions (90.6% vs. 80.6%, and 89.1% vs. 81.3%; p < 0.001). Reader scores indicated that 40-keV VMI were more suitable for metric lesion measurements and provided greater diagnostic confidence compared to standard reformats (median, 5 vs. 3, and 5 vs. 4; both p < 0.001).

CONCLUSION

Low-keV VMI reconstructions improve reliability of quantitative size measurements and diagnostic accuracy for the assessment of CRLM compared to standard linearly-blended images.

Evaluation of soft-plaque stenoses in coronary artery stents using conventional and monoenergetic images: first in-vitro experience and comparison of two different dual-energy techniques

Background

Non-invasive coronary imaging after stent placement remains challenging. Favorable results for dual-energy computed tomography (DECT) derived monoenergetic (MonoE) images have been reported for this purpose. Nowadays, there are different dual-energy techniques available, each with specific advantages and disadvantages. However, for the evaluation of coronaries after stent implantation there is no systematic comparison between different dual-energy techniques. Therefore, the aim of our study was to compare two widely used DECT systems using an in-stent restenosis (ISR) phantom setup.

Methods

Soft-plaque-like stenoses (~50% of lumen) were inserted into ten coronary stents embedded in contrast-filled vessel phantoms. A dual-source CT (DSCT) and a dual-layer CT (DLCT) with comparable acquisition and reconstruction parameters were used. Conventional polyenergetic (PolyE) and MonoE images with 9 different levels (40-120 keV) were calculated. ISR assessability was evaluated by subjective scoring using a 5-point scale and by the following quantitative parameters: image noise, visible lumen diameter (VLD) and ISR contrast-to-noise ratio (CNR).

Results

A non-significant trend towards larger VLD in DLCT images was observed. Highest noise was found in low-keV MonoE with significantly higher values for DSCT than for DLCT. Conversely, noise was significantly lower for DSCT at higher-keV MonoE. Peak ISR CNR values were found at low-keV MonoE with no significant difference between both systems. However, for PolyE and mid-energy MonoE, CNRs were significantly higher for DSCT. Subjective image quality was significantly better for PolyE and low-keV MonoE than for high-keV MonoE, also without significant difference between both systems.

Conclusions

Conspicuity of ISR benefits from DECT. Peak CNRs were comparable for both DECT systems and low-keV MonoE offered the highest CNR values and best subjective image quality. In contrast, high-keV MonoE cannot be recommended for stent evaluation due to poor CNR values and therefore significantly limited visualization of stenoses.

Single source split filter dual energy: Image quality and liver lesion detection in abdominal CT

PURPOSE

Aim of this study was to evaluate image quality of single source dual energy CT (SSDE-CT) using split filter technique in oncologic abdominal CT.

METHOD

51 consecutive patients with newly diagnosed breast carcinoma were prospectively enrolled in this study and underwent a staging examination of the abdomen using SSDE-CT (120 kV, split filter technique, 400 ref. mAs). Inline default images (DI) and post-processed virtual monoenergetic images at 40 keV, 50 keV, 60 keV, 70 keV and 80 keV were reconstructed. Objective image quality was evaluated as contrast to noise ratio (CNR) for liver parenchyma, portal vein, spleen, pancreas, aorta and hypoattenuating liver lesions. Subjective image quality was rated on a 5-point scale. Image quality at different keV settings was analyzed in paired t-tests.

RESULTS

CNR was highest at 40 keV for vessels (portal vein: 9.0, aorta: 8.8, all p < 0.001) and for upper abdominal organs (spleen: 4.8, all p < 0.001; pancreas: 2.7, all p < 0.01 except p = 0.93 for 50 keV; liver parenchyma: 3.4, all p < 0.01). Highest CNR values for hypoattenuating liver lesions were found at 40 keV (7.7, all p < 0.001). Overall subjective image quality was highest with 80 keV and DI (both 4.8, all p < 0.001). Artifacts were most pronounced at 40 keV.

CONCLUSIONS

High image quality can be obtained with SSDE-CT of the abdomen. Lowest monoenergetic reconstructions provide the highest image contrast and should be used for vessel evaluation. The best trade-off between artifacts and parenchymal contrast can be obtained with 80 keV images.

Dual-energy CT: theoretical principles and clinical applications

The physical principles of dual-energy computed tomography (DECT) are as old as computed tomography (CT) itself. To understand the strengths and the limits of this technology, a brief overview of theoretical basis of DECT will be provided. Specific attention will be focused on the interaction of X-rays with matter, on the principles of attenuation of X-rays in CT toward the intrinsic limits of conventional CT, on the material decomposition algorithms (two- and three-basis-material decomposition algorithms) and on effective Rho-Z methods. The progresses in material decomposition algorithms, in computational power of computers and in CT hardware, lead to the development of different technological solutions for DECT in clinical practice. The clinical applications of DECT are briefly reviewed in relation to the specific algorithms.

CT artifacts from port systems: Virtual monoenergetic reconstructions from spectral-detector CT reduce artifacts and improve depiction of surrounding tissue

PURPOSE

CT artifacts from port-systems are a common problem in staging- and restaging-examinations and reduce image quality and diagnostic assessment. The purpose of this study was to investigate the reduction of these artifacts using virtual monoenergetic images (VMI) from dual-energy spectral-detector CT (SDCT) in comparison to conventional CT-images (CI).

METHOD

50 SDCT-datasets of patients with artifacts from port-chamber and port-catheters were included in this IRB-approved, retrospective study. CI and VMI (range, 40-200 keV, 10 keV increment) were reconstructed from the same acquisition. The quantitative image analysis was performed ROI-based assessing mean and standard deviation of attenuation (HU) in most pronounced hypo- and hyperdense artifacts surrounding to the port-chamber and the distal end of the port-catheter in the superior vena cava. Subjectively, artifact reduction and diagnostic assessment of surrounding soft tissue were rated on 5-point Likert-scales.

RESULTS

In comparison to CI, VMI of higher keV-values showed strong reduction of hypo- and hyperattenuating artifacts around the port-chamber and port-catheter (CI/VMI_200keV: hypodense -104.7 ± 124.7HU/10.8 ± 58.1HU and -101.6 ± 101.5HU/-36.7 ± 32.9HU; hyperdense 240.8 ± 151.6HU/79.6 ± 81.3HU and 108.6 ± 129.3HU/25.9 ± 31.9HU; all p < 0.001). Image noise could also be reduced significantly. The subjective analysis showed significantly reduced artifacts around the port-chamber and port-catheter (CI/VMI_200keV: hypodense 3(1-4)/5(4-5) and 3(2-4)/5(4-5); hyperdense 3(1-4)/5(4-5) and 3(2-3)/5(3-5); all p < 0.001) and improved diagnostic assessment of pectoral/subclavian soft tissue for VMI of ≥100keV. Ratings for diagnostic assessment were best between 140-200 keV. Overall interrater agreement was high (ICC = 0.79).

CONCLUSIONS

Higher keV VMI enabled a significant reduction of artifacts from port-systems around the chamber and the catheter leading to improved assessment of surrounding soft tissue.

Low-keV virtual monoenergetic imaging reconstructions of excretory phase spectral dual-energy CT in patients with urothelial carcinoma: A feasibility study

OBJECTIVES

To compare objective and subjective image quality between low keV virtual monoenergetic images (VMI) of the excretory phase and conventional venous phase images derived from spectral dual-energy CT (DECT) in the assessment of urothelial carcinoma.

METHODS

26 consecutive patients with histologically confirmed urothelial carcinoma who received clinically indicated venous- and excretory phase abdominal CT scans were included retrospectively. Attenuation, image noise as well as signal- and contrast-to-noise-ratio (SNR, CNR) in venous and excretory phase CT and excretory phase VMI from 40 to 70 keV were obtained from ROI-based measurements in the following regions: urothelial carcinoma, liver, pancreas, renal cortex, subcutaneous fat, renal vein/artery, portal vein, urinary bladder wall, lymph nodes, prostate/uterus. Subjective vessel contrast and delineation of primary tumor manifestations and distant metastases were rated on 5-point Likert scales.

RESULTS

In comparison to venous phase CT, attenuation and SNR in excretory phase VMI40keV were higher (p < 0.001), except for liver parenchyma, where they were comparable (p = 0.07 and p = 0.17, respectively). Regarding image noise, no significant difference was found between venous phase CT and excretory phase VMI40keV (p-range: 0.08-1.00), except for liver, portal vein and renal artery, where it was lower in VMI40keV (p < 0.05). CNR of urothelial carcinoma to circumjacent bladder wall was significantly higher in excretory phase VMI40keV compared to venous phase CT. Subjective vessel contrast and delineation of primary tumor and distant metastases received equivalent or higher Likert scores in excretory phase VMI40keV than in venous phase CT.

CONCLUSION

This feasibility study indicates that in the assessment of urothelial carcinoma, virtual monoenergetic excretory phase images at 40 keV acquired with spectral DECT could be feasible to maintain subjective and objective image quality as provided by conventional venous phase images. Still, equivalence with regards to metastatic lesion detection requires further investigation before employing this technique in a potential signal-scan, single-bolus approach.

Noise-optimised virtual monoenergetic imaging of dual-energy CT: effect on metal artefact reduction in patients with lumbar internal fixation

PURPOSE

The purpose of this study was to evaluate the effects of noise-optimised virtual monoenergetic imaging (VMI+) reconstructions on reducing metal artefacts compared to traditional virtual monoenergetic imaging (VMI) and linearly blended (M_0.6) reconstructions in patients with lumbar metal internal fixation in dual-energy CT (DECT).

METHODS

Forty patients who underwent DECT were evaluated in this retrospective study. Images were reconstructed with M_0.6 and with VMI+ and VMI at 10-keV intervals from 40 keV to 190 keV. Attenuation and noise were measured in the hyperdense artefacts, hypodense artefacts, spinal canal, abdominal aorta (AA), and inferior vena cava (IVC). An artefact index (AI) was calculated. A subjective evaluation of the metal-bone interface, surrounding soft tissue, spinal canal, AA, and IVC was conducted.

RESULTS

The AI values for the hypodense artefacts, spinal canal, and IVC were lowest in the 130 keV VMI+ series, for the hyperdense artefacts in the 120 keV VMI+ series, and for the AA in the 190 keV VMI+ series. Except for the hypodense artefacts, the AI values were lower compared to the M_0.6 images and all the VMI series (all p < 0.05). The subjective image quality was highest at 130 keV VMI+ for the metal-bone interface, surrounding soft tissue, AA, and IVC, and at 120 keV VMI+ for the spinal canal. Except for the AA, these rating scores were higher compared to the M_0.6 images and the entire VMI series (all p < 0.05).

CONCLUSIONS

DECT with high-keV VMI+ efficiently reduces metal artefacts and shows superior image quality in patients with lumbar internal fixation. These slides can be retrieved from Electronic Supplementary Material.

Dual energy computed tomography virtual monoenergetic imaging: technique and clinical applications

Dual energy CT (DECT) has evolved into a commonly applied imaging technique in clinical routine due to its unique post-processing opportunities for improved evaluation of all body areas. Reconstruction of virtual monoenergetic imaging (VMI) series has shown beneficial effects for both non-contrast and contrast-enhanced DECT due to the flexibility to calculate low-keV VMI reconstructions to increase contrast and iodine attenuation, or to compute high-keV VMI reconstructions to reduce beam-hardening artefacts. The goal of this review article is to explain the technical background of VMI and noise-optimized VMI+ algorithms and to give an overview of useful clinical applications of the VMI technique in DECT of various body regions.