Dual-layer dual-energy CT for characterization of adrenal nodules: can virtual unenhanced images replace true unenhanced acquisitions?

Multi-reader multiparametric DECT study evaluating different strengths of iterative and deep learning-based image reconstruction techniques

OBJECTIVES

To perform a multi-reader comparison of multiparametric dual-energy computed tomography (DECT) images reconstructed with deep-learning image reconstruction (DLIR) and standard-of-care adaptive statistical iterative reconstruction-V (ASIR-V).

METHODS

This retrospective study included 100 patients undergoing portal venous phase abdominal CT on a rapid kVp switching DECT scanner. Six reconstructed DECT sets (ASIR-V and DLIR, each at three strengths) were generated. Each DECT set included 65 keV monoenergetic, iodine, and virtual unenhanced (VUE) images. Using a Likert scale, three radiologists performed qualitative assessments for image noise, contrast, small structure visibility, sharpness, artifact, and image preference. Quantitative assessment was performed by measuring attenuation, image noise, and contrast-to-noise ratios (CNR). For the qualitative analysis, Gwet's AC2 estimates were used to assess agreement.

RESULTS

DECT images reconstructed with DLIR yielded better qualitative scores than ASIR-V images except for artifacts, where both groups were comparable. DLIR-H images were rated higher than other reconstructions on all parameters (p-value < 0.05). On quantitative analysis, there was no significant difference in the attenuation values between ASIR-V and DLIR groups. DLIR images had higher CNR values for the liver and portal vein, and lower image noise, compared to ASIR-V images (p-value < 0.05). The subgroup analysis of patients with large body habitus (weight ≥ 90 kg) showed similar results to the study population. Inter-reader agreement was good-to-very good overall.

CONCLUSION

Multiparametric post-processed DECT datasets reconstructed with DLIR were preferred over ASIR-V images with DLIR-H yielding the highest image quality scores.

CLINICAL RELEVANCE STATEMENT

Deep-learning image reconstruction in dual-energy CT demonstrated significant benefits in qualitative and quantitative image metrics compared to adaptive statistical iterative reconstruction-V.

KEY POINTS

Dual-energy CT (DECT) images reconstructed using deep-learning image reconstruction (DLIR) showed superior qualitative scores compared to adaptive statistical iterative reconstruction-V (ASIR-V) reconstructed images, except for artifacts where both reconstructions were rated comparable. While there was no significant difference in attenuation values between ASIR-V and DLIR groups, DLIR images showed higher contrast-to-noise ratios (CNR) for liver and portal vein, and lower image noise (p value < 0.05). Subgroup analysis of patients with large body habitus (weight ≥ 90 kg) yielded similar findings to the overall study population.

Detection of moderate hepatic steatosis on contrast-enhanced dual-source dual-energy CT: Role and accuracy of virtual non-contrast CT

PURPOSE

To investigate diagnostic accuracy of virtual non contrast (VNC) images, based on dual-source dual-energy CT (dsDECT), for detection of at least moderate steatosis and to define a threshold value to make this diagnosis on VNC.

METHODS

This single-institution retrospective study included patients who had multi-phasic protocol dsDECT. Regions of interests were placed in different segments of the liver and spleen on true non-contrast (TNC), VNC, and portal-venous phase (PVP) images. At least moderate steatosis was defined as liver attenuation (LHU) < 40 HU on TNC. Diagnostic performance of VNC to detect steatosis was determined and the new threshold was tested in a validation cohort.

RESULTS

236 patients were included in training cohort. Mean liver attenuation values were 51.3 ± 10.8 HU and 58.1 ± 11.5 HU for TNC and VNC (p < 0.001), with a mean difference (VNC - TNC) of 6.8 ± 6.9 HU. Correlation between TNC and VNC was strong (r = 0.81, p < 0.001). The AUCs of LHU on VNC for detection of hepatic steatosis were 0.92 (95 % Cl: 0.86-0.98), 0.92 (95 % Cl: 0.87-0.97), 0.92 (95 % Cl: 0.86-0.99), 0.91 (95 % Cl: 0.84-0.97), and 0.87 (95 % Cl: 0.80-0.95) for entire liver, left lateral, left medial, right anterior, and right posterior segments, respectively. VNC had sensitivity/specificity of 100 % /42 % when using a threshold of 40 HU; they were 69 % and 95 %, respectively, when using optimized threshold of 46 HU. This threshold showed similar performance in validation cohort (n = 80).

CONCLUSIONS

Hepatic attenuation on VNC has promising performance for detection of at least moderate steatosis. Proposed threshold of 46 HU provides high specificity and moderate sensitivity to detect steatosis.

Expanding Role of Dual-Energy CT for Genitourinary Tract Assessment in the Emergency Department, From the AJR Special Series on Emergency Radiology

Among explored applications of dual-energy CT (DECT) in the abdomen and pelvis, the genitourinary (GU) tract represents an area where accumulated evidence has established the role of DECT to provide useful information that may change management. This review discusses established applications of DECT for GU tract assessment in the emergency department (ED) setting, including characterization of renal stones, evaluation of traumatic injuries and hemorrhage, and characterization of incidental renal and adrenal findings. Use of DECT for such applications can reduce the need for additional multiphase CT or MRI examinations and reduce follow-up imaging recommendations. Emerging applications are also highlighted, including use of low-energy virtual monoenergetic images (VMIs) to improve image quality and potentially reduce contrast media doses and use of high-energy VMIs to mitigate renal mass pseudoenhancement. Finally, implementation of DECT into busy ED radiology practices is presented, weighing the trade-off of additional image acquisition, processing time, and interpretation time against potential additional useful clinical information. Automatic generation of DECT-derived images with direct PACS transfer can facilitate radiologists' adoption of DECT in busy ED environments and minimize impact on interpretation times. Using the described approaches, radiologists can apply DECT technology to improve the quality and efficiency of care in the ED.

Dual-Energy Computed Tomography Applications in the Genitourinary Tract

By virtue of material differentiation capabilities afforded through dedicated postprocessing algorithms, dual-energy CT (DECT) has been shown to provide benefit in the evaluation of various diseases. In this article, we review the diagnostic use of DECT in the assessment of genitourinary diseases, with emphasis on its role in renal stone characterization, incidental renal and adrenal lesion characterization, retroperitoneal trauma, reduction of radiation, and contrast dose and cost-effectiveness potential. We also discuss future perspectives of the DECT scanning mode, including the use of novel contrast injection strategies and photon-counting detector computed tomography.

Dual-energy CT in the differentiation between adrenal adenomas and metastases: Usefulness of material density maps and monochromatic images

OBJECTIVE

To evaluate the behavior of adrenal adenomas and metastases with dual-energy CT, analyzing the attenuation coefficient in monochromatic images at three different levels of energy (45, 70, and 140 keV) and the tissue concentrations of fat, water, and iodine in material density maps, with the aim of establishing optimal cutoffs for differentiating between these lesions and comparing our results against published evidence.

MATERIALS AND METHODS

This retrospective case-control study included oncologic patients diagnosed with adrenal metastases in the 6-12 months prior to the study who were followed up in our hospital between January and June 2020. For each case (patient with metastases) included in the study, we selected a control (patient with an adrenal adenoma) with a nodule of similar size. All patients were studied with a rapid-kilovoltage-switching dual-energy CT scanner, using a biphasic acquisition protocol. We analyzed the concentration of iodine in paired water-iodine images, the concentration of fat in the paired water-fat images, and the concentration of water in the paired iodine-water and fat-water images, in both the arterial and portal phases. We also analyzed the attenuation coefficient in monochromatic images (at 55, 70, and 140 keV) in the arterial and portal phases.

RESULTS

In the monochromatic images, in both the arterial and portal phases, the attenuation coefficient at all energy levels was significantly higher in the group of patients with metastases than in the group of patients with adenomas. This enabled us to calculate the optimal cutoffs for classifying lesions as adenomas or metastases, except for the arterial phase at 55 KeV, where the area under the receiver operating characteristic curve (AUC) for the estimated threshold (0.68) was not considered accurate enough to classify the lesions. For the arterial phase at 70 keV, the AUC was 0.76 (95% CI: 0.663‒0.899); the optimal cutoff (42.4 HU) yielded 92% sensitivity and 60% specificity. For the arterial phase at 140 keV, the AUC was 0.94 (95% CI: 0.894‒0.999); the optimal cutoff (18.9 HU) yielded 88% sensitivity and 94% specificity). For the portal phase at 55 keV, the AUC was 0.76 (95% CI: 0.663‒0.899); the optimal cutoff (95.4 HU) yielded 68% sensitivity and 84% specificity. For the portal phase at 70 keV, the AUC was 0.82 (95% CI: 0.757‒0.955); the optimal cutoff (58.4 HU) yielded 80% sensitivity and 84% specificity. For the portal phase at 140 keV, the AUC was 0.9 (95% CI: 0.834‒0.987); the optimal cutoff (16.35 HU) yielded 96% sensitivity and 84% specificity. In the material density maps, in the arterial phase, significant differences were found only for the iodine-water pair, where the concentration of water was higher in the group with metastases (1018.8 ± 7.6 mg/cm3 vs. 998.6 ± 8.0 mg/cm3 for the group with adenomas, p < 0.001). The AUC was 0.97 (95% CI: 0.893‒0.999); the optimal cutoff (1012.5 mg/cm3) yielded 88% sensitivity and 96% specificity. The iodine-water pair was also significantly higher in metastases (1019.7 ± 12.1 mg/cm3 vs. 998.5 ± 9.1 mg/cm3 in adenomas, p < 0.001). The AUC was 0.926 (95% CI: 0.807‒0.977); the optimal cutoff (1009.5 mg/cm3) yielded 92% sensitivity and 92% specificity. Although significant results were also observed for the fat-water pair in the portal phase, the AUC was insufficient to enable a sufficiently accurate cutoff for classifying the lesions. No significant differences were found in the fat-water maps or iodine-water maps in the arterial or portal phase or in the water-fat map in the arterial phase.

CONCLUSIONS

Monochromatic images show differences between the behavior of adrenal adenomas and metastases in oncologic patients studied with intravenous-contrast-enhanced CT, where the group of metastases had higher attenuation than the group of adenomas in both the arterial and portal phases; this pattern is in line with the evidence published for adenomas. Nevertheless, to our knowledge, no other publications report cutoffs for this kind of differentiation in contrast-enhanced monochromatic images obtained in rapid-kilovoltage-switching dual-energy CT scanners, and this is the first new contribution of our study. Regarding the material density maps, our results suggest that the water-iodine pair is a good tool for differentiating between adrenal adenomas and metastases, in both the arterial and portal phases. We propose cutoffs for differentiating these lesions, although to our knowledge no cutoffs have been proposed for portal-phase contrast-enhanced images obtained with rapid-kilovoltage-switching dual-energy CT scanners.

Adrenal Neoplasms: Lessons from Adrenal Multidisciplinary Tumor Boards

The radiologic diagnosis of adrenal disease can be challenging in settings of atypical presentations, mimics of benign and malignant adrenal masses, and rare adrenal anomalies. Misdiagnosis may lead to suboptimal management and adverse outcomes. Adrenal adenoma is the most common benign adrenal tumor that arises from the cortex, whereas adrenocortical carcinoma (ACC) is a rare malignant tumor of the cortex. Adrenal cyst and myelolipoma are other benign adrenal lesions and are characterized by their fluid and fat content, respectively. Pheochromocytoma is a rare neuroendocrine tumor of the adrenal medulla. Metastases to the adrenal glands are the most common malignant adrenal tumors. While many of these masses have classic imaging appearances, considerable overlap exists between benign and malignant lesions and can pose a diagnostic challenge. Atypical adrenal adenomas include those that are lipid poor; contain macroscopic fat, hemorrhage, and/or iron; are heterogeneous and/or large; and demonstrate growth. Heterogeneous adrenal adenomas may mimic ACC, metastasis, or pheochromocytoma, particularly when they are 4 cm or larger, whereas smaller versions of ACC, metastasis, and pheochromocytoma and those with washout greater than 60% may mimic adenoma. Because of its nonenhanced CT attenuation of less than or equal to 10 HU, a lipid-rich adrenal adenoma may be mimicked by a benign adrenal cyst, or it may be mimicked by a tumor with central cystic and/or necrotic change such as ACC, pheochromocytoma, or metastasis. Rare adrenal tumors such as hemangioma, ganglioneuroma, and oncocytoma also may mimic adrenal adenoma, ACC, metastasis, and pheochromocytoma. The authors describe cases of adrenal neoplasms that they have encountered in clinical practice and presented to adrenal multidisciplinary tumor boards. Key lessons to aid in diagnosis and further guide appropriate management are provided. © RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Dual Energy-Derived Metrics for Differentiating Adrenal Adenomas From Nonadenomas on Single-Phase Contrast-Enhanced CT

BACKGROUND. Adrenal masses are often indeterminate on single-phase postcontrast CT. Dual-energy CT (DECT) with three-material decomposition algorithms may aid characterization. OBJECTIVE. The purpose of this study was to compare the diagnostic performance of metrics derived from portal venous phase DECT, including virtual noncontrast (VNC) attenuation, fat fraction, iodine density, and relative enhancement ratio, for characterizing adrenal masses. METHODS. This retrospective study included 128 patients (82 women, 46 men; mean age, 64.6 ± 12.7 [SD] years) who between January 2016 and December 2019 underwent portal venous phase abdominopelvic DECT that showed a total of 139 adrenal lesions with an available reference standard based on all imaging, clinical, and pathologic records (87 adenomas, 52 nonadenomas [48 metastases, two adrenal cortical carcinomas, one ganglioneuroma, one hematoma]). Two radiologists placed ROIs to determine the following characteristics of the masses: VNC attenuation, fat fraction, iodine density normalized to portal vein, and for masses with VNC greater than 10 HU, relative enhancement ratio (ratio of portal venous phase attenuation to VNC attenuation). Readers' mean measurements were used for ROC analyses, and clinically optimal thresholds were derived as thresholds yielding the highest sensitivity at 100% specificity. RESULTS. Adenomas and nonadenomas were significantly different (all p < .001) in VNC attenuation (mean ± SD, 18.5 ± 12.9 vs 34.1 ± 8.9 HU), fat fraction (mean ± SD, 24.3% ± 8.2% vs 14.2% ± 5.6%), normalized iodine density (mean ± SD, 0.34 ± 0.15 vs 0.17 ± 0.17), and relative enhancement ratio (mean ± SD, 186% ± 96% vs 58% ± 59%). AUCs for all metrics ranged from 0.81 through 0.91. The metric with highest sensitivity for adenoma at the clinically optimal threshold (i.e., 100% specificity) was fat fraction (threshold, ≥ 23.8%; sensitivity, 59% [95% CI, 48-69%]) followed by VNC attenuation (≤ 15.2 HU; sensitivity, 39% [95% CI, 29-50%]), relative enhancement ratio (≥ 214%; sensitivity, 37% [95% CI, 25-50%]), and normalized iodine density (≥ 0.90; sensitivity, 1% (95% CI, 0-60%]). VNC attenuation at the traditional true noncontrast attenuation threshold of 10 HU or lower had sensitivity of 28% (95% CI, 19-38%) and 100% specificity. Presence of fat fraction 23.8% or greater or relative enhancement ratio 214% or greater yielded sensitivity of 68% (95% CI, 57-77%) with 100% specificity. CONCLUSION. For adrenal lesions evaluated with single-phase DECT, fat fraction had higher sensitivity than VNC attenuation at both the clinically optimal threshold and the traditional threshold of 10 HU or lower. CLINICAL IMPACT. By helping to definitively diagnose adenomas, DECT-derived metrics can help avoid downstream imaging for incidental adrenal lesions.

Liver Iodine Quantification With Photon-Counting Detector CT: Accuracy in an Abdominal Phantom and Feasibility in Patients

RATIONALE AND OBJECTIVES

To compare the accuracy of iodine quantification in liver parenchyma and lesions between dual-source photon-counting detector CT (PCD-CT) and dual-source energy-integrating detector CT (EID-CT) in a phantom and to demonstrate the feasibility of iodine quantification with PCD-CT in liver parenchyma and lesions in patients.

MATERIALS AND METHODS

An anthropomorphic abdominal phantom with a liver insert containing parenchyma and lesions was imaged on a clinical PCD-CT at 120kV and in the dual-energy mode on an EID-CT with kV-combinations of 80/Sn150kV, 90/Sn150kV, and 100/Sn150kV. Three patient sizes were imaged at three different radiation doses (CTDI_vol: 5, 10, 15mGy). Thirty patients with liver cysts, hemangiomas or metastases imaged with PCD-CT were retrospectively included. Iodine maps were reconstructed and iodine concentrations were measured in liver parenchyma and lesions. For the phantom, iodine error was quantified as the absolute difference to the vendor's specifications as reference.

RESULTS

Overall iodine error was 0.33 ± 0.29, 0.34 ± 0.32, 0.39 ± 0.37, 0.35 ± 0.39 mgI/mL for 80/Sn150kV, 90/Sn150kV, 100/Sn150kV of EID-CT, and PCD-CT, respectively, without significant differences between PCD-CT and EID-CT (p > 0.05). Radiation dose did not significantly influence error of PCD-CT (p > 0.05) nor EID-CT (p > 0.05). For both scanners, smaller patient sizes were associated with lower errors (p < 0.05). Iodine concentration and base material attenuation significantly influenced quantification for EID-CT (p < 0.05) but not PCD-CT (p > 0.05). In patients, iodine quantification was feasible in liver parenchyma, cysts, hemangiomas, and metastases.

CONCLUSION

Iodine quantification with PCD-CT is accurate in simulated liver parenchyma and lesions irrespective of radiation dose, iodine concentration, and base attenuation and is feasible in common liver lesions in patients.

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.

Dual-Energy CT of the Abdomen: Radiology In Training

A 61-year-old man with an esophageal cancer diagnosis underwent staging dual-energy CT of the chest and abdomen in the portal venous phase after contrast media administration. Aside from the primary tumor and suspicious local lymph nodes, CT revealed hypoattenuating ambiguous liver lesions, an incidental right adrenal nodule, and a right renal lesion with soft-tissue attenuation. In addition, advanced atherosclerosis of the abdominal aorta and its major branches was noted. This article provides a case-based review of dual-energy CT technologies and their applications in the abdomen. The clinical utility of virtual monoenergetic images, virtual unenhanced images, and iodine maps is discussed.

Virtual non-contrast detector-based spectral CT predictably overestimates tissue density for the characterisation of adrenal lesions compared to true non-contrast CT

PURPOSE

To establish if virtual non-contrast (VNC) images generated from contrast-enhanced detector-based spectral CT could replace true non-contrast (TNC) imaging for the characterisation of adrenal masses.

METHODS

TNC and VNC images were retrospectively reviewed for 39 patients with one or more adrenal lesions who underwent contrast-enhanced spectral CT of the upper abdomen. Lesions were categorised as either 'adenoma' or 'indeterminate/other lesion' based on current reference standards. The CT density of each lesion was measured on both image sets by two readers and compared using Wilcoxon signed-rank test. ROC analysis with Youden's J index method was performed to determine the optimal attenuation cut-off for diagnosing benign adenoma on VNC images.

RESULTS

Forty-four lesions were included, 37 of which were diagnosed as adenomas. There were significant differences between TNC and VNC measurements for both readers (mean difference 9.1 HU for reader 1; 9.8 HU for reader 2; p < 0.01). Optimal attenuation thresholds for diagnosing adenomas on VNC were 25.3 HU (reader 1) and 23.9 HU (reader 2) for the entire population, and 18.3 HU (reader 1) and 19.7 HU (reader 2) for lipid-rich adenomas < 10 HU on TNC imaging.

CONCLUSION

There is insufficient evidence to support the use of VNC as a substitute for TNC images in the characterisation of adrenal lesions. VNC using a detector-based spectral CT scanner shows a predictable increase in attenuation values compared to TNC. Thus, future studies might be better directed towards finding a new threshold value for diagnosing benign adrenal adenomas on VNC imaging.