RATIONALE AND OBJECTIVES:Our purpose is to explore the role of dual-energy computed tomography (DECT) and virtual monoenergetic energy levels in reducing shoulder artifact to improve visualization of the cervical spinal canal.MATERIALS AND METHODS:A retrospective review of 171 consecutive DECT scans of the neck (95 male, 65 female; mean age, 60.9 years, ranging from 18 to 88 years; with 11 excluded because of nondiagnostic image quality) during an 8-month period was performed with postprocessing of monoenergetic images at 50, 70, 100, and 140 keV. Subjective comparisons and objective image noise between the monoenergetic images and standard computed tomography (CT) were analyzed by 1-way analysis of variance to determine the optimal DECT energy level with the highest image quality.RESULTS:Subjectively, 100-keV DECT best visualizes the spinal canal relative to standard CT, 50 and 70 keV ( P < 0.01), and was superior to 140 keV for reader 1 ( P < 0.01). Objectively, 100 keV demonstrated less noise relative to 50 keV (72.02; P < 0.01). There was no difference in noise between 100 keV and 70 keV, or between 100 keV and standard CT, which also demonstrated lower noise relative to 50-, 70-, and 140-keV levels (91.53, P < 0.01; 29.84, P < 0.01; and 22.66, P < 0.03).CONCLUSION:Dual-energy CT at 100 keV may be the preferred DECT monoenergetic level for soft tissue assessment. Increasing energy level is associated with reduction in shoulder artifact, with no difference in noise between 100 keV and standard CT, although 100-keV images may be subjectively better.

Background Renal angiomyolipoma (AML) are benign masses that require detection of macroscopic fat for accurate diagnosis. Purpose To evaluate fat material-specific images derived from dual-energy computed tomography (DECT) to diagnose renal AML. Material and Methods This retrospective case-control study evaluated 25 renal AML and 44 solid renal masses (41 renal cell carcinomas, three other tumors) imaged with rapid-kVp-switch DECT (120 kVp non-contrast-enhanced [NECT], 70-keV corticomedullary [CM], and 120-kVp nephrographic [NG]-phase CECT) during 2017–2018. A radiologist measured attenuation (Hounsfield Units [HU]) on NECT, CM-CECT, NG-CECT, and fat concentration (mg/mL) using fat-water base-pair images. Results At NECT, 100% (44/44) non-AML and 4.0% (1/25) AML measured >–15 HU. At CM-CECT and NG-CECT, 24.0% (6/25) and 20.0% (5/25) AML measured >–15 HU (size 6–20 mm). To diagnose AML, area under receiver operating characteristic curve (AUC) using –15 HU was: 0.98 (95% confidence interval [CI] 0.98–1.00) NECT, 0.88 (95% CI 0.79–0.91) CM-CECT, and 0.90 (95% CI 0.82–0.98) NG-CECT. At DECT, fat concentration was higher in AML (163.7 ± 333.9 [–553.0 to 723.5] vs. –2858.1 ± 460.3 [–2421.2 to –206.0] mg/mL, P<0.001). AUC to diagnose AML using ≥–206.0 mg/mL threshold was 0.98 (95% CI 0.95–1.0) with sensitivity/specificity of 92.0%/96.7%. Of AML, 8.0% (2/25) were incorrectly classified; one of these was fat-poor. AUC was higher for fat concentration compared to HU measurements on CM-CECT and NG-CECT ( P=0.009–0.050) and similar to NECT ( P=0.98). Conclusion DECT material-specific fat images can help confirm the presence of macroscopic fat in renal AML which may be useful to establish a diagnosis if unenhanced CT is unavailable.

This study aimed to assess material-specific iodine and fat images for diagnosis of clear cell renal cell carcinoma (cc-RCC) compared to papillary RCC (p-RCC) and other renal masses. With IRB approval, we identified histologically confirmed solid renal masses that underwent rapid-kVp-switch DECT between 2016 and 2018: 25 cc-RCC (7 low grade versus 18 high grade), 11 p-RCC, and 6 other tumors (2 clear cell papillary RCC, 2 chromophobe RCC, 1 oncocytoma, 1 renal angiomyomatous tumor). A blinded radiologist measured iodine and fat concentration on material-specific iodine–water and fat–water basis pair images. Comparisons were performed between groups using univariate analysis and diagnostic accuracy calculated by ROC. Iodine concentration was higher in cc-RCC (6.14 ± 1.79 mg/mL) compared to p-RCC (1.40 ± 0.54 mg/mL, p < 0.001), but not compared to other tumors (5.0 ± 2.2 mg/mL, p = 0.370). Intratumoral fat was seen in 36.0% (9/25) cc-RCC (309.6 ± 234.3 mg/mL [71.1–762.3 ng/mL]), 9.1% (1/11) papillary RCC (97.11 mg/mL), and no other tumors (p = 0.036). Iodine concentration ≥ 3.99 mg/mL achieved AUC and sensitivity/specificity of 0.88 (CI 0.76–1.00) and 92.31%/82.40% to diagnose cc-RCC. To diagnose p-RCC, iodine concentration ≤ 2.5 mg/mL achieved AUC and sensitivity/specificity of 0.99 (0.98–1.00) and 100%/100%. The presence of intratumoral fat had AUC 0.64 (CI 0.53–0.75) and sensitivity/specificity of 34.6%/93.8% to diagnose cc-RCC. A logistic regression model combining iodine concentration and presence of fat increased AUC to 0.91 (CI 0.81–1.0) with sensitivity/specificity of 80.8%/93.8% to diagnose cc-RCC. Iodine concentration values are highly accurate to differentiate clear cell RCC from papillary RCC; however, they overlap with other tumors. Fat-specific images may improve differentiation of clear cell RCC from other avidly enhancing tumors. • Clear cell renal cell carcinoma (RCC) has significantly higher iodine concentration than papillary RCC, but there is an overlap in values comparing clear cell RCC to other renal tumors. • Iodine concentration ≤ 2.5 mg/mL is highly accurate to differentiate papillary RCC from clear cell RCC and other renal tumors. • The presence of microscopic fat on material-specific fat images was specific for clear cell RCC, helping to differentiate clear cell RCC from other avidly enhancing renal tumors.

OBJECTIVE. The objective of our study was to evaluate iodine concentration and attenuation change in Hounsfield unit (ΔHU) thresholds to diagnose enhancement in renal masses at rapid-kilovoltage-switching dual-energy CT (DECT). MATERIALS AND METHODS. We evaluated 30 consecutive histologically confirmed solid renal masses (including nine papillary renal cell carcinomas [RCCs]) and 27 benign cysts (17 simple and 10 hemorrhagic or proteinaceous cysts) with DECT December 2016 and May 2018. A blinded radiologist measured iodine concentration (in milligrams per milliliter) and ΔHU (attenuation on enhanced CT - attenuation on unenhanced CT) using 70-keV corticomedullary (CM) phase virtual monochromatic and 120-kVp nephrographic (NG) phase images. The accuracies of previously described enhancement thresholds were compared by ROC curve analysis. RESULTS. An iodine concentration of ≥ 2.0 mg/mL and an iodine concentration of ≥ 1.2 mg/mL achieved sensitivity, specificity, and the area under the ROC curve (AUC) of 73.3%, 100.0%, and 0.87 and 86.7%, 100.0%, and 0.93, respectively. On 70-keV CM phase images, ΔHU ≥ 20 HU and ΔHU ≥ 15 HU yielded sensitivity, specificity, and AUC of 80.0%, 100.0%, and 0.90 and 90.0%, 100.0%, and 0.95, respectively. The numbers of incorrectly classified papillary RCCs were as follows: iodine concentration of ≥ 2.0 mg/mL, 77.8% (7/9; range, 0.7-1.6 mg/mL); iodine concentration of ≥ 1.2 mg/mL, 44.4% (4/9; range, 0.7-0.9 mg/mL); ΔHU ≥ 20 HU on 70-keV CM phase images, 66.7% (6/9; range, 4-17 HU); and ΔHU ≥ 15 HU on 70-keV DECT images, 33.3% (3/9; 4-12 HU). No cyst pseudoenhancement occurred on DECT. For 120-kVp NG phase DECT, ΔHU ≥ 20 HU and ΔHU ≥ 15 HU yielded sensitivity, specificity, and AUC of 93.3%, 96.3%, and 0.95 and 100.0%, 88.9%, and 0.94, respectively. With ΔHU ≥ 20 HU, 22.2% (2/9) (range, 15-18 HU) of papillary RCCs were misclassified and there was one pseudoenhancing cyst. With ΔHU ≥ 15 HU, no papillary RCCs were misclassified but 11.1% (3/27) of cysts showed pseudoenhancement. Only an iodine concentration of ≥ 2.0 mg/mL showed significantly lower accuracy than other measures (p = 0.031-0.045). CONCLUSION. DECT applied in the CM phase performed best using an iodine concentration of ≥ 1.2 mg/mL or a 70-keV ΔHU ≥ 15 HU; these parameters improved sensitivity for the detection of enhancement in renal masses without instances of cyst pseudoenhancement.

OBJECTIVE. The purpose of this study was to compare attenuation values (in Hounsfield units) and degree of enhancement (attenuation change) in renal masses using 120-kVp polychromatic (conventional) CT and 70-keV monochromatic dual-energy CT (DECT). MATERIALS AND METHODS. Twenty-two patients with 39 renal masses (24 Bosniak category I and II cysts and 15 solid masses under active surveillance) underwent conventional CT (120-kVp unenhanced and contrast-enhanced CT) and rapid kilovoltage-switching DECT (120-kVp unenhanced CT and 70-keV contrast-enhanced CT). The mean (+/- SD) time between scans was 648 +/- 943 days. A radiologist measured attenuation on matched image sets coregistered between examinations. Absolute attenuation and attenuation change were compared using independent t tests, Pearson correlation, and Bland Altman analysis. RESULTS. There was no difference in attenuation on 120-kVp versus 70-keV contrast-enhanced CT images for cysts (9.5 +/- 5.5 HU [range, -2 to 20 HU] vs 10.1 +/- 4.6 HU [range, -2 to 16 HU]; p = 0.33) and solid masses (110.1 +/- 72.9 HU [range, 35-267 HU] vs 119.1 +/- 73.7 HU [range, 33-265 I IU]; p = 0.04). There also was no difference in attenuation change for 120-kVp contrast-enhanced CT minus 120-kVp unenhanced CT (cysts, 3.5 +/- 3.9 HU [range, -2 to 13 HU]; solid masses, 80.7 +/- 73.3 HU [range, 9-227 HU]; p = 0.45) or for 70-keV contrast-enhanced CT minus 120-kVp unenhanced CT (cysts, 4.3 +/- 41 HU [range, -3 to 12 HU]; solid masses, 89.8 +/- 74.1 I IU [range, 7-226 I IU]; p = 0.04). The correlation was strong to almost perfect (beta = 0.83-0.98) with substantial agreement There was no difference in attenuation of cysts and solid masses comparing 120-kVp acquisitions acquired at different time points (p = 0.200.92). The correlation was strong to almost perfect (beta= 0.72-0.95) with substantial agreement. CONCLUSION. There are no differences in absolute attenuation or degree of enhancement comparing 70-keV monochromatic CT to conventional 120-kVp CT in renal cysts and solid masses.

Stroke is associated with vulnerable carotid artery plaques showing specific histopathologic features, namely a lipid-rich necrotic core, intraplaque hemorrhage, ulceration, and thin fibrous cap. While ultrasound and computed tomography (CT) can identify carotid plaques and determine the extent of stenosis, magnetic resonance imaging (MRI) provides further information regarding plaque composition and morphology. In this feasibility study, three patients with symptomatic, moderately stenosed plaques were imaged with CT angiography (CTA) and MRI (3T and 1.5T) without a dedicated receiver coil. The patients subsequently underwent carotid endarterectomy with en-bloc excision of the plaque. The CT and MR images were analyzed independently by three neuroradiologists to identify vulnerable plaque features. The images were correlated with the histopathology to confirm the findings. All three patients had one or more vulnerable plaque features on histopathology. MRI allowed for better characterization of these features when compared to CTA. The pre- and post-contrast T1-weighted (T1W) images were most helpful for identifying the lipid-rich necrotic core and thin fibrous cap, while the time of flight-magnetic resonance angiography (TOF-MRA) and contrast-enhanced (CE)-MRA were excellent for detecting plaque hemorrhage and ulceration, respectively. The 3T images showed superior spatial and contrast resolution compared to the 1.5T images for all sequences. By providing direct correlation between imaging and histopathology, this study demonstrates that 3T MRI without a dedicated surface coil is an excellent tool for assessing plaque vulnerability. In smaller hospitals or those with limited resources, it is reasonable to consider conventional MRI for patient risk stratification. Further studies are needed to determine how MRI and plaque vulnerability can be incorporated into routine clinical practice.

Purpose: Imaging plaque morphology, in addition to luminal grading, may improve stroke risk-management by identifying structural atherosclerotic plaques alterations responsible for cerebrovascular events. The purpose of this study was to evaluate the agreement between our enhanced ultrasound (US) imaging method and high-resolution cross-sectional imaging modalities, such as multidetector-row computed tomography (CT) and magnetic resonance imaging (MRI), in the characterization of vulnerable plaques.Methods: Sixty tissue-like phantoms were created to simulate various types of diseased plaque segments. We prospectively assessed each sample with US, CT, and MRI. Plaque characteristics considered included surface irregularity, ulceration, fissure, and presence of internal fluid core(s). We evaluated the agreement between and among the three modalities, as well as the accuracy of each compared with the true pathology.Results: There was moderate to substantial agreement among the three modalities in the detection of morphologic characteristics. There was no significant difference in accuracy between US and CT in the presence of ulceration(s) (P = .23), lucency (P = .23), or fissures (P = .07); however, US was significantly more accurate than MRI for each of these characteristics (P = .0001, P = .0001, P = .02, respectively). None of the three modalities did display any significant difference in accuracy in the identification of irregular surface. There was substantial agreement among the three radiologists (intraclass correlation coefficient, 0.61; 95% confidence interval, 0.46-0.74) in their assessment of plaque subtype, ranging from 80%-85% accuracy in identifying the plaque subtypes for each classification.Conclusions: Enhanced plaque imaging can identify potentially significant plaque characteristics and provide insight into early causative conditions of carotid atherosclerosis. Our results suggest that the types of plaque pathologies derived from our US method showed good agreement with CT and surpass information gathered on MRI. This imaging protocol could potentially shift the paradigm in early carotid plaque imaging likely to predict the onset of vulnerable plaques, thus improving preventative management of atherosclerosis.