Intraindividual Consistency of Iodine Concentration in Dual-Energy Computed Tomography of the Chest and Abdomen

Spectral CT for non-invasive evaluation of bladder cancer grade

OBJECTIVE

To investigate the potential role of dual-energy spectral computer tomography (CT) quantitative parameters in the definition of bladder cancer (BCa) pathological grading.

METHODS

This retrospective study evaluated the use of spectral CT imaging features for BCa. From 2021 to 2023, 63 patients with histologically-confirmed BCa diagnosis were examined at our Institution. The patients were pathologically divided, following international guidelines, into two groups: low-grade (n = 24) and high-grade urothelial carcinoma group (n = 39). The iodine concentrations (IC), the normalized iodine concentrations (NIC), and the slope of the spectrum curve (SLOPE) were calculated along with the measure of each lesion CT value on the monochromatic image from 40 to 120 keV. The diagnostic performance was assessed by Receiver operator characteristic curve (ROC) analysis.

RESULTS

The high-grade group showed significantly higher mean values of IC, SLOPE, and HU in 40 KeV monoenergetic images (VMI40 HU). AUC values for NIC, SLOPE, IC, and VMI40 HU were 0,677, 0,745, 0,745, and 0,755 respectively. In multivariate logistic regression models with backward stepwise, including all quantitative parameters, only VMI40 HU remained statistically significant to correlate with high-grade tumors.

CONCLUSION

Preliminary data shows that quantitative parameters of dual-energy spectral CT can be helpful to characterize low-grade and high-grade urothelial bladder tumors. The prediction of high-grade BCa with non-invasive methods (e.g. dlCT) can aid in early detection of muscle-invasive and worse prognostic tumors that need more aggressive and timely treatments, personalizing the management on the risk of recurrence.

Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-based quantitative parameters to predict high Ki-67 proliferation index in pancreatic ductal adenocarcinoma

OBJECTIVE

To develop and validate a model integrating dual-layer detector spectral computed tomography (DLCT) three-dimensional (3D) volume of interest (VOI)-based quantitative parameters and clinical features for predicting Ki-67 proliferation index (PI) in pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

A total of 162 patients with histopathologically confirmed PDAC who underwent DLCT examination were included and allocated to the training (114) and validation (48) sets. 3D VOI-iodine concentration (IC), 3D VOI-slope of the spectral attenuation curves, and 3D VOI-effective atomic number were obtained from the portal venous phase. The significant clinical features and DLCT quantitative parameters were identified through univariate analysis and multivariate logistic regression. The discrimination capability and clinical applicability of the clinical, DLCT, and DLCT-clinical models were quantified by the Receiver Operating Characteristic curve (ROC) and Decision Curve Analysis (DCA), respectively. The optimal model was then used to develop a nomogram, with the goodness-of-fit evaluated through the calibration curve.

RESULTS

The DLCT-clinical model demonstrated superior predictive capability and a satisfactory net benefit for Ki-67 PI in PDAC compared to the clinical and DLCT models. The DLCT-clinical model integrating 3D VOI-IC and CA125 showed area under the ROC curves of 0.939 (95% CI, 0.895-0.982) and 0.915 (95% CI, 0.834-0.996) in the training and validation sets, respectively. The nomogram derived from the DLCT-clinical model exhibited favorable calibration, as depicted by the calibration curve.

CONCLUSIONS

The proposed model based on DLCT 3D VOI-IC and CA125 is a non-invasive and effective preoperative prediction tool demonstrating favorable predictive performance for Ki-67 PI in PDAC.

CRITICAL RELEVANCE STATEMENT

The dual-layer detector spectral computed tomography-clinical model could help predict high Ki-67 PI in pancreatic ductal adenocarcinoma patients, which may help clinicians provide appropriate and individualized treatments.

KEY POINTS

Dual-layer detector spectral CT (DLCT) could predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). The DLCT-clinical model improved the differential diagnosis of Ki-67. The nomogram showed satisfactory calibration and net benefit for discriminating Ki-67.

Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques

OBJECTIVES

To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches.

METHODS

Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NICPV:portal vein; NICAA:abdominal aorta; NICALL:overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration.

RESULTS

Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28-46.87) %, dsDECT vs. rsDECT 29.08 (16.59-62.55) %, rsDECT vs. dlDECT 22.85 (7.52-33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03-26.1) %, dsDECT vs. rsDECT 15.67 (8.86-25.56) %, rsDECT vs. dlDECT 10.92 (4.92-22.79) %). NICALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NICALL in the pancreas and the liver (F-values, 12.26 and 23.78; both, p < 0.0001).

CONCLUSIONS

We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution. After normalization, the scanner type still had a significant effect on iodine variability in the pancreas and liver.

CLINICAL RELEVANCE STATEMENT

Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging.

KEY POINTS

• Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92-15.76%) and highest variability in the liver (range 22.85-29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.

Dual-layer dual-energy CT-derived pulmonary perfusion for the differentiation of acute pulmonary embolism and chronic thromboembolic pulmonary hypertension

OBJECTIVES

To evaluate dual-layer dual-energy computed tomography (dlDECT)-derived pulmonary perfusion maps for differentiation between acute pulmonary embolism (PE) and chronic thromboembolic pulmonary hypertension (CTEPH).

METHODS

This retrospective study included 131 patients (57 patients with acute PE, 52 CTEPH, 22 controls), who underwent CT pulmonary angiography on a dlDECT. Normal and malperfused areas of lung parenchyma were semiautomatically contoured using iodine density overlay (IDO) maps. First-order histogram features of normal and malperfused lung tissue were extracted. Iodine density (ID) was normalized to the mean pulmonary artery (MPA) and the left atrium (LA). Furthermore, morphological imaging features for both acute and chronic PE, as well as the combination of histogram and morphological imaging features, were evaluated.

RESULTS

In acute PE, normal perfused lung areas showed a higher mean and peak iodine uptake normalized to the MPA than in CTEPH (both p < 0.001). After normalizing mean ID in perfusion defects to the LA, patients with acute PE had a reduced average perfusion (IDmean,LA) compared to both CTEPH patients and controls (p < 0.001 for both). IDmean,LA allowed for a differentiation between acute PE and CTEPH with moderate accuracy (AUC: 0.72, sensitivity 74%, specificity 64%), resulting in a PPV and NPV for CTEPH of 64% and 70%. Combining IDmean,LA in the malperfused areas with the diameter of the MPA (MPAdia) significantly increased its ability to differentiate between acute PE and CTEPH (sole MPAdia: AUC: 0.76, 95%-CI: 0.68-0.85 vs. MPAdia + 256.3 * IDmean,LA - 40.0: AUC: 0.82, 95%-CI: 0.74-0.90, p = 0.04).

CONCLUSION

dlDECT enables quantification and characterization of pulmonary perfusion patterns in acute PE and CTEPH. Although these lack precision when used as a standalone criterion, when combined with morphological CT parameters, they hold potential to enhance differentiation between the two diseases.

CLINICAL RELEVANCE STATEMENT

Differentiating between acute PE and CTEPH based on morphological CT parameters is challenging, often leading to a delay in CTEPH diagnosis. By revealing distinct pulmonary perfusion patterns in both entities, dlDECT may facilitate timely diagnosis of CTEPH, ultimately improving clinical management.

KEY POINTS

• Morphological imaging parameters derived from CT pulmonary angiography to distinguish between acute pulmonary embolism and chronic thromboembolic pulmonary hypertension lack diagnostic accuracy. • Dual-layer dual-energy CT reveals different pulmonary perfusion patterns between acute pulmonary embolism and chronic thromboembolic pulmonary hypertension. • The identified parameters yield potential to enable more timely identification of patients with chronic thromboembolic pulmonary hypertension.

Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters

OBJECTIVE

To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve.

RESULTS

Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency.

CONCLUSIONS

The DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients.

CRITICAL RELEVANCE STATEMENT

The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression.

KEY POINTS

• Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.

Accuracy and Precision of Iodine Quantification in Subtracted Micro-Computed Tomography: Effect of Reconstruction and Noise Removal Algorithms

PURPOSE

To evaluate the effect of reconstruction and noise removal algorithms on the accuracy and precision of iodine concentration (CI) quantified with subtracted micro-computed tomography (micro-CT).

PROCEDURES

Two reconstruction algorithms were evaluated: a filtered backprojection (FBP) algorithm and a simultaneous iterative reconstruction technique (SIRT) algorithm. A 3D bilateral filter (BF) was used for noise removal. A phantom study evaluated and compared the image quality, and the accuracy and precision of CI in four scenarios: filtered FBP, filtered SIRT, non-filtered FBP, and non-filtered SIRT. In vivo experiments were performed in an animal model of chemically-induced mammary cancer.

RESULTS

Linear relationships between the measured and nominal CI values were found for all the scenarios in the phantom study (R2 > 0.95). SIRT significantly improved the accuracy and precision of CI compared to FBP, as given by their lower bias (adj. p-value = 0.0308) and repeatability coefficient (adj. p-value < 0.0001). Noise removal enabled a significant decrease in bias in filtered SIRT images only; non-significant differences were found for the repeatability coefficient. The phantom and in vivo studies showed that CI is a reproducible imaging parameter for all the scenarios (Pearson r > 0.99, p-value < 0.001). The contrast-to-noise ratio showed non-significant differences among the evaluated scenarios in the phantom study, while a significant improvement was found in the in vivo study when SIRT and BF algorithms were used.

CONCLUSIONS

SIRT and BF algorithms improved the accuracy and precision of CI compared to FBP and non-filtered images, which encourages their use in subtracted micro-CT imaging.

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals

Purpose

The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of bone marrow iodine uptake after intravenous contrast application, and examine its dependence on vBMD, iodine blood pool, patient age, and sex.

Method

Retrospective analysis of oncological patients without evidence of metastatic disease. DECT examinations were performed on a spectral detector CT scanner in portal venous contrast phase. The thoracic and lumbar spine were segmented by a pre-trained neural network, obtaining volumetric iodine concentration data [mg/ml]. vBMD was assessed using a phantomless, CE-certified software [mg/cm3]. The iodine blood pool was estimated by ROI-based measurements in the great abdominal vessels. A multivariate regression model was fit with the dependent variable "median bone marrow iodine uptake". Standardized regression coefficients (β) were calculated to assess the impact of each covariate.

Results

678 consecutive DECT exams of 189 individuals (93 female, age 61.4 ± 16.0 years) were evaluated. AI-based segmentation provided volumetric data of 97.9% of the included vertebrae (n=11,286). The 95^th percentile of bone marrow iodine uptake, as a surrogate for the upper margin of the physiological distribution, ranged between 4.7-6.4 mg/ml. vBMD (p <0.001, mean β=0.50) and portal vein iodine blood pool (p <0.001, mean β=0.43) mediated the strongest impact. Based thereon, adjusted reference values were calculated.

Conclusion

The bone marrow iodine uptake demonstrates a distinct profile depending on vBMD, iodine blood pool, patient age, and sex. This study is the first to provide the adjusted reference values.

Utility of dual-layer spectral-detector CT imaging for predicting pathological tumor stages and histologic grades of colorectal adenocarcinoma

Objectives

To assess the utility of Dual-layer spectral-detector CT (DLCT) in predicting the pT stage and histologic grade for colorectal adenocarcinoma (CRAC).

Methods

A total of 131 patients (mean 62.7 ± 12.9 years; 72 female, 59 male) with pathologically confirmed CRAC (35 pT1-2, 61 pT3, and 35 pT4; 32 high grade and 99 low grade), who received dual-phase DLCT were enrolled in this retrospective study. Normalized iodine concentration (NIC), slope of the spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured for each lesion by two radiologists independently. Intraobserver reliability and interobserver agreement were assessed. The above values were compared between three pT-stage and two histologic-grade groups. The correlation between the pT stages and above values were assessed. Receiver operating characteristic (ROC) curves were calculated to evaluate the diagnostic efficacy.

Results

Intra-class correlation coefficients were ranged from 0.856 to 0.983 for all measurements. Eff-Z [7.21(0.09) vs 7.31 (0.10) vs 7.35 (0.19)], NIC_AP [0.11 (0.05) vs 0.15 (0.08) vs 0.15 (0.08)], NIC_VP [0.27 (0.06) vs 0.34 (0.11) vs 0.35 (0.12)], λHU_AP [1.20 (0.45) vs 1.93 (1.18) vs 2.37 (0.91)], and λHU_VP [2.07 (0.68) vs 2.35 (0.62) vs 3.09 (1.07)] were significantly different among pT stage groups (all P<0.001) and exhibited a positive correlation with pT stages (r= 0.503, 0.455, 0.394, 0.512, 0.376, respectively, all P<0.001). Eff-Z [7.37 (0.10) vs 7.28 (0.08)], NIC_AP[0.20 (0.10) vs 0.13 (0.08)], NIC_VP[0.35 (0.07) vs 0.31 (0.11)], and λHU_AP [2.59 (1.11) vs 1.63 (0.75)] in the high-grade group were markedly higher than those in the low-grade group (all P<0.05). For discriminating the advanced- from early-stage CARC, the AUCs of Eff-Z, NIC_AP, NIC_VP, λHU_AP, and λHU_VP were 0.83, 0.80, 0.79, 0.86, and 0.68, respectively (all P<0.001). For discriminating the high- from low-grade CARC, the AUCs of Eff-Z, NIC_AP, NIC_VP, and λHU_AP were 0.81, 0.81, 0.64, and 0.81, respectively (all P<0.05).

Conclusions

The quantitative parameters derived from DLCT may provide new markers for assessing pT stages and histologic differentiation in patients with CRAC.

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.

Spectral Detector CT-Derived Pulmonary Perfusion Maps and Pulmonary Parenchyma Characteristics for the Semiautomated Classification of Pulmonary Hypertension

Objectives

To evaluate the usefulness of spectral detector CT (SDCT)-derived pulmonary perfusion maps and pulmonary parenchyma characteristics for the semiautomated classification of pulmonary hypertension (PH).

Methods

A total of 162 consecutive patients with right heart catheter (RHC)-proven PH of different aetiologies as defined by the current ESC/ERS guidelines who underwent CT pulmonary angiography (CTPA) on SDCT and 20 patients with an invasive rule-out of PH were included in this retrospective study. Semiautomatic lung segmentation into normal and malperfused areas based on iodine density (ID) as well as automatic, virtual non-contrast-based emphysema quantification were performed. Corresponding volumes, histogram features and the ID SkewnessPerfDef-Emphysema-Index (δ-index) accounting for the ratio of ID distribution in malperfused lung areas and the proportion of emphysematous lung parenchyma were computed and compared between groups.

Results

Patients with PH showed a significantly greater extent of malperfused lung areas as well as stronger and more homogenous perfusion defects. In group 3 and 4 patients, ID skewness revealed a significantly more homogenous ID distribution in perfusion defects than in all other subgroups. The δ-index allowed for further subclassification of subgroups 3 and 4 (p &lt; 0.001), identifying patients with chronic thromboembolic PH (CTEPH, subgroup 4) with high accuracy (AUC: 0.92, 95%-CI, 0.85–0.99).

Conclusion

Abnormal pulmonary perfusion in PH can be detected and quantified by semiautomated SDCT-based pulmonary perfusion maps. ID skewness in malperfused lung areas, and the δ-index allow for a classification of PH subgroups, identifying groups 3 and 4 patients with high accuracy, independent of reader expertise.

Using quantitative parameters derived from pretreatment dual-energy computed tomography to predict histopathologic features in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) patients with a high tumor grade, lymphovascular invasion (LVI), or perineural invasion (PNI) tend to demonstrate a poor prognosis in clinical series. Thus, the identification of histopathological features, including tumor grade, LVI, and PNI, before treatment could be used to stratify the prognosis of patients with HNSCC. This study aimed to assess whether quantitative parameters derived from pretreatment dual-energy computed tomography (DECT) can predict the histopathological features of patients with HNSCC.

METHODS

In this study, 72 consecutive patients with pathologically confirmed HNSCC were enrolled and underwent dual-phase (noncontrast-enhanced phase and contrast-enhanced phase) DECT examinations. Normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit curve (λ_HU), and normalized effective atomic number (NZ_eff) were calculated. The attenuation values on 40-140 keV noise-optimized virtual monoenergetic images [VMIs (+)] in the contrast-enhanced phase were recorded. The diagnostic performance of the quantitative parameters for predicting histopathological features, including tumor grade, LVI, and PNI, was assessed by receiver operating characteristic curves.

RESULTS

The NIC, λ_HU, NZ_eff, and attenuation value on the VMIs (+) at 40 keV (A₄₀) in the grade III group, LVI-positive group, and PNI-positive group were significantly higher than those in the grade I and II groups, the LVI-negative group, and the PNI-negative group (all P values <0.05). A multivariate logistic regression model combining these 4 quantitative parameters improved the diagnostic performance of the model in predicting tumor grade, LVI, and PNI (areas under the curve: 0.969, 0.944, and 0.931, respectively).

CONCLUSIONS

Quantitative parameters derived from pretreatment DECT, including NIC, λ_HU, NZ_eff, and A_4,0 were found to be imaging markers for predicting the histopathological characteristics of HNSCC. Combining all these characteristics improved the predictive performance of the model.

Longitudinal reproducibility of attenuation measurements on virtual unenhanced images: multivendor dual-energy CT evaluation

OBJECTIVES

The accuracy of virtual unenhanced (VUE) images has been extensively investigated, yet data on their longitudinal reproducibility is limited. The study purpose was to evaluate the longitudinal reproducibility of VUE attenuation measurements on three different dual-energy CT (DECT) scanner types.

METHODS

A total of 137 patients with repeated abdominal DECT either on a rapid kV switching (rsDECT; n = 46), a dual-layer detector (dlDECT; n = 43), or a dual-source scanner (dsDECT; n = 48) were retrospectively included. Attenuation was measured on VUE and corresponding contrast-enhanced images in the liver, spleen, kidneys, aorta, portal vein, and fat. Longitudinal reproducibility was evaluated by calculating the absolute inter-scan differences (HU) and the inter-scan variation (%). Measurement pairs with differences ≤ 10 HU were considered reproducible. Influence of contrast-enhanced attenuation on VUE reproducibility was analyzed using linear regression.

RESULTS

The scanner-specific cohorts showed similar age (p-range: 0.35-0.99), sex (p-range: 0.68-1), body weight (p-range: 0.26-0.87), body diameter (p-range: 0.34-0.76), and inter-scan time (p-range: 0.52-0.83). In total, 94.9% of VUE measurements were reproducible for rsDECT, 93.8% for dlDECT, and 90.6% for dsDECT. Overall inter-scan variation was lowest in fat (4.0 (1.7-8.2)%) and highest in tissues with high contrast enhancement: the aorta (13.3 (4.6-21.3)%), portal vein (10.8 (5.7-19.8)%), and kidneys (10.7 (3.9-18.0)%). Significant differences in inter-scan variation were found between the scanner types for the aorta, portal vein, kidneys, and spleen. Inter-scan differences in contrast-enhanced attenuation significantly influenced inter-scan differences in VUE attenuation (p < 0.001; t-ratio: 4.34).

CONCLUSIONS

Longitudinal reproducibility of VUE attenuation was high for all scanners, yet inter-scan variation of VUE attenuation was influenced by contrast enhancement, showing greatest magnitude and discrepancy between scanner types in vessels and the kidneys.

KEY POINTS

• We found that 94.9% of attenuation measurements on virtual unenhanced images were reproducible for rapid kV switching DECT, 93.8% for dual-layer detector DECT, and 90.6% for dual-source DECT. • Inter-scan variation of attenuation in virtual unenhanced images was comparable between the three scanner types in the liver and fat, whereas inter-scan variation in the spleen, kidneys, portal vein, and aorta showed significant differences between scanner types (p < 0.05). • Inter-scan attenuation differences in contrast-enhanced images significantly influenced inter-scan differences in virtual unenhanced attenuation (p < 0.001, t-ratio: 4.34), suggesting a residual impact of contrast enhancement differences between examinations.

Value of spectral detector computed tomography to differentiate infected from noninfected thoracoabominal fluid collections

PURPOSE

To investigate the diagnostic value of spectral detector CT (SDCT)-derived virtual non-contrast (VNC), virtual monoenergetic images (VMI) and iodine overlays (IO) for distinguishing infected from noninfected fluid collections (FC) in the chest or abdomen.

METHOD

This retrospective study included 58 patients with venous phase SDCT with 77 FC. For all included FC, microbiological analysis of aspirated fluid served as reference. For quantitative analysis, wall thickness was measured, and (ROI)-based analysis performed within the fluid, the FC's wall (if any) and the aorta. Two radiologists qualitatively evaluated visibility of wall enhancement, diagnostic confidence regarding infection of fluid collection, confidence of CT-guided drainage catheter placement and visibility of anatomical landmarks in conventional images (CI) and VNC, VMI_40keV, IO.

RESULTS

Wall thickness significantly differed between infected (n = 46) and noninfected (n = 31) FC (3.5 ± 1.8 mm vs. 1.4 ± 1.8 mm, AUC = 0.81; p < 0.05). Fluid attenuation and wall enhancement was significantly higher in infected as compared to noninfected FC in all reconstructions (p < 0.05, respectively). Highest AUC regarding A) attenuation in fluid was yielded in CI and VMI_70,80keV (0.75); B) wall enhancement in CI (0.88) followed by iodine concentration (0.86). Contrast-to-noise ratio of wall vs. fluid was highest in VMI_40keV (p < 0.05). All assessed qualitative parameters received significantly higher ratings when using spectral reconstructions vs. CI (p for all <0.05), except for visibility of wall enhancement.

CONCLUSION

Spectral reconstructions improve the assessment of infected from noninfected thoracoabdominal fluid collections and depiction of wall enhancement. Diagnostic performance of the quantitative measurements in spectral reconstructions were comparable with measurements in conventional images.

A Method for Reducing Variability Across Dual-Energy CT Manufacturers in Quantification of Low Iodine Content Levels

Background: Clinical use of the dual-energy CT (DECT) iodine quantification technique is hindered by between-platform (i.e., across different manufacturers) variability in iodine concentration (IC), particularly at low iodine levels. Objective: To develop in an anthropomorphic phantom a method for reducing between-platform variability in quantification of low iodine content levels using DECT and to evaluate the method's performance in patients undergoing serial clinical DECT examinations on different platforms. Methods: An anthropomorphic phantom in three body sizes, incorporating varied lesion types and scanning conditions, was imaged with three distinct DECT implementations from different manufacturers at varying radiation exposures. A cross-platform iodine quantification model for correcting between-platform variability at low iodine content was developed using the phantom data. The model was tested in a retrospective series of 30 patients (20 men, 10 women; median age, 62 years) who each underwent three serial contrast-enhanced DECT examinations of the abdomen and pelvis (90 scans total) for routine oncology surveillance, using the same three DECT platforms as in the phantom. Estimated accuracy of phantom IC values was summarized using rootmean-squared error (RMSE) relative to known IC. Between-platform variability in patients was summarized using root-mean-square-deviation (RMSD). RMSE and RMSD were compared between platform-based IC (ICPB) and cross-platform IC (ICCP). ICPB was normalized to aorta and portal vein. Results: In the phantom study, mean RMSE of ICPB across platforms and other experimental conditions was 0.65 ± 0.18 mgI/mL compared with 0.40 ± 0.075 mgI/mL for ICCP (38% decrease in mean RMSE; P<.05). Intra-patient between-platform variability across serial DECT examinations was lower for ICPB than ICCP (RMSD: 97% vs 88%; P<.001). Between-platform variability was not reduced by normalization of ICPB to aorta (RMSD: 97% vs 101%; P=.12) or portal vein (RMSD: 97% vs 97%; P=.81). Conclusion: The developed cross-platform method significantly decreased between-platform variability occurring at low iodine content with platform-based DECT iodine quantification. Clinical Impact: With further validation, the cross-platform method, which has been implemented as a webbased app, may expand clinical use of DECT iodine quantification, yielding meaningful IC values that reflect tissue biologic viability or treatment response in patients who undergo serial examinations on different platforms.

Differentiating pulmonary metastasis from benign lung nodules in thyroid cancer patients using dual-energy CT parameters

OBJECTIVES

To explore the importance of quantitative characteristics of dual-energy CT (DECT) between pulmonary metastasis and benign lung nodules in thyroid cancer.

METHODS

In this retrospective study, we identified 63 patients from our institution's database with pathologically proven thyroid cancer who underwent DECT to assess pulmonary metastasis. Among these patients, 22 had 55 pulmonary metastases, and 41 had 97 benign nodules. If nodules showed increased iodine uptake on I-131 single-photon emission computed tomography-computed tomography or increased size in follow-up CT, they were considered metastatic. We compared the clinical findings and DECT parameters of both groups and performed a receiver operating characteristic analysis to evaluate the optimal cutoff values of the DECT parameters.

RESULTS

Patients with metastases were significantly older than patients with benign nodules (p = 0.048). The DECT parameters of the metastatic nodules were significantly higher than those of the benign nodules (iodine concentration [IC], 5.61 ± 2.02 mg/mL vs. 1.61 ± 0.98 mg/mL; normalized IC [NIC], 0.60 ± 0.20 vs. 0.16 ± 0.11; NIC using pulmonary artery [NIC_PA], 0.60 ± 0.44 vs. 0.15 ± 0.11; slope of the spectral attenuation curves [λHU], 5.18 ± 2.54 vs. 2.12 ± 1.39; and Z-effective value [Z_eff], 10.0 ± 0.94 vs. 8.79 ± 0.75; all p < 0.001). In the subgroup analysis according to nodule size, all DECT parameters of the metastatic nodules in all subgroups were significantly higher than those of the benign nodules (all p < 0.05). The cutoff values for IC, NIC, λHU, NIC_PA, and Z_eff for diagnosing metastases were 3.10, 0.29, 3.57, 0.28, and 9.34, respectively (all p < 0.001).

CONCLUSIONS

DECT parameters can help to differentiate metastatic and benign lung nodules in thyroid cancer.

KEY POINTS

• DECT parameters can help to differentiate metastatic and benign lung nodules in patients with thyroid cancer. • DECT parameters showed a significant difference between benign lung nodules and lung metastases, even for nodules with diameters ≥ 3 mm and < 5 mm. • Among the DECT parameters, the highest diagnostic accuracy for differentiating pulmonary metastases from benign lung nodules was achieved with the NIC and IC, followed by the NIC_PA and λHU, and their cutoff values were 0.29, 3.10, 0.28, and 3.57, respectively.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Dual-energy CT in predicting Ki-67 expression in laryngeal squamous cell carcinoma

PURPOSE

To investigate whether multiple dual-energy computed tomography (DECT) parameters can noninvasively predict the Ki-67 expression (associated with survival and prognosis) in laryngeal squamous cell carcinoma (LSCC).

METHODS

Eighty-eight patients with histologically proven LSCC were retrospectively reviewed. Multiple DECT-derived parameters were measured and correlated with Ki-67 expression by Spearman correlation analysis. Comparisons of the DECT-derived parameters between tumors with low- and high-level expression of Ki-67 were made with the t-tests.

RESULTS

The iodine concentration (IC), normalized IC (NIC), effective atomic number (Z_eff), 40-80 keV, and slope (k) values were positively correlated with Ki-67 expression (all p < 0.05, rho=0.367-0.548). Among all DECT-derived parameters, NIC value had the highest r value in correlation with Ki-67 expression. The IC, NIC, Z_eff, 40-80 keV, and slope (k) values were significantly higher in LSCC with high Ki-67 expression than in those with low Ki-67 expression (all p < 0.05).

CONCLUSIONS

Multiple DECT-derived parameters (IC, NIC, Z_eff, 40-80 keV, and slope (k)) can be used as predictors of survival and prognosis in LSCC, among which the NIC value is the strongest.