Differentiation of lung cancers from inflammatory masses with dual-energy spectral CT imaging

Predictive value of spectral computed tomography parameters for EGFR gene mutation in non-small-cell lung cancer

AIM

To explore the predictive value of morphological signs and quantitative parameters from spectral CT for EGFR gene mutations in intermediate and advanced non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

This retrospective observational study included patients with intermediate or advanced NSCLC at Xinjiang Medical University Affiliated Tumor Hospital between January 2017 and December 2019. The patients were divided into the EGFR gene mutation-positive and -negative groups.

RESULTS

Seventy-nine patients aged 60.75 ± 9.66 years old were included: 32 were EGFR mutation-positive, and 47 were negative. There were significant differences in pathological stage (P<0.001), tumor diameter (P=0.019), lobulation sign, intrapulmonary metastasis, mediastinal lymph node metastasis, distant metastasis (P<0.001), bone metastasis (P<0.001), arterial phase normalized iodine concentration (NIC) (P=0.001), venous phase NIC (P=0.001), slope of the energy spectrum curve (λ) (P<0.001), and CT value at 70 keV in arterial phase (P=0.004) and venous phase (P=0.003) between the EGFR mutation-positive and -negative patients. The multivariable logistic regression analysis showed that intrapulmonary metastasis, distant metastasis, venous phase NIC, venous phase λ, and pathological stage were independent factors predicting EGFR gene mutations, with high diagnostic power (AUC = 0.975, 91.5% sensitivity, and 90.6% specificity).

CONCLUSION

The pathological stage and the spectral CT parameters of intrapulmonary metastasis, distant metastasis, venous phase NIC, and venous phase λ might pre-operatively predict EGFR gene mutations in intermediate and advanced NSCLC.

Thoracic Diseases: Technique and Applications of Dual-Energy CT

Dual-energy computed tomography (DECT) is one of the most promising technological innovations made in the field of imaging in recent years. Thanks to its ability to provide quantitative and reproducible data, and to improve radiologists' confidence, especially in the less experienced, its applications are increasing in number and variety. In thoracic diseases, DECT is able to provide well-known benefits, although many recent articles have sought to investigate new perspectives. This narrative review aims to provide the reader with an overview of the applications and advantages of DECT in thoracic diseases, focusing on the most recent innovations. The research process was conducted on the databases of Pubmed and Cochrane. The article is organized according to the anatomical district: the review will focus on pleural, lung parenchymal, breast, mediastinal, lymph nodes, vascular and skeletal applications of DECT. In conclusion, considering the new potential applications and the evidence reported in the latest papers, DECT is progressively entering the daily practice of radiologists, and by reading this simple narrative review, every radiologist will know the state of the art of DECT in thoracic diseases.

Value of dual-layer spectral detector computed tomography in the diagnosis of benign/malignant solid solitary pulmonary nodules and establishment of a prediction model

Objective

This study aimed to investigate the role of spectral detector computed tomography (SDCT) quantitative parameters and their derived quantitative parameters combined with lesion morphological information in the differential diagnosis of solid SPNs.

Methods

This retrospective study included basic clinical data and SDCT images of 132 patients with pathologically confirmed SPNs (102 and 30 patients in the malignant and benign groups, respectively). The morphological signs of SPNs were evaluated and the region of interest (ROI) was delineated from the lesion to extract and calculate the relevant SDCT quantitative parameters, and standardise the process. Differences in qualitative and quantitative parameters between the groups were statistically analysed. A receiver operating characteristic (ROC) curve was constructed to evaluate the efficacy of the corresponding parameters in the diagnosis of benign and malignant SPNs. Statistically significant clinical data, CT signs and SDCT quantitative parameters were analysed using multivariate logistic regression to determine the independent risk factors for predicting benign and malignant SPNs, and the best multi-parameter regression model was established. Inter-observer repeatability was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots.

Results

Malignant SPNs differed from benign SPNs in terms of size, lesion morphology, short spicule sign, and vascular enrichment sign (P< 0.05). The SDCT quantitative parameters and their derived quantitative parameters of malignant SPNs (SAR40keV, SAR70keV, Δ40keV, Δ70keV, CER40keV, CER70keV, NEF40keV, NEF70keV, λ, NIC, NZeff) were significantly higher than those of benign SPNs (P< 0.05). In the subgroup analysis, most parameters could distinguish between benign and adenocarcinoma groups (SAR40keV, SAR70keV, Δ40keV, Δ70keV, CER40keV, CER70keV, NEF40keV, NEF70keV, λ, NIC, and NZeff), and between benign and squamous cell carcinoma groups (SAR40keV, SAR70keV, Δ40keV, Δ70keV, NEF40keV, NEF70keV, λ, and NIC). However, there were no significant differences between the parameters in the adenocarcinoma and squamous cell carcinoma groups. ROC curve analysis indicated that NIC, NEF70keV, and NEF40keV had higher diagnostic efficacy for differentiating benign and malignant SPNs (area under the curve [AUC]:0.869, 0.854, and 0.853, respectively), and NIC was the highest. Multivariate logistic regression analysis showed that size (OR=1.138, 95% CI 1.022-1.267, P=0.019), Δ70keV (OR=1.060, 95% CI 1.002-1.122, P=0.043), and NIC (OR=7.758, 95% CI 1.966-30.612, P=0.003) were independent risk factors for the prediction of benign and malignant SPNs. ROC curve analysis showed that the AUC of size, Δ70keV, NIC, and a combination of the three for differential diagnosis of benign and malignant SPNs were 0.636, 0.846, 0.869, and 0.903, respectively. The AUC for the combined parameters was the largest, and the sensitivity, specificity, and accuracy were 88.2%, 83.3% and 86.4%, respectively. The SDCT quantitative parameters and their derived quantitative parameters in this study exhibited satisfactory inter-observer repeatability (ICC: 0.811-0.997).

Conclusion

SDCT quantitative parameters and their derivatives can be helpful in the differential diagnosis of benign and malignant solid SPNs. The quantitative parameter, NIC, is superior to the other relevant quantitative parameters and when NIC is combined with lesion size and Δ70keV value for comprehensive diagnosis, the efficacy could be further improved.

Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign

OBJECTIVES

To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs).

MATERIALS AND METHODS

A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application.

RESULTS

The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC_65keV-AP = 0.92, AUC_65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability.

CONCLUSIONS

Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Z_eff-AP was significantly superior to conventional model in the discrimination of SPSNs.

The value of dual-energy spectral CT in differentiating solitary pulmonary tuberculosis and solitary lung adenocarcinoma

BACKGROUND

To explore the value of dual-energy spectral CT in distinguishing solitary pulmonary tuberculosis (SP-TB) from solitary lung adenocarcinoma (S-LUAD).

METHODS

A total of 246 patients confirmed SP-TB (n = 86) or S-LUAD (n = 160) were retrospectively included. Spectral CT parameters include CT40keV value, CT70keV value, iodine concentration (IC), water concentration (WC), effective atomic number (Zeff), and spectral curve slope (λ70keV). Data were measured during the arterial phase (AP) and venous phase (VP). Chi-square test was used to compare categorical variables, Wilcoxon rank-sum test was used to compare continuous variables, and a two-sample t-test was used to compare spectral CT parameters. ROC curves were used to calculate diagnostic efficiency.

RESULTS

There were significant differences in spectral CT quantitative parameters (including CT40keV value [all P< 0.001] , CT70keV value [all P< 0.001], λ70keV [P< 0.001, and P = 0.027], Zeff [P =0.015, and P = 0.001], and IC [P =0.002, and P = 0.028]) between the two groups during the AP and VP. However, WC (P = 0.930, and P = 0.823) was not statistically different between the two groups. The ROC curve analysis showed that the AUC in the AP and VP was 90.9% (95% CI, 0.873-0.945) and 83.4% (95% CI, 0.780-0.887), respectively. The highest diagnostic performance (AUC, 97.6%; 95% CI, 0.961-0.991) was achieved when all spectral CT parameters were combined with clinical variables.

CONCLUSION

Dual-energy spectral CT has a significant value in distinguishing SP-TB from S-LUAD.

Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules

Objectives

This study aimed to investigate the ability of quantitative parameters of dual-energy computed tomography (DECT) and nodule size for differentiation between lung cancers and benign lesions in solid pulmonary nodules.

Materials and Methods

A total of 151 pathologically confirmed solid pulmonary nodules including 78 lung cancers and 73 benign lesions from 147 patients were consecutively and retrospectively enrolled who underwent dual-phase contrast-enhanced DECT. The following features were analyzed: diameter, volume, Lung CT Screening Reporting and Data System (Lung-RADS) categorization, and DECT-derived quantitative parameters including effective atomic number (Zeff), iodine concentration (IC), and normalized iodine concentration (NIC) in arterial and venous phases. Multivariable logistic regression analysis was used to build a combined model. The diagnostic performance was assessed by area under curve (AUC) of receiver operating characteristic curve, sensitivity, and specificity.

Results

The independent factors for differentiating lung cancers from benign solid pulmonary nodules included diameter, Lung-RADS categorization of diameter, volume, Zeff in arterial phase (Zeff_A), IC in arterial phase (IC_A), NIC in arterial phase (NIC_A), Zeff in venous phase (Zeff_V), IC in venous phase (IC_V), and NIC in venous phase (NIC_V) (all P < 0.05). The IC_V, NIC_V, and combined model consisting of diameter and NIC_V showed good diagnostic performance with AUCs of 0.891, 0.888, and 0.893, which were superior to the diameter, Lung-RADS categorization of diameter, volume, Zeff_A, and Zeff_V (all P < 0.001). The sensitivities of IC_V, NIC_V, and combined model were higher than those of IC_A and NIC_A (all P < 0.001). The combined model did not increase the AUCs compared with IC_V (P = 0.869) or NIC_V (P = 0.633).

Conclusion

The DECT-derived IC_V and NIC_V may be useful in differentiating lung cancers from benign lesions in solid pulmonary nodules.

Association between quantitative spectral CT parameters, Ki-67 expression, and invasiveness in lung adenocarcinoma manifesting as ground-glass nodules

BACKGROUND

Few studies about lung ground-glass nodules (GGNs) have been done using non-enhancement spectral computed tomography (CT) imaging.

PURPOSE

To examine the association between spectral CT parameters, Ki-67 expression, and invasiveness in lung adenocarcinoma manifesting as GGNs.

MATERIAL AND METHODS

Spectral CT parameters were analyzed in 106 patients with lung GGNs. The Ki-67 labeling index (Ki-67 LI) was measured, and patients were divided into low expression and high expression groups according to the number of positive-stained cells (low expression ≤10%; high expression >10%). Spectral CT parameters were compared between low and high expression groups. The correlation between spectral CT parameters and Ki-67 LI was estimated by Spearman correlation analysis. Cases were divided into a preinvasive and minimally invasive adenocarcinoma (MIA) group (atypical adenomatous hyperplasia, adenocarcinoma in situ, and MIA) and invasive adenocarcinoma (IA) group. Spectral CT parameters were compared between the two groups. The diagnostic performance was evaluated using receiver operating characteristic analysis.

RESULTS

There were significant differences in water concentration of lesions (WCL) and monochromatic CT values between the low and high expression groups. CT 40 keV had the highest correlation coefficient with Ki-67 LI. WCL and monochromatic CT values were significantly higher in the IA group than in the pre/MIA group. The value of area under the curve of CT 40 keV was 0.946 (95% confidence interval=0.905-0.988) for differentiating the two groups; the cutoff was -280.66 Hu.

CONCLUSION

Spectral CT is an effective non-invasive method for the prediction of proliferation and invasiveness in lung adenocarcinoma manifesting as GGNs.

Combined whole-lesion radiomic and iodine analysis for differentiation of pulmonary tumors

Quantitative radiomic and iodine imaging features have been explored for diagnosis and characterization of tumors. In this work, we invistigate combined whole-lesion radiomic and iodine analysis for the differentiation of pulmonary tumors on contrast-enhanced dual-energy CT (DECT) chest images. 100 biopsy-proven solid lung lesions on contrast-enhanced DECT chest exams within 3 months of histopathologic sampling were identified. Lesions were volumetrically segmented using open-source software. Lesion segmentations and iodine density volumes were loaded into a radiomics prototype for quantitative analysis. Univariate analysis was performed to determine differences in volumetric iodine concentration (mean, median, maximum, minimum, 10th percentile, 90th percentile) and first and higher order radiomic features (n = 1212) between pulmonary tumors. Analyses were performed using a 2-sample t test, and filtered for false discoveries using Benjamini–Hochberg method. 100 individuals (mean age 65 ± 13 years; 59 women) with 64 primary and 36 metastatic lung lesions were included. Only one iodine concentration parameter, absolute minimum iodine, significantly differed between primary and metastatic pulmonary tumors (FDR-adjusted p = 0.015, AUC 0.69). 310 (FDR-adjusted p = 0.0008 to p = 0.0491) radiomic features differed between primary and metastatic lung tumors. Of these, 21 features achieved AUC ≥ 0.75. In subset analyses of lesions imaged by non-CTPA protocol (n = 72), 191 features significantly differed between primary and metastatic tumors, 19 of which achieved AUC ≥ 0.75. In subset analysis of tumors without history of prior treatment (n = 59), 40 features significantly differed between primary and metastatic tumors, 11 of which achieved AUC ≥ 0.75. Volumetric radiomic analysis provides differentiating capability beyond iodine quantification. While a high number of radiomic features differentiated primary versus metastatic pulmonary tumors, fewer features demonstrated good individual discriminatory utility.

The value of radiomics based on dual-energy CT for differentiating benign from malignant solitary pulmonary nodules

OBJECTIVE

To investigate the value of monochromatic dual-energy CT (DECT) images based on radiomics in differentiating benign from malignant solitary pulmonary nodules.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board, and informed consent was waived. Pathologically confirmed lung nodules smaller than 3 cm with integrated arterial phase and venous phase (AP and VP) gemstone spectral imaging were retrospectively identified. After extracting the radiomic features of each case, principal component analysis (PCA) was used for feature selection, and after training with the logistic regression method, three classification models (Model_AP, Model_VP and Model_Combination) were constructed. The performance was assessed by the area under the receiver operating curve (AUC), and the efficacy of the models was validated using an independent cohort.

RESULTS

A total of 153 patients were included and divided into a training cohort (n = 107) and a validation cohort (n = 46). A total of 1130 radiomic features were extracted from each case. The PCA method selected 22, 25 and 35 principal components to construct the three models. The diagnostic accuracy of Model_AP, Model_VP and Model_Combination was 0.8043, 0.6739, and 0.7826 in the validation set, with AUCs of 0.8148 (95% CI 0.682-0.948), 0.7485 (95% CI 0.602-0.895), and 0.8772 (95% CI 0.780-0.974), respectively. The DeLong test showed that there were significant differences in the AUCs between Model_AP and Model_Combination (P = 0.0396) and between Model_VP and Model_Combination (P = 0.0465). However, the difference in AUCs between Model_AP and Model_VP was not significant (P = 0.5061). These results demonstrate that Model_Combination shows a better performance than the other models. Decision curve analysis proved the clinical utility of this model.

CONCLUSIONS

We developed a radiomics model based on monochromatic DECT images to identify solitary pulmonary nodules. This model could serve as an effective tool for discriminating benign from malignant pulmonary nodules in patients. The combination of arterial phase and venous phase imaging could significantly improve the model performance.

Differentiation Between Solitary Pulmonary Inflammatory Lesions and Solitary Cancer Using Gemstone Spectral Imaging

BACKGROUND

The distinction between solitary inflammatory lesion and solitary lung cancer remains a challenge because of their considerable overlapping computed tomography (CT) imaging features.

PURPOSE

This study aimed to verify whether spectral CT parameters can differentiate solitary lung cancer from solitary inflammatory lesions and to find their correlations with lesion size.

METHODS

A total of 78 patients with solitary lung lesions were included in our study. All of them underwent enhanced CT scans with Gemstone Spectral Imaging (GSI) mode, which was one of the dual-energy imaging technologies. According to maximum diameter (Dmax) of the lesion, regions of interest were collected and divided into inflammatory (group I: <3 cm [IA], n = 17; ≥3 cm [IB], n = 14) and cancer groups (group II: <3 cm [IIA], n = 20; ≥3 cm [IIB], n = 27). Computed tomography values (HU40keV, HU70keV), effective atomic number (Zeff), iodine concentration (IC), normalized IC (NIC), and spectral curve slopes (λ30, λ40) of each region of interest were calculated. The NIC was defined as the IC ratio of the lesion to the descending aorta. Mann-Whitney U test was used for intergroup (I vs II, IA vs IIA, IB vs IIB) and intragroup (IA vs IB, IIA vs IIB) comparisons, and receiver operating characteristic curve analysis was performed. Correlation analysis was applied to find the relationship between Dmax and GSI parameters.

RESULTS

No significant correlation was found between GSI parameters and Dmax in the inflammatory group, whereas inverse correlations were found in the cancer group. Gemstone spectral imaging parameters (except HU70keV) of group IIA were significantly higher than those of group IIB. There were significant differences in HU40keV, IC, NIC, λ30, and λ40 between groups IB and IIB under both arterial and venous phase (P values < 0.05), whereas the area under the curve for λ30 under venous phase was largest, and sensitivity and specificity were 96.32% and 85.71%, respectively. However, only HU40keV and HU70keV values under the arterial phase of IIA were significantly higher than those of IA.

CONCLUSIONS

Quantitative parameters of GSI demonstrated an inverse correlation with the lesion size of solitary lung cancer, and GSI parameters can be new ways to differentiate solitary lung cancer from solitary inflammatory lesions.

CT Signs and Differential Diagnosis of Peripheral Lung Cancer and Inflammatory Pseudotumor: A Meta-Analysis

We aimed to systematically evaluate the imaging features of peripheral lung cancer and inflammatory pseudotumor. PubMed, Embase, Cochrane Library, Chinese Knowledge Infrastructure (CNKI), Wanfang database (Wanfang), and Chinese Biomedical Network (CBM) were searched to collect relevant studies on CT image comparison of peripheral lung cancer and inflammatory pseudotumor. The search time was from database establishment to July 15, 2021. The search language was limited to Chinese and English. Data from the literature were screened and extracted, and meta-analysis was performed using Stata 16.0 software. A total of 8 cohort studies were included in this meta-analysis, including 675 patients. Meta-analysis showed that the lesion size of inflammatory pseudotumor was greater than that of peripheral lung cancer, and the difference had statistical significance [SMD = 0.29, 95% CI (0.01, 0.58), P < 0.05]. The difference in HU value between inflammatory pseudotumor and peripheral lung cancer CT had no statistical significance [SMD = -0.09, 95% CI (-0.79, 0.60), P > 0.05]. The HU value of enhanced CT of inflammatory pseudotumor was higher than that of peripheral lung cancer, and the difference had statistical significance [SMD = 0.75, 95% CI (0.15, 1.34), P < 0.05]. The incidence of calcification of inflammatory pseudotumor was significantly higher than that of peripheral lung cancer, and the difference had statistical significance [RR = 2.85, 95% CI (1.33, 6.11), P < 0.05]. The incidence of long hair puncture sign of inflammatory pseudotumor was lower than that of peripheral lung cancer, and the difference had statistical significance [RR = 0.49, 95% CI (0.24, 0.97), P < 0.05]. There was no significant difference between inflammatory pseudotumor and peripheral lung cancer in terms of cavity incidence, vacuole sign, pleural indentation, and bronchial inflation sign (P > 0.05). Based on the available literature evidence, it can be found that there are differences in the CT signs between peripheral lung cancer and inflammatory pseudotumor, and the lesion size, HU value on enhanced CT, incidence of calcification, and incidence of burr sign may be important indicators for differentiating peripheral lung cancer from inflammatory pseudotumor.

Noninvasive evaluation of hypoxia in rabbit VX2 lung transplant tumors using spectral CT parameters and texture analysis

AIM

Noninvasive evaluation of hypoxia in rabbit VX2 lung transplant tumors using spectral CT parameters and texture analysis.

MATERIALS AND METHODS

Twenty-five VX2 lung transplant tumors of twenty-two rabbits were included in the study. Contrast-enhanced spectral CT scanning in the arterial phase (AP) and venous phase (VP) was performed. Tumors were divided into strong and weak hypoxic groups by hypoxic probe staining results. Spectral CT image-related parameters [70 keV CT value, normalized iodine concentration (NIC), slope of spectral HU curve (λ_HU)] were measured and the texture analysis on the monochromatic images was performed. Imaging parameters and texture features between tumors with different hypoxic degrees were compared and their diagnostic efficacies for predicting hypoxia in lung cancers were analyzed using receiver operating characteristic (ROC) curve.

RESULTS

NIC in VP and λ_HU in VP of the strong hypoxic group were significantly higher than those in the weak hypoxic group (p < 0.05). For the texture features, entropy in VP and kurtosis in AP were significantly different between the two hypoxic groups. According to ROC analysis, λ_HU in VP had a better diagnostic ability for predicting hypoxia in tumors [Area Under Curve (AUC): 0.883, sensitivity: 85.7%, specificity: 100%]. The combination of four features improved AUC to 0.955.

CONCLUSION

NIC in VP, λ_HU in VP, entropy in VP and kurtosis in AP have certain values in predicting tumor hypoxia and a combination of image parameters and texture features improves diagnostic efficiency.

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.

Whole-lesion histogram analysis of mono-exponential and bi-exponential diffusion-weighted imaging in differentiating lung cancer from benign pulmonary lesions using 3 T MRI

AIM

To investigate whether whole-lesion histogram analysis of apparent diffusion coefficient (ADC) values derived from mono-exponential and bi-exponential diffusion-weighted imaging (DWI) can differentiate lung cancer from benign pulmonary lesions.

MATERIALS AND METHODS

Thirty-two patients with lung cancer and 17 patients with benign pulmonary lesions were included retrospectively. All patients underwent DWI before surgery or biopsy. ADC histogram parameters, including mean, percentile values (10^th and 90^th), kurtosis, and skewness, were calculated independently by two radiologists. The histogram parameters were compared between patients with lung cancer and benign lesions. Receiver operating characteristic curves were constructed to evaluate the diagnostic performance.

RESULTS

The ADC_Mean, ADC_10th, D_Mean, D_10th were significantly lower in lung cancer (1.187 ± 0.144 × 10^-3; 0.440 ± 0.062 × 10^-3; 1.068 ± 0.108 × 10^-3; and 0.422 ± 0.049 × 10^-3 mm/s) compared to benign lesions (1.418 ± 0.274 × 10^-3; 0.555 ± 0.113 × 10^-3; 1.216 ± 0.149 × 10^-3; and 0.490 ± 0.044 × 10^-3 mm/s; p<0.05). The ADC_Skewness and D_Skewness were significantly different between lung cancer (2.35 ± 0.72; 2.58 ± 1.14) and benign lesions (1.85 ± 0.54; 1.59 ± 1.47; p<0.05). D_10th was robust in differentiating lung cancer from benign lesions. Using 0.453 × 10^-3 mm/s as the optimal threshold, the sensitivity, specificity, and accuracy of D_10th were 78.12%, 82.35%, and 79.6%, respectively.

CONCLUSION

Whole-lesion histogram analysis of ADC values derived by mono-exponential and bi-exponential DWI using 3 T magnetic resonance imaging helps distinguish lung cancer from benign pulmonary lesions.

Consolidated lung on contrast-enhanced chest CT: the use of spectral-detector computed tomography parameters in differentiating atelectasis and pneumonia

Objectives

To investigate the value of spectral-detector computed tomography (SDCT) parameters for the quantitative differentiation between atelectasis and pneumonia on contrast-enhanced chest CT.

Material and methods

Sixty-three patients, 22 clinically diagnosed with pneumonia and 41 with atelectasis, underwent contrast-enhanced SDCT scans during the venous phase. CT numbers (Hounsfield Units [HU]) were measured on conventional reconstructions (CON_120kVp) and the iodine concentration (C_iodine, [mg/ml]), and effective atomic number (Z_eff) on spectral reconstructions, using region-of-interest (ROI) analysis. Receiver operating characteristics (ROC) and contrast-to-noise ratios (CNRs) were calculated to assess each reconstruction's potential to differentiate between atelectasis and pneumonia.

Results

On contrast-enhanced SDCT, the difference between atelectasis and pneumonia was significant on CON_120kVp, C_iodine, and Z_eff images (p < 0.001). On CON_120kVp images, a threshold of 81 HU achieved a sensitivity of 93 % and a specificity of 95 % for identifying pneumonia, while C_iodine and Z_eff images reached the same sensitivity but lower specificities of 85 % and 83 %. CON_120kVp images showed significantly higher CNRs between normal lung and atelectasis or pneumonia with 30.63 and 27.69 compared to C_iodine images with 3.54 and 1.27 and Z_eff images with 4.22 and 7.63 (p < 0.001). None of the parameters could differentiate atelectasis and pneumonia without contrast media.

Conclusions

Contrast-enhanced SDCT can differentiate atelectasis and pneumonia based on the spectral parameters C_iodine, and Z_eff. However, they had no added value compared to CT number measurement on CON_120kVp images. Furthermore, contrast media is still needed for a differentiation based on quantitative SDCT parameters.

Material decomposition using iodine quantification on spectral CT for characterising nodules in the cirrhotic liver: a retrospective study

Background

There is limited scientific evidence on the potential of spectral computed tomography (SCT) for differentiation of nodules in the cirrhotic liver. We aimed to assess SCT-generated material density (MD) parameters for nodule characterisation in cirrhosis.

Methods

Dynamic dual-energy SCT scans of cirrhotic patients performed over 3 years were retrospectively reviewed. They were classified as hepatocellular carcinoma (HCC), regenerative or indeterminate, according to the European Association for the Study of the Liver criteria. MD maps were generated to calculate the area under the curve (AUC) and cutoff values to discriminate these nodules in the hepatic arterial phase (HAP) and portal venous phase (PVP). MD maps included iodine concentration density (ICD) of the liver and nodule, lesion-to-normal liver ICD ratio (LNR) and difference in nodule ICD between HAP and PVP.

Results

Three hundred thirty nodules belonging to 300 patients (age 53.0 ± 12.7 years, mean ± standard deviation) were analysed at SCT (size 2.3 ± 0.8 cm, mean ± SD). One hundred thirty-three (40.3%) nodules were classified as HCC, 147 (44.5%) as regenerative and 50 (15.2%) as indeterminate. On histopathology, 136 (41.2%) nodules were classified as HCC, 183 (55.5%) as regenerative and 11 (3.3%) as dysplastic. All MD parameters on HAP and the nodule  difference in ICD could discriminate pathologically proven HCC or potentially malignant nodules from regenerative nodules (p < 0.001). The AUC was 82.4% with a cutoff > 15.5 mg/mL for nodule ICD, 81.3% > 1.8 for LNR-HAP and 81.3% for difference in ICD > 3.5 mg/mL.

Conclusion

SCT-generated MD parameters are viable diagnostic tools for differentiating malignant or potentially malignant from benign nodules in the cirrhotic liver.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41747-021-00220-6.

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

Background

Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.

Methods

Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λ_HU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT_40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.

Results

Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λ_HU, and CT_40keV performed better in the VP (NIC_VP, λ_VPHU, and CT_VP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NIC_VP, λ_VPHU, and CT_VP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NIC_AP (AUC =0.89) were greater than other parameters. NIC_AP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.

Conclusions

Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

Dual-energy CT for differentiating early glottic squamous cell carcinoma from chronic inflammation and leucoplakia of vocal cord: comparison with simulated conventional 120 kVp CT

AIM

To evaluate the value of dual-energy (DE) computed tomography (CT) in discriminating early glottic squamous cell carcinoma (eGSCC) from chronic inflammation and leucoplakia of the vocal cord, and to compare the diagnostic efficiency of DECT with that of simulated conventional 120 kVp CT.

MATERIALS AND METHODS

Seventy patients with glottic lesions confirmed by histopathology (38 cases with eGSCC, 11 cases with chronic inflammation, 21 cases with leucoplakia) were enrolled in this prospective study. The DECT-derived parameters were measured and compared using independent sample t-test. Receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance, and comparison of the area under the ROC curve (AUC) was made using the Z test to further select the best diagnostic parameters.

RESULTS

Significantly higher iodine concentration (IC), normalised IC (NIC), effective atomic number (Z_eff), 40-100 keV (20 keV-interval), slope(k), and Mix-0.3 values were found in eGSCC than those in chronic inflammation, leucoplakia, and inflammation + leucoplakia (all p<0.05). Compared with attenuation measurement of simulated conventional 120 kVp CT, the NIC, 60 keV values derived from DECT showed significantly higher AUC in discriminating these glottic lesions (p<0.05).

CONCLUSIONS

DECT is more accurate for differentiating eGSCC from chronic inflammation and leucoplakia when compared with simulated conventional 120 kVp CT.

Application of Dual-Energy Spectral Computed Tomography to Thoracic Oncology Imaging

Computed tomography (CT) is an important imaging modality in evaluating thoracic malignancies. The clinical utility of dual-energy spectral computed tomography (DESCT) has recently been realized. DESCT allows for virtual monoenergetic or monochromatic imaging, virtual non-contrast or unenhanced imaging, iodine concentration measurement, and effective atomic number (Z_eff map). The application of information gained using this technique in the field of thoracic oncology is important, and therefore many studies have been conducted to explore the use of DESCT in the evaluation and management of thoracic malignancies. Here we summarize and review recent DESCT studies on clinical applications related to thoracic oncology.

Comparison of virtual non-contrast dual-energy CT and a true non-contrast CT for contouring in radiotherapy of 3D printed lung tumour models in motion: a phantom study

OBJECTIVES

This work aims to investigate whether virtual non-contrast (VNC) dual-energy CT(DECT) of contrasted lung tumours can be used as an alternative for true non-contrast (TNC) images in radiotherapy. Two DECT techniques and a TNC CT were compared and influences on gross tumour volume (GTV) volume and CT number from motion artefacts in three-dimensional printed lung tumour models (LTM) in amotion phantom were examined.

METHODS

Two spherical LTMs (diameter 3.0 cm) with different inner shapes were created in a three-dimensional printer. The inner shapes contained water or iodine (concentration 5 mg ml^-1) and were scanned with a dual-source DECT (ds-DECT), single-source sequential DECT (ss-DECT) and TNC CT in a respiratory motion phantom (15 breaths/min, amplitude 1.5 cm). CT number and volume of LTMs were measured. Therefore, two GTVs were contoured.

RESULTS

Deviations in GTV volume (outer shape) of LTMs in motion for contrast-enhanced ss-DECT and ds-DECT VNC images compared to TNC images are not significant (p > 0.05). Relative GTV volume and CT number deviations (inner shapes) of LTMs in motion were 6.6 ± 0.6% and 104.4 ± 71.2 HU between ss-DECT and TNC CT and -8.4 ± 10.6% and 25.5 ± 58.5 HU between ds-DECT and TNC, respectively.

CONCLUSION

ss-DECT VNC images could not sufficiently subtract iodine from water in LTMs inmotion, whereas ds-DECT VNC images might be a valid alternative to a TNC CT.

ADVANCES IN KNOWLEDGE

ds-DECT provides a contrasted image for contouring and a non-contrasted image for radiotherapy treatment planning for LTM in motion.

Improved differentiation between primary lung cancer and pulmonary metastasis by combining dual-energy CT-derived biomarkers with conventional CT attenuation

OBJECTIVES

To assess the clinical utility of dual-energy CT (DE-CT)-derived iodine concentration (IC) and effective Z (Z^eff) in addition to conventional CT attenuation (HU) for the discrimination between primary lung cancer (LC) and pulmonary metastases (PM) from different primary malignancies.

METHODS

DE-CT scans of 79 patients with LC (3 histopathologic subgroups) and 89 patients with PM (5 histopathologic subgroups) were evaluated. Quantitative IC, Z^eff, and conventional HU values were extracted and normalized to the thoracic aorta. Differences between groups were assessed by pairwise Welch's t test. Correlation and linear regression analyses were used to examine the relationship of imaging parameters in LC and PM. Diagnostic accuracy was measured by the area under receiver operator characteristic curve (AUC) and validated based on resampling methods.

RESULTS

Significant differences between subgroups of LC and PMs were noted for all imaging parameters, with the highest number of significant pairs for IC. In univariate analysis, only IC was a significant diagnostic feature for discriminating LC from PM (p = 0.03). All quantitative imaging parameters correlated significantly (p < 0.0001, respectively), with the highest correlation between IC and Z^eff (r = 0.91), followed by IC and HU (r = 0.76) and Z^eff and HU (r = 0.73). Diagnostic models combining IC or Z^eff with HU (IC+HU: AUC = 0.73; Z^eff+HU: AUC = 0.69; IC+Z^eff+HU: AUC = 0.73) were not significantly different and outperformed individual parameters (IC: AUC = 0.57; Z^eff: AUC = 0.57; HU: AUC = 0.55) in diagnostic accuracy (p < 0.05, respectively).

CONCLUSION

DE-CT-derived IC or Z^eff and conventional HU represent complementary imaging parameters, which, if used in combination, may improve the differentiation between LC and PM.

KEY POINTS

• Individual quantitative imaging parameters derived from DE-CT (iodine concentration, effective Z) and conventional CT (HU) provide complementary diagnostic information for the differentiation of primary lung cancer and pulmonary metastases. • A combination of conventional HU and DE-CT parameters enhances the diagnostic utility of individual parameters.

Assessment of Solitary Pulmonary Nodules Based on Virtual Monochrome Images and Iodine-Dependent Images Using a Single-Source Dual-Energy CT with Fast kVp Switching

With lung cancer being the most common malignancy diagnosed worldwide, lung nodule assessment has proved to be one of big challenges of modern medicine. The aim of this study was to examine the usefulness of Dual Energy Computed Tomography (DECT) in solitary pulmonary nodule (SPN) assessment. Between January 2017 and June 2018; 65 patients (42 males and 23 females) underwent DECT scans in the late arterial phase (AP) and venous phase (VP). We concluded that imaging at an energy level of 65 keV was the most accurate in detecting malignancy in solitary pulmonary nodules (SPNs) measuring ≤30 mm in diameter on virtual monochromatic maps. Both virtual monochromatic images and iodine concentration maps prove to be highly useful in differentiating benign and malignant pulmonary nodules. As for iodine concentration maps, the analysis of venous phase images resulted in the highest clinical usefulness. To summarize, DECT may be a useful tool in the differentiation of benign and malignant SPNs. A single-phase DECT examination with scans acquired 90 s after contrast media injection is recommended.

Spectral CT in Lung Cancer: Usefulness of Iodine Concentration for Evaluation of Tumor Angiogenesis and Prognosis

OBJECTIVE. The purpose of this study was to investigate the correlation between iodine concentration (IC) derived from spectral CT and angiogenesis and the relationships between IC and clinical-pathologic features associated with lung cancer prognosis. SUBJECTS AND METHODS. Sixty patients with lung cancer were enrolled and underwent spectral CT. The IC, IC difference (ICD), and normalized IC (NIC) of tumors were measured in the arterial phase, venous phase (VP), and delayed phase. The microvessel densities (MVDs) of CD34-stained specimens were evaluated. Correlation analysis was performed for IC and MVD. The relationships between the IC index showing the best correlations with MVD and clinical-pathologic findings of pathologic types, histologic differentiation, tumor size, lymph node status, pathologic TNM stage, and intratumoral necrosis were investigated. RESULTS. The mean (± IQR) MVD of all tumors was 42.00 ± 27.50 vessels per field at ×400 magnification, with two MVD distribution types. The MVD of lung cancer correlated positively with the IC, ICD, and NIC on three-phase contrast-enhanced scanning (r range, 0.581-0.800; all p < 0.001), and the IC in the VP showed the strongest correlation with MVD (r = 0.800; p < 0.001). The correlations between IC and MVD, ICD and MVD, and NIC and MVD varied depending on whether the same scanning phase or same IC index was used. The IC in the VP showed statistically significant differences in the pathologic types of adenocarcinoma and squamous cell carcinoma, histologic differentiation, tumor size, and status of intratumoral necrosis of lung cancer (p < 0.05), but was not associated with nodal metastasis and pathologic TNM stages (p > 0.05). CONCLUSION. IC indexes derived from spectral CT, especially the IC in the VP, were useful indicators for evaluating tumor angiogenesis and prognosis.

The associations among quantitative spectral CT parameters, Ki-67 expression levels and EGFR mutation status in NSCLC

Dual-energy spectral computed tomography (DESCT) is based on fast switching between high and low voltages from view to view to obtain dual-energy imaging data, and it can generate monochromatic image sets, iodine-based material decomposition images and spectral CT curves. Quantitative spectral CT parameters may be valuable for reflecting Ki-67 expression and EGFR mutation status in non-small-cell lung cancer (NSCLC). We investigated the associations among the quantitative parameters generated in DESCT and Ki-67 expression and EGFR mutation in NSCLC. We studied sixty-five NSCLC patients with preoperative DESCT scans, and their specimens underwent Ki-67 and EGFR evaluations. Statistical analyses were performed to identify the spectral CT parameters for the diagnosis of Ki-67 expression and EGFR mutation status. We found that tumour grade and the slope of the spectral CT curve in the venous phase were the independent factors influencing the Ki-67 expression level, and the area under the curve (AUC) of the slope of the spectral CT curve in the venous phase in the receiver operating characteristic analysis for distinguishing different Ki-67 expression levels was 0.901. Smoking status and the normalized iodine concentration in the venous phase were independent factors influencing EGFR mutation, and the AUC of the two-factor combination for predicting the presence of EGFR mutation was 0.807. These results show that spectral CT parameters may be useful for predicting Ki-67 expression and the presence of EGFR mutation in NSCLC.

Extra-abdominal dual-energy CT applications: a comprehensive overview

Unlike conventional computed tomography, dual-energy computed tomography is a relatively novel technique that exploits ionizing radiations at different energy levels. The separate radiation sets can be achieved through different technologies, such as dual source, dual layers or rapid switching voltage. Body tissue molecules vary for their specific atomic numbers and electron density, and the interaction with different sets of radiations results in different attenuations, allowing to their final distinction. In particular, iodine recognition and quantification have led to important information about intravenous contrast medium delivery within the body. Over the years, useful post-processing algorithms have also been validated for improving tissue characterization. For instance, contrast resolution improvement and metal artifact reduction can be obtained through virtual monoenergetic images, dose reduction by virtual non-contrast reconstructions and iodine distribution highlighting through iodine overlay maps. Beyond the evaluation of the abdominal organs, dual-energy computed tomography has also been successfully employed in other anatomical districts. Although lung perfusion is one of the most investigated, this evaluation has been extended to narrowly fields of application, such as musculoskeletal, head and neck, vascular and cardiac. The potential pool of information provided by dual-energy technology is already wide and not completely explored, yet. Therefore, its performance continues to raise increasing interest from both radiologists and clinicians.

Is there any correlation between spectral CT imaging parameters and PD-L1 expression of lung adenocarcinoma?

Background

The aim of this study was to explore whether spectral computed tomography (CT) imaging parameters are associated with PD‐L1 expression of lung adenocarcinoma.

Methods

Spectral CT imaging parameters (iodine concentrations [IC] of lesion in arterial phase [ICLa] and venous phase [ICLv], normalized IC [NICa/NICv]‐normalized to the IC in the aorta, slope of the spectral HU curve [λHUa/λHUv] and enhanced monochromatic CT number [CT40keVa/v, CT70keVa/v] on 40 and 70 keV images) were analyzed in 34 prospectively enrolled lung adenocarcinoma patients with common molecular pathological markers including PD‐L1 expression detected with immunohistochemistry. Patients were divided into two groups: positive PD‐L1 expression and negative PD‐L1 expression groups. Two‐sample Mann‐Whitney U test was used to test the difference of spectral CT imaging parameters between the two groups.

Results

The CT40keVa (127.03 ± 37.92 vs. −54.69 ± 262.04), CT40keVv (124.39 ± 34.71 vs. −45.73 ± 238.97), CT70keVa (49.56 ± 11.76 vs. −136.51 ± 237.08) and CT70keVv (46.13 ± 15.81 vs. −133.10 ± 230.72) parameters in the positive PD‐L1 expression group of lung adenocarcinoma were significantly higher than the negative PD‐L1 expression group (all P < 0.05). There was no difference detected in IC, NIC and λHU of the arterial and venous phases between both groups (all P > 0.05).

Conclusion

CT40keVa, CT40keVv, CT70keVa and CT70keVv were increased in positive PD‐L1 expression. These parameters may be used to distinguish the PD‐L1 expression state of lung adenocarcinoma.

Dual-energy spectral CT characteristics in surgically resected lung adenocarcinoma: comparison between Kirsten rat sarcoma viral oncogene mutations and epidermal growth factor receptor mutations

BACKGROUND

Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) are the two most frequent and well-known oncogene of lung adenocarcinoma. The purpose of this study is to compare the characteristics measured with dual-energy spectral computed tomography (DESCT) in lung adenocarcinoma patients who have KRAS and EGFR gene mutations.

METHODS

Patients with surgically resected lung adenocarcinoma (n = 72) were enrolled, including 12 patients with KRAS mutations and 60 patients with EGFR mutations. DESCT quantitative parameters, including the CT number at 70 keV, the slopes of the spectral attenuation curves (slope λ HU), normalized iodine concentration (NIC), normalized water concentration (NWC), and effective atomic number (effective Z), were analyzed. A multiple logistic regression model was applied to discriminate clinical and DESCT characteristics between the types of mutations.

RESULTS

The KRAS mutation was more common in people who smoked than the EGFR mutation. Nodule type differed significantly between the KRAS and EGFR groups (P = 0.035), and all KRAS mutation adenocarcinomas were solid nodules. Most DESCT quantitative parameters differed significantly between solid nodules and subsolid nodules. CT number at 70 keV, slope λ HU, NIC, and effective Z differed significantly between the KRAS and EGFR groups (P = 0.006, 0.017, 0.013 and 0.010) with solid lung adenocarcinoma. Multivariate logistic analysis of DESCT and clinical features indicated that besides smoking history, the CT value at 70 keV (OR = 0.938, P = 0.009) was significant independent factor that could be used to differentiate KRAS and EGFR mutations in solid lung adenocarcinoma.

CONCLUSIONS

DESCT would be a potential tool to differentiate lung adenocarcinoma patients with a KRAS mutation from those with an EGFR mutation.

FORCE dual-energy CT in pathological grading of clear cell renal cell carcinoma

The aim of the present study was to examine the value of FORCE dual-energy CT in grading the clear cell renal cell carcinoma (ccRCC). A total of 35 cases of ccRCC were included. Hematoxylin and eosin staining was performed, and the cases were divided into low- (Fuhrman I-II) and high-grade (Fuhrman III-IV) groups. FORCE dual-energy CT parameters, including virtual network computing CT value (VNCV), iodine overlay value (IOV), mixed energy CT value (MEV), iodine concentration (IC), normalized iodine concentration (NIC), NIC based on aorta (NICA), NIC based on cortex (NICC) and NIC based on medulla (NICM), were analyzed and compared. Receiver operating characteristic analysis was also performed. There were significant differences in the arterial phase IOV, MEV and IC, and the venous phase IOV and IC between the low- and high-grade groups. No significant differences were observed in VNCV and MEV between the low -and high-grade groups in the venous phase. Significant differences were observed in the NICA and NICC between these two groups, however no difference was observed in NICM. There were significant differences in the tumor CT values for the arterial phase at the 40, 60, 80 and 100 kiloelectron volt (keV) between the low- and high-grade groups, while no significant differences were observed at the 120-140 keV levels. The k-slope for the low-grade group was significantly higher than the high-grade group. In addition, the area under curve for the arterial phase IOV, arterial phase MEV, arterial phase IC, aortic NIC, cortical NIC, venous phase IOV, venous phase IC and curve slope K of mono-energy CT value suggested high value in diagnosis of low- and high-grade ccRCC cases.

Quantitative features of dual-energy spectral computed tomography for solid lung adenocarcinoma with EGFR and KRAS mutations, and ALK rearrangement: a preliminary study

Background

The present work aimed to evaluate radio-genomic associations of quantitative parameters obtained by dual-energy spectral computed tomography (DESCT) for solid lung adenocarcinoma with epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations, as well as anaplastic lymphoma kinase (ALK) rearrangement.

Methods

Ninety-six cases of solid lung cancer were selected and assessed for EGFR and KRAS mutations, and ALK rearrangement. Then, they underwent chest DESCT, and quantitative parameters, including water concentration (WC), iodine concentration (IC), CT value at 70 keV, effective atomic number (Effective-Z) and spectral Hounsfield unit curve slope (λHU slope) were measured. Finally, the associations of quantitative radiological features with various gene alterations were evaluated.

Results

The positive rates were 51.0% (49/96) for EGFR, 13.5% (13/96) for KRAS and 16.7% (16/96) for ALK. In univariate analysis, EGFR mutation was associated with smoking status, CT value at 70 keV, IC, Effective-Z, and λHU slope; KRAS mutation was associated with CT value at 70 keV, IC, Effective-Z, and λHU slope, and ALK rearrangement was correlated with age and WC. In multivariate analysis, smoking status (OR =2.924, P=0.019) and CT value at 70 keV (OR =1.036, P=0.006) were significantly associated with EGFR mutation; Effective-Z and age were significantly associated with KRAS mutation (OR =0.047, P=0.032) and ALK rearrangement (OR =0.933, P=0.008), respectively.

Conclusions

Quantitative analysis of DESCT could help detect solid lung adenocarcinoma harboring EGFR or KRAS mutation, or ALK rearrangement.

Invasive Pulmonary Adenocarcinomas Versus Preinvasive Lesions Appearing as Pure Ground-Glass Nodules: Differentiation Using Enhanced Dual-Source Dual-Energy CT

OBJECTIVE. The objective of our study was to investigate the potentials of enhanced dual-source dual-energy CT (DECT) and three-planar measurements for differentiating invasive pulmonary adenocarcinomas (IPAs) from preinvasive lesions appearing as pure ground-glass nodules (pGGNs). MATERIALS AND METHODS. Thirty-nine patients with 53 pGGNs who underwent enhanced dual-source DECT were included in this retrospective study. All pGGNs were pathologically confirmed and categorized into two groups: preinvasive lesions or IPAs. The traditional CT features of the pGGNs were evaluated on unenhanced images. Quantitative parameters were measured on iodine-enhanced images of dual-source DECT in three planes, and both intra- and interobserver reproducibility analyses were performed to assess the measurement reproducibility of quantitative parameters. To identify significant factors for differentiating IPAs from preinvasive lesions, we performed logistic regression analysis and ROC curve analysis. RESULTS. For traditional CT features, only lesion size and unenhanced CT attenuation value showed significant differences between preinvasive lesions and IPAs (p < 0.05). Preinvasive lesions and IPAs exhibited significant differences in attenuation on virtual images, so-called "virtual HU" or "VHU," and the modified normalized iodine concentration (NIC) (p < 0.05), and both intra- and interobserver agreement for the quantitative measurements were excellent. Multivariate logistic regression analysis revealed that larger lesion size (adjusted odds ratio [OR], 3.65) and higher modified NIC (adjusted OR, 19.01) were significant differentiators of IPAs from preinvasive lesions (p < 0.05). ROC curve analysis revealed that modified NIC showed excellent performance (AUC, 0.924) and significantly higher performance than lesion size (AUC, 0.711) for differentiating IPAs from preinvasive lesions. CONCLUSION. In pGGNs, a lesion with a modified NIC value of more than 0.29 can be a very specific discriminator of IPAs from preinvasive lesions, and IPAs can be accurately and reliably differentiated from preinvasive lesions using enhanced dual-source DECT and three-planar measurements.

Spectral Computed Tomography Imaging in the Differential Diagnosis of Lung Cancer and Inflammatory Myofibroblastic Tumor

OBJECTIVE

The aim of this study was to explore the value of spectral computed tomography (CT) imaging in differentiating lung cancer from inflammatory myofibroblastic tumor (IMT).

METHODS

One hundred twelve patients with 96 lung cancers and 16 IMTs underwent spectral CT during arterial phase (AP) and venous phase (VP). The normalized iodine concentration in AP (NICAP) and VP (NICVP), slope of spectral Hounsfield unit curve in AP (λAP) and VP (λVP), and normalized iodine concentration difference between AP and VP (ICD) were calculated. The 2-sample t test compared quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Receiver operating characteristic curves were generated to calculate sensitivity and specificity. Sensitivity and specificity of the qualitative and quantitative studies were compared.

RESULTS

The patients with IMT had significantly higher NICAP, NICVP, λAP, λVP, and ICD than did the patients with lung cancer (P < 0.05). The threshold NICVP of 0.425 would yield the highest sensitivity and specificity of 92.7% and 81.3%, respectively, for differentiating lung cancer from IMT. The logistic regression model produced from combining quantitative parameters NICAP, NICVP, λAP, and λVP provided a sensitivity and specificity of 100% and 81.3%, respectively, for differentiating lung cancer from IMT.

CONCLUSIONS

Spectral CT imaging with the quantitative analysis may help to increase the accuracy of differentiating lung cancer from IMT.

Spectral Computed Tomography for the Quantitative Assessment of Patients With Carcinoma of the Gastroesophageal Junction: Initial Differentiation Between a Diagnosis of Squamous Cell Carcinoma and Adenocarcinoma

OBJECTIVE

This study aimed to distinguish between esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) using spectral computed tomography (CT) and to discuss the accuracy according to an optimal threshold of single and combined parameters.

METHODS

In this monoinstitution study, 61 patients, 35 of whom had ESCC and 26 had EAC confirmed by surgery or esophagoscopy, were recruited from August 2016 to March 2017. Enrolled patients underwent dual-phase chest CT enhancement. The spectral CT parameters (NIC, NICD, NICratio, Zeff, Zeff-C, K40-70 keV, K80-100 keV, and K110-140 keV) were measured during arterial phase (AP) and venous phase (VP). Binary logistic regression was used to calculate combined predictive probability. Thresholds of quantitative parameters and diagnostic accuracy were calculated using receiver operating characteristic curve.

RESULTS

Compared with ESCC, higher NICAP, NICVP, NICD, Zeff AP, Zeff VP, Zeff-C AP, and Zeff-C VP were observed for EAC, whereas NICratio was lower for EAC. Higher K40-70 keV, K80-100 keV, and K110-140 keV were exhibited in EAC than in ESCC. Area under the curve (AUC) of NICAP, K40-70 keV AP, and Zeff AP were 0.720, 0.730, and 0.706, respectively. The area under the curve of new combined predictive value of NICAP and λ40-0 keV AP was 0.804. The sensitivity and specificity were 77.80% and 80.60%, respectively, when the threshold of new predictive value was 0.60.

CONCLUSION

The diagnostic accuracy obtained by using NICAP and K40-70 keV AP combined is better than that obtained using a single parameter in differentiation between a diagnosis of squamous cell carcinoma and adenocarcinoma.

Virtual monoenergetic reconstruction of contrast-enhanced CT scans of the abdomen and pelvis at 40 keV improves the detection of peritoneal metastatic deposits

PURPOSE

To evaluate the role of virtual monoenergetic imaging (VMI) in the detection of peritoneal metastatic disease in contrast-enhanced computed tomography (CT) of the abdomen and pelvis and to compare this technique to the conventional 120 kV mixed dataset.

MATERIALS AND METHODS

Institutional review board approval was obtained with no informed consent required for this retrospective analysis. 43 consecutive patients with histopathologically confirmed peritoneal disease were scanned using a standard protocol on a 128-section dual-source, dual-energy CT system (100/140 keV). Scans were retrospectively reconstructed at VMI energy levels from 40-110 keV in 10 keV increments and were analyzed both quantitatively and qualitatively. CNR values for peritoneal metastatic deposits were recorded using region of interest (ROI) analysis at each energy level for all VMI datasets. Subjective analysis was performed by two independent fellowship-trained readers with combined experience of greater than 15 years. Qualitative parameters included diagnostic acceptability, subjective noise, and contrast resolution and confidence.

RESULTS

The contrast-to-noise ratios (CNRs) for peritoneal metastatic deposits at the different VMI energy levels were compared using a one-way ANOVA with Tukey Post Test, and the optimal CNR was observed at 40 keV (p < 0.0001). Qualitative parameters were compared using a Paired T Test. Subjective noise, diagnostic acceptability, and contrast resolution was significantly better on the conventional images, but readers reported increased confidence on VMI at 40 keV (p < 0.001).

CONCLUSION

VMI reconstruction of contrast-enhanced dual-energy CT scans of the abdomen and pelvis at 40 keV maximizes the conspicuity of metastatic peritoneal deposits and improves radiologists' diagnostic confidence compared with conventional CT images. We recommend using virtual monoenergetic datasets at 40 keV as a tool for improving the detection of these lesions in routine clinical practice.

Can spectral computed tomography imaging improve the differentiation between malignant and benign pulmonary lesions manifesting as solitary pure ground glass, mixed ground glass, and solid nodules?

BACKGROUND

This study quantitatively assessed the efficacy of spectral computed tomography (CT) imaging parameters for differentiating the malignancy and benignity of solitary pulmonary nodules (SPNs) manifesting as ground glass nodules (GGNs) and solid nodules (SNs).

METHODS

The study included 114 patients with SPNs (61 GGNs, and 53 SNs) who underwent CT plain and enhanced scans in the arterial (a) and venous (v) phases using the spectral imaging mode. The spectral CT imaging parameters included: iodine concentrations (IC) of lesions in the arterial (ICLa) and venous (ICLv) phases; normalized IC (NICa/NICv, normalized to the IC in the aorta); the slope of the spectral Hounsfield unit (HU) curve (λHUa/λHUv); and monochromatic CT number (CT40keVa/v, CT70keVa/v) enhancement on 40 and 70 keV images. The two-sample Mann-Whitney U test was used to compare quantitative parameters between malignant and benign SPNs, SNs, and GGNs.

RESULTS

Pathology revealed 75 lung cancer cases, 3 metastatic nodules, 14 benign nodules, and 22 inflammatory nodules. Among the 53 SNs there were 37 malignant and 16 benign nodules. Among the 61 GGNs there were 41 malignant and 20 benign nodules. Overall, the CT40keVa, λHUa, CT40keVv, λHUv, and ICLv of benign SPNs were all greater than those of malignant SPNs (all P < 0.05). For GGNs, CT40keVa/v, CT70keVa/v, λHUa/λHUv, and ICLv of malignant GGNs were all lower than those of benign GGNs.

CONCLUSION

Spectral CT imaging is a more promising method for distinguishing malignant from benign nodules, especially in nodules manifesting as GGNs in contrast-enhanced scanning.

Spectral CT Analysis of Solitary Pulmonary Nodules for Differentiating Malignancy from Benignancy: The Value of Iodine Concentration Spatial Distribution Difference

Objective

The objective is to assess the value of spatial distribution difference in iodine concentration between malignant and benign solitary pulmonary nodules (SPNs) by analyzing multiple parameters of spectral CT.

Methods

Sixty patients with 39 malignant nodules and 21 benign nodules underwent chest contrast CT scans using spectral imaging mode during pulmonary arterial phase (PP), arterial phase (AP), and venous phase (VP). Iodine concentrations of proximal and distal regions in pulmonary nodules on iodine-based material decomposition images were recorded. Normalized iodine concentration (NIC) and the differences in NIC between the proximal and the distal regions (dNIC) were calculated. The two-sample t-test and Mann-Whitney U-test were performed to compare the multiple parameters generated from spectral CT between malignant and benign nodules. Receiver operating characteristic (ROC) curves were generated to calculate sensitivity and specificity.

Results

NIC in the proximal region (NIC_pro) and NIC in the distal region (NIC_dis) between malignant and benign nodules at AP (NIC_pro, P=0.012; NIC_dis, P=0.024), and VP (NIC_pro, P=0.005; NIC_dis, P =0.004) were significantly different. NIC_pro at PP (P = 0.037) was also found significantly different between malignant and benign nodules; however, no significant differences were found in NIC_dis at PP (P = 0.093). In addition, the dNIC of malignant nodules was significantly higher than that of benign ones at PP (median and interquartiles (0.31, 0.11, 0.57 versus -0.26, -0.5, -0.1); p≤0.001), AP (mean dNIC, 0.093 ±0.094 versus -0.075±0.060; p≤0.001), and VP (mean dNIC, 0.171±0.137 versus -0.183±0.127; p≤0.001). The sensitivity and specificity (93%, 95%, respectively) of dNIC during VP were higher than other parameters, with a threshold value of -0.07.

Conclusions

Spectral CT imaging with multiple parameters such as NIC_pro, NIC_dis, and dNIC may be a new method for differentiating malignant SPNs from benign ones.

Iodine Quantification Using Dual-Energy Computed Tomography for Differentiating Thymic Tumors

The aim of the study was to explore the efficacy of iodine quantification with dual-energy computed tomography (DECT) in differentiating thymoma, thymic carcinoma, and thymic lymphoma.

MATERIALS AND METHODS

Fifty-seven patients with pathologically confirmed low-risk thymoma (n = 16), high-risk thymoma (n = 15), thymic carcinoma (n = 14), and thymic lymphoma (n = 12) underwent chest contrast-enhanced DECT scan were enrolled in this study. Tumor DECT parameters including iodine-related Hounsfield unit (IHU), iodine concentration (IC), mixed HU (MHU), and iodine ratio in dual phase, slope of energy spectral HU curve (λ), and virtual noncontrast (VNC) were compared for differences among 4 groups by one-way analysis of variance. Receiver operating characteristic curve was used to determine the efficacy for differentiating the low-risk thymoma from other thymic tumor by defined parameters.

RESULTS

According to quantitative analysis, dual-phase IHU, IC, and MHU values in patients with low-risk thymoma were significantly increased compared with patients with high-risk thymoma, thymic carcinoma, and thymic lymphoma (P < 0.05/4).The venous phase IHU value yielded the highest performance with area under the curve of 0.893, 75.0% sensitivity, and 89.7% specificity for differentiating the low-risk thymomas from high-risk thymomas or thymic carcinoma at the cutoff value of 34.3 HU. When differentiating low-risk thymomas from thymic lymphoma, the venous phase IC value obtained the highest diagnostic efficacy with the area under the curve of 0.969, and sensitivity, specificity, and cutoff value were 87.5%, 100.0%, and 1.25 mg/mL, respectively.

CONCLUSIONS

Iodine quantification with DECT may be useful for differentiating the low-risk thymomas from other thymic tumors.

Identification of epidermal growth factor receptor mutations in pulmonary adenocarcinoma using dual-energy spectral computed tomography

OBJECTIVES

To explore the role of dual-energy spectral computed tomography (DESCT) quantitative characteristics for the identification of epidermal growth factor receptor (EGFR) mutation status in a cohort of East Asian patients with pulmonary adenocarcinoma.

MATERIALS AND METHODS

Patients with lung adenocarcinoma who underwent both DESCT chest examination and EGFR test were retrospectively selected from our institution's database. The DESCT visual morphological features and quantitative parameters, including the CT number at 70 keV, normalized iodine concentration (NIC), normalized water concentration, and slopes of the spectral attenuation curves (slope λ HU [Hounsfield unit]), were evaluated or calculated. The patients were divided into two groups: the EGFR mutation group and EGFR wild-type group. Statistical analyses were performed to identify the DESCT quantitative parameters for diagnosis of EGFR mutation status.

RESULTS

EGFR mutations were detected in 66 (55.0%) of the 120 enrolled patients. The univariate analysis revealed that sex, smoking history, CT texture, NIC, and slope λ HU were significantly associated with EGFR mutation status (p = 0.037, 0.001, 0.047, 0.010, and 0.018, respectively). The multivariate logistic analysis revealed that smoking history (odds ratio [OR] = 3.23, p = 0.005) and NIC (OR = 58.026, p = 0.049) were the two significant predictive factors associated with EGFR mutations. Based on this analysis, the smoking history and NIC were combined to determine the predictive value for EGFR mutations with the area under the curve of 0.702.

CONCLUSIONS

NIC may be a potential quantitative DESCT parameter for predicting EGFR mutations in patients with pulmonary adenocarcinoma.

KEY POINTS

• DESCT can provide multiple quantitative image parameters compared to conventional CT. • Identification of the radio-genomic relation between DESCT and EGFR status can help to define molecular subcategories of lung adenocarcinoma, which is valuable for personalized clinical targeted therapy. • NIC may be a potential DESCT quantitative parameter for predicting EGFR mutations in pulmonary adenocarcinoma.

CT spectral parameters and serum tumour markers to differentiate histological types of cancer histology

AIM

To evaluate lung cancer histology type using computed tomography (CT) spectral quantitative parameters combining with serum tumour markers.

MATERIALS AND METHODS

Patients with suspicious lung cancer underwent CT spectral imaging and serum tumour markers. CT spectral quantitative parameters including attenuation value, the slope of spectral curve (λ), iodine concentration, water concentration, and effective atomic number (Zeff) were acquired. Serum levels of tumour markers including carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), and cytokeratin fragment CYFRA21-1 were also obtained. All the values were compared among different histological types of lung cancer. The diagnostic efficiencies of serum tumour markers, CT spectral parameters, and a combination of them were computed by statistical analysis.

RESULTS

CEA and NSE levels were higher in adenocarcinoma and neuroendocrine tumour, respectively, while SCC-Ag and CYFRA21-1 levels were higher in squamous cell cancer. There was no significant difference in attenuation among the groups (p>0.05), whereas λ in the arterial phase, and Zeff and IC in both the arterial and venous phases were significantly different among groups (p<0.05). According to the area under the receiver operating characteristic (ROC) curve (AUC) and Youden's index, the diagnostic efficiency of serum tumour markers were higher than that of CT spectral parameters. Moreover, AUCs of combined serum and CT indicators were larger than that of combined serum markers and combined CT spectral parameters between squamous cell cancer and adenocarcinoma as well as between squamous cell cancer and neuroendocrine tumour.

CONCLUSION

CT spectral quantitative parameters and serum tumour markers are valuable in evaluating histological types of lung cancer. In combination they can significantly improve diagnostic efficiency.

The Role of Dual-Energy Computed Tomography in Assessment of Abdominal Oncology and Beyond

The added value and strength of dual energy computed tomography for the evaluation of oncologic patients revolve around the use of lower energy reconstructed images and iodine material density images. Lower keV simulated monoenergetic images optimize soft tissue tumor to nontumoral attenuation differences and increase contrast to noise ratios to improve lesion detection. Iodine material density images or maps are helpful from a qualitative standpoint for image interpretation because they result in improved detection and characterization of tumors and lymph node involvement, and from a quantitative assessment by enabling interrogation of specific properties of tissues to predict and assess therapeutic response.

Diagnostic value of single-source dual-energy spectral computed tomography in differentiating parotid gland tumors: initial results

Background

An accurate preoperative diagnosis that helps distinguish between benign and malignant parotid gland tumors is very important because the results strongly affect surgical procedures. We aimed to evaluate the value of single-source dual-energy computed tomography (ssDECT) in differentiating malignant from benign parotid gland tumors.

Methods

Fifty patients underwent enhanced neck ssDECT scanning before surgery. The images were analyzed using the gemstone spectral imaging (GSI) viewer software.

Results

Fifty-two tumors (43 patients) were confirmed histopathologically, comprising of 12 pleomorphic adenomas (PAs), 24 Warthin tumors (WTs) (15 patients), and 16 malignant tumors (MTs). The iodine concentration (IC), normalized iodine concentration to common carotid artery (NIC_A) and slope value of the spectral curve (λ_HU) of the WTs were significantly higher than those of MTs and PAs (all P<0.05). The optimal IC, NIC_A and λ_HU thresholds for differentiating PAs from MTs were 0.91 mg/mL, 0.15 and 1.09, respectively, achieving sensitivities of 91.7%, 91.7% and 91.7%, specificities of 95.0%, 85.0% and 95.0%, and accuracies of 94.2%, 86.5% and 94.2%, respectively for distinguishing PAs from MTs. The optimal IC, NIC_A and λ_HU thresholds for distinguishing WTs from MTs were 1.46 mg/mL, 0.20 and 1.72, achieving sensitivities of 91.7%, 95.8% and 91.7%, and specificities of 89.3%, 85.7% and 89.3%, respectively. The accuracy was 90.4%, 90.4% and 90.4%, respectively.

Conclusions

The parameters of ssDECT in enhanced CT scans are useful in the differential diagnosis of parotid tumors.

Gemstone spectral imaging in lung cancer: A preliminary study

The present study aimed to evaluate the application of gemstone spectral imaging (GSI) for multi-parameter quantitative measurement in lung cancer.The study retrospectively enrolled 30 patients with lung cancer who underwent chest contrast enhanced CT scan with GSI mode. The GSI viewer was used for image display and data analysis. Optimal energy value, CT values at 40 keV, 70 keV and optimal energy level, spectral curve slope, effective atomic number (Zeff), iodine concentration (IC), and water concentration (WC) at the region of interest were measured and analyzed by statistical methods.The optimal energy value for optimal contrast-to-noise ratio on plain scan, arterial phase and venous phase was 62.2 ± 5.38 keV, 50.63 ± 3.84 keV, and 52.5 ± 3.7 keV, respectively. There were significant differences in CT values at different energy levels on each scan phase (P = .033). The spectral curve slope values among 40 to 70 keV, 40 to 100 keV, and 40 to 140 keV were significantly different (P < .001). No significant difference with the slope between arterial phase and venous phase at each energy level interval was observed. Zeff on plain scan, arterial phase, and venous phase was 7.75 ± 0.15, 8.38 ± 0.37, and 8.38 ± 0.30, respectively. Positive correlation was observed among IC, normalized IC, and Zeff on enhanced scan.Multiparameter of GSI can be used for lung tumor lesion evaluation. Different parameters were correlated and provide multiple qualitative and quantitative information together.

Intermanufacturer Comparison of Dual-Energy CT Iodine Quantification and Monochromatic Attenuation: A Phantom Study

Purpose To determine the accuracy of dual-energy computed tomographic (CT) quantitation in a phantom system comparing fast kilovolt peak-switching, dual-source, split-filter, sequential-scanning, and dual-layer detector systems. Materials and Methods A large elliptical phantom containing iodine (2, 5, and 15 mg/mL), simulated contrast material-enhanced blood, and soft-tissue inserts with known elemental compositions was scanned three to five times with seven dual-energy CT systems and a total of 10 kilovolt peak settings. Monochromatic images (50, 70, and 140 keV) and iodine concentration images were created. Mean iodine concentration and monochromatic attenuation for each insert and reconstruction energy level were recorded. Measurement bias was assessed by using the sum of the mean signed errors measured across relevant inserts for each monochromatic energy level and iodine concentration. Iodine and monochromatic errors were assessed by using the root sum of the squared error of all measurements. Results At least one acquisition paradigm per scanner had iodine biases (range, -2.6 to 1.5 mg/mL) with significant differences from zero. There were no significant differences in iodine error (range, 0.44-1.70 mg/mL) among the top five acquisition paradigms (one fast kilovolt peak switching, three dual source, and one sequential scanning). Monochromatic bias was smallest for 70 keV (-12.7 to 15.8 HU) and largest for 50 keV (-80.6 to 35.2 HU). There were no significant differences in monochromatic error (range, 11.4-52.0 HU) among the top three acquisition paradigms (one dual source and two fast kilovolt peak switching). The lowest accuracy for both measures was with a split-filter system. Conclusion Iodine and monochromatic accuracy varies among systems, but dual-source and fast kilovolt-switching generally provided the most accurate results in a large phantom. ^© RSNA, 2017 Online supplemental material is available for this article.

Preliminary study on the diagnostic value of single-source dual-energy CT in diagnosing cervical lymph node metastasis of thyroid carcinoma

Background

To investigate the value of single-source dual-energy spectral CT imaging in improving the accuracy of preoperative diagnosis of lymph node metastasis of thyroid carcinoma.

Methods

Thirty-four thyroid carcinoma patients were enrolled and received spectral CT scanning before thyroidectomy and cervical lymph node dissection surgery. Iodine-based material decomposition (MD) images and 101 sets of monochromatic images from 40 to 140 keV were reconstructed after CT scans. The iodine concentrations (IC) of lymph nodes were measured on the MD images and was normalized to that of common carotid artery to obtain the normalized iodine concentration (NIC). The CT number of lymph nodes as function of photon energy was measured on the 101 sets of images to generate a spectral HU curve and to calculate its slope λ_HU. The measurements between the metastatic and non-metastatic lymph nodes were statistically compared and receiver operating characteristic (ROC) curves were used to determine the optimal thresholds of these measurements for diagnosing lymph nodes metastasis.

Results

There were 136 lymph nodes that were pathologically confirmed. Among them, 102 (75%) were metastatic and 34 (25%) were non-metastatic. The IC, NIC and the slope λ_HU of the metastatic lymph nodes were 3.93±1.58 mg/mL, 0.70±0.55 and 4.63±1.91, respectively. These values were statistically higher than the respective values of 1.77±0.71 mg/mL, 0.29±0.16 and 2.19±0.91 for the non-metastatic lymph nodes (all P<0.001). ROC analysis determined the optimal diagnostic threshold for IC as 2.56 mg/mL, with the sensitivity, specificity and accuracy of 83.3%, 91.2% and 85.3%, respectively. The optimal threshold for NIC was 0.289, with the sensitivity, specificity and accuracy of 96.1%, 76.5% and 91.2%, respectively. The optimal threshold for the spectral curve slope λ_HU was 2.692, with the sensitivity, specificity and accuracy of 88.2%, 82.4% and 86.8%, respectively.

Conclusions

The measurements obtained in dual-energy spectral CT improve the sensitivity and accuracy for preoperatively diagnosing lymph node metastasis in thyroid carcinoma.

Regional Distribution of Pulmonary Blood Volume with Dual-Energy Computed Tomography: Results in 42 Subjects

RATIONALE AND OBJECTIVES

The noninvasive approach of lung perfusion generated from dual-energy computed tomography acquisitions has entered clinical practice. The purpose of this study was to analyze the regional distribution of iodine within distal portions of the pulmonary arterial bed on dual-source, dual-energy computed tomography examinations in a cohort of subjects without cardiopulmonary pathologies.

MATERIALS AND METHODS

The study population included 42 patients without cardiorespiratory disease, enabling quantitative and qualitative analysis of pulmonary blood volume after administration of a 40% contrast agent. Qualitative analysis was based on visual assessment. Quantitative analysis was obtained after semiautomatic division of each lung into 18 areas.

RESULTS

The iodine concentration did not significantly differ between the right (R) and left (L) lungs (P = .49), with a mean attenuation of 41.35 Hounsfield units (HU) and 41.14 HU, respectively. Three regional gradients of attenuation were observed between: (a) lung bases and apices (P < .001), linked to the conditions of examination (mean Δ: 6.23 in the R lung; 5.96 in the L lung); (b) posterior and anterior parts of the lung (P < .001) due to gravity (mean Δ: 11.92 in the R lung ; 15.93 in the L lung); and (c) medullary and cortical lung zones (P < .001) (mean Δ: 9.35 in the R lung ; 8.37 in the L lung). The intensity of dependent-nondependent (r = 0.42; P < .001) and corticomedullary (r = 0.58; P < .0001) gradients was correlated to the overall iodine concentration.

CONCLUSION

Distribution of pulmonary blood volume is influenced by physiological gradients and scanning conditions.