Dual-energy Spectral Computed Tomography Research Articles

Relationship between abdominal fat volume and bone base material pairs from dual-energy spectral computed tomography in young and middle-aged patients with metabolic syndrome.

Metabolic syndrome (MetS) has complex effects on bone health, and dual-energy spectral computed tomography (CT) has become increasingly valuable for bone quantification. However, the relationship between bone base material pairs (BMPs) and abdominal fat volume in patients with MetS remains underexplored. This study thus aimed to analyze the relationship between abdominal fat volume and various bone BMPs using dual-energy spectral CT in young and middle-aged patients with MetS. Patients with MetS who underwent sleeve gastrectomy at the Center of Obesity and Metabolic Diseases, Beijing Shijitan Hospital, Capital Medical University, from June to November 2021 were retrospectively collected. The abdominal fat measurements and BMPs were acquired using dual-energy spectral CT imaging. These included the volumes of total abdominal fat (TAF), abdominal visceral fat (AVF), and abdominal subcutaneous fat (ASF), as well as bone densities based on hydroxyapatite (water), i.e., HAP (water), and calcium (water), i.e., Ca (water), BMPs. After grouping the patients by sex, we analyzed the differences in clinical and imaging features. The correlation between the clinical and imaging parameters of patients with MetS was evaluated with Pearson correlation coefficients. Age- and sex-adjusted partial correlation analysis between fat volume and bone BMPs was conducted for patients of different sexes. Additionally, multiple linear regression analyses were performed with age, sex, and TAF volume as the independent variables and with Ca (water) and HAP (water) as dependent variables. A total of 112 young and middle-aged patients with MetS were included in this study, including 85 females and 27 males. Compared to male patients with MetS, the females with MetS exhibited higher lumbar Ca (water) and HAP (water) BMPs, with lower volumes of TAF and AVF and a smaller abdominal circumference (P<0.01). The volumes of TAF, AVF, and ASF were negatively correlated with the average Ca (water) and HAP (water) BMPs in the first to third lumbar vertebrae (L1-L3) (P<0.05). Ca (water) and HAP (water) BMPs decreased with age and increasing TAF volume (P<0.001). The fitted equations for the relationship between bone BMPs with age, sex, and TAF volume were as follows: (I) bone Ca (water) BMP = 76.469 - 0.500 age + 6.762 sex - 0.002 TAF volume; (II) bone HAP (water) BMP =171.704 - 1.138 age + 11.825 sex - 0.004 TAF volume. In young and middle-aged patients with MetS, the abdominal fat volume was negatively correlated with lumbar bone Ca (water) and HAP (water) BMPs, implying that increased abdominal fat volume may play a crucial role in the pathogenesis of osteopenia among those with MetS. The reduction of bone Ca (water) and HAP (water) with high abdominal fat volume may hold clinical significance for fracture risk in individuals with MetS.

One-step inverse generation network for sparse-view dual-energy CT reconstruction and material imaging

Objective. Sparse-view dual-energy spectral computed tomography (DECT) imaging is a challenging inverse problem. Due to the incompleteness of the collected data, the presence of streak artifacts can result in the degradation of reconstructed spectral images. The subsequent material decomposition task in DECT can further lead to the amplification of artifacts and noise. Approach. To address this problem, we propose a novel one-step inverse generation network (OIGN) for sparse-view dual-energy CT imaging, which can achieve simultaneous imaging of spectral images and materials. The entire OIGN consists of five sub-networks that form four modules, including the pre-reconstruction module, the pre-decomposition module, and the following residual filtering module and residual decomposition module. The residual feedback mechanism is introduced to synchronize the optimization of spectral CT images and materials. Main results. Numerical simulation experiments show that the OIGN has better performance on both reconstruction and material decomposition than other state-of-the-art spectral CT imaging algorithms. OIGN also demonstrates high imaging efficiency by completing two high-quality imaging tasks in just 50 seconds. Additionally, anti-noise testing is conducted to evaluate the robustness of OIGN. Significance. These findings have great potential in high-quality multi-task spectral CT imaging in clinical diagnosis.

Correlation Between Quantitative Parameters Obtained by Dual Energy Spectral CT and Prognostic Histopathological Factors and Biomarkers in Breast Cancer

Rationale and ObjectivesTo investigate the correlation between quantitative parameters obtained by dual energy spectral computed tomography (DESCT) and various histopathological factors and biomarkers associated with the prognosis of breast cancer. Materials and MethodsQuantitative parameters such as iodine content (IC), normalized IC (nIC), iodine enhancement (IE) and normalized IE (nIE) were measured on virtual monochromatic images and iodine mapping images obtained from DESCT in 116 female breast cancer patients. The relationship between these parameters and prognostic biomarkers such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status and Ki67 levels, as well as the correlation with histological grade (HG), lymphovascular invasion (LVI), and metastatic axillary lymphadenopathy (LAP) were evaluated. ResultsER-negative tumors had significantly higher values of IC, nIC, IE, and nIE compared to ER-positive tumors. PR-negative tumors had significantly higher values of IE and nIEc compared to PR-positive tumors. HER2 overexpressed and Ki-67 high proliferation tumors showed significantly higher values of all quantitative parameters compared to HER2 negative and Ki-67 low proliferation tumors. All quantitative parameters were significantly higher in HG 3 tumors, tumors with detected LVI, and tumors with metastatic axillary LAP compared to low-grade tumors, LVI-negative tumors and tumors without metastatic axillary lymph nodes, respectively. ConclusionQuantitative parameters of IC and IE obtained from DESCT have shown potential for predicting prognosis in breast cancer patients. Higher values of these parameters have been found to correlate with poor prognostic biomarkers and histopathological features. These results suggest that quantitative DESCT imaging may offer an additional benefit in the noninvasive prediction of breast cancer prognosis.

Dual-energy CT-based radiomics in predicting EGFR mutation status non-invasively in lung adenocarcinoma

ObjectivesPatients with epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma (LUAD) can benefit from individualized targeted therapy. This study aims to develop, compare, analyse prediction models based on dual-energy spectral computed tomography (DESCT) and CT-based radiomic features to non-invasively predict EGFR mutation status in LUAD. Materials and methodsPatients with LUAD (n = 175), including 111 patients with and 64 patients without EGFR mutations, were enrolled in the current study. All patients were randomly divided into a training dataset (122 cases) and validation dataset (53 cases) at a ratio of 7:3. After extracting CT-based radiomic, DESCT and clinical features, we built seven prediction models and a nomogram of the best prediction. Receiver operating characteristic (ROC) curves and the mean area under the curve (AUC) values were used for comparisons among the models to obtain the best prediction model for predicting EGFR mutations. ResultsThe best distinguishing ability is the combined model incorporating radiomic, DESCT and clinical features for predicting the EGFR mutation status with an AUC of 0.86 (95 % CI: 0.79–0.92) in the training group and an AUC value of 0.83 (95 % CI: 0.73, 0.96) in the validation group. ConclusionsOur study provides a predictive nomogram non-invasively with a combination of CT-based radiomic, DESCT and clinical features, which can provide image-based biological information for targeted therapy of LUAD with EGFR mutations.

Preoperative prediction of the lymphovascular tumor thrombus of colorectal cancer with the iodine concentrations from dual-energy spectral CT

BackgroundThe aim of this study was to explore application value of iodine concentration from dual-energy spectral computed tomography (DESCT) in preoperative prediction of lymphovascular tumor thrombus in patients with colorectal cancer (CRC).MethodsWe finally retrospectively analyzed 50 patients with CRC who underwent abdominal DESCT before receiving any preoperative treatment and underwent surgery to obtain pathological specimens which were stained with hematoxylin-eosin (HE) staining. According to the presence of cancer cell nests in blood vessels and lymphatic vessels, the subjects were divided into the positive group and negative group of lymphovascular tumor thrombus. Two radiologists independently measured the normalized iodine concentration (NIC) values, effective atomic number (Zeff) and CT values of virtual monochromatic images (VMIs) at 40–90 keV of the primary tumors in the arterial phase (AP) and venous phase (VP). Used SPSS 17.0 to calculate the receiver operating characteristic (ROC) curve to evaluate diagnostic value.ResultsThe patients were divided into lymphovascular tumor thrombus positive group(n = 16) and negative group(n = 34). The values of NIC-AP and NIC-VP in the positive group were 0.17 ± 0.09, 0.51 ± 0.13, respectively. And those in the negative group were 0.15 ± 0.06, 0.43 ± 0.12, respectively. There was significant difference in NIC-VP value between the two groups (p = 0.039), but there was no significant difference in NIC-AP value (p = 0.423). The optimal threshold value of NIC-VP value for diagnosis of lymphovascular tumor thrombus was 0.364. The sensitivity was 68.8% and the specificity was 67.6%.ConclusionsThe NIC-VP value of DESCT can be used to predict the presence or absence of the lymphovascular tumor thrombus in CRC patients before operation, which is helpful to select the best treatment scheme and evaluate its prognosis.

Dual-energy spectral CT in assessment of pleural effusion

Background: Pleural effusion is a common clinical problem. The ability to differentiate between benign and malignant pleural effusions has many clinical benefits. However, few studies have investigated the diagnostic value of dual-energy spectral computed tomography (DECT) in pleural effusion. Objective: To evaluate the diagnostic values of DECT for assessment of pleural effusion. Materials and Methods: We retrospectively analyzed data from 87 patients presenting with pleural effusion who underwent chest DECT from October 2019 to November 2020. Two reviewers blindly reviewed the CT images of pleural effusion in consensus. The pleural fluid attenuation in standard conventional CT images and monoenergetic images, at 40 keV, 100 keV and 140 keV, were recorded. Data pertaining to the effective atomic number, the iodine concentration (IC)and associated CT findings including pleural thickening, pleural nodules and extrapleural fat clouding was analyzed. Results: Of 87 patients, 44 were presented with benign effusions and the remaining 43 were presented with malignancy.There were no statistically significant differences in differentiating between benign and malignant pleural effusions by using the attenuation values, the effective atomic number or the IC. Irregular pleural thickening and pleural nodules were detected statistically significant in the patients with malignant pleural effusions with moderate accuracy, (48.83%; p &lt; 0.01; AuROC 0.7103 and 34.88%; p &lt; 0.01; AuROC 0.654 respectively). Conclusion: DECT attenuation values did not show any reliable clinical value in the differentiation between benign and malignant pleural effusions. The presence of pleural nodules or irregular pleural thickening would suggest malignant pleural effusion with moderate accuracy.

Development and validation of a dual-energy CT-based model to estimate the malignant probability of distal gastric wall thickening.

This study developed and validated a viable model for the preoperative diagnosis of malignant distal gastric wall thickening based on dual-energy spectral computed tomography (DEsCT). The imaging data of 208 patients who were diagnosed with distal gastric wall thickening using DEsCT were retrospectively collected and divided into a training cohort (n=151) and a testing cohort (n=57). The patient's clinical data and pathological information were collated. The multivariable logistic regression model was built using 5 selected features, and subsequently, a 10-fold cross-validation was performed to identify the optimal model. A nomogram was established based on the training cohort. Finally, the diagnostic performance of the best model was compared to the existing conventional CT scheme through evaluating the discrimination ability in the testing cohort in terms of the receiver operating characteristic curve (ROC), calibration, and clinical usefulness. Stepwise regression analysis identified 5 candidate variables with the smallest Akaike information criteria (AIC), namely, the venous phase spectral curve [VP_ SC; odds ratio (OR) 8.419], focal enhancement (OR 3.741), arterial phase mixed (OR 1.030), tumor site (OR 0.573), and diphasic shape change (DP_shape change; OR 2.746). The best regression model with 10-fold cross-validation consisting of VP_SC and focal enhancement was built using the 5 candidate variables. The average area under the ROC curve (AUC) of the model from the 10-fold cross-validation was 0.803 (sensitivity of 69.2%, specificity of 94.1%, and accuracy of 74.8%). In the testing cohort, the DEsCT model identified using the regression model performed better (AUC 0.905, sensitivity 81.3%, specificity 85.4%, and accuracy 84.2%) than did the conventional CT scheme (AUC 0.852, sensitivity 80.0%, specificity 76.6%, and accuracy 77.2%). The nomogram based on the DEsCT model showed good calibration and provided a better net benefit for predicting malignancy of distal gastric wall thickening. Comprehensive assessment with the DEsCT-based model can be used to facilitate the individualized diagnosis of malignancy risk in patients presenting with distal gastric wall thickening.

A phantom study using dual-energy spectral computed tomography imaging: Comparison of image quality between two adaptive statistical iterative reconstruction (ASiR, ASiR-V) algorithms for evaluating ground-glass nodules of the lung.

To assess the image quality of the two adaptive statistical iterative reconstruction (ASiR and ASiR-V) algorithms for evaluating ground-glass nodules (GGNs) of the lung. The chest phantom with ground-glass simulated pulmonary nodules was scanned by dual-energy spectral computed tomography (CT) using gemstone spectral imaging mode. The image was reconstructed with ASiR and ASiR-V from 0 (FBP) to 90% blending percentages, respectively. The average noise and signal-to-noise ratio (SNR) of reconstruction images were calculated. The data were statistically analyzed. Compared with FBP, as the percentage of ASiR and ASiR-V increased from 10 to 90%, image noise reduced by 3.7%-45.2% and 14.1%-73.8%, respectively, and the SNR increased accordingly. There was significantly higher SNR value of ASiR-V images as the percentages of IR increased to 50% or greater, compared to those of ASiR. Subjective image quality scores of ASiR and ASiR-V improved significantly as percentage increased from 10 to 80% for ASiR and ASiR-V (peaked at 60% for both of them). Both ASiR and ASiR-V can reduce the image noise and improve the objective image quality for presenting pulmonary nodules on dual-energy spectral CT imaging compared with FBP. ASiR-V provided further image quality improvement than ASiR, and both ASiR and ASiR-V 60% had the highest image quality score.

Development of a Nomogram Combining Clinical Risk Factors and Dual-Energy Spectral CT Parameters for the Preoperative Prediction of Lymph Node Metastasis in Patients With Colorectal Cancer

ObjectiveThis study aimed to develop a dual-energy spectral computed tomography (DESCT) nomogram that incorporated both clinical factors and DESCT parameters for individual preoperative prediction of lymph node metastasis (LNM) in patients with colorectal cancer (CRC).Material and MethodsWe retrospectively reviewed 167 pathologically confirmed patients with CRC who underwent enhanced DESCT preoperatively, and these patients were categorized into training (n = 117) and validation cohorts (n = 50). The monochromatic CT value, iodine concentration value (IC), and effective atomic number (Eff-Z) of the primary tumors were measured independently in the arterial phase (AP) and venous phase (VP) by two radiologists. DESCT parameters together with clinical factors were input into the prediction model for predicting LNM in patients with CRC. Logistic regression analyses were performed to screen for significant predictors of LNM, and these predictors were presented as an easy-to-use nomogram. The receiver operating characteristic curve and decision curve analysis (DCA) were used to evaluate the clinical usefulness of the nomogram.ResultsThe logistic regression analysis showed that carcinoembryonic antigen, carbohydrate antigen 199, pericolorectal fat invasion, ICAP, ICVP, and Eff-ZVP were independent predictors in the predictive model. Based on these predictors, a quantitative nomogram was developed to predict individual LNM probability. The area under the curve (AUC) values of the nomogram were 0.876 in the training cohort and 0.852 in the validation cohort, respectively. DCA showed that our nomogram has outstanding clinical utility.ConclusionsThis study presents a clinical nomogram that incorporates clinical factors and DESCT parameters and can potentially be used as a clinical tool for individual preoperative prediction of LNM in patients with CRC.

Application of contrast-enhanced dual-energy spectral CT for differentiating borderline from malignant epithelial ovarian tumours

To investigate the value of contrast-enhanced dual-energy spectral computed tomography (CT) in differentiating borderline epithelial ovarian tumours (BEOTs) from malignant epithelial ovarian tumours (MEOTs). Sixty patients who underwent pelvic contrast-enhanced spectral CT were divided into two groups for analysis based on the tumour types confirmed at histopathological examination (26 BEOTs and 34 MEOTs). The regions of interest (ROIs) were selected on solid tumour components to measure attenuation values on monochromatic image sets (40-140 keV) in all imaging phases and tumour iodine concentrations (IC) on material decomposition images. Differences in the attenuation value between the unenhanced and contrast-enhanced phases (enhancement degree) and between energy strengths (slope k, k=[attenuation at 40 keV- attenuation at 140 keV]/100) were calculated. All measurements between the two groups were compared with independent t-test. Receiver operating characteristic (ROC) curves were generated to calculate the sensitivity, specificity and area under the ROC curve (AUC). Logistic regression analysis was used to evaluate the diagnostic efficacy of using combined parameters in two-phase contrast-enhanced images. In the arterial phase (AP) and venous phase (VP), the BEOTs had significantly lower enhancement than MEOTs from 40 to 100 keV (p<0.05). The k values and IC values both showed significant differences in the AP and VP (p<0.05). Combining parameters in two contrast-enhanced phases provided 80.8% sensitivity and 82.4% specificity in differentiating MEOTs from BEOTs with an AUC of 0.844. Dual-energy spectral CT provides a multiparametric approach in differentiating BEOTs from MEOTs with the best diagnostic efficacy using combined parameters in the AP and VP images.

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

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

Effect of radiomics from different virtual monochromatic images in dual-energy spectral CT on the WHO/ISUP classification of clear cell renal cell carcinoma

To investigate the effect of radiomics obtained from different virtual monochromatic images (VMIs) in dual-energy spectral computed tomography (CT) on the World Health Organization/International Association for Urological Pathology (WHO/ISUP) classification of clear cell renal cell carcinoma (ccRCC). A retrospective study of 99 ccRCC patients who underwent contrast-enhanced dual-energy CT was undertaken. ccRCC was confirmed at surgery or biopsy and graded according to the WHO/ISUP pathological grading criteria as low grade (n=68, grade I and II) or high grade (n=31, grade III and IV). Radiomics risk scores (RRSs) for differentiating high and low grades of ccRCC were constructed from 11 sets of VMI in (40-140 keV, 10 keV interval) the cortical phase. Receiver operating characteristic (ROC) curves were drawn and the area under the curves (AUCs) was calculated to evaluate the discriminatory power of RRS for each VMI. The Hosmer-Lemeshow test was used to evaluate the goodness-of-fit of each model and the decision curve was used to analyse its net benefit to patients. The AUC values for distinguishing low-from high-grade ccRCC with RRS of 40-140 keV VMIs were all >0.920. The Hosmer-Lemeshow test showed that the p-values of RRS of VMIs were >0.05, suggesting good fits. In the decision curve analysis, RRS from the 40-140 keV VMIs had similar decision curves and provided better net benefits than considering all patients either as high-grade or low-grade. The RRS obtained from multiple VMIs in dual-energy spectral CT have high diagnostic efficiencies for distinguishing between low- and high-grade ccRCC with no significant differences between different VMIs.

The value of a dual-energy spectral CT quantitative analysis technique in acute pancreatitis

To explore the value of dual-energy spectral computed tomography (DESCT) in evaluating the clinical severity of acute pancreatitis. Seventy patients with acute pancreatitis (AP) confirmed by clinical examination were included in this study. All patients underwent unenhanced/double-phase enhanced CT in spectral imaging mode. Iodine concentration and normalised iodine concentration (NIC) were measured retrospectively with a spectral imaging viewer (GSI Viewer). All data were analysed by analysis of variance. Receiver operating characteristic (ROC) curves were constructed to determine the optimal threshold for predicting the clinical severity of AP. Seventy patients were included in the study comprising 30 mild, 22 moderate, and 18 severe cases of AP. The CT attenuation value, iodine concentration, and NIC were decreased with increasing clinical severity. Moreover, there were significant differences between the mild group and the severe group (p<0.05), as well as between the moderate group and the severe group (p<0.05). The area under the ROC curve AUC of each value was larger in arterial phase than in portal venous phase. The most sensitive value between the mild and severe groups in AP was the NIC (arterial phase: 0.19±0.06; portal venous phase: 0.45±0.09). DESCT can provide multiple parameters to determine the severity of AP.

Development of a dual-energy spectral computed tomography-based nomogram for the preoperative discrimination of histological grade in colorectal adenocarcinoma patients.

The usefulness of a dual-energy spectral computed tomography (DESCT)-based nomogram in discriminating between histological grades of colorectal adenocarcinoma (CRAC) is unclear. This study aimed to develop such a nomogram and assess its ability to preoperatively discriminate between histological grades in CRAC patients. Primary tumors monochromatic CT value, iodine concentration (IC) value, and effective atomic number (Eff-Z) in the arterial (AP) and venous phases (VP) were retrospectively compared between patients with high-grade (n=65) and low-grade (n=108) CRAC who underwent preoperative abdominal DESCT. Univariate analysis was used to compare the DESCT parameters and clinical factors between these two patient groups. Statistically significant features in the univariate analysis were included in the multivariate logistic regression model to identify the indicators for building a nomogram that could discriminate between histological grades in CRAC patients. The clinical usefulness of the nomogram and its value for predicting overall survival were statistically evaluated. The logistic regression analysis showed that age, clinical T stage, clinical N stage, and IC values in AP and VP were significant independent predictors for high-grade CRAC. A quantitative nomogram developed based on these predictors showed excellent performance for discriminating between the histological grades, with an area under the curve (AUC) of 0.886 and excellent agreement in the calibration curve. The Kaplan-Meier curve for overall survival showed that our nomogram identified a significant difference between the high- and low-risk groups [hazard ratio (HR), 2.188; 95% CI, 1.072-4.465; P=0.027). This study presents a nomogram that incorporates DESCT parameters and clinical factors and can potentially be used as a clinical tool for individual preoperative prediction of CRAC histological grade.

Comparative Study on Iron Content Detection by Energy Spectral CT and MRI in MDS Patients.

Objective: The purpose of this study was to identify the difference between dual energy spectral computed tomography (DECT) and magnetic resonance imaging (MRI) used to detect liver/cardiac iron content in Myelodysplastic syndrome (MDS) patients with differently adjusted serum ferritin (ASF) levels.Method: Liver and cardiac iron content were detected by DECT and MRI. Patients were divided into different subgroups according to the level of ASF. The receiver operating characteristic curve (ROC) analysis was applied in each subgroup. The correlation between iron content detected by DECT/MRI and ASF was analyzed in each subgroup.Result: ROC curves showed that liver virtual iron content (LVIC) Az was significantly less than liver iron concentration (LIC) Az in the subgroup with ASF < 1,000 ng/ml. There was no significant difference between LVIC Az and LIC Az in the subgroup with 1,000 ≤ ASF < 2,500 ng/ml and 2,500 ≤ ASF < 5,000 ng/ml. LVIC Az was significantly higher than LIC Az in the subgroup with ASF <5,000 and 5,000 ≤ ASF ng/ml. In patients undergoing DECT and MRI examination on the same day, ASF was significantly correlated with LVIC, whereas no significant correlation was observed between ASF and LIC. After removing the data of ASF > 5,000 mg/L in LIC, LIC became correlated with ASF. There was no significant difference between the subgroup with 2,500 ≤ ASF < 5,000 ng/ml and 5,000 ng/ml ≤ ASF in LIC expression. Furthermore, both LIC and liver VIC had significant correlations with ASF in patients with ASF < 2,500 ng/ml, while LVIC was still correlated with ASF, LIC was not correlated with ASF in patients with 2,500 ng/ml ≤ ASF. Moreover, neither cardiac VIC nor myocardial iron content (MIC) were correlated with ASF in these subgroups.Conclusion: MRI and DECT were complementary to each other in liver iron detection. In MDS patients with high iron content, such as ASF ≥ 5,000 ng/ml, DECT was more reliable than the MRI in the assessment of iron content. But in patients with low iron content, such as ASF < 1,000 ng/ml, MRI is more reliable than DECT. Therefore, for the sake of more accurately evaluating the iron content, the appropriate detection method can be selected according to ASF.

Quantitative evaluation of bone marrow infiltration using dual-energy spectral computed tomography in patients with multiple myeloma

To explore the potential value of quantitative parameters derived from dual-energy spectral computed tomography (DESCT) as comparing to the parameters derived from magnetic resonance imaging (MRI) in detecting bone marrow (BM) infiltration and distinguishing different patterns of BM infiltration in patients diagnosed with Multiple myeloma (MM). This study involved 35MM patients and 15 healthy control subjects who had undergone spinal DESCT and MRI. Pattern assignment was based on visual assessment of MR images, and the regions of interest were defined on both DESCT and apparent diffusion coefficient maps. Quantitative values of DESCT parameters were measured and compared between infiltrated and healthy bone marrow. Receiver operating characteristic (ROC) analysis was performed to determine potential utility of DESCT parameters in identifying BM infiltration and different patterns defined by MRI. Sensitivity and specificity under the optimal thresholds determined by the Youden Index were also calculated. Statistical differences were observed between the DESCT parameters including Ca(Water), Water(Ca), HAP(Fat), Fat(HAP) and Effective atomic number (Eff-Z) but not for the 70-keV CT value between the infiltrated and healthy BM (all P < 0.001). The 70keV CT value and Ca(Water), HAP(Fat) and Eff-Z values were also found to be statistically different in comparing different infiltration patterns (all P < 0.05). Performance of the model-based parameter Ca/Water was superior in differentiating between infiltrated and healthy BM in which the area under ROC curve, AUC = 0.856 [95% CI, 81.4-89.1%] with sensitivity = 0.841 and specificity = 0.768, as well as between MM patients and control subjects (AUC = 0.910 [95% CI, 79.5-97.3%], sensitivity = 0.829 and specificity = 1.000). Analysis of DESCT offers potential as a quantitative method to detect infiltrated BM and evaluate infiltration patterns of BM in patients diagnosed with MM.

A comparison study of dual-energy spectral CT and 18F-FDG PET/CT in primary tumors and lymph nodes of lung cancer.

We aimed to investigate whether there is a correlation between dual-energy spectral computed tomography (DESCT) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) parameters in primary tumor and metastatic lymph nodes in patients with newly diagnosed lung cancer. Primary tumor and metastatic lymph nodes of 68 patients diagnosed with lung cancer were evaluated retrospectively with 18F-FDG PET/CT and DESCT imaging. The histologic subtypes were adenocarcinoma (n=29), squamous cell carcinoma (SCC) (n=26), small cell lung cancer (SCLC) (n=11), and large cell neuroendocrine cancer (LCNEC) (n=2). In terms of PET parameters, SUVmax, SUVmean, SULmax, SULmean, SULpeak, and normalized SUL values were obtained for primary tumors and metastatic lymph nodes. In terms of DESCT parameters, maximum and mean iodine content (IC), normalized IC values, iodine enhancement (IE) and normalized IE values were calculated. We found no correlation between DESCT and 18F-FDG PET/CT parameters in primary tumors and metastatic lymph nodes. In addition, no correlation was found in the analysis performed in any of the histologic subgroups. In patients with a primary tumor <3 cm, there was a moderate negative correlation between the parameters SUVmax-ICmax (r= -0.456, p = 0.043), SUVmean-ICmax (r= -0.464, p = 0.039) SULmean-ICmax (r= -0.497, p = 0.026), SUVmax-ICmean (r= -0.527, p = 0.020), SULmean-ICmean (r= -0.499, p = 0.025), and SULpeak-ICmean (r= -0.488, p = 0.029). We consider that DESCT and 18F-FDG PET/CT indicate different characteristics of the tumors and should not supersede each other.

Histological subtypes of solid-dominant invasive lung adenocarcinoma: differentiation using dual-energy spectral CT

To investigate the value of dual-energy spectral computed tomography (DESCT) for evaluating the histological subtypes of solid-dominant invasive lung adenocarcinoma (SILADC). Sixty-seven patients with SILADC were enrolled. All patients underwent DESCT and were divided into Group I (those with a lepidic/acinar/papillary predominant pattern) and Group II (those with a solid/micropapillary predominant pattern) based on their correlation with prognosis. Patient clinicopathological characteristics, DESCT morphological features, and quantitative parameters of the tumours were compared between both groups. Multiparametric analysis was performed using binary logistic regression with DESCT findings. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of single-parameter and multiparametric analysis. Patient gender, lymph nodes status, pathological TNM stage, and histological differentiation significantly differed between the two groups (all p<0.05). Moreover, significant differences were observed between both groups in DESCT morphological features including tumour size, necrosis, calcification, air bronchogram, and vascular convergence sign, and quantitative parameters including K40-65 keV, effective atomic number, and water concentration on unenhanced CT and iodine concentration in the arterial and venous phases (all p<0.05). Multiparametric analysis showed that tumour size, air bronchogram, K40-65 keV and effective atomic number on unenhanced CT were the most effective variations for predicting the histological subtypes of SILADC and obtained an area under the ROC curve (AUC) of 0.906. DESCT was useful for differentiating histological subtypes with different prognosis of SILADC.

Replacing true unenhanced imaging in renal carcinoma with virtual unenhanced images in dual-energy spectral CT: a feasibility study

To investigate the clinical value of virtual unenhanced (VNC) spectral computed tomography (CT) images to replace the conventional true unenhanced spectral CT images (TNC) in diagnosing renal carcinoma. Fifty-six cases of renal carcinoma confirmed by histopathology underwent conventional plain CT and contrast-enhanced spectral CT at arterial phase (AP) and venous phase (VP). VNC images were generated on an AW4.6 workstation. The CT attenuation, image noise, contrast-to-noise ratio (CNR), and signal-noise-ratio (SNR) of the renal lesions and normal kidneys, long and short axis diameters of the lesion were measured from the three image sets and analysed using one-way analysis of variance (ANOVA). Two radiologists evaluated image quality subjectively using a five-point score, and lesion signature using a three-point score. Image quality scores were compared statistically and tested for consistency. The two reviewers had good agreement for subjective evaluation (Kappa>0.70) and there was no difference in the quality of the scores among the three image groups. The lesion signature scores were all above the acceptable level. The CNR and SNR values in VNC were significantly higher than in TNC (p<0.05). VNC images had lower renal noise than in TNC (p<0.05). There was no difference in the long and short axis diameters of the lesion among the three image groups. VNC had higher CT attenuation values for the lesion and kidney than TNC (p<0.05), but the differences were <5 HU. VNC images in spectral CT may be used to replace the conventional plain CT to reduce imaging duration and radiation dose in diagnosing renal carcinoma.

Optimize non-contrast head CT imaging tasks using multiple virtual monochromatic image sets in dual-energy spectral CT.

To demonstrate the value of optimizing non-contrast head imaging tasks by using the multiple virtual monochromatic spectral imaging (VMSI) sets in dual-energy spectral computed tomography (CT) and determine the optimal energy levels for various tasks in imaging head. This retrospective study includes 55 patients (29 women and 26 men, average age of 54.5±12.3years) who underwent non-contrast head CT in spectral imaging mode. For each patient, 21 VMSI sets from 40 to 140 keV at 5 keV intervals and 120 kVp-like image were reconstructed. Signal-to-noise ratio (SNR) for gray matter (GM) and white matter (WM), contrast-to-noise ratio (CNR) between GM and WM, subcalvarial artifact index (SAI) and posterior fossa artifact index (PFAI) were measured by placing regions-of-interest (ROIs) in nine areas of the brain. Two radiologists subjectively rated the image quality in terms of GM-WM differentiation, beam hardening artifacts in the subcalvarial space, and posterior fossa. The overall image noise was evaluated using a 5-point Likert scale. Measurement data were then statistically analyzed. The optimal energy level for viewing the supratentorial brain and reducing beam hardening artifacts in the subcalvarial space and posterior fossa was 65 keV and 75 keV, respectively. All corresponding measurements at these energy levels were significantly better than those measured at other energy levels (all P < 0.05). Dual-energy spectral CT imaging provides a set of virtual monochromatic spectral imaging and can be selected on-demand to optimize the imaging tasks in non-contrast head CT. VMSI reconstruction of dual-energy unenhanced head CT scans at 65-75 keV enables to maximize image quality.