Dual-Energy Computed Tomography in Urological Diseases: A Narrative Review.

Dual-Energy computed tomography (DECT) with its various advanced techniques, including Virtual Non-Contrast (VNC), effective atomic number (Z-eff) calculation, Z-maps, Iodine Density Index (IDI), and so on, holds great promise in the diagnosis and management of urogenital tumours. In this narrative review, we analyze the current status of knowledge of this technology to provide better lesion characterization, improve the staging accuracy, and give more precise treatment response assessments in relation to urological tumours.

A case of bilateral adrenal infarction with preserved adrenal function diagnosed by dual-energy computed tomography.

We report a case wherein adrenal function remained preserved despite bilateral adrenal infarction, as evidenced by dual-energy computed tomography (DECT) iodine density images. The patient was a 37-year-old man with a history of antiphospholipid syndrome concomitant with systemic lupus erythematosus. The patient underwent contrast-enhanced DECT, which revealed bilateral adrenal infarction. Laboratory tests revealed preserved adrenal function. On the iodine density images, the infarcted and noninfarcted areas in the adrenal glands were visually different. The volume of the non-infarcted area was 8.9 mL, which was 41% of the total adrenal volume. DECT may be a useful complementary tool for assessing the preservation of adrenal function.

Diagnostic Value of Carotid Plaque Assessment with AIS Based on Quantitative Parameters of Dual-Layer Detector Spectral CT.

Purpose: To investigate the quantitative assessment of carotid plaque by each parameter of dual-layer detector spectral CT and its diagnostic value in patients with acute cerebral infarction. Patients and Methods: Eighty-three patients with carotid atherosclerotic plaques who underwent spectral CT scanning were retrospectively included. Forty-two patients with acute ischaemic stroke (AIS) were included in the study group, and 41 patients without AIS were included in the control group. We compared the detection of carotid plaques in the two groups and the differences in the spectral quantitative parameters of the plaques in the two groups, and their diagnostic efficacy was obtained. Results: The detection rate of carotid plaques in the AIS group was higher than that in the non-AIS group (p<0.05); the carotid plaques in the AIS group mainly consisted of non-calcified plaques, while those in the non-AIS group mainly consisted of calcified plaques. The effective atomic number (Zeff), slope of the energy spectrum curve (λH), electron density (ED), and iodine-no-water value of the carotid plaques in the AIS group were lower than those in the non-AIS (p<0.05). For the differentiation of the carotid plaques in the AIS group from those in the non-AIS group, the area under the curve (AUC) of Zeff amounted to 0.637 (cut-off value: 11.865; sensitivity: 72.5%; specificity: 56.2%), the AUC of λH amounted to 0.628 (cut-off value: 19.56; sensitivity: 76.3%; specificity: 51.6%), and that for ED amounted to 0.624 (cut-off value: 110.45; sensitivity: 60.0%; specificity: 64.1%), AUC of iodine-no-water value amounted to 0.645 (cut-off value: 9.125; sensitivity: 61.3%; specificity: 65.6%). Conclusion: In summary, the quantitative parameters of dual-layer detector spectral CT can be used to assess plaque stability and have certain value in the diagnosis of AIS. The quantitative parameters can effectively differentiate carotid plaques in AIS and non-AIS patients.

Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma.

OBJECTIVE: To investigate the diagnostic value of dual-energy computed tomography (DECT) quantitative parameters in the identification of regional lymph node metastasis in pancreatic ductal adenocarcinoma (PDAC). METHODS: This retrospective diagnostic study assessed 145 patients with pathologically confirmed pancreatic ductal adenocarcinoma from August 2016-October 2020. Quantitative parameters for targeted lymph nodes were measured using DECT, and all parameters were compared between benign and metastatic lymph nodes to determine their diagnostic value. A logistic regression model was constructed; the receiver operator characteristics curve was plotted; the area under the curve (AUC) was calculated to evaluate the diagnostic efficacy of each energy DECT parameter; and the DeLong test was used to compare AUC differences. Model evaluation was used for correlation analysis of each DECT parameter. RESULTS: Statistical differences in benign and metastatic lymph nodes were found for several parameters. Venous phase iodine density had the highest diagnostic efficacy as a single parameter, with AUC 0.949 [95% confidence interval (CI):0.915-0.972, threshold: 3.95], sensitivity 79.80%, specificity 96.00%, and accuracy 87.44%. Regression models with multiple parameters had the highest diagnostic efficacy, with AUC 0.992 (95% CI: 0.967-0.999), sensitivity 95.96%, specificity 96%, and accuracy 94.97%, which was higher than that for a single DECT parameter, and the difference was statistically significant. CONCLUSION: Among all DECT parameters for regional lymph node metastasis in PDAC, venous phase iodine density has the highest diagnostic efficacy as a single parameter, which is convenient for use in clinical settings, whereas a multiparametric regression model has higher diagnostic value compared with the single-parameter model.

Prediction of pancreatic fibrosis by dual-energy CT-derived extracellular volume fraction: Comparison with MRI.

OBJECTIVES: To investigate the correlation between dual-energy CT (DECT) and MRI measurements of the extracellular volume fraction (ECV) and to assess the accuracy of both methods in predicting pancreatic fibrosis (PF). METHODS: We retrospectively analyzed 43 patients who underwent pancreatectomy and preoperative pancreatic DECT and MRI between November 2018 and May 2022. The ECV was calculated using the T1 relaxation time (for MR-ECV) or absolute enhancement (for DECT-ECV) at equilibrium phase (180 s after contrast injection in our study). Pearson coefficient and Bland-Altman analysis were used to compare the correlation between the two ECVs, Spearman correlations were used to investigate the association between imaging parameters and PF, Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the ECVs for advanced fibrosis (F2-F3), and multivariate logistic regression analysis was used to examine the relationship between PF and imaging parameters. RESULTS: There was a strong correlation between DECT- and MR-derived ECVs (r = 0.948; p < 0.001). The two ECVs were positively correlated with PF (DECT: r = 0.647, p < 0.001; MR: r = 0.614, p < 0.001), and the mean values were 0.34 ± 0.08 (range: 0.22-0.62) and 0.35 ± 0.09 (range: 0.24-0.66), respectively. The area under the operating characteristic curve (AUC) for subjects with advanced fibrosis diagnosed by ECV was 0.86 for DECT-ECV and 0.87 for MR-ECV. Multivariate logistic regression analysis showed that the DECT-ECV was an independent predictor of PF. CONCLUSIONS: The ECV could be an effective predictor of histological fibrosis, and DECT is equivalent to MRI for characterizing pancreatic ECV changes.

Crohn's disease inflammation severity assessment with iodine density from photon counting CT enterography: comparison with endoscopic histopathology.

PURPOSE: To determine optimal iodine density thresholds for active inflammation in CD patients with PCCT enterography and determine if iodine density can be used to stratify CD activity severity. METHODS: A retrospective PACS search identified patients with CD imaged with PCCT enterography from 4/11/2022 to 10/30/2022 and with clinical notes, endoscopic/surgical pathology and available source PCCT data for iodine density analysis. Two abdominal radiologists with expertise in CD each drew two region of interest measurements within the visibly most affected region of terminal or neoterminal ileum wall on commercially available system (SyngoVia). Radiologists were blinded to clinical information and pathologic findings. Disease activity and severity were recorded from the pathology report. Harvey-Bradshaw Index, medications, and laboratory values were recorded. Receiver operating characteristic (ROC) curves were utilized to determine the optimum iodine density threshold for active inflammation and mild versus moderate-to-severe inflammation. Intra- and inter-reader agreement was assessed by intra-class correlation coefficient (ICC). RESULTS: 23 CD patients (15 females; mean [SD] age: 52 [17] years) imaged with PCCT enterography were included. 15/23 had active inflammation: 9/15 mild, 4/15 moderate, and 2/15 severe active inflammation. The optimal iodine density threshold for active inflammation was 2.7 mg/mL, with 97% sensitivity, 100% specificity, and 98% accuracy (AUC = 1.00). The optimal iodine density threshold for distinguishing mild from moderate-to-severe inflammation was 3.4 mg/mL, with 83% sensitivity, 89% specificity, and 87% accuracy (AUC = 0.85). Intra-reader reliability (R1/R2) ICC was 0.81/0.86. Inter-reader reliability ICC was 0.94. CONCLUSION: Iodine density from PCCT enterography can distinguish mild from moderate-to-severe active inflammation.

Nomogram Based on Dual-Layer Spectral Detector CTA Parameter for the Prediction of Infarct Core in Patients with Acute Ischemic Stroke.

(1) Background: Acute ischemic stroke (AIS) is time-sensitive. The accurate identification of the infarct core and penumbra areas in AIS patients is an important basis for formulating treatment plans, and is the key to dual-layer spectral detector computed tomography angiography (DLCTA), a safer and more accurate diagnostic method for AIS that will replace computed tomography perfusion (CTP) in the future. Thus, this study aimed to investigate the value of DLCTA in differentiating infarct core from penumbra in patients with AIS to establish a nomogram combined with spectral computed tomography (CT) parameters for predicting the infarct core and performing multi-angle evaluation. (2) Methods: Data for 102 patients with AIS were retrospectively collected. All patients underwent DLCTA and CTP. The patients were divided into the non-infarct core group and the infarct core group, using CTP as the reference. Multivariate logistic regression analysis was used to screen predictors related to the infarct core and establish a nomogram model. The receiver operating characteristic (ROC) curve, the calibration curve, and decision curve analysis (DCA) were used to evaluate the predictive efficacy, accuracy, and clinical practicability of the model, respectively. (3) Results: Multivariate logistic analysis identified three independent predictors: iodine density (OR: 0.022, 95% CI: 0.003-0.170, p < 0.001), hypertension (OR: 7.179, 95% CI: 1.766-29.186, p = 0.006), and triglycerides (OR: 0.255, 95% CI: 0.109-0.594, p = 0.002). The AUC-ROC of the nomogram was 0.913. Calibration was good. Decision curve analysis was clinically useful. (4) Conclusions: The spectral CT parameters, specifically iodine density values, effectively differentiate between the infarct core and penumbra areas in patients with AIS. The nomogram, based on iodine density values, showed strong predictive power, discrimination, and clinical utility to accurately predict infarct core in AIS patients.

Evaluation of microcirculation in asymptomatic cerebral infarction with multi-parameter imaging of spectral CT.

OBJECTIVE: To investigate the role of spectral CT multiparametric imaging in the evaluation of cerebral microcirculatory perfusion. METHODS: The imaging data of 145 patients with asymptomatic cerebral infarction confirmed by MR were retrospectively analyzed, and all cases underwent head CTA and cranial CT perfusion imaging (CTP) on double-layer detector spectral CT. Single energy level images (MonoE45 keV), iodine density maps, and effective atomic number maps were reconstructed based on spectral CTA data, and CT values, iodine density values, and effective atomic number values were measured in the infarcted area, healthy control area, centrum semiovale and posterior limb of the internal capsule, respectively; perfusion values, such as cerebral blood volume (CBV) values, cerebral blood flow (CBF) values, time to peak (TTP) values, and mean passage time, were measured in the above-mentioned areas on CTP images. (TTP) values, and mean time to passage (MTT) values. CT values, iodine density values, effective atomic number values, and perfused CBV, CBF, TTP, and MTT values were compared between the infarcted area and the healthy side, the center of the hemianopia, and the posterior limb of the internal capsule. The role of spectral CT parameters and perfusion parameters in the evaluation of asymptomatic cerebral infarction was analyzed. RESULTS: CT values, iodine density values, and effective atomic number values were statistically different between the infarcted area and the healthy side; CT values, iodine density values, and effective atomic number values were not statistically different between the infarcted side and the healthy side of the hemispheric centrum and the posterior limb of the internal capsule; CBV and CBF were statistically different between the infarcted side and the healthy side, and MTT and TTP were not statistically different. There were statistically significant differences in TTP between the infarcted area and the healthy side of the hemiaxial center, and no statistically significant differences in CBV, CBF, and MTT. There were no statistical differences in CBV, CBF, TTP, and MTT in the inner capsule area. ROC curve analysis of spectral CT-related parameters and CT perfusion parameters for the diagnosis of asymptomatic cerebral infarction: area under the curve of MonoE 45Kv 0.71, area under the curve of iodine density values 0.76, area under the curve of effective atomic number values 0.74; area under the curve of CBV value 0.64, area under the curve of CBF value 0.61, area under the curve of MTT value 0.50, The area under the TTP curve was 0.52. The area under the ROC curve of the multivariate logistic regression model based on spectral parameters is 0.76, which is higher than that of the logistic regression model with perfusion parameters (P < 0.05). CONCLUSION: Spectral CT can better demonstrate small intracranial ischemic lesions, and iodine density values have a better evaluation of microcirculation in asymptomatic cerebral infarcts.

Clinical significance of dual-energy dual-layer CT parameters in differentiating small-sized gastrointestinal stromal tumors from leiomyomas.

PURPOSE: Small gastrointestinal stromal tumors (GISTs) can generally have nonspecific CT findings similar to those with benign submucosal tumors of the stomach. The purpose of this study was to explore the potential dual-layer dual-energy CT (dlDECT) parameters to differentiate small-sized (≤ 4 cm) GISTs from leiomyomas of the stomach. MATERIALS AND METHODS: This retrospective study included 26 SMTs ≤ 4 cm in diameter with pathological confirmation of either GIST (n = 17) or leiomyoma (n = 9) from May 2018 to January 2022. All patients received contrast-enhanced CT. The normalized iodine concentration (NIC) and spectral slope (λHU) were compared between GIST and leiomyoma. Receiver-operating characteristic (ROC) curves were plotted and the areas under the curve (AUCs) were calculated to estimate the diagnostic performance of these markers for differentiating GISTs from leiomyomas. RESULTS: NIC was significantly higher in GIST than in leiomyoma in the portal (P = 0.0019) and delayed phases (P = 0.0011). λHU was significantly higher in GIST than in leiomyoma in the portal (P = 0.0006) and delayed phases (P = 0.0009). AUC of the ROC curves using NIC to differentiate between GIST and leiomyoma were 0.875 and 0.895 in the portal and delayed phase; using λHU, they were 0.918 and 0.902 in the portal and delayed phase. CONCLUSION: dlDECT parameters including NIC and λHU show promise as indicators for differentiating small-sized GISTs from leiomyomas.

Crohn's disease phenotype analysis with iodine density from dual-energy CT enterography.

PURPOSE: To compare dual-source dual-energy CT enterography (dsDECTE) obtained iodine density (I) (mg/mL) and I normalized to the aorta (I%) with Crohn's disease (CD) phenotypes defined by the SAR-AGA small bowel CD consensus statement. METHODS: Fifty CD patients (31 male, 19 female; mean [SD] age: 50.4 [15.2] years) who underwent dsDECTE were retrospectively identified. Two abdominal radiologists assigned CD phenotypes: no active inflammation (group-2), active inflammation without (group-3) or with luminal narrowing (group-4), stricture with active inflammation (group-5), stricture without active inflammation (group-1), and penetrating disease (group-6). Semiautomatic prototype software was used to determine the median I and I% of CD-affected small bowel mucosa for each patient. The means of the I and I% medians were compared among 4 groups ("1 + 2", "3 + 4", "5", "6") using one-way ANOVA (significance level 0.05 for each outcome) for each outcome individually followed by Tukey's range test for pairwise comparisons with adjusted p-values (overall alpha = 0.05). RESULTS: Mean [SD] I was 2.14 [1.07] mg/mL for groups 1 + 2 (n = 16), 3.54 [1.71] mg/mL for groups 3 + 4 (n = 15), 5.5 [3.27] mg/mL for group- "5" (n = 9), and 3.36 [1.43] mg/mL for group-"6" (n = 10) (ANOVA p = .001; group "1 + 2" versus "5" adj-p = .0005). Mean [SD] I% was 21.2 [6.13]% for groups 1 + 2, 39.47 [9.71]% for groups 3 + 4, 40.98 [11.76]% for group-5, and 35.01 [7.58]% for group-6 (ANOVA p < .0001; groups "1 + 2" versus "3 + 4" adj-p < .0001, group "1 + 2" versus "5" adj-p < .0001, and groups "1 + 2" versus "6" adj-p = .002). CONCLUSION: Iodine density obtained from dsDECTE significantly differed among CD phenotypes defined by SAR-AGA, with I (mg/mL) increasing with phenotype severity and decreasing for penetrating disease. I and I% can be used to phenotype CD.

The diagnostic value of quantitative parameters on dual-layer detector-based spectral CT in identifying ischaemic stroke.

Objective: To investigate the diagnostic value of quantitative parameters of spectral computed tomography (CT) in ischaemic stroke areas. Methods: The medical records of 57 patients with acute ischaemic stroke (AIS) who underwent plain computed tomography (CT) head scans, CT angiography (CTA), and CT perfusion (CTP) were retrospectively reviewed. The ischaemic areas (including the core infarct area and penumbra) and non-ischaemic areas in each patient were quantitatively analyzed using F-STROKE software. Two independent readers measured the corresponding values of the spectroscopic quantitative parameters (effective atomic number [Zeff value], iodine density value, and iodine-no-water value) in the ischaemic area and contralateral normal area alone. The differences in spectroscopic quantitative parameters between the two groups were compared, and their diagnostic efficacy was obtained. Results: The Zeff, iodine-no-water value, and iodine density value of the ischaemic area all showed significant lower than those of non-ischaemic tissue (P < 0.001). For differentiating the ischaemic area from non-ischaemic tissue, the area under the curve (AUC) of the Zeff value reached 0.869 (cut-off value: 7.385; sensitivity: 93.0%; specificity: 70.2%), the AUC of the iodine density value reached 0.932 (cut-off value: 0.235; sensitivity: 91.2%; specificity: 82.5%), and the AUC of the iodine-no-water value reached 0.922 (cut-off value: 0.205; sensitivity: 96.5%; specificity: 78.9%). Conclusion: The study showed the spectral CT would be a potential novel rapid method for identifying AIS. The spectral CT quantitative parameters (Zeff, iodine density values, and iodine-no-water values) can effectively differentiate the ischaemic area from non-ischaemic tissue in stroke patients.

Role of iodine density value on dual-energy CT for detection of high tumor cell proportion region in lung cancer during CT-guided transthoracic biopsy.

OBJECTIVE: This study aimed to identify regions with at least 20% tumor cell content in lung cancer tumors by using spectral parameters from dual-layer spectral detector computed tomography (SDCT) to design the puncture path for transthoracic lung biopsy (TTLB). MATERIALS AND METHODS: This prospective study recruited patients with suspected lung cancer. Forty-one patients were enrolled to identify the high tumor cell proportion region (HTPR) and then another 15 patients to validate the accuracy of the HTPR. In each of the 41 patients, the suspected regions with high or low tumor cell proportions were punctured according to local iodine density (IoD) values for separate biopsies. The tumor cell proportions of 82 specimens were assessed and classified into high and low tumor cell proportions based on the threshold value of 20 %. The performance of spectral parameters was analyzed to distinguish the HTPR (tumor cell proportion ≥ 20 %) from the low tumor cell proportion region (LTPR). The cutoff value of optimal spectral parameter was used to prospectively guide the biopsy of the HTPR in 15 cases for further validation, and then the accuracy was calculated. RESULTS: The AUC values of spectral parameters were all higher than those of CTconventional in identifying the HTPR (all P < 0.05). The IoD with a cutoff value of 0.59 mg/mL in arterial phase (AP) yielded good performance (specificity: 97.10 %) in identifying the HTPR. It was applied to 15 cases for validation, and the accuracy rate was 100 %. CONCLUSION: Spectral CT parameters can be used to identify regions with at least 20% tumor cell content in lung cancer for biopsies.

Imaging biomarkers to stratify lymph node metastases in abdominal CT - Is radiomics superior to dual-energy material decomposition?

Purpose: To assess the potential of radiomic features in comparison to dual-energy CT (DECT) material decomposition to objectively stratify abdominal lymph node metastases. Materials and methods: In this retrospective study, we included 81 patients (m, 57; median age, 65 (interquartile range, 58.7-73.3) years) with either lymph node metastases (n = 36) or benign lymph nodes (n = 45) who underwent contrast-enhanced abdominal DECT between 06/2015-07/2019. All malignant lymph nodes were classified as unequivocal according to RECIST criteria and confirmed by histopathology, PET-CT or follow-up imaging. Three investigators segmented lymph nodes to extract DECT and radiomics features. Intra-class correlation analysis was applied to stratify a robust feature subset with further feature reduction by Pearson correlation analysis and LASSO. Independent training and testing datasets were applied on four different machine learning models. We calculated the performance metrics and permutation-based feature importance values to increase interpretability of the models. DeLong test was used to compare the top performing models. Results: Distance matrices and t-SNE plots revealed clearer clusters using a combination of DECT and radiomic features compared to DECT features only. Feature reduction by LASSO excluded all DECT features of the combined feature cohort. The top performing radiomic features model (AUC = 1.000; F1 = 1.000; precision = 1.000; Random Forest) was significantly superior to the top performing DECT features model (AUC = 0.942; F1 = 0.762; precision = 0.800; Stochastic Gradient Boosting) (DeLong < 0.001). Conclusion: Imaging biomarkers have the potential to stratify unequivocal lymph node metastases. Radiomics models were superior to DECT material decomposition and may serve as a support tool to facilitate stratification of abdominal lymph node metastases.

Diagnosis of pulmonary artery sarcoma and differential diagnosis of pulmonary embolism with double-detector spectral CT: a case report / 中国医师杂志

Objective:The differential diagnosis of pulmonary artery sarcoma (PAS) and pulmonary embolism (PE) by double-detector spectral computerized tomography (CT) provides a new way to improve the detection rate of PAS and reduce the misdiagnosis rate.Methods:In the way of retrospective study, the Philips Nebula Workstation (ISP) was used to reconstruct electron density map, iodine density map and spectral curve in the spectral CT plain scan and enhancement of the PAS patient. In the plain scan image, the low density areas of the ascending aorta and the right pulmonary trunk were selected to measure their electronic density values. In the chest enhancement image, the iodine density of PAS area and PE area were measured respectively, and the spectral curves of PSA area and PE area were compared.Results:The electron density of the ascending aorta and the right pulmonary trunk in the low density area of the PAS patient during the plain scan of spectral CT were 104.4% EDW (relative to the percentage of the electron density of water) and 102.2% EDW, respectively, which were lower than those in the normal ascending aorta area. The fusion image of mixed energy and electron density clearly reflected the scope of the lesion. The iodine density in PAS area was 1.89 mg/ml, and the iodine density in PE area was 0.03 mg/ml during the enhancement phase. The iodine uptake in PAS area was significantly higher than that in PE area. The slope of PAS region was 2.08, and the slope of PE region was -1.86. The slopes of the two spectral curves were inconsistent.Conclusions:The electronic density, iodine density and spectral curve measured by double-detector spectral CT may provide powerful imaging basis for the diagnosis of PAS and the differentiation of PAS from PE, which is helpful for the early diagnosis of the lesions, and also provide basis for the biopsy location of the mixed lesions of PAS and PE.

Value of Dual-Energy CT Perfusion Analysis in Patients with Acute Pancreatitis: Correlation and Discriminative Diagnostic Accuracy with Varying Disease Severity.

Background: This study investigates the correlation and discriminative diagnostic accuracy of dual-energy CT (DECT)-derived imaging biomarkers in patients with acute pancreatitis of varying severity. Methods: In this retrospective study, we included 51 patients with acute pancreatitis who had undergone portal-venous phase DECT of the abdomen. Three blinded readers independently performed region-of-interest measurements on DECT images in the inflammatory pancreatic parenchyma. The correlation between modified CT severity index (CTSI) and quantitative imaging parameters was investigated using Pearson correlation coefficient. We performed receiver operator curve (ROC) analysis to assess diagnostic accuracy of the quantitative image parameters for the differentiation between mild/moderate versus severe acute pancreatitis. The optimal discriminative cut-off value to diagnose severe acute pancreatitis was determined using the Youden index. Results: Moderate correlations were found between CTSI scores and iodine density (Pearson's correlation coefficient r = −0.65; p < 0.001), as well as attenuation (r = −0.55; p < 0.001) and normalized iodine uptake (r = −0.50; p < 0.001). ROC curve analysis revealed highest ability to differentiate mild/moderate from severe acute pancreatitis for iodine density (AUC = 0.86, 95% confidence interval 0.75 to 0.97). An optimal iodine density threshold of ≤1.63 mg/mL was found to indicate severe acute pancreatitis with a sensitivity of 81.3% and specificity of 77.1%. Conclusion: DECT-derived iodine density correlates with acute pancreatitis severity and may facilitate prediction of severe acute pancreatitis.

Iodine uptake of adrenal glands: A novel and reliable spectral dual-layer computed tomographic-derived biomarker for acute septic shock.

OBJECTIVES: Septic shock is a potentially fatal condition. This study aims to assess whether iodine uptake and iodine density of abdominal organs on dual-layer spectral detector computed tomography (SDCT) could serve as a new imaging biomarker for patients in septic shock. METHODS: Here, 95 patients who received contrast-enhanced abdominal CT examinations were included and separated into two groups: group A - septic shock; group B - no shock condition. Preselected abdominal (right and left adrenal gland, right and left kidney, infrarenal inferior vena cava (IVC), pancreas, spleen, and liver) localizations were independently evaluated by two radiologists, who measured iodine concentrations (mg/ml) and Hounsfield units (HU). RESULTS: In all, 1520 measurements of iodine concentrations in mg/ml and HU were performed, with 27 patients in group A and 68 in group B. Iodine concentrations in mg/ml and HU correlated significantly in all organs measured. The corresponding correlation coefficient (r) ranged from 0.809 (pancreas) to 0.963 (right kidney). Inter-rater reliability (IRR) was very good for mg/ml (κ = 0.8; p < 0.01) and good for HU (κ = 0.773; p < 0.01) measurements. The mean iodine concentration and HU of the adrenal glands in septic and nonseptic patients was 4.88 ± 1.16 mg/ml/153 ± 36 HU and 2.67 ± 1.07 mg/ml/112 ± 41 HU, respectively. Iodine concentrations in the adrenal glands were significantly higher in group A than in group B patients (p < 0.01). The other organs remained unaffected and no significant difference was observed between patients in group A and B. Patients in group A presented significantly more often with an iodine uptake of >3.5 mg/ml of one adrenal gland (sensitivity = 0.926, specificity = 0.849, AUC = 0.951) or/and a combined concentration of >7 mg/ml of both adrenal glands (sensitivity = 0.889, specificity = 0.836, AUC = 0.928). CONCLUSION: SDCT-derived iodine concentration of the adrenal glands could serve as a novel imaging biomarker for patients in acute septic shock. Our data suggest that an iodine uptake of >3.5 mg/ml of at least one adrenal gland or a combined iodine uptake of >7 mg/ml in both adrenal glands identifies patients in this condition.

A novel fast kilovoltage switching dual-energy computed tomography technique with deep learning: Utility for non-invasive assessments of liver fibrosis.

PURPOSE: To investigate whether the iodine density of liver parenchyma in the equilibrium phase and extracellular volume fraction (ECV) measured by deep learning-based spectral computed tomography (CT) can enable noninvasive liver fibrosis staging. METHOD: We retrospectively analyzed 63 patients who underwent dynamic CT using deep learning-based spectral CT before a hepatectomy or liver transplantation. The iodine densities of the liver parenchyma (I-liver) and abdominal aorta (I-aorta) were independently measured by two radiologists using iodine density images at the equilibrium phase. The iodine-density ratio (I-ratio: I-liver/I-aorta) and CT-ECV were calculated. Spearman's rank correlation analysis was used to evaluate the relationship between the I-ratio or CT-ECV and liver fibrosis stage, and receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performances of the I-ratio and CT-ECV. RESULTS: The I-ratio and CT-ECV showed significant positive correlations with liver fibrosis stage (ρ = 0.648, p < 0.0001 and ρ = 0.723, p < 0.0001, respectively). The areas under the ROC curve for the CT-ECV were 0.882 (F0 vs ≥ F1), 0.873 (≤F1 vs ≥ F2), 0.848 (≤F2 vs ≥ F3), and 0.891 (≤F3 vs F4). CONCLUSIONS: Deep learning-based spectral CT may be useful for noninvasive assessments of liver fibrosis.

Crohn's disease active inflammation assessment with iodine density from dual-energy CT enterography: comparison with endoscopy and conventional interpretation.

PURPOSE: To compare terminal ileum (TI) mucosal iodine density obtained at dual-energy CT enterography (DECTE) with conventional CT interpretation and endoscopy in patients with Crohn's disease (CD). MATERIALS AND METHODS: Twenty-three CD patients (14 men; mean[SD] age:48.1[16.7] years) with endoscopy within 30 days of DECTE were retrospectively identified. An inflammatory bowel disease gastroenterologist reviewed endoscopic images. Two radiologists qualitatively assessed the presence of active TI inflammation. Mean iodine density normalized to the aorta (I%), mean absolute iodine density (I), and iodine density standard deviation (ISD) from the distal 2 cm ileum (TI) mucosa obtained using semiautomatic prototype software were compared with endoscopic assessment using Mann Whitney tests. The optimal threshold I% and I were determined from receiver operating curves (ROC). Sensitivity and specificity of conventional interpretation and determined iodine thresholds were compared using McNemar's test. Inter-reader agreement was assessed using kappa. A p < 0.05 indicated statistical significance. RESULTS: Twelve (52.1%) patients had endoscopic active inflammation. I% was 37.9[13.3]% for patients with and 21.7[7.5]% for patients without endoscopic active inflammation (p = 0.001). The optimal ROC threshold 24.6% had 100% sensitivity and 81.8% specificity (AUC = 0.909, 95% CI 0.777-1). I was 2.44[0.73]mg/mL for patients with and 1.77[1.00]mg/mL for patients without active endoscopic inflammation (p = 0.0455). The optimal ROC threshold 1.78 mg/mL I had 91.7% sensitivity and 63.6% specificity (AUC = 0.75, 95% CI 0.532-0.968). ISD was similar for patients with and without endoscopic active inflammation (0.82[0.33]mg/mL and 0.77[0.28]mg/mL, respectively, p = 0.37). Conventional interpretation sensitivity and specificity (R1/R2) were 83.3%/91.7% and 72.7%/54.5%, respectively (all p > 0.05) with moderate inter-reader agreement (Κ = 0.542[95% CI 0.0202-0.088]). CONCLUSION: Mean normalized iodine density is highly sensitive and specific for endoscopic active inflammation. DECTE could be considered as a surrogate to endoscopy in CD patients. Despite trends towards improved sensitivity and specificity compared with conventional interpretation, future larger studies are needed.

Identification of novel prognostic factors focusing on clinical outcomes in patients with non-small cell lung cancer after stereotactic body radiotherapy.

Stereotactic body radiotherapy (SBRT) has attracted extensive attention as an effective treatment for patients with early-stage non-small cell lung cancer. However, the factors affecting prognosis after SBRT have not been fully elucidated. The aim of the present study was to investigate the prognostic factors associated with overall survival (OS) and local control (LC) after SBRT. Between March 2003 and March 2020, 497 patients with primary or oligo-metastatic lung cancer who underwent SBRT treatment were retrospectively reviewed. Univariate analysis was performed against various factors related to patient and tumor characteristics using Kaplan-Meier method. Furthermore, the factors with statistically significant differences identified via univariate analysis underwent a stratified Cox proportional hazard regression analysis. The median follow-up period for all patients was 26.17 months (range, 0.36-194.37), and the 5-year OS and LC rates were 66.3 and 86.0%, respectively. Multivariate analysis showed that surfactant protein-D (SP-D), tumor CT values (TCTV) and iodine density values (IDV) were independent prognostic factors for OS, and histology, TCTV and IDV were for LC. Although histology was not selected as a prognostic factor related to OS, it was indicated that patients with squamous cell carcinoma were associated with the SP-D high group compared with the SP-D normal group. In addition, TCTV was correlated to water density values, which tended to decrease with increasing IDV. From these findings, SP-D and TCTV were identified as potential new candidate prognostic factors after SBRT, and it is possible that combining SP-D and histology, and TCTV and IDV may improve the accuracy of prognostic prediction.

Improved characterization of focal airway lesions using spectral detector dual energy CT.

Clinicians should be aware of SDCT as a useful tool in the assessment of focal airway lesions. Spectral detector dual-energy computed tomography (SDCT) is a relatively novel imaging technology which has been utilized to aid in the diagnosis of many cardiothoracic conditions. Specifically, the availability of generated iodine density maps, virtual monoenergetic images, and effective atomic number maps allow for better evaluation of thoracic lesions compared to conventional CT. SDCT has previously been shown to be useful in the differentiation of benign vs malignant pulmonary nodules, pleural lesions, and lymph nodes. We describe 3 cases in which a patient presents with an indeterminate tracheal or bronchial lesion on conventional CT and subsequent SDCT reconstructions provided additional information which helped guide diagnosis or management of the patient. The goal is to help clinicians understand the benefit of SDCT in the detection and workup of airway lesions.