Dual-layer spectral-detector CT for detecting liver steatosis by using proton density fat fraction as reference.

OBJECTIVES: To evaluate the diagnostic accuracy of liver dual-layer spectral-detector CT (SDCT) derived parameters of liver parenchyma for grading steatosis with reference to magnetic resonance imaging-based proton density fat fraction (MRI-PDFF). METHODS: Altogether, 320 consecutive subjects who underwent MRI-PDFF and liver SDCT examinations were recruited and prospectively enrolled from four Chinese hospital centers. Participants were classified into normal (n = 152), mild steatosis (n = 110), and moderate/severe(mod/sev) steatosis (n = 58) groups based on MRI-PDFF. SDCT liver parameters were evaluated using conventional polychromatic CT images (CTpoly), virtual mono-energetic images at 40 keV (CT40kev), the slope of the spectral attenuation curve (λ), the effective atomic number (Zeff), and liver to spleen attenuation ratio (L/S ratio). Linearity between SDCT liver parameters and MRI-PDFF was examined using Spearman correlation. Cutoff values for SDCT liver parameters in determining steatosis grades were identified using the area under the receiver-operating characteristic curve analyses. RESULTS: SDCT liver parameters demonstrated a strong correlation with PDFF, particularly Zeff (rs = -0.856; p < 0.001). Zeff achieved an area under the curve (AUC) of 0.930 for detecting the presence of steatosis with a sensitivity of 89.4%, a specificity of 82.4%, and an AUC of 0.983 for detecting mod/sev steatosis with a sensitivity of 93.1%, a specificity of 93.5%, the corresponding cutoff values were 7.12 and 6.94, respectively. Zeff also exhibited good diagnostic performance for liver steatosis grading in subgroups, independent of body mass index. CONCLUSION: SDCT liver parameters, particularly Zeff, exhibit excellent diagnostic accuracy for grading steatosis. CRITICAL RELEVANCE STATEMENT: Dual-layer SDCT parameter, Zeff, as a more convenient and accurate imaging biomarker may serve as an alternative indicator for MRI-based proton density fat fraction, exploring the stage and prognosis of liver steatosis, and even metabolic risk assessment. KEY POINTS: Liver biopsy is the standard for grading liver steatosis, but is limited by its invasive nature. The diagnostic performance of liver steatosis using SDCT-Zeff outperforms conventional CT parameters. SDCT-Zeff accurately and noninvasively assessed the grade of liver steatosis.

Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.

OBJECTIVE: To investigate the value of radiomics analysis of dual-layer spectral-detector computed tomography (DLSCT)-derived iodine maps for predicting tumor deposits (TDs) preoperatively in patients with colorectal cancer (CRC). MATERIALS AND METHODS: A total of 264 pathologically confirmed CRC patients (TDs + (n = 80); TDs - (n = 184)) who underwent preoperative DLSCT from two hospitals were retrospectively enrolled, and divided into training (n = 124), testing (n = 54), and external validation cohort (n = 86). Conventional CT features and iodine concentration (IC) were analyzed and measured. Radiomics features were derived from venous phase iodine maps from DLSCT. The least absolute shrinkage and selection operator (LASSO) was performed for feature selection. Finally, a support vector machine (SVM) algorithm was employed to develop clinical, radiomics, and combined models based on the most valuable clinical parameters and radiomics features. Area under receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis were used to evaluate the model's efficacy. RESULTS: The combined model incorporating the valuable clinical parameters and radiomics features demonstrated excellent performance in predicting TDs in CRC (AUCs of 0.926, 0.881, and 0.887 in the training, testing, and external validation cohorts, respectively), which outperformed the clinical model in the training cohort and external validation cohorts (AUC: 0.839 and 0.695; p: 0.003 and 0.014) and the radiomics model in two cohorts (AUC: 0.922 and 0.792; p: 0.014 and 0.035). CONCLUSION: Radiomics analysis of DLSCT-derived iodine maps showed excellent predictive efficiency for preoperatively diagnosing TDs in CRC, and could guide clinicians in making individualized treatment strategies. CLINICAL RELEVANCE STATEMENT: The radiomics model based on DLSCT iodine maps has the potential to aid in the accurate preoperative prediction of TDs in CRC patients, offering valuable guidance for clinical decision-making. KEY POINTS: Accurately predicting TDs in CRC patients preoperatively based on conventional CT features poses a challenge. The Radiomics model based on DLSCT iodine maps outperformed conventional CT in predicting TDs. The model combing DLSCT iodine maps radiomics features and conventional CT features performed excellently in predicting TDs.

Quantitative parameters of dual-layer spectral detector computed tomography for evaluating differentiation grade and lymphovascular and perineural invasion in colorectal adenocarcinoma.

PURPOSE: To explore the predictive value of dual-layer spectral detector CT (SDCT) quantitative parameters for determining differentiation grade, lymphovascular invasion (LVI) and perineural invasion (PNI) in colorectal adenocarcinoma (CRAC) patients. METHODS: A total of 106 eligible patients with CRAC were included in this study. Spectral parameters, including CT values at 40 and 100 keV, the effective atomic number (Zeff), the iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and the normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP), were compared according to the differentiation grade and the status of LVI and PNI. The diagnostic accuracies of the quantitative parameters with statistical significance were determined via receiver operating characteristic (ROC) curves, and the area under the curve (AUC) was calculated. RESULTS: There were 57 males and 49 females aged 43-86 (69 ± 10) years. The measured values of the spectral quantitative parameters of the CRAC were consistent within the observer (ICC range: 0.800-0.926). The 40 keV-AP, IC-AP, NIC-AP, 40 keV-VP, and IC-VP were significantly different among the different differentiation grades in the CRAC (P = 0.040, AUC = 0.673; P = 0.035, AUC = 0.684; P = 0.031, AUC = 0.639; P = 0.044, AUC = 0.663 and P = 0.035, AUC = 0.666, respectively). A statistically significant difference was observed in 40 keV-VP, 100 keV-VP, Zeff-VP, IC-VP, and λHU-VP between LVI-positive and LVI-negative patients (P = 0.003, AUC = 0.688; P = 0.015, AUC = 0.644; P = 0.001, AUC = 0.688; P = 0.001, AUC = 0.703 and P = 0.003, AUC = 0.677, respectively). There were no statistically significant differences in the values of the spectral parameters of the PNI state of patients with CRAC (P > 0.05). CONCLUSION: The quantitative parameters of SDCT had good diagnostic efficacy in differentiating between different grades and statuses of LVI in patients with CRAC; however, SDCT did not have value for identifying the state of PNI.

Feasibility of Reduced Iodine Loads for Vascular Assessment Prior to Transcatheter Aortic Valve Implantation (TAVI) Using Spectral Detector CT.

Reduced iodine loads for computed tomography (CT)-based vascular assessment prior to transcatheter aortic valve implantation (TAVI) may be feasible in conjunction with a spectral detector CT scanner. This prospective single-center study considered 100 consecutive patients clinically referred for pre-TAVI CT. They were examined on a dual-layer detector CT scanner to obtain an ECG-gated cardiac scan and a non-ECG-gated aortoiliofemoral scan. Either a standard contrast media (SCM) protocol using 80 mL Iohexol 350 mgI/mL (iodine load: 28 gI) or a body-mass-index adjusted reduced contrast media (RCM) protocol using 40-70 mL Iohexol 350 mgI/mL (iodine load: 14-24.5 gI) were employed. Conventional images and virtual monoenergetic images at 40-80 keV were reconstructed. A threshold of 250 HU was set for sufficient attenuation along the arterial access pathway. A qualitative assessment used a five-point Likert scale. Sufficient attenuation in the thoracic aorta was observed for all patients in both groups using conventional images. In the abdominal, iliac, and femoral segments, sufficient attenuation was observed for the majority of patients when using virtual monoenergetic images (SCM: 96-100% of patients, RCM: 88-94%) without statistical difference between both groups. Segments with attenuation measurements below the threshold remained qualitatively assessable as well. Likert scores were 'excellent' for virtual monoenergetic images 50 keV and 55 keV in both groups (RCM: 1.2-1.4, SCM: 1.2-1.3). With diagnostic image quality maintained, it can be concluded that reduced iodine loads of 14-24.5 gI are feasible for pre-TAVI vascular assessment on a spectral detector CT scanner.

A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.

BACKGROUND: This study aimed to evaluate the efficacy of radiomics signatures derived from polyenergetic images (PEIs) and virtual monoenergetic images (VMIs) obtained through dual-layer spectral detector CT (DLCT). Moreover, it sought to develop a clinical-radiomics nomogram based on DLCT for predicting cancer stage (early stage: stage I-II, advanced stage: stage III-IV) in pancreatic ductal adenocarcinoma (PDAC). METHODS: A total of 173 patients histopathologically diagnosed with PDAC and who underwent contrast-enhanced DLCT were enrolled in this study. Among them, 49 were in the early stage, and 124 were in the advanced stage. Patients were randomly categorized into training (n = 122) and test (n = 51) cohorts at a 7:3 ratio. Radiomics features were extracted from PEIs and 40-keV VMIs were reconstructed at both arterial and portal venous phases. Radiomics signatures were constructed based on both PEIs and 40-keV VMIs. A radiomics nomogram was developed by integrating the 40-keV VMI-based radiomics signature with selected clinical predictors. The performance of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves analysis (DCA). RESULTS: The PEI-based radiomics signature demonstrated satisfactory diagnostic efficacy, with the areas under the ROC curves (AUCs) of 0.92 in both the training and test cohorts. The optimal radiomics signature was based on 40-keV VMIs, with AUCs of 0.96 and 0.94 in the training and test cohorts. The nomogram, which integrated a 40-keV VMI-based radiomics signature with two clinical parameters (tumour diameter and normalized iodine density at the portal venous phase), demonstrated promising calibration and discrimination in both the training and test cohorts (0.97 and 0.91, respectively). DCA indicated that the clinical-radiomics nomogram provided the most significant clinical benefit. CONCLUSIONS: The radiomics signature derived from 40-keV VMI and the clinical-radiomics nomogram based on DLCT both exhibited exceptional performance in distinguishing early from advanced stages in PDAC, aiding clinical decision-making for patients with this condition.

Evaluation of peri-plaque pericoronary adipose tissue attenuation in coronary atherosclerosis using a dual-layer spectral detector CT.

Purpose: This study aimed to evaluate the differences between pericoronary adipose tissue (PCAT) attenuation at different measured locations in evaluating coronary atherosclerosis using spectral computed tomography (CT) and to explore valuable imaging indicators. Methods: A total of 330 patients with suspicious coronary atherosclerosis were enrolled and underwent coronary CT angiography with dual-layer spectral detector CT (SDCT). Proximal and peri-plaque fat attenuation index (FAI) of stenosis coronary arteries were measured using both conventional images (CIs) and virtual monoenergetic images (VMIs) ranging from 40 keV to 100 keV. The slopes of the spectral attenuation curve (λ) of proximal and peri-plaque PCAT at three different monoenergetic intervals were calculated. Additionally, peri-plaque FAI on CI and virtual non-contrast images, and effective atomic number were measured manually. Results: A total of 231 coronary arteries with plaques and lumen stenosis were finally enrolled. Peri-plaque FAICI and FAIVMI were significantly higher in severe stenosis than in mild and moderate stenosis (p < 0.05), while peri-plaque λ, proximal FAI, and proximal λ were not statistically different. Proximal FAI, peri-plaque FAI, and peri-plaque λ were significantly higher in low-density non-calcified plaque (LD-NCP) and non-calcified plaque (NCP) than in calcified plaque (p < 0.01). Peri-plaque FAI was the highest in the LD-NCP group, while proximal FAI was the highest in the NCP group. In severe stenosis and in LD-NCP, peri-plaque FAI was significantly higher than proximal FAI (p < 0.05). The manually measured parameters related to peri-plaque PCAT attenuation had a positive correlation with the results of peri-plaque FAI measured automatically. Conclusion: Peri-plaque PCAT has more value in assessing coronary atherosclerosis than proximal PCAT. Peri-plaque PCAT attenuation is expected to be used as a standard biomarker for evaluating plaque vulnerability and hemodynamic characteristics.

The value of preoperative diagnosis of colorectal adenocarcinoma pathological T staging based on dual-layer spectral-detector computed tomography extracellular volume fraction: a preliminary study.

PURPOSE: To investigate the value of preoperative diagnosis of colorectal adenocarcinoma (CRAC) pathological T staging based on dual-layer spectral-detector computed tomography (DLCT) extracellular volume fraction (ECV) of CRAC lesions. METHODS: We prospectively collected clinical and DLCT imaging data from 165 patients with CRAC who attended two hospitals from June 2022 to April 2023. The enrolled patients were divided into a training group (n = 110, from Hospital 1) and an external validation group (n = 55, from Hospital 2). Measuring and calculating DLCT parameters of lesions, including CT values of 40 and 100 keV virtual mono-energetic images (VMI), iodine concentration (IC) and effective atomic number (Eff-Z) in the arterial phases (AP) and venous phases (VP), and ECV in the delayed phase (DP). The differences in clinical characteristics and DLCT parameters were compared between different pT subgroups. The correlation between DLCT parameters and pT stages were evaluated by Spearman correlation analysis. A multifactorial binary logistic stepwise forward regression analysis was performed to obtain independent influences associated with pT stage. Receiver operating characteristic curves (ROCs) were used to assess diagnostic efficacy and were expressed as area under the curve (AUC). RESULTS: Each DLCT parameter was higher in pT3 stage tumors than in pT1-2 stage tumors (all P < 0.05). The highest correlation was found between ECV and pT stage (r = 0.637). ECV were independent influences associated with pT stage. ECV had excellent diagnostic efficacy for CRAC pT staging in both the training and external validation groups (AUC = 0.919 and 0.892). CONCLUSION: ECV based on DLCT measurement can be used for preoperative noninvasive diagnosis of CRAC pT staging with excellent diagnostic efficacy. It can provide a new imaging marker for the preoperative evaluation of CRAC and help clinicians formulate individualized treatment earlier. However, it needs to be confirmed with a larger sample size.

Quantitative parameters of dual-layer spectral detector computed tomography for evaluating Ki-67 and human epidermal growth factor receptor 2 expression in colorectal adenocarcinoma.

Background: Ki-67 and human epidermal growth factor receptor 2 (HER2) are key biomarkers in evaluating the prognosis of colorectal adenocarcinoma (CRAC). The purpose of this study was to investigate the value of quantitative parameters in dual-layer spectral detector computed tomography (SDCT) for evaluating the expression of Ki-67 and HER2 in CRAC. Methods: In this retrospective, cross-sectional study, 88 eligible patients with pathologically confirmed CRAC were selected from Taicang Hospital of Traditional Chinese Medicine between May 2021 and April 2023. The study participants underwent enhanced SDCT of the whole abdomen within 2 weeks before to surgery, did not receive antitumor therapy, and had complete immunohistochemical (IHC) indexes. Patients with nonadenocarcinoma pathologic types, poor quality of spectral CT images, or no complete immunohistochemistry results were excluded. Spectral parameters including CT values at 40 and 100 keV, effective atomic number, iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP) were analyzed for their value in distinguishing between the high and low expression of Ki-67 and HER2-positive and -negative status in CRAC. The statistical significance of the SDCT parameters between the different groups of Ki-67 expression and those of HER2 status was assessed with the Mann-Whitney test. Spearman correlation analysis was used to analyze the correlation between the SDCT parameters and the extent of Ki-67 expression and HER2 expression status. The receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated. Results: The SDCT parameters of CT values at 40 keV, effective atomic number, IC, and the λHU in the VP showed significant differences between the Ki-67 high- and low-expression groups in CRAC (P=0.035, P=0.041, P=0.036, and P=0.044, respectively), with AUCs of 0.639 [95% confidence interval (CI): 0.512-0.766], 0.634 (95% CI: 0.508-0.761), 0.638 (95% CI: 0.510-0.766), and 0.633 (95% CI: 0.504-0.762), respectively. The expression of CRAC Ki-67 was positively correlated with CT values at 40 keV (r=0.227; P=0.034), effective atomic number (r=0.219; P=0.040), IC (r=0.225; P=0.035), and the λHU in VP (r=0.216; P=0.043). SDCT parameter values showed no statistical difference between negative and positive expression in HER2 (all P values >0.05). There was no significant correlation between SDCT parameters and the expression of HER2 in CRAC (all P values >0.05). Conclusions: The quantitative parameters of SDCT in the VP provide valuable information for distinguishing between the low expression and high expression of Ki-67 in CRAC.

Performance of dual-layer spectrum CT virtual monoenergetic images to assess early rectal adenocarcinoma T-stage: comparison with MR.

OBJECTIVES: To evaluate the image quality and utility of virtual monoenergetic images (VMI) of dual-layer spectrum computed tomography (DLSCT) in assessing preoperative T-stage for early rectal adenocarcinoma (ERA). METHODS: This retrospective study included 67 ERA patients (mean age 62 ± 11.1 years) who underwent DLSCT and MR examination. VMI 40-200 keV and poly energetic image (PEI) were reconstructed. The image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and tumor contrast of different energy levels were calculated and compared, respectively. Two radiologists independently assess the image quality of the VMIs and PEI using 5-point scales. The diagnostic accuracies of DLSCT and HR-MRI for ERA T-staging were evaluated and compared. RESULTS: The maximum noise was observed at VMI 40 keV, and noise at VMI 40-200 keV in the arterial and venous phases showed no significant difference (all p > 0.05). The highest SNR and CNR were obtained at VMI 40 keV, significantly greater than other energy levels and PEI (all p < 0.05). Tumor contrast was more evident than PEI at 40-100 keV in the arterial phase and at 40 keV in the venous phase (all p < 0.05). When compared with PEI, VMI 40 keV yielded the highest scores for overall image quality, tumor visibility, and tumor margin delineation, especially in the venous phase (p < 0.05). The overall diagnostic accuracy of DLSCT and HR-MRI for T-stage was 65.67 and 71.64% and showed no significant difference (p > 0.05). CONCLUSIONS: VMI 40 keV improves image quality and accuracy in identifying lesions, providing better diagnostic information for ERA staging. CRITICAL RELEVANCE STATEMENT: Low-keV VMI from DLSCT can improve tumor staging accuracy for early rectal carcinoma, helping guide surgical intervention decisions, and has shed new light on the potential breakthroughs of assessing preoperative T-stage in RC. KEYPOINTS: • Compared with PEI, low-keV VIM derived from DLSCT, particularly at the 40 keV, significantly enhanced the objective and subjective image quality of ERA. • Using VMI 40 keV helped increase lesion detectability, leading to improved diagnostic accuracy for ERA. • Low-keV VMI from DLSCT has shed new light on the potential breakthroughs of assessing preoperative T-stage in RC.

Low Dose Iodinated Contrast Material and Radiation for Virtual Monochromatic Imaging in Craniocervical Dual-Layer Spectral Detector Computed Tomography Angiography: A Prospective and Randomized Study.

RATIONALE AND OBJECTIVES: To investigate the feasibility of virtual monochromatic imaging (VMI) of dual-layer spectral detector computed tomography (SDCT) to reduce iodinated contrast material (CM) and radiation dose in craniocervical computed tomography angiography (CTA). MATERIALS AND METHODS: A total of 280 consecutively selected patients performed craniocervical CTA with SDCT were prospectively selected and randomly divided into four groups (A, DoseRight index (DRI) 31, iopromide 370mgI/mL, volume 0.8 mL/kg; B, DRI 26, iopromide 370mgI/mL, volume 0.4 mL/kg; C, DRI 26, ioversol 320mgI/mL, volume 0.4 mL/kg; D, DRI 26, iohexol 300mgI/mL, volume 0.4 mL/kg). 50-70 kiloelectron volts (keV) VMIs in group B were reconstructed and compared to group A to select the optimal keV. Then, the optimal keV in groups B, C and D was reconstructed and compared. Objective image quality, including vascular attenuation, image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), was evaluated. Subjective image quality was assessed using a 5-point Likert scale. In addition, the effective dose (ED), iodine load and iodine delivery rate (IDR) were compared between groups A and D. RESULTS: 55 keV VMI was the optimal VMI in group B. The objective and subjective image quality of 55 keV VMI in group B were equal to or better than those of the CI in group A. The SNR, CNR and subjective image quality in group D were similar to those in group B (P > 0.05). The ED, iodine load and IDR of group D were reduced by 44%, 59% and 19%, respectively, when compared to those of group A. CONCLUSION: Low dose iodinated CM and radiation for 55 keV VMI in craniocervical CTA using SDCT could still provide equivalent or better image quality than the conventional scanning protocol.

Virtual non-contrast images of detector-based spectral computed tomography in dogs: a promising alternative to true non-contrast images in veterinary medicine.

Introduction: In veterinary medicine, abdominal computer tomographic (CT) examinations regularly require a minimum of two scans, with a native scan (true unenhanced, TUE) as a reference for the subsequent contrast-enhanced CT scan (CECT). Spectral detector CT (SDCT) offers the possibility to calculate virtual non-contrast (VNC) images from the post-contrast scan, but this has not yet been investigated in veterinary medicine. The purpose of this study was to assess the reliability of VNC images for abdominal organs in 44 dogs without abdominal pathologies by evaluating their quantitative and qualitative parameters compared to TUE images. We hypothesized that the subtraction of iodine is sufficient in the VNC series compared to the TUE series and that the image quality of the SDCT series is superior to conventional CT images. Methods: Corresponding attenuation values in the VNC and TUE series regarding the regions of interest (ROI) in different parenchymal organs and major vessels of the abdominal cavity were assessed by means of a two one-sided t-test (TOST) and Bland-Altman plots. Additionally, the signal-to-noise ratio (SNR) was calculated for each ROI in the different series. In the second step, two board-certified veterinary radiologists made a qualitative assessment of VNC images vs. TUE images in consensus by rating the iodine subtraction, image noise, and image quality of VNC images based on a specific 5-point Likert scale. Results: The difference in corresponding Hounsfield units (HUs) between TUE and VNC images was less than 10 HU in 78.67% of all ROIs. Regarding the limit of less than 10 HU, in the performed TOST, significant p-values of < 0.05 were reached for the liver, spleen, pancreas, and musculature, implying equivalence of both modalities. The quality of spectral base image (SBI) data was rated equivalent to calculated conventional images in the subjective assessment by reaching an average Likert scale score of 3.2 points. Discussion: VNC images calculated from SDCT data prove a valid alternative to conventional TUE images in the abdominal organs of canine patients without abdominal pathology. VNC offers the possibility to reduce time under general anesthesia and minimize radiation exposure. Future studies are needed to prove the application of this method in clinically diseased patients.

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.

Dual-layer spectral-detector CT for predicting microsatellite instability status and prognosis in locally advanced gastric cancer.

OBJECTIVE: To construct and validate a prediction model based on dual-layer detector spectral CT (DLCT) and clinico-radiologic features to predict the microsatellite instability (MSI) status of gastric cancer (GC) and to explore the relationship between the prediction results and patient prognosis. METHODS: A total of 264 GC patients who underwent preoperative DLCT examination were randomly allocated into the training set (n = 187) and validation set (n = 80). Clinico-radiologic features and DLCT parameters were used to build the clinical and DLCT model through multivariate logistic regression analysis. A combined DLCT parameter (CDLCT) was constructed to predict MSI. A combined prediction model was constructed using multivariate logistic regression analysis by integrating the significant clinico-radiologic features and CDLCT. The Kaplan-Meier survival analysis was used to explore the prognostic significant of the prediction results of the combined model. RESULTS: In this study, there were 70 (26.52%) MSI-high (MSI-H) GC patients. Tumor location and CT_N staging were independent risk factors for MSI-H. In the validation set, the area under the curve (AUC) of the clinical model and DLCT model for predicting MSI status was 0.721 and 0.837, respectively. The combined model achieved a high prediction efficacy in the validation set, with AUC, sensitivity, and specificity of 0.879, 78.95%, and 75.4%, respectively. Survival analysis demonstrated that the combined model could stratify GC patients according to recurrence-free survival (p = 0.010). CONCLUSION: The combined model provides an efficient tool for predicting the MSI status of GC noninvasively and tumor recurrence risk stratification after surgery. CRITICAL RELEVANCE STATEMENT: MSI is an important molecular subtype in gastric cancer (GC). But MSI can only be evaluated using biopsy or postoperative tumor tissues. Our study developed a combined model based on DLCT which could effectively predict MSI preoperatively. Our result also showed that the combined model could stratify patients according to recurrence-free survival. It may be valuable for clinicians in choosing appropriate treatment strategies to avoid tumor recurrence and predicting clinical prognosis in GC. KEY POINTS: • Tumor location and CT_N staging were independent predictors for MSI-H in GC. • Quantitative DLCT parameters showed potential in predicting MSI status in GC. • The combined model integrating clinico-radiologic features and CDLCT could improve the predictive performance. • The prediction results could stratify the risk of tumor recurrence after surgery.

Preoperative predicting invasiveness of lung adenocarcinoma manifesting as ground-glass nodules based on multimodal images of dual-layer spectral detector CT radiomics models.

OBJECTIVE: To construct and validate conventional and radiomics models based on dual-layer spectral CT radiomics for preoperative prediction of lung ground glass nodules (GGNs) invasiveness. MATERIALS AND METHODS: A retrospective study was conducted on 176 GGNs patients who underwent chest non-contrast enhancement scan on dual-layer spectral detector CT at our hospital within 2 weeks before surgery. Patients were randomized into the training cohort and testing cohort. Clinical features, imaging features and spectral quantitative parameters were collected to establish a conventional model. Radiomics models were established by extracting 1781 radiomics features form regions of interest of each spectral image [120 kVp poly energetic images (PI), 60 keV images and electron density maps], respectively. After selecting the optimal radiomic features and integrating multiple machine learning models, the conventional model, PI model, 60 keV model, electron density (ED) model and combined model based on multimodal spectral images were finally established. The performance of these models was assessed through the evaluation of discrimination, calibration, and clinical application. RESULTS: In the conventional model, age, vacuole sign, 60 keV and ED were independent risk factors of invasiveness. The combined model using logistic regression-least absolute shrinkage and selection operator classifiers was the optimal model with a higher area under the curve of the training (0.961, 95% confidence interval, CI: 0.932-0.991) and testing set (0.944, 0.890-0.999). CONCLUSION: The combined models are helpful to predict the invasiveness of GGNs before surgery and guide the individualized treatment of patients.

Diagnosis of benign and malignant thyroid nodules by a dual-layer spectral detector CT-based nomogram.

Introduction: Preoperative diagnosis of benign and malignant thyroid nodules is crucial for appropriate clinical treatment and individual patient management. In this study, a double-layer spectral detector computed tomography (DLCT)-based nomogram for the preoperative classification of benign and malignant thyroid nodules was developed and tested. Methods: A total of 405 patients with pathological findings of thyroid nodules who underwent DLCT preoperatively were retrospectively recruited. They were randomized into a training cohort (n=283) and a test cohort (n=122). Information on clinical features, qualitative imaging features and quantitative DLCT parameters was collected. Univariate and multifactorial logistic regression analyses were used to screen independent predictors of benign and malignant nodules. A nomogram model based on the independent predictors was developed to make individualized predictions of benign and malignant thyroid nodules. Model performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis(DCA). Results: Standardized iodine concentration in the arterial phase, the slope of the spectral hounsfield unit(HU) curves in the arterial phase, and cystic degeneration were identified as independent predictors of benign and malignant thyroid nodules. After combining these three metrics, the proposed nomogram was diagnostically effective, with AUC values of 0.880 for the training cohort and 0.884 for the test cohort. The nomogram showed a better fit (all p > 0.05 by Hosmer-Lemeshow test) and provided a greater net benefit than the simple standard strategy within a large range of threshold probabilities in both cohorts. Discussion: The DLCT-based nomogram has great potential for the preoperative prediction of benign and malignant thyroid nodules. This nomogram can be used as a simple, noninvasive, and effective tool for the individualized risk assessment of benign and malignant thyroid nodules, helping clinicians make appropriate treatment decisions.

Added value of spectral parameters in diagnosing metastatic lymph nodes of pT1-2 rectal cancer.

PURPOSE: To investigate the added value of spectral parameters derived from dual-layer spectral detector CT (SDCT) in diagnosing metastatic lymph nodes (LNs) of pT1-2 (stage 1-2 determined by pathology) rectal cancer. METHODS: A total of 80 LNs (57 non-metastatic LNs and 23 metastatic LNs) from 42 patients with pT1-T2 rectal cancer were retrospectively analyzed. The short-axis diameter of LNs was measured, then its border and enhancement homogeneity were evaluated. All spectral parameters, including iodine concentration (IC), effective atomic number (Zeff), normalized IC (nIC), normalized Zeff (nZeff), and slope of the attenuation curve (λ), were measured or calculated. The chi-square test, Fisher's exact test, independent-samples t-test, or Mann-Whitney U test was used to compare the differences of each parameter between the non-metastatic group and the metastatic group. Multivariable logistic regression analyses were used to determine the independent factors for predicting LN metastasis. Diagnostic performances were assessed by ROC curve analysis and compared with the DeLong test. RESULTS: The short-axis diameter, border, enhancement homogeneity, and each spectral parameter of LNs showed significant differences between the two groups (P < 0.05). The nZeff and short-axis diameter were independent predictors of metastatic LNs (P < 0.05), with areas under the curve (AUC) of 0.870 and 0.772, sensitivity of 82.5% and 73.9%, and specificity of 82.6% and 78.9%. After combining nZeff and the short-axis diameter, the AUC (0.966) was the highest with sensitivity of 100% and specificity of 87.7%. CONCLUSION: The spectral parameters derived from SDCT might help us to improve the diagnostic accuracy of metastatic LNs in patients with pT1-2 rectal cancer, the highest diagnostic performance can be achieved after combining nZeff with the short-axis diameter of LNs.

Prediction of Microvascular Invasion in Solitary AFP-Negative Hepatocellular Carcinoma ≤ 5 cm Using a Combination of Imaging Features and Quantitative Dual-Layer Spectral-Detector CT Parameters.

RATIONALE AND OBJECTIVES: AFP-negative hepatocellular carcinoma (AFPN-HCC) within 5 cm is a special subgroup of HCC. This study aimed to investigate the value of dual-layer spectral-detector CT (DLCT) and construct a scoring model based on imaging features as well as DLCT for predicting microvascular invasion (MVI) in AFPN-HCC within 5 cm. METHODS: This retrospective study enrolled 104 HCC patients who underwent multiphase contrast-enhanced DLCT studies preoperatively. Combined radiological features (CR) and combined DLCT quantitative parameter (CDLCT) were constructed to predict MVI. Multivariable logistic regression was applied to identify potential predictors of MVI. Based on the coefficient of the regression model, a scoring model was developed. The predictive efficacy was assessed through ROC analysis. RESULTS: Microvascular invasion (MVI) was found in 28 (26.9%) AFPN-HCC patients. Among single parameters, the effective atomic number in arterial phase demonstrated the best predictive efficiency for MVI with an area under the curve (AUC) of 0.792. CR and CDLCT showed predictive performance with AUCs of 0.848 and 0.849, respectively. A risk score (RS) was calculated using the independent predictors of MVI as follows: RS = 2 × (mosaic architecture) + 2 × (corona enhancement) + 2 × (incomplete tumor capsule) + 2 × (2-trait predictor of venous invasion [TTPVI]) + 3 × (CDLCT > -1.229). Delong's test demonstrated this scoring system could significantly improve the AUC to 0.929 compared with CR (p = 0.016) and CDLCT (p = 0.034). CONCLUSION: The scoring model combining radiological features with DLCT provides a promising tool for predicting MVI in solitary AFPN-HCC within 5 cm preoperatively.

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 (AUC65keV-AP = 0.92, AUC65keV-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 Zeff-AP was significantly superior to conventional model in the discrimination of SPSNs.

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

Objectives: To evaluate the usefulness of spectral detector CT (SDCT)-derived pulmonary perfusion maps and pulmonary parenchyma characteristics for the semiautomated classification of pulmonary hypertension (PH). Methods: A total of 162 consecutive patients with right heart catheter (RHC)-proven PH of different aetiologies as defined by the current ESC/ERS guidelines who underwent CT pulmonary angiography (CTPA) on SDCT and 20 patients with an invasive rule-out of PH were included in this retrospective study. Semiautomatic lung segmentation into normal and malperfused areas based on iodine density (ID) as well as automatic, virtual non-contrast-based emphysema quantification were performed. Corresponding volumes, histogram features and the ID SkewnessPerfDef-Emphysema-Index (δ-index) accounting for the ratio of ID distribution in malperfused lung areas and the proportion of emphysematous lung parenchyma were computed and compared between groups. Results: Patients with PH showed a significantly greater extent of malperfused lung areas as well as stronger and more homogenous perfusion defects. In group 3 and 4 patients, ID skewness revealed a significantly more homogenous ID distribution in perfusion defects than in all other subgroups. The δ-index allowed for further subclassification of subgroups 3 and 4 (p < 0.001), identifying patients with chronic thromboembolic PH (CTEPH, subgroup 4) with high accuracy (AUC: 0.92, 95%-CI, 0.85-0.99). Conclusion: Abnormal pulmonary perfusion in PH can be detected and quantified by semiautomated SDCT-based pulmonary perfusion maps. ID skewness in malperfused lung areas, and the δ-index allow for a classification of PH subgroups, identifying groups 3 and 4 patients with high accuracy, independent of reader expertise.

Dual-layer spectral detector CT for contrast agent concentration, dose and injection rate reduction: Utility in imaging of the superior mesenteric artery.

PURPOSE: To investigate the feasibility of contrast agent and injection rate reduction for dual-layer spectral detector computed tomography (SDCT) imaging of the superior mesenteric artery (SMA) using virtual monochromatic image (VMI). METHODS: A total of 102 patients who underwent abdominal arterial phase-enhanced SDCT examination due to suspected abdominal diseases were prospectively selected and divided into control group, low concentration/dose groups (groups 370-0.7, 300-1.0, and 300-0.9) and low injection rate groups (groups 2-370 and 2-350). Compared with the control group, low concentration/dose groups and low injection rate groups lowered the concentration/dose or injection rate of the contrast agent to varying degrees. The raw data obtained in each group were reconstructed using hybrid-iterative reconstruction and projection spatial-spectral reconstruction algorithm. The image quality of the SMA in conventional images (CI) and in VMIs40-140 kiloelectron volt (keV) (interval: 10 keV) during the arterial phase was analyzed. Multiplanar reformation images and volume rendering images of the SMA were reconstructed. Image quality objective evaluation indexes included the CT values, contrast-to-noise ratio, signal-to-noise ratio, and diameter of the SMA. The diameter of the SMA was determined by the CT values profile curve and its full width at half maximum. Two doctors independently evaluated the subjective image quality of multiplanar reformation coronal images and volume rendering images according to a 5-point scale. Repeated analysis of variance and Friedman test were used to compare the differences in the objective evaluation indexes and subjective scores between VMIs and CI in the same group. The Dunnett's t-test or Dunnett's T3 test and Kruskal-Wallis H-test were used to compare the differences in the objective evaluation indexes and subjective scores between the experimental and control groups. RESULTS: VMIs of the SMA in each group had the best image quality at 60 keV, and VMI60 keV in each group were better than their respective CI to varying degrees. Although the objective (CT values, contrast-to-noise ratio, and signal-to-noise ratio) and subjective (subjective scores) indexes of CI in the low concentration/dose groups and low injection rate groups were lower than those of CI in the control group to varying degrees, these indexes of VMI60 keV in the low concentration/dose groups and group 2-370 were equal to or even better than the CI in the control group. CONCLUSIONS: VMI60 keV using SDCT could effectively reduce the contrast agent load while providing equivalent or better SMA image quality compared with CI obtained using a conventional contrast agent protocol. When the injection rate was lowered to 2.0 ml/s for a high-concentration contrast agent (370 mgI/ml), the SMA image quality at VMI60 keV was comparable with that of the CI in the control group.