Value of CT spectral imaging in the differential diagnosis of thymoma and mediastinal lymphoma

Preoperative assessment of Ki-67 expression in hepatocellular carcinoma using a multi-parametric spectral CT approach

Background

Ki-67 is a pivotal biomarker for evaluating the prognosis of hepatocellular carcinoma (HCC). This study aimed to investigate the utility of qualitative and quantitative parameters derived from spectral computed tomography (CT) in assessing Ki-67 expression in HCC.

Methods

This prospective, single-center study included 89 patients (94 lesions) with pathologically confirmed HCC from February 2023 to February 2024. Participants underwent enhanced abdominal spectral CT scans within one week prior to surgery. The patients were divided into the following two groups based on the positive rate of Ki-67 (Ki-67%): a high-expression group (Ki-67 >20%, n=42); and a low-expression group (Ki-67 ≤20%, n=52). The spectral parameters assessed included CT values at 40 and 70 keV, iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), normalized iodine concentration (NIC) during the arterial phase (AP) and portal venous phase (PVP), and extracellular volume (ECV) fraction. Statistical significance of spectral CT parameters related to Ki-67 expression status was compared across different groups, and correlations between spectral CT parameters and Ki-67 expression levels were analyzed.

Results

Significant differences were observed between the low and high Ki-67 expression groups concerning age, alpha-fetoprotein (AFP) levels, and capsule integrity (P=0.002, P=0.013, and P=0.005, respectively). Notable differences were also found in intratumoral NIC-AP, NIC-PVP, AP slope, PVP slope, and ECV fraction (P=0.017, P=0.005, P=0.001, P<0.001, and P=0.001, respectively). Meanwhile, in the comparative analysis between the low and high expression group of Ki-67, there were no statistically significant differences in the peritumoral <1 cm NIC-AP and NIC-PVP, as well as transtumoral NIC-AP and NIC-PVP levels (P>0.05). Ki-67 expression in HCC exhibited negative correlations with intratumoral NIC-AP (r=-0.248; P=0.016), NIC-PVP (r=-0.291; P=0.004), AP slope (r=-0.330; P=0.001), PVP slope (r=-0.367; P<0.001), and ECV fraction (r=-0.339; P=0.001).

Conclusions

Qualitative and quantitative parameters from spectral CT provide valuable information for distinguishing between low and high Ki-67 expression in HCC.

CT radiomics and human-machine hybrid system for differentiating mediastinal lymphomas from thymic epithelial tumors

BACKGROUND

It is difficult for radiologists, especially junior radiologists with limited experience to make differential diagnoses between mediastinal lymphomas and thymic epithelial tumors (TETs) due to the overlapping imaging features. The purpose of this study was to develop and validate a CT-based clinico-radiomics model for differentiating lymphomas from TETs and to investigate whether a human-machine hybrid system can assist junior radiologists in improving their diagnostic performance.

METHODS

The patients who underwent contrast-enhanced chest CT and pathologically confirmed with lymphoma or TET at two centers from January 2011 to December 2019 and from January 2017 to December 2021 were retrospectively included and split as training/validation set and external test set, respectively. Clinical and radiomic signatures were pre-selected by elastic-net, and the models were established with the selected signatures using ensemble learning. Three radiologists independently reviewed CT images and assessed each case of the external test set with knowledge of the relevant clinical information. The diagnoses of reader 1, reader 2, and reader 3 were compared with those of the models in the external test set and further separately input to the model's ensemble process as a human-machine system to make final decisions in the external test set. The improvement of diagnostic performance of radiologists by human-machine system was evaluated by the area under the receiver operating characteristic curve and increase rate.

RESULTS

A total of 95 patients (51 with lymphomas and 44 with TETs) at Center 1 and 94 (52 with lymphomas and 42 with TETs) at Center 2 were enrolled and divided into training/validation sets and external test set, respectively. The diagnostic performance of the clinico-radiomics model has outperformed the junior radiologists and senior radiologist in AUC (clinico-radiomics model: 0.85 (0.76,0.92); reader 2: 0.70 (0.60,0.80); reader 3: 0.60 (0.49,0.71), reader 1: 0.76 (0.66,0.86), respectively) in the external test set. The human-machine hybrid system demonstrated significant increases in AUC (reader 1 + model: 0.87 (0.79,0.94), an increase of 14%; reader 2 + model: 0.86 (0.77,0.93), an increase of 23%; reader 3 + model: 0.84 (0.76,0.91), an increase of 40%), compared to the human performance alone.

CONCLUSIONS

The clinico-radiomics model outperformed three radiologists in differentiating lymphomas from TETs on CT. The use of the human-machine hybrid system significantly improved the performance of radiologists, especially junior radiologists. It provides a real-time decision tool to reduce bias and mistakes in radiologist diagnosis and enhances the diagnostic confidence of junior radiologists. This attempt may lead to more human-machine hybrid systems being explored in the diagnosis of different diseases to drive future clinical applications.

Assessment of solitary pulmonary nodules using dual-layer spectral detector computed tomography

We aim to quantitatively investigate the difference between benign and malignant solid pulmonary nodules that appeared on dual-energy spectral computed tomography, and assess the diagnostic accuracy of several parameters derived from computed tomography in differentiating malignant from benign pulmonary nodules. Between September 2021 and December 2022, spectral images of 71 patients (male:female = 44:27, mean age = 71.0 years) confirmed by pathology were retrospectively analyzed in the venous phase. Patients were classified into the malignant group and the benign group. The iodine concentration values of the nodules, normalized iodine concentration of the nodules to the neighboring vessels, virtual monochromatic images of 40 and 80 keV, and slope of the spectral curve were calculated and compared between the benign and malignant groups. Receiver operating characteristic curves and the area under the curve were performed to assess the diagnostic performance of the above parameters. Both virtual monochromatic images and iodine concentration maps prove to be highly useful in differentiating benign and malignant pulmonary nodules. The malignant pulmonary nodules have higher iodine density and slope of the spectral curve than the benign lesions. The combined model of iodine density and curve slope with an optimal cutoff of 0.39 (area under the curve = 0.82) yielded a sensitivity of 95% and a specificity of 63%. Contrast-enhanced dual-energy spectral computed tomography allows promising capability of distinguishing malignant from benign lesions, potential for avoiding unnecessary invasive procedure or surgery.

Nomogram combining pre-operative clinical characteristics and spectral CT parameters for predicting the WHO/ISUP pathological grading in clear cell renal cell carcinoma

PURPOSE

To develop a novel clinical-spectral-computed tomography (CT) nomogram incorporating clinical characteristics and spectral CT parameters for the preoperative prediction of the WHO/ISUP pathological grade in clear cell renal cell carcinoma (ccRCC).

METHODS

Seventy-three ccRCC patients who underwent spectral CT were included in this retrospective analysis from December 2020 to June 2023. The subjects were pathologically divided into low- and high-grade groups (WHO/ISUP 1/2, n = 52 and WHO/ISUP 3/4, n = 21, respectively). Information on clinical characteristics, conventional CT imaging features, and spectral CT parameters was collected. Multivariate logistic regression analyses were conducted to create a nomogram combing clinical data and image data for preoperatively predicting the pathological grade of ccRCC, and the area under the curve (AUC) was utilized to assess the predictive performance of the model.

RESULTS

Multivariate logistic regression analyses revealed that age, systemic immune-inflammation index (SII), and the slope of the spectrum curve in the cortex phase (CP-K) were independent predictors for predicting high-grade ccRCC. The clinical-spectral-CT model exhibited high evaluation efficacy, with an AUC of 0.933 (95% confidence interval [CI]: 0.878-0.998; sensitivity: 0.810; specificity: 0.923). The calibration curve revealed that the predicted probability of the clinical-spectral-CT nomogram could better fit the actual probability, with high calibration. The Hosmer-Lemeshow test showed that the model had a good fitness (χ2 = 5.574, p = 0.695).

CONCLUSION

The clinical-spectral-CT nomogram has the potential to predict WHO/ISUP grading of ccRCC preoperatively.

Contrast-enhanced CT-based radiomics differentiate anterior mediastinum lymphoma from thymoma without myasthenia gravis and calcification

AIM

To explore the value of a radiomics model based on enhanced computed tomography (CT) in differentiating anterior mediastinal lymphoma (AML) and thymoma without myasthenia gravis (MG) and calcification.

MATERIALS AND METHODS

The present study analysed patients who were diagnosed histologically with AML and thymoma in three independent institutions. All pre-treatment patients underwent enhanced CT. In the training group of patients from institutions 1 (the First Affiliated Hospital of Kunming Medical University) and 3 (the Yunnan Cancer Hospital), two radiologists independently analysed the enhanced CT images and performed manual segmentation of each tumour. Radiomics features were screened using interobserver interclass coefficient (ICC) analysis, feature correlation analysis, and L1 regularisation. The discriminative efficacy of the logistic regression model was evaluated using receiver operating characteristic (ROC) analysis. Validation group of patients from institution 2 (the Second Affiliated Hospital of Zhejiang University School of Medicine) was used to validate the proposed models.

RESULTS

A total of 114 patients were enrolled in this study and 1,743 radiomics features were extracted from the enhanced CT images. After feature screening, the remaining 37 robust radiomics features were used to construct the model. In the training group, the AUC of the model was 0.987 (95% confidence interval [CI]: 0.976-0.999), the sensitivity, specificity, and accuracy were 0.912, 0.946, and 0.924, respectively. In the validation group, the AUC of the model was 0.798 (95% CI: 0.683-0.913), the sensitivity, specificity, and accuracy were 0.760, 0.700, and 0.743, respectively.

CONCLUSION

The radiomics model created provided effective information to assist in the selection of clinical strategies, thus reducing unnecessary procedures in patients with AML and guiding direct surgery in patients with thymoma to avoid biopsy.

A diagnostic model based on 18F-FDG PET/CT parameters in improving the differential diagnosis of invasive thymic epithelial tumors and anterior mediastinal lymphomas

BACKGROUND

Accurately distinguishing between invasive thymic epithelial tumors (TETs) and anterior mediastinal lymphoma before surgery is crucial for subsequent treatment choices. But currently, the diagnosis of invasive TET is sometimes difficult to distinguish from anterior mediastinal lymphoma.

OBJECTIVE

To assess the application of fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography/computer tomography (PET/CT) in the differential diagnosis of TETs and anterior mediastinal lymphomas.

METHODS

18F-FDG PET/CT images of 133 invasive TETs and anterior mediastinal lymphomas patients were retrospectively analyzed. In particular, the tumor's longest diameter and maximum standardized uptake value (SUVmax) were evaluated. The SUVmax and longest diameter values of the two groups were analyzed by using the receiver operating characteristic (ROC) curve to determine the optimal threshold and diagnostic efficiency.

RESULTS

Age, myasthenia gravis, SUVmax and tumor longest diameter differed significantly between invasive TETs and anterior mediastinal lymphomas patients. The tumor location, calcification, relationship with adjacent vessels and distant metastasis differed significantly between the groups. The ROC analysis showed an AUC for SUVmax and tumor longest diameter of 0.841 and 0.737. Respectively, the cutoff values with the best diagnostic performance were 9.65 (sensitivity: 77.78%, specificity: 81.97%) and 6.65 (sensitivity: 80.56%, specificity: 62.30%) for SUVmax and tumor longest diameter. The diagnostic model of SUVmax, calcification, relationship with surrounding blood vessels, lymph node metastasis and lung metastasis in the highest AUC of 0.935 (sensitivity: 90.16%, specificity: 88.89%). In addition, we incorporated splenic involvement and metastatic sub-diaphragmatic lymph node into Model 2 as a new predictive model 3 for differential diagnosis and found a significant improvement in the diagnostic performance of Model 3.

CONCLUSION

The diagnostic model composed of 18F-FDG PET parameters is improving the differential diagnosis of invasive TETs and anterior mediastinal lymphomas.

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.

A nomogram for predicting postoperative complications based on tumor spectral CT parameters and visceral fat area in gastric cancer patients

PURPOSE

To construct a nomogram combining tumor spectral CT parameters and visceral fat area (VFA) to predict postoperative complications (POCs) in patients with gastric cancer (GC).

METHOD

This retrospective study included 101 GC patients who underwent preoperative abdominal spectral CT scan and were divided into two groups (37 with POCs and 64 without POCs) according to the Clavien-Dindo classification standard. Logistic regression was used to establish spectral, VFA, and combined models for predicting POCs. The combined prediction model was presented as a nomogram, and the diagnostic performance of each model was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

The AUCs of the VFA and spectral model were 0.71 (95% CI: 0.62-0.80) and 0.81 (95% CI: 0.72-0.88), respectively. VFA, the slope of spectral curve (λ) in venous phase (λ-VP) and tumor Hounsfield units on monoenergetic images 40 keV in VP (MonoE40keV-VP) were independent predictors of POCs in GC. The nomogram yielded an AUC of 0.89 (95% CI: 0.81-0.94). The combined model was superior to the VFA or spectral models by comparing their AUCs (P = 0.000 and 0.022).

CONCLUSIONS

The nomogram based on two tumor spectral parameters (λ-VP, MonoE40keV-VP) and VFA could serve as a convenient tool for predicting the POCs of GC patients.

Differentiating invasive thymic epithelial tumors from mediastinal lung cancer using spectral CT parameters

PURPOSE

The purpose of the study was to explore the importance of quantitative characteristics of spectral CT between invasive thymic epithelial tumors (TETs) and mediastinal lung cancer.

METHODS

We analyzed 54 patients (28 with invasive TETs and 26 with mediastinal lung cancer) who underwent spectral CT. During the arterial and venous phase, we measured the CT70keV, effective atomic number (Zeff), iodine concentration (IC), and water concentration (WC) and calculated the slope of the spectral curve (K100keV). We compared the clinical findings and spectral CT parameters of both groups and performed receiver operating characteristic analysis to evaluate the diagnostic efficacy and the optimal cutoff values of the spectral CT parameters.

RESULTS

During the AP and VP, the CT70keV, Zeff, IC, and K100keV were significantly higher in patients with invasive TETs than those in patients with mediastinal lung cancer (p < 0.05). WC was not statistically significantly different between the two groups (p > 0.05). ROC curve analysis revealed that all quantitative parameters combined in the AP and VP provided the best diagnostic performance in identifying invasive TETs from mediastinal lung cancer (AUC = 0.88, p = 0.002, sensitivity = 0.89 and specificity = 0.77). The cutoff values in the AP for CT70keV, IC, Zeff, and K100keV to differentiate invasive TETs from mediastinal lung cancer were 75.55, 15.86, 8.45, and 1.71, respectively. The cutoff values in the VP for CT70keV, IC, Zeff, and K100keV to differentiate them were 67.06, 15.74, 8.50, and 1.81, respectively.

CONCLUSIONS

Spectral CT imaging has potential value in the differential diagnosis of invasive TETs and mediastinal lung cancer.

Quantitative texture analysis based on dynamic contrast enhanced MRI for differential diagnosis between primary thymic lymphoma from thymic carcinoma

To evaluate the value of texture analysis based on dynamic contrast enhanced MRI (DCE-MRI) in the differential diagnosis of thymic carcinoma and thymic lymphoma. Sixty-nine patients with pathologically confirmed (thymic carcinoma, n = 32; thymic lymphoma, n = 37) were enrolled in this retrospective study. Ktrans, Kep and Ve maps were automatically generated, and texture features were extracted, including mean, median, 5th/95th percentile, skewness, kurtosis, diff-variance, diff-entropy, contrast and entropy. The differences in parameters between the two groups were compared and the diagnostic efficacy was calculated. The Ktrans-related significant features yielded an area under the curve (AUC) of 0.769 (sensitivity 90.6%, specificity 51.4%) for the differentiation between thymic carcinoma and thymic lymphoma. The Kep-related significant features yielded an AUC of 0.780 (sensitivity 87.5%, specificity 62.2%). The Ve-related significant features yielded an AUC of 0.807 (sensitivity 75.0%, specificity 78.4%). The combination of DCE-MRI textural features yielded an AUC of 0.962 (sensitivity 93.8%, specificity 89.2%). Five parameters were screened out, including age, Ktrans-entropy, Kep-entropy, Ve-entropy, and Ve-P95. The combination of these five parameters yielded the best discrimination efficiency (AUC of 0.943, 93.7% sensitivity, 81.1% specificity). Texture analysis of DCE-MRI may be helpful to distinguish thymic carcinoma from thymic lymphoma.

Value of CT spectral imaging in the differential diagnosis of sarcoidosis and Hodgkin's lymphoma based on mediastinal enlarged lymph node: A STARD compliant article

To investigate the imaging characteristics of sarcoidosis and Hodgkin's lymphoma based on mediastinal enlarged lymph node using spectral CT and evaluate whether the quantitative information can improve the differential diagnosis of these diseases. This retrospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Overall, 21 patients with sarcoidosis and 39 patients with Hodgkin's lymphoma were examined with CT spectral imaging during the arterial phase (AP) and venous phase (VP). The CT values on 40 to 140 keV monochromatic images and iodine (water) concentrations of enlarged lymph nodes were obtained in AP and VP. Iodine concentrations (ICs) were normalized to the iodine concentration in the aorta. The differences in normalized iodine concentrations (NICs) and hounsfield units (HU) curve slop (λHU) were calculated. Anatomical distribution of mediastinal lymph nodes and morphologic features were also compared. Receiver operating characteristic curves were generated to help establish threshold values for the parameters required for the significant differentiation of sarcoidosis from lymphomas. The CT values on 40 to 100 keV monochromatic images in AP and 40 to 50 keV in VP were higher in sarcoidosis than those in Hodgkin's lymphoma, the differences were statistically significant (P < .05); NICs during the AP and λHU during the AP (VP) in patients with sarcoidosis differed significantly from those in patients with Hodgkin's lymphoma. Receiver operating characteristic curves analysis showed that the monochromatic CT value on 40 keV in AP had the highest sensitivity (71.4%) and specificity (100%) in differentiating sarcoidosis from Hodgkin's lymphoma. The anatomic distribution, coalescence, calcification, compression, enhancement pattern and enhancement degree of the mediastinal enlarged lymph node differed significantly between the groups (P < .05). The combination of monochromatic CT value, NICs and λHU had higher sensitivity and specificity than did those of conventional qualitative CT image analysis during the combined phases. CT spectral imaging has promising potential for the diagnostic differentiation of Hodgkin's lymphomas and sarcoidosis. The monochromatic CT value, iodine content and λHU could be valuable parameters for differentiating Hodgkin's lymphomas and sarcoidosis based on mediastinal enlarged lymph node.

The value of diffusion-weighted and dynamic contrast-enhanced imaging in the diagnosis of thymic epithelial tumors

Background: Thymic epithelial tumors (TETs) are clinically the most frequently encountered neoplasm of the prevascular mediastinum in adults. The role of chest magnetic resonance (MR) imaging has been increasingly stressed thanks to its excellent contrast resolution, freedom from ionizing radiation, and capability to provide additional information regarding tumors' cellular structure and vascularity. Methods: This study aimed to establish the relationship between the MR findings and pathological classification of TETs, focusing on diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) imaging. This retrospective cross-sectional study included 44 TET patients who underwent chest MR scanning. The tumors were classified into three groups according to the WHO classification: low-risk thymoma (LRT), high-risk thymoma (HRT), and non-thymoma (NT). Along with morphological characteristics, the apparent diffusion coefficient (ADC) value, time-intensity curve (TIC) pattern, and time to peak enhancement (TTP) of the tumors were recorded and compared between the three groups. Results: A smooth contour and complete or almost complete capsule were suggestive of LRTs. The median ADC value of the 44 tumors was 0.95 × 10-3 mm2/sec. Among the three groups, LRTs had the highest ADC values, while NTs had the lowest. The differences between the ADC values of the three groups were statistically significant (p = 0.006). Using an ADC cutoff of 0.82 × 10-3 mm2/sec to differentiate between LRTs and tumors of the two remaining groups, the area under the curve was 0.775, sensitivity was 100%, specificity was 50%, and accuracy was 65.91%. The washout (type 3) TIC pattern was the most prevalent, accounting for 45.45% of the population; this pattern was also predominantly observed in LRTs (71.43%). Although the median TTP of LRTs was lower than that of HRTs or NTs, no statistically significant differences were found between the TTPs of the three groups (p = 0.170). Conclusions: MR is a good imaging modality to preoperatively assess TETs. Morphological features, ADC value, TIC pattern, and TTP are helpful in preoperatively predicting TET pathology.

Computed Tomography-Based Radiomics for Differentiation of Thymic Epithelial Tumors and Lymphomas in Anterior Mediastinum

Objective

To investigate the differential diagnostic performance of computed tomography (CT)-based radiomics in thymic epithelial tumors (TETs) and lymphomas in anterior mediastinum.

Methods

There were 149 patients with TETs and 93 patients with lymphomas enrolled. These patients were assigned to a training set (n = 171) and an external validation set (n = 71). Dedicated radiomics prototype software was used to segment lesions on preoperative chest enhanced CT images and extract features. The multivariable logistic regression algorithm was used to construct three models according to clinico-radiologic features, radiomics features, and combined features, respectively. Performance of the three models was compared by using the area under the receiver operating characteristic curves (AUCs). Decision curve analysis was used to evaluate clinical utility of the three models.

Results

For clinico-radiologic model, radiomics signature model, and combined model, the AUCs were 0.860, 0.965, 0.975 and 0.843, 0.961, 0.955 in the training cohort and the test cohort, respectively (all P<0.05). The accuracies of each model were 0.836, 0.895, 0.918 and 0.845, 0.901, 0.859 in the two cohorts, respectively (all P<0.05). Compared with the clinico-radiologic model, better diagnostic performances were found in the radiomics signature model and the combined model.

Conclusions

Radiomics signature model and combined model exhibit outstanding and comparable differential diagnostic performances between TETs and lymphomas. The CT-based radiomics analysis might serve as an effective tool for accurately differentiating TETs from lymphomas before treatment.

Dual-energy CT perfusion imaging for differentiating invasive thymomas, thymic carcinomas, and lymphomas in adults

AIM

To evaluate the role of dual-energy computed tomography perfusion (DECTP) imaging in differentiating invasive thymomas (ITs), thymic cancers (TCs), and lymphomas in adults.

MATERIALS AND METHODS

Ninety-five patients with solid masses in the prevascular mediastinum who underwent DECTP examinations were enrolled in this study. The perfusion parameters (blood flow, BF; blood volume, BV; mean transit time, MTT; permeability surface, PS) and spectral parameters (water concentration, WC; iodine concentration, IC; normalised iodine concentration, NIC; the slope of spectral radiodensity [Hounsfield units] curve, λ_HU) of the lesions were analysed.

RESULTS

There were no differences in the MTT or WC values among ITs, TCs, and lymphomas (all p>0.05). The IC, NIC, and λ_HU values in the optimal arterial and venous phases and PS values of TCs were higher than those of ITs and lymphomas (all p<0.05), and there were no differences between ITs and lymphomas (all p>0.05). The BF and BV values of lymphomas were lower than those of ITs and TCs (all p<0.05), and there were no differences between ITs and TCs (all p>0.05). The cut-off values for BF and BV used to differentiate lymphomas from ITs and TCs were 42.83 ml/min/100 g and 4.66 ml/100 g, respectively (area under the receiver operating characteristic curve: 0.847 and 0.839; sensitivity, 80.6% and 82.1%; specificity, 75% and 71.4%; accuracy, 78.9% and 81.1%).

CONCLUSIONS

The perfusion and spectral parameters of DECTP imaging help to identify ITs, TCs, and lymphomas, and BF and BV values help to differentiate lymphomas from ITs and TCs.

Usefulness of 18F-FDG PET/CT in treatment-naive patients with thymic squamous cell carcinoma

OBJECTIVE

Thymic squamous cell carcinoma (TSCC) is very rare. This study aims to investigate the clinical utility of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in treatment-naive patients with TSCC.

METHODS

The tumor metabolic parameters of 18F-FDG PET/CT, including maximum standard uptake value (SUVmax), metabolic tumor volume of primary lesion (MTV-P) and combination of primary lesion and metastases (MTV-C), and total lesion glycolysis of primary lesion (TLG-P) and combination of primary lesion and metastases (TLG-C) were collected. Age, sex, smoking, serum tumor markers, tumor size, Masaoka-Koga stage, TNM stage, contrast-enhanced CT scan, and tumor immunity were also reviewed. Moreover, progression-free survival (PFS) and overall survival (OS) of these patients were analyzed.

RESULTS

Forty-two treatment-naive patients with TSCC were enrolled in this study. All primary tumors were FDG-avid with the average SUVmax of 10.0 ± 4.5 (range, 1.5-20.4). Higher SUVmax, MTV-C, and TLG-C were observed in advanced Masaoka-Koga stage than early stage, and higher SUVmax was found in advanced TNM stage than early stage. Next, 36 out of 42 patients performed chest contrast-enhanced CT scan, which showed SUVmax associated with the enhancement degree of CT. Moreover, 27 out of 42 lesions were assessed tumor immunity, and the detective rates of PD-L1, PD-1, CD4, CD8, and Foxp3 were 59.3%, 37.0%, 59.3%, 100%, and 77.8%, respectively. Higher SUVmax was observed in lesions with lower CD4-positive tumor-infiltrating lymphocytes. Furthermore, 12- and 24-month PFS and OS rates were 62.0% vs 32.8% and 84.5% vs 68.9%, respectively. Multivariate Cox regression analysis showed that only MTV-C was an independent predictor of PFS.

CONCLUSION

18F-FDG PET/CT is useful in evaluating tumor staging, assessing CT enhancement degree, and detecting tumor immunity of TSCC before treatment. 18F-FDG PET/CT could also be a promising tool to provide prognostic information for treatment-naive patients with TSCC.

Advancement in Diagnostic Imaging of Thymic Tumors

Thymic tumors are rare neoplasms even if they are the most common primary neoplasm of the anterior mediastinum. In the era of advanced imaging modalities, such as functional MRI, dual-energy CT, perfusion CT and radiomics, it is possible to improve characterization of thymic epithelial tumors and other mediastinal tumors, assessment of tumor invasion into adjacent structures and detection of secondary lymph nodes and metastases. This review aims to illustrate the actual state of the art in diagnostic imaging of thymic lesions, describing imaging findings of thymoma and differential diagnosis.

Fat content quantification using dual-energy CT for differentiation of anterior mediastinal lesions from normal or hyperplastic thymus

BACKGROUND

Detection of fat content in thymic lesions is crucial to differentiate thymic hyperplasia from thymic tumors or other anterior mediastinal pathologies.

PURPOSE

To assess the feasibility of dual-energy CT (DECT) fat content quantification for the differentiation of anterior mediastinal lesions from benign thymic lesions and the normal spectrum of the thymus.

MATERIALS AND METHODS

Chest DECT images of 465 patients (median 61 years, 63% female) were visually evaluated by two radiologists and semiquantitatively scored based on the degree of fatty degeneration ranging from completely fatty (score 0) to predominantly soft-tissue (score 3), and anterior mediastinal mass (score 4). A subset of scans (n =134 including all cases with scores 2-4 and 20 randomly-selected cases from scores 0 and 1) underwent quantitative DECT analysis (fat fraction, iodine density, and conventional CT value). DECT values were compared across the semiquantitative scores.

RESULTS

Results of visual evaluation included 35 with predominantly solid thymus (score 3) and 15 with anterior mediastinal mass (score 4). The most common clinical diagnoses of the 15 masses (including 8 with pathologic confirmation) were metastases (n = 10) and lymphoma (n = 4). CT values in the abnormal thymus were significantly higher than those in score 3 (median: 69.7 HU versus 19.9 HU, P <0.001). There was no significant difference in iodine density values (median: 1.7 mg/ml versus 1 mg/ml, P = 0.09). However, the fat fraction value was significantly lower in the abnormal thymus (score 4) than in the predominantly soft-tissue attenuation thymuses (score 3) (median: 12.8% versus 38.7%, P <0.001). ROC curve analysis showed that fat fraction had an AUC of 0.96 (P <0.001), with a cutoff of <39.2% fat fraction yielding 100% sensitivity and 85% specificity.

CONCLUSION

DECT fat fraction measurements of the thymus may provide additional value in distinguishing anterior mediastinal lesions from benign thymus. Use of DECT may reduce the need for subsequent imaging evaluation.

Differentiating malignant and benign necrotic lung lesions using kVp-switching dual-energy spectral computed tomography

BACKGROUND

Necrotic pulmonary lesions manifest as relatively low-density internally on contrast-enhanced computed tomography (CT). However, using CT to differentiate malignant and benign necrotic pulmonary lesions is challenging, as these lesions have similar peripheral enhancement. With the introduction of dual-energy spectral CT (DESCT), more quantitative parameters can be obtained and the ability to differentiate material compositions has been highly promoted. This study investigated the use of kVp-switching DESCT in differentiating malignant from benign necrotic lung lesions.

METHODS

From October 2016 to February 2019, 40 patients with necrotic lung cancer (NLC) and 31 with necrotic pulmonary mass-like inflammatory lesion (NPMIL) were enrolled and underwent DESCT. The clinical characteristics of patients, CT morphological features, and DESCT quantitative parameters of lesions were compared between the two groups. Binary logistic regression analysis was performed to identify the independent prognostic factors differentiating NPMIL from NLC. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of single-parameter and multiparametric analyses.

RESULTS

Significant differences in age, C-reactive protein concentration, the slope of the spectral curve from 40 to 65 keV (K_40-65 keV) of necrosis in non-contrast-enhanced scanning (NCS), arterial phase (AP) and venous phase (VP), effective atomic number of necrosis in NCS, and iodine concentration (IC) of the solid component in VP were observed between groups (all p < 0.05). The aforementioned parameters had area under the ROC curve (AUC) values of 0.747, 0.691, 0.841, 0.641, 0.660, 0.828, and 0.754, respectively, for distinguishing between NLC and NPMIL. Multiparametric analysis showed that age, K_40-65 keV of necrosis in NCS, and IC of the solid component in VP were the most effective factors for differentiating NLC from NPMIL, with an AUC of 0.966 and percentage of correct class of 88.7%.

CONCLUSIONS

DESCT can differentiate malignant from benign necrotic lung lesions with a relatively high accuracy.

Revolution spectral CT for urinary stone with a single/mixed composition in vivo: a large sample analysis

PURPOSE

To analyze various compositions of urinary stones using revolution spectral CT (rapid kV switching dual-energy CT) in vivo.

METHODS

202 patients with urinary stones underwent spectral CT before surgery. Zeff peak, overall scope and CT values were detected. Moreover, water/iodine attenuating material images were obtained. Removed stones were subjected to infrared spectroscopy after surgery. The results of infrared spectroscopy were compared with CT.

RESULTS

28 stones (14.08%) with single composition, 165 stones with two mixed compositions (81.68%), and 9 stones with three mixed compositions (4.46%) were observed. When Zeff peaks of stones with single/mixed compositions were summarized together, 146 peaks of calcium oxalate monohydrate, 119 peaks of calcium oxalate dihydrate, 55 peaks of carbapatite, 38 peaks of urate, 16 peaks of struvite, and 11 peaks of brushite were totally observed. 93.8% of calcium oxalate monohydrate had Zeff peaks between 13.3 and 14.0. 91.6% of calcium oxalate dihydrate had peaks between 12.0 and 13.3. For carbapatite, 90.9% of stones had peaks from 14.0 to 15.0. A total of 94.8% of urate had peaks between 7.0 and 11.0. 93.8% of struvite had peaks between 11.0 and 13.0, and 90.9% of brushite had peaks between 12.0 and 14.0. Moreover, densities of urate, struvite and brushite were low density in iodine-based images and high-density in water-based images.

CONCLUSION

The in-vivo analysis of spectral CT in urinary stone revealed characteristics of different compositions, especially mixed compositions. An in-vivo predictive model may be constructed to distinguish stone compositions.

Multiparametric dual-energy CT for distinguishing nasopharyngeal carcinoma from nasopharyngeal lymphoma

OBJECTIVES

To determine the optimal kiloelectron volt of noise-optimized virtual monoenergetic images [VMI (+)] for visualization of nasopharyngeal carcinoma (NPC) and nasopharyngeal lymphoma (NPL), and to explore the clinical value of quantitative parameters derived from dual-energy computed tomography (DECT) for distinguishing the two entities.

MATERIALS AND METHODS

Eighty patients including 51 with NPC and 29 with NPL were enrolled. The VMIs (+) at 40-80 keV with an interval of 10 keV were reconstructed by contrast enhanced images. The overall image quality and demarcation of lesion margins, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed in VMIs (+) and polyenergetic images (PEI). Normalized iodine concentration (NIC), slope of the spectral Hounsfield unit curve (λ_HU) and effective atomic number (Z_eff) were calculated. Diagnostic performance was assessed by receiver operating characteristic (ROC) curve.

RESULTS

The 40 keV VMI (+) yielded highest overall image quality scores, demarcation of lesion margins scores, SNR and CNR. The values of NIC, λ_HU and Z_eff in NPL were higher than those in NPC (P <  0.001). Multivariate logistic regression model combining NIC, λ_HU and Z_eff showed the best performance for distinguishing NPC from NPL (AUC: 0.947, sensitivity: 93.1 % and specificity: 92.2 %).

CONCLUSION

VMI (+) reconstruction at 40 keV was optimal for visualizing NPC and NPL. Quantitative parameters derived from DECT were helpful for differentiating NPC from NPL.

Relationship Between Computed Tomography Imaging Features and Clinical Characteristics, Masaoka-Koga Stages, and World Health Organization Histological Classifications of Thymoma

Objectives: Computed tomography (CT) is an important technique for evaluating the condition and prognosis of patients with thymomas, and it provides guidance regarding treatment strategies. However, the correlation between CT imaging features, described using standard report terms, and clinical characteristics, Masaoka-Koga stages, and World Health Organization (WHO) classifications of patients with thymomas has not been described in detail nor has risk factor analysis been conducted. Methods: Overall, 159 patients with thymomas who underwent preoperative contrast-enhanced CT between September 2011 and December 2018 were retrospectively reviewed. We assessed the clinical information, CT imaging features, and pathological findings for each patient. A total of 89 patients were specially used to evaluate postoperative recurrence or metastasis between September 2011 and December 2015 to obtain an appropriate observation period. The relationship between CT imaging features and clinical characteristics, Masaoka-Koga stage, and WHO histological classification were analyzed, and related risk factors based on CT imaging features were identified. Results: CT imaging features did not significantly differ based on sex or age. Some imaging features demonstrated significant differences between the groups with and without related clinical characteristics. Contour (odds ratio [OR] = 3.711, P = 0.005), abutment ≥50% (OR = 4.277, P = 0.02), and adjacent lung abnormalities (OR = 3.916 P = 0.031) were independent risk factors for relapse or metastasis. Among all imaging features, there were significant differences between stage I/II and III/IV lesions in tumor size, calcification, infiltration of surrounding fat, vascular invasion, pleural nodules, elevated hemidiaphragm, and pulmonary nodules. Tumor size (odds ratio = 1.261, P = 0.014), vascular invasion (OR = 2.526, P = 0.023), pleural nodules (OR = 2.22, P = 0.048), and pulmonary nodules (OR = 3.106, P = 0.006) were identified as independent risk factors. Tumor size, contour, internal density, infiltration of surrounding fat, and pleural effusion significantly differed between low- and high-risk thymomas. Tumor size (OR = 1.183, P = 0.048), contour (OR = 2.288, P = 0.003), internal density (OR = 2.192, P = 0.024), and infiltration of surrounding fat (OR = 2.811 P = 0.005) were independent risk factors. Conclusions: Some CT imaging features demonstrated significant correlations with clinical characteristics, Masaoka-Koga clinical stages, and WHO histological classifications in patients with thymomas. Familiarity with CT features identified as independent risk factors for these related clinical characteristics can facilitate preoperative evaluation and treatment management for the patients with thymoma.