Comparison of spectral computed tomography imaging parameters between squamous cell carcinoma and adenocarcinoma at the gastroesophageal junction

2020 ◽  
pp. 1-9
Author(s):  
Yi-Chuan Ma ◽  
Shun-Hua Zhang ◽  
Zong-Yu Xie ◽  
Fei Guo ◽  
Ai-Qi Chen
Keyword(s):  
Computed Tomography ◽  
Squamous Cell Carcinoma ◽  
Roc Curve ◽  
Gastroesophageal Junction ◽  
Ct Imaging ◽  
Arterial Phase ◽  
Spectral Ct ◽  
Imaging Parameters ◽  
Spectral Computed Tomography ◽  
Venous Phase

OBJECTIVE: To compare the spectral computed tomography (CT) imaging parameters between squamous cell carcinoma (SCC) and adenocarcinoma (AC) at the gastroesophageal junction (GEJ). METHODS: A total of 80 patients were enrolled in this retrospective study. Among them, 35 were diagnosed with SCC (SCC group) and 45 were diagnosed with AC (AC group). All patients underwent an enhanced scan with spectral CT. The following CT imaging parameters were evaluated: iodine concentration (IC), water content (WC), effective atomic number (Eff-Z) and slope of the spectral HU curve (λHU) of lesions. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of spectral CT imaging parameters for diagnosis of SCC and AC. RESULTS: Patients with SCC had lower IC, Eff-Z, and λHU in arterial phase and venous phase compared with AC (p< 0.05). There were no significant differences in WC between the two groups. ROC curve analyses revealed that IC, Eff-Z, and λHU in arterial phase and venous phase were predictors for diagnosis of SCC and AC (AUC > 0.5). Moreover, the IC, Eff-Z and λHU in venous phase had better differential diagnostic performances than that in arterial phase. CONCLUSIONS: Spectral CT could be useful in the differential diagnosis of SCC and AC at the GEJ. Therefore, a routine spectral CT scan is recommended for patients with carcinoma of the GEJ.

scholarly journals Spectral Computed Tomography Findings of Peripheral Lung Adenocarcinoma and Peripheral Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Liangna Deng ◽  
Guojing Zhang ◽  
Xiaoqiang Lin ◽  
Mengyuan Jing ◽  
Tao Han ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Roc Curve ◽  
Water Concentration ◽  
Arterial Phase ◽  
Roc Curve Analysis ◽  
Contrast Enhanced Ct ◽  
Significant Difference

Abstract Background: To investigate the spectral computed tomography (CT) findings of peripheral adenocarcinoma (P-AC) and peripheral squamous cell carcinoma (P-SCC) in lung. Methods: In this retrospective study, A total of 273 patients (150 patients with P-AC and 123 patients with P-SCC) confirmed by surgery and pathology who underwent chest contrast enhanced CT scan with GSI mode, including arterial phase (AP) and venous phase (VP). During two phases, The CT40keV, CT70keV, CT100keV values, iodine concentration (IC), water concentration (WC), effective atomic number (Zeff) were measured and the slope of the spectral curve (K) was calculated. Differences between two groups were compared using two-sample t-test, Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was also calculated to calculate diagnostic efficacies.Results: There was significant difference in gender between the two groups (P < 0.05), No significant difference between other clinical features and symptoms (P > 0.05). For AP and VP, the CT40keV, CT70keV, K70keV, IC and Zeff of P-AC were significantly higher than those of P-SCC (P<0.05), but there was no significant difference in WC and CT100keV between the two groups. ROC curve analysis showed that the combination of all quantitative parameters in AP and VP had the best diagnostic performance, with the area under the curve, sensitivity and specificity of 92%, 88%, and 84%, respectively.Conclusions: Spectral CT can provide reference for the differentiation of P-AC and P-SCC.

scholarly journals Quantitative Analysis of Hypervascular Hepatic Metastases and Hepatocellular Carcinoma using Spectral CT Imaging

2019 ◽  
Author(s):  
Zhiqiang Yang ◽  
Xinyi Wang ◽  
Hao Shi
Keyword(s):  
Hepatocellular Carcinoma ◽  
Quantitative Analysis ◽  
Spectral Curve ◽  
Iodine Concentration ◽  
Ct Imaging ◽  
Arterial Phase ◽  
Spectral Ct ◽  
Portal Venous Phase ◽  
Significant Difference ◽  
Venous Phase

Abstract Objective The goal of this study is to evaluate the performance of spectral CT-based quantitative analysis in differential diagnosis of hypervascular hepatic metastasis (HVHM) and hepatocellular carcinoma (HCC). Methods Spectral CT scans were performed for 47 patients with hepatic malignant tumors, including 20 patients with HVHM and 27 patients with HCC, which generated the following sets of data: single energy images in the arterial phase; iodine and water maps; marginal areas of lesions that manifested apparent signal intensification; and energy spectral parameters of normal liver tissues and abdominal aorta. Subsequently, we calculated the normalized iodine concentrations (NIC), lesion-normal parenchyma iodine concentration ratio (LNR), iodine concentration difference (ICD) between the arterial phase and the venous phase, and the spectral curve slope. An independent samples t test and receiver operating characteristic (ROC) curve analysis were applied to examine these quantitative parameters. Results In the arterial phase, the HVHM and HCC groups displayed no differences in NIC, LNR, or spectral curve slope (P > 0.05). In the venous phase, the two groups displayed significant differences in NIC, LNR, and spectral curve slope; the NIC was 0.59 ± 0.08 for the HVHM group and 0.4 5 ± 0.10 for the HCC group; the LNR was 1.17 ± 0.22 and 0.92 ± 0.16, respectively; the spectral curve slope was 1.85 ± 0.49 and 1.18 ± 0.34, respectively. In addition, there was no significant difference in ICD between the HVHM group (0.54 ± 0.39 g/L) and HCC group (0.45 ± 0.39 g/L) (P > 0.05). Finally, there were no significant differences of water or iodine concentration between the arterial phase and venous phase (P > 0.05). Taken together, the spectral curve slope in the portal venous phase had the best performance in differentiating HVHM from HCC. Conclusions HVHM and HCC have apparent differences in spectral curve and concentrations of radiocontrast agents in the portal venous phase. Hence, spectral CT imaging provides a new multiparameter quantitative approach for differentiating HVHM and HCC.

scholarly journals Quantitative Analysis of Hypervascular Hepatic Metastases and Hepatocellular Carcinoma using Spectral CT Imaging

2020 ◽  
Author(s):  
Zhiqiang Yang ◽  
Xinyi Wang ◽  
Hao Shi
Keyword(s):  
Hepatocellular Carcinoma ◽  
Quantitative Analysis ◽  
Spectral Curve ◽  
Iodine Concentration ◽  
Ct Imaging ◽  
Arterial Phase ◽  
Spectral Ct ◽  
Portal Venous Phase ◽  
Significant Difference ◽  
Venous Phase

Abstract Background The goal of this study is to evaluate the performance of spectral CT-based quantitative analysis in differential diagnosis of hypervascular hepatic metastasis (HVHM) and hepatocellular carcinoma (HCC). Methods Spectral CT scans were performed for 47 patients with hepatic malignant tumors, including 20 patients with HVHM and 27 patients with HCC, which generated the following sets of data: single energy images in the arterial phase; iodine and water maps; marginal areas of lesions that manifested apparent signal intensification; and energy spectral parameters of normal liver tissues and abdominal aorta. Subsequently, we calculated the normalized iodine concentrations (NIC), lesion-normal parenchyma iodine concentration ratio (LNR), iodine concentration difference (ICD) between the arterial phase and the venous phase, and the spectral curve slope. An independent samples t test and receiver operating characteristic (ROC) curve analysis were applied to examine these quantitative parameters. Results In the arterial phase, the HVHM and HCC groups displayed no differences in NIC, LNR, or spectral curve slope ( P > 0.05). In the venous phase, the two groups displayed significant differences in NIC, LNR, and spectral curve slope; the NIC was 0.59 ± 0.08 for the HVHM group and 0.4 5 ± 0.10 for the HCC group; the LNR was 1.17 ± 0.22 and 0.92 ± 0.16, respectively; the spectral curve slope was 1.85 ± 0.49 and 1.18 ± 0.34, respectively. In addition, there was no significant difference in ICD between the HVHM group (0.54 ± 0.39 g/L) and HCC group (0.45 ± 0.39 g/L) ( P > 0.05). Finally, there were no significant differences of water or iodine concentration between the arterial phase and venous phase ( P > 0.05). Taken together, the spectral curve slope in the portal venous phase had the best performance in differentiating HVHM from HCC. Conclusions HVHM and HCC have apparent differences in spectral curve and concentrations of radiocontrast agents in the portal venous phase. Hence, spectral CT imaging provides a new multiparameter quantitative approach for differentiating HVHM and HCC.

scholarly journals Discrimination of mediastinal metastatic lymph nodes in NSCLC based on radiomic features in different phases of CT imaging

2019 ◽  
Author(s):  
Xue Sha ◽  
Guan Zhong Gong ◽  
Qing Tao Qiu ◽  
Jing Hao Duan ◽  
Deng Wang Li ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Multivariate Logistic Regression Analysis ◽  
Ct Images ◽  
Ct Imaging ◽  
Arterial Phase ◽  
Metastatic Lymph Nodes ◽  
Metastatic Lymph ◽  
Venous Phase

Abstract Background: We aimed to develop radiomic models based on different phases of computed tomography (CT) imaging and to investigate the efficacy of models for diagnosing mediastinal metastatic lymph nodes (LNs) in non-small cell lung cancer (NSCLC). Methods: We selected 231 mediastinal LNs confirmed by pathology results as the subjects, which were divided into training (n=163) and validation cohorts (n=68). The regions of interest (ROIs) were delineated on CT scans in the plain phase, arterial phase and venous phase, respectively. Radiomic features were extracted from the CT images in each phase. A least absolute shrinkage and selection operator (LASSO) algorithm was used to select features, and multivariate logistic regression analysis was used to build models. We constructed six models (orders 1-6) based on the radiomic features of the single- and dual-phase CT images. The performance of the radiomic model was evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV). Results: A total of 846 features were extracted from each ROI, and 10, 9, 5, 2, 2, and 9 features were chosen to develop models 1-6, respectively. All of the models showed excellent discrimination, with AUCs greater than 0.8. The plain CT radiomic model, model 1, yielded the highest AUC, specificity, accuracy and PPV, which were 0.926 and 0.925; 0.860 and 0.769; 0.871 and 0.882; and 0.906 and 0.870 in the training and validation sets, respectively. When the plain and venous phase CT radiomic features were combined with the arterial phase CT images, the sensitivity increased from 0.879 and 0.919 to 0.949 and 0979 and the NPV increased from 0.821 and 0.789 to 0.878 and 0.900 in the training group, respectively. Conclusions: All of the CT radiomic models based on different phases all showed high accuracy and precision for the diagnosis of LN metastasis (LNM) in NSCLC patients. When combined with arterial phase CT, the sensitivity and NPV of the model was be further improved.

scholarly journals Differentiation of mediastinal metastatic lymph nodes in NSCLC based on radiomic features of different phase CT imaging

2019 ◽  
Author(s):  
Xue Sha ◽  
Guan Zhong Gong ◽  
Qing Tao Qiu ◽  
Jing Hao Duan ◽  
Deng Wang Li ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Multivariate Logistic Regression Analysis ◽  
Ct Images ◽  
Ct Imaging ◽  
Arterial Phase ◽  
Metastatic Lymph Nodes ◽  
Metastatic Lymph ◽  
Venous Phase

Abstract Background To develop radiomic models based on different phases of computed tomography (CT) imaging and investigate the efficacy of models to diagnose mediastinal metastatic lymph nodes in non-small cell lung cancer (NSCLC).Methods We selected 231 mediastinal lymph nodes confirmed by pathology results as the subjects, which were divided into training (n=163) and validation cohorts (n=68). The regions of interest (ROIs) were delineated on CT scans of the plain phase, arterial phase and venous phase, respectively. Radiomic features were extracted from the CT images of each phase. Least absolute shrinkage and selection operator (LASSO) was used to select features, and multivariate logistic regression analysis was used to build models. We constructed six models (orders of 1-6) based on radiomic features of the single- and dual-phase CT images. The performance of the radiomic model was evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV).Results A total of 846 features were extracted from each ROI, and 10, 9, 5, 2, 2, and 9 features were chosen to develop models 1-6. All of the models showed superior differentiation, with AUCs greater than 0.8. The plain CT radiomic model, model 1, yielded the highest AUC, specificity, accuracy and PPV, which were 0.926 VS 0.925, 0.860 VS 0.769, 0.871 VS 0.882 and 0.906 VS 0.870 in the training and validation sets, respectively. When the plain and venous phase CT radiomic features were combined with the arterial phase CT images, the sensitivity increased from 0.879, 0.919 to 0.949, 0979 and the NPV increased from 0.821, 0.789 to 0.878, 0.900 in the training group, respectively.Conclusion CT radiomic models based on different phases all showed high accuracy and precision in the diagnosis of LNM in NSCLC patients. When combined with arterial phase CT, the sensitivity and NPV of the model can be further improved.

Interaction of quantitative 18 F-FDG-PET-CT imaging parameters and human papillomavirus status in oropharyngeal squamous cell carcinoma

Head & Neck ◽  
2015 ◽  
Vol 38 (4) ◽  
pp. 529-535 ◽  
Author(s):  
Charlotte S. Schouten ◽  
Sara Hakim ◽  
R. Boellaard ◽  
Elisabeth Bloemena ◽  
Patricia A. Doornaert ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Human Papillomavirus ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Fdg Pet ◽  
Ct Imaging ◽  
Oropharyngeal Squamous Cell Carcinoma ◽  
Imaging Parameters ◽  
Pet Ct ◽  
Fdg Pet Ct
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