Role of endoscopic ultrasound-guided fine needle aspiration in the diagnosis of mass lesions

Han, Chaoqun; Lin, Rong; Zhang, Qin; Li, Jun; Zhang, Ding; Hou, Xiaohua

doi:10.3892/etm.2016.3433

Cited by 12 publications

(8 citation statements)

References 37 publications

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“…The combined model of enhanced CT images yielded an optimal AUC in both training and test datasets (training dataset: 0.941, test dataset: 0.938). Invasive procedures such as endoscopic biopsy of the mediastinal mass are dangerous, because these masses are near the heart and mediastinal great vessels [ 22 , 23 ]. Thus, a non-invasive biomarker that can be obtained preoperatively to diagnose anterior mediastinal cysts from type B1 and B2 thymomas will be valuable in clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Can computed tomography-based radiomics potentially discriminate between anterior mediastinal cysts and type B1 and B2 thymomas?

Liu

Pang³

et al. 2020

BioMed Eng OnLine

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Background Anterior mediastinal cysts (AMC) are often misdiagnosed as thymomas and undergo surgical resection, which caused unnecessary treatment and medical resource waste. The purpose of this study is to explore potential possibility of computed tomography (CT)-based radiomics for the diagnosis of AMC and type B1 and B2 thymomas. Methods A group of 188 patients with pathologically confirmed AMC (106 cases misdiagnosed as thymomas in CT) and thymomas (82 cases) and underwent routine chest CT from January 2010 to December 2018 were retrospectively analyzed. The lesions were manually delineated using ITK-SNAP software, and radiomics features were performed using the artificial intelligence kit (AK) software. A total of 180 tumour texture features were extracted from enhanced CT and unenhanced CT, respectively. The general test, correlation analysis, and LASSO were used to features selection and then the radiomics signature (radscore) was obtained. The combined model including radscore and independent clinical factors was developed. The model performances were evaluated on discrimination, calibration curve. Results Two radscore models were constructed from the unenhanced and enhanced phases based on the selected four and three features, respectively. The AUC, sensitivity, and specificity of the enhanced radscore model were 0.928, 89.3%, and 83.8% in the training dataset and 0.899, 84.6%, and 87.5% in the test dataset (higher than the unenhanced radscore model). The combined model of enhanced CT including radiomics features and independent clinical factors yielded an AUC, sensitivity and specificity of 0.941, 82.1%, and 94.6% in the training dataset and 0.938, 92.3%, and 87.5% in the test dataset (higher than the unenhanced combined model and enhanced radscore model). Conclusions The study suggested the possibility that the combined model in enhanced CT provided a potential tool to facilitate the differential diagnosis of AMC and type B1 and B2 thymomas.

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Section: Discussionmentioning

confidence: 99%

Can computed tomography-based radiomics potentially discriminate between anterior mediastinal cysts and type B1 and B2 thymomas?

Liu

Pang³

et al. 2020

BioMed Eng OnLine

View full text Add to dashboard Cite

show abstract

“…The combined model of enhanced CT images yielded an optimal AUC in both training and test datasets (Training dataset: 0.941, test dataset:0.938). Invasive procedures such as endoscopic biopsy of the mediastinal mass is dangerous because these masses are near the heart and mediastinal great vessels [21,22]. Thus, a non-invasive biomarker that can be obtained preoperatively to diagnose anterior mediastinal cysts from type B1 and B2 thymomas will be valuable in clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Can Computed Tomography-Based Radiomics Potentially Discrimination Between Anterior Mediastinal Cysts and type B1 and B2 thymomas

Liu

Pang

et al. 2020

Preprint

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Background Anterior mediastinal cysts (AMC) are often misdiagnosed as thymomas and undergo surgical resection, which caused unnecessary treatment and medical resources waste. The purpose of this study was to explore potential possibility of computed tomography (CT)-based radiomics for the diagnosis of AMC and type B1 and B2 thymomas. Methods A group of 188 patients with pathologically confirmed AMC (106 cases mischarged as thymomas in CT) and thymomas (82 cases) and underwent routine chest CT from January 2010 to December 2018 were retrospectively analyzed. The lesions were manually delineated using ITK-SNAP software, and radiomics features were performed using the Artificial Intelligence Kit (AK) software. A total of 396 tumor texture features were extracted from enhanced CT and unenhanced CT, respectively. The general test, correlation analysis and LASSO were used to features selection and then the radiomics signature (radscore) were obtained. The combined model including radscore and independent clinical factors were developed. The model performances were evaluated on discrimination, calibration curve. Results Two radscore model were constructed from the unenhanced and enhanced phases based on the selected 4 and 3 features, respectively. The AUC, sensitivity, and specificity of the enhanced radscore model were 0.928, 89.3% and 83.8% in the training dataset and 0.899, 84.6%, 87.5% in the test dataset (higher than the unenhanced radscore model). The combined model of enhanced CT including radiomics features and independent clinical factors yielded an AUC, sensitivity and specificity of 0.941, 82.1%, and 94.6% in the training dataset and 0.938, 92.3%, and 87.5% in the test dataset (higher than the unenhanced combined model and enhanced radscore model). Conclusions The study suggested the possibility that the combined model in enhanced CT provided a potential tool to facilitate the differential diagnosis of AMC and type B1 and B2 thymomas.

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“…However, mild thickening of the MP layer may be not only due to cancer infiltration (T2 stage) but also inflammatory reaction (T1 stage). Moreover, fibrosis and edema that produced hypoechoic changes also made EUS evaluation confusion [24,25].…”

Section: The Eus Image Features For Different Tumor T Stagesmentioning

confidence: 99%

The New American Joint Committee on Cancer T Staging System for Stomach: Increased Complexity without Clear Improvement in Predictive Accuracy for Endoscopic Ultrasound

Han

Tao

Zhang

et al. 2020

Preprint

Self Cite

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Background: The efficacy of endoscopic ultrasound (EUS) for determining T category is variable for gastric cancer. The aim of this study is to evaluate the superiority of EUS by using the 6th edition American Joint Committee on Cancer (AJCC) staging system for stomach cancer compared to the new 7th/8th edition.Methods: A retrospective analysis of clinical and EUS imaging features of 348 gastric carcinoma patients who underwent radical resection were collected. Differences between the 6th edition and 7th/8th edition T staging system for EUS preoperative evaluated were compared.Results: The accuracy of EUS T staging was 72.4% for 7th/8th edition and 78.4% for 6th edition; especially the T3 stage accuracy was significantly worse when T3 group status was changed. The tumor location, EUS type and histological type were associated with inaccuracy. We further analyzed the EUS image features for each tumor T stage and found muscularis propria (MP) visible indistinctly or obvious thickening were considered to be indicators that lesions involved to the MP with a sensitivity of 81.3%; MP disappeared completely and accompanied with serosal layer intact might be a marker that lesion invaded to the subserosa; We also found that irregularities in the outer edge of the gastric wall were markers of gastric serosal layer penetration with a positive predictive value of 92.2%.Conclusions: The increased complexity of the 7th/8th edition T staging system is accompanied by worsening in the predictive accuracy for EUS as compared to the 6th edition. Furthermore, the tumor location, EUS type, histological type and EUS image features for each tumor T stage should warrant attention.

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Role of endoscopic ultrasound-guided fine needle aspiration in the diagnosis of mass lesions

Cited by 12 publications

References 37 publications

Can computed tomography-based radiomics potentially discriminate between anterior mediastinal cysts and type B1 and B2 thymomas?

Can computed tomography-based radiomics potentially discriminate between anterior mediastinal cysts and type B1 and B2 thymomas?

Can Computed Tomography-Based Radiomics Potentially Discrimination Between Anterior Mediastinal Cysts and type B1 and B2 thymomas

The New American Joint Committee on Cancer T Staging System for Stomach: Increased Complexity without Clear Improvement in Predictive Accuracy for Endoscopic Ultrasound

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