Preoperative Gross Classification of Gastric Adenocarcinoma: Comparison of Double Contrast-Enhanced Ultrasound and Multi-Detector Row CT

Yan, Caoxin; Bao, Xiaofeng; Shentu, Weihui; Chen, Jian; Liu, Chunmei; Ye, Qin; Wang, Liuhong; Tan, Yangbin; Huang, Pintong

doi:10.1016/j.ultrasmedbio.2016.01.030

Cited by 19 publications

(48 citation statements)

References 37 publications

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“…Contrast agents not only provide stomach distension and remove air in the gastric lumen but also produce a homogeneous hyperechoic volume in the gastrointestinal lumen, thus providing a relatively stronger background to the gastrointestinal wall and hypoechoic tumors than water from our experience and that of other researchers . Moreover, they can remain longer in the gastric lumen than water, thus offering enough time for the examination …”

Section: Discussionmentioning

confidence: 83%

“…The layers of the gastric wall can be differentiated transabdominally with oral contrast agents inside the gastric lumen . In this retrospective analysis, the overall accuracy of tumor staging using transabdominal oral contrast‐enhanced US (86% [36 of 42]) was comparable with that for contrast‐enhanced CT (83% [35 of 42]).…”

Section: Discussionmentioning

confidence: 87%

“…When the contrast agent entered the stomach, the conjunction of the cardia and gastric fundus visualized as a trumpet‐like appearance. The gastric body and antrum were imaged in the right lateral position, with continuous scanning in both transverse and longitudinal sections and angling of the transducer toward the left subcostal area . Gastric emptying (contraction and relaxation) was observed in real time.…”

Section: Methodsmentioning

confidence: 99%

“…Transcutaneous US imaging has not been considered an appropriate method for routinely assessing stomach disorders and cancer because the accuracy and reliability of hydrosonography are low, and there have been contrast agent–related side effects (such as nausea, vomiting, and diarrhea) . At this time, there is a new type of cereal‐based oral contrast agent that can produce nearly homogeneous hyperechogenicity in the gastric lumen and can remain for enough time for a detailed examination . However, there is little research on the preoperative tumor staging of gastric cancer using this oral contrast agent.…”

mentioning

confidence: 99%

“…[13][14][15][16] At this time, there is a new type of cereal-based oral contrast agent that can produce nearly homogeneous hyperechogenicity in the gastric lumen and can remain for enough time for a detailed examination. [17][18][19][20][21] However, there is little research on the preoperative tumor staging of gastric cancer using this oral contrast agent. We hypothesized that cereal-based oral contrast-enhanced transcutaneous US can enable the preoperative tumor staging of advanced gastric cancer with accuracies comparable to those achieved with transverse contrast-enhanced CT.…”

mentioning

confidence: 99%

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Comparison of Oral Contrast‐Enhanced Transabdominal Ultrasound Imaging With Transverse Contrast‐Enhanced Computed Tomography in Preoperative Tumor Staging of Advanced Gastric Carcinoma

Sun

Huang

et al. 2017

J of Ultrasound Medicine

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Section: Discussionmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 87%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Comparison of Oral Contrast‐Enhanced Transabdominal Ultrasound Imaging With Transverse Contrast‐Enhanced Computed Tomography in Preoperative Tumor Staging of Advanced Gastric Carcinoma

Sun

Huang

et al. 2017

J of Ultrasound Medicine

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Preoperative Tumor Staging of Gastric Cancer: Comparison of Double Contrast‐Enhanced Ultrasound and Multidetector Computed Tomography

Miao

et al. 2019

J of Ultrasound Medicine

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Objectives-The purpose of this study was to compare the sensitivity and specificity of double contrast-enhanced ultrasound (CEUS) and multidetector computed tomography (MDCT) in the preoperative tumor staging of gastric cancer (GC) to stratify patients for suitable treatment.Methods-Fifty-four patients with GC proved by histologic findings were included. The sensitivity and specificity of double CEUS and MDCT for tumor staging were calculated and compared. The differences between these methods were evaluated by using the area under the curve (AUC) from a receiver operating characteristic curve analysis.Results-There were no significant differences in AUC values for T1 and T2 stages between double CEUS and MDCT (P = .190 and .256, respectively). However, the sensitivity of double CEUS in the detection of the T1 stage was higher than that of MDCT (88% versus 75%). The AUC values of MDCT for T3 and T4 stages were 0.833 and 0.905, which were both significantly higher than those of double CEUS (0.759 and 0.696; P < .05). The sensitivities of double CEUS and MDCT for the T3 stage were both 89%, but the accuracy and specificity of double CEUS were lower than those of MDCT (76% versus 83% and 63% versus 78%). The specificities of double CEUS and MDCT for the T4 stage were both 98%, but the accuracy and sensitivity of double CEUS were lower than those of MDCT (85% versus 94% and 42% versus 83%).Conclusions-Multidetector CT is superior to double CEUS for T3 and T4 GC, and double CEUS may be regarded as an important complementary method to MDCT.

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Specific Borrmann classification in advanced gastric cancer by an ensemble multilayer perceptron network: a multicenter research

et al. 2021

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Purpose Borrmann classification in advanced gastric cancer (AGC) is necessarily associated with personalized surgical strategy and prognosis. But few radiomics research studies have focused on specific Borrmann classification, and there is yet no consensus regarding what machine learning methods should be the most effective. Methods A combined size of 889 AGC patients was retrospectively enrolled from two centers. Radiomic features were extracted from tumors manually delineated on preoperative computed tomography images. Two classification experiments (Borrmann I/II/III vs. IV and Borrmann II vs. III) were conducted. In each task, we combined three common feature selection methods and five typical machine learning classifiers to construct 15 basic classification models, and then fed the 15 predictions to a designed multilayer perceptron (MLP) network. Results In internal and external validation cohorts, the proposed ensemble MLP yielded good performance with area under curves of 0.767 and 0.702 for Borrmann I/II/III vs. IV, as well as 0.768 and 0.731 for Borrmann II vs. III. Considering the imbalanced distribution of four Borrmann types (I, 2.9%; II, 12.8%; III, 69.5%; IV, 14.7%), the ensemble MLP surpassed the overfitting barrier and attained fine specificity (0.667 and 0.750 for Borrmann I/II/III vs. IV; 0.714 and 0.620 for Borrmann II vs. III) and sensitivity (0.795 and 0.610 for Borrmann I/II/III vs. IV; 0.652 and 0.703 for Borrmann II vs. III). Also, survival analysis showed that patients could be significantly risk stratified by MLP predicted types in both experiments (p < 0.0001, log‐rank test). Conclusions This study proposed an MLP‐based ensemble learning architecture, which could identify Borrmann type IV automatically and improve the differentiation of Borrmann type II from III. The study provided a new view for specific Borrmann classification in clinical practice.

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Preoperative Gross Classification of Gastric Adenocarcinoma: Comparison of Double Contrast-Enhanced Ultrasound and Multi-Detector Row CT

Cited by 19 publications

References 37 publications

Comparison of Oral Contrast‐Enhanced Transabdominal Ultrasound Imaging With Transverse Contrast‐Enhanced Computed Tomography in Preoperative Tumor Staging of Advanced Gastric Carcinoma

Comparison of Oral Contrast‐Enhanced Transabdominal Ultrasound Imaging With Transverse Contrast‐Enhanced Computed Tomography in Preoperative Tumor Staging of Advanced Gastric Carcinoma

Preoperative Tumor Staging of Gastric Cancer: Comparison of Double Contrast‐Enhanced Ultrasound and Multidetector Computed Tomography

Specific Borrmann classification in advanced gastric cancer by an ensemble multilayer perceptron network: a multicenter research

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