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| Name | Class |
|---|---|
| Zhongnan Hospital | OTHER |
| Wuhan Central Hospital | OTHER |
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The investigators conduct a prospective, multicenter diagnostic trial primarily aimed at evaluating the value of contrast-enhanced harmonic endoscopic ultrasound (CEH-EUS) in differentiating gastrointestinal stromal tumors (GISTs) from leiomyomas, as well as its predictive utility in the risk stratification of GISTs.
This study adopts a prospective, multicenter, self-controlled (pre-post) design. Patients with upper gastrointestinal subepithelial lesions (SELs) detected under white-light endoscopy will be consecutively enrolled. Each patient will first undergo endoscopic ultrasound (EUS) examination, during which lesion characteristics-including tumor size, margins, internal echogenicity, and originating layer-will be recorded. The contrast-specific extended pure harmonic detection (ExPHD) mode will then be activated, the mechanical index (MI) will be set to 0.3, and 2.4 mL of contrast agent (SonoVue) will be injected intravenously, followed by a 5 mL saline flush. Real-time dynamic imaging will be recorded for 120 seconds, capturing the arterial, venous, and delayed phases.
Histopathological results from surgical or endoscopic resection will serve as the reference standard. The diagnostic performance of EUS and contrast-enhanced EUS (CE-EUS) for differentiating gastrointestinal stromal tumors (GISTs) from leiomyomas and for predicting GIST risk stratification will be compared.
Patients meeting the inclusion criteria will be consecutively recruited. The primary outcome indicators are the sensitivity of CEH-EUS versus EUS in the differential diagnosis between GIST and leiomyoma, as well as in risk stratification of GIST. A prospective, self-controlled design will be used, with a type I error (α) of 0.05 (two-sided) and type II error (β) of 0.20, yielding a power of 0.80. Based on prior studies, the sensitivity of CEH-EUS for differentiating GISTs from leiomyomas is 87%, while that of EUS is approximately 72%-73%. Using McNemar's test for paired binary data (e.g., the same subject evaluated by two methods for positive diagnosis), the minimum sample size required for GIST patients is 121. Given that GISTs account for 67%-68% of all SELs, the required combined sample size of GIST and leiomyoma cases is 178. Accounting for an estimated 20% dropout rate, the final minimum sample size is 222 cases. For the GIST risk stratification analysis, prior studies report a sensitivity of 93% for CEH-EUS and 80% for EUS. McNemar's test was again used for sample size estimation. To meet the statistical requirements, 110 low-risk GIST cases are needed. Considering that low-risk GISTs comprise about 70% of all GISTs, and factoring in a 20% dropout rate, the total number of prospectively enrolled GIST patients required is 196. Since the risk stratification task requires a larger sample size and GISTs are the target of both diagnostic and stratification objectives, the final planned total sample size is 288 patients with GISTs or leiomyomas, which satisfies the statistical requirements for all primary study endpoints.
The study team will screen patients based on inclusion and exclusion criteria, ensure that all necessary examinations are completed to confirm eligibility, and obtain written informed consent from all prospective participants before conducting any study-related procedures.
This is a purely observational study. No additional interventions will be performed on participants, nor will they incur any extra costs. Patient access to optimal diagnostic or therapeutic options will not be affected. The primary potential risk is the breach of patient privacy. A strict data security and monitoring plan will be implemented, and participants will be informed that their data will be used for clinical research purposes.
The diagnostic performance of EUS and CE-EUS in differentiating GISTs from leiomyomas and in risk stratification of GISTs will be compared, with histopathological diagnosis serving as the gold standard. Diagnostic performance will be evaluated using paired analysis. All statistical tests will be two-sided, with significance defined as P < 0.05. Continuous variables will be presented as mean ± standard deviation, and categorical variables as counts and percentages.(1) Diagnostic performance: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC) will be calculated for both CEH-EUS and EUS as interpreted by expert endoscopists. To address class imbalance (e.g., GIST vs. other lesions), F1-score (harmonic mean) and balanced accuracy will also be computed. (2) Continuous variables: Comparisons with baseline will be performed using paired t-tests, analysis of variance (ANOVA), or rank-sum tests, as appropriate to data distribution. (3) Categorical variables: Group comparisons will use Chi-square tests (including Cochran-Mantel-Haenszel Chi-square) or Fisher's exact test. (4) Baseline comparability: Demographic and baseline characteristics will be compared using independent t-tests or Chi-square tests to assess balance between groups. (5) Effectiveness analysis: The primary effectiveness endpoint is the diagnostic accuracy for upper gastrointestinal subepithelial lesions. Differences in proportions and the Youden index will be compared using approximate Z-tests or Chi-square tests, with adjustment for center effects. (6) Statistical software: All statistical analyses will be performed using SPSS version 26.0.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| All Participants | All enrolled patients with upper gastrointestinal subepithelial lesions confirmed by histopathology. Each participant underwent both endoscopic ultrasound (EUS) and contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) examinations. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Endoscopic Ultrasound | Diagnostic Test | Conventional EUS will be performed to evaluate lesion size, echogenicity, border, and layer of origin for differentiation between GISTs and leiomyomas and risk stratification of GISTs. |
| Measure | Description | Time Frame |
|---|---|---|
| Diagnostic accuracy of CE-EUS and EUS for differentiating GIST from leiomyoma | The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall diagnostic accuracy of CE-EUS and conventional EUS will be calculated based on histopathological diagnosis as the gold standard. | Within 1 month after final histopathological diagnosis |
| Accuracy of CE-EUS and EUS in predicting malignant potential (risk stratification) of gastrointestinal stromal tumors | The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall diagnostic accuracy of CE-EUS and conventional EUS will be calculated based on histopathological diagnosis as the gold standard. | Within 1 month after final histopathological diagnosis |
| Measure | Description | Time Frame |
|---|---|---|
| Comparison of CEH-EUS Imaging Characteristics Between GIST and Leiomyoma | Contrast-enhancement patterns and perfusion characteristics will be recorded and compared between histologically confirmed GISTs and leiomyomas. | Within 1 month after histopathological diagnosis |
| Quantitative TIC Parameter Analysis for Differential Diagnosis and Risk Stratification |
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Inclusion Criteria:
Age ≥18 years and ≤ 85 years;
Subepithelial lesion in the gastrointestinal tract identified under white-light endoscopy and scheduled for CEH-EUS examination to determine the nature of the lesion;
EUS image quality meets the following quality control standards:
Patients with GIST confirmed by surgical or endoscopic resection pathology, and patients with leiomyoma confirmed by surgical resection, EUS-guided tissue sampling, or other biopsy techniques;
Written informed consent is obtained.
Exclusion Criteria:
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All participants aged 18-85 years with gastrointestinal subepithelial lesions identified by endoscopy, undergoing both EUS and CEH-EUS for diagnostic evaluation. Only patients with histologically confirmed GISTs or leiomyomas will be included.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Bin Cheng | Contact | 13986097542 | b.cheng@tjh.tjmu.edu.cn |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | Wuhan | Hubei | 430030 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36470211 | Result | Abe K, Tominaga K, Yamamiya A, Inaba Y, Kanamori A, Kondo M, Suzuki T, Watanabe H, Kawano M, Sato T, Yoshitake N, Ohwada T, Konno M, Hanatsuka K, Masuyama H, Goda K, Haruyama Y, Irisawa A; NUTSHELL20 Study group. Natural History of Small Gastric Subepithelial Lesions Less than 20 mm: A Multicenter Retrospective Observational Study (NUTSHELL20 Study). Digestion. 2023;104(3):174-186. doi: 10.1159/000527421. Epub 2022 Dec 5. | |
| 28947860 |
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| Contrast-Enhanced Harmonic Endoscopic Ultrasound (CEH-EUS) | Diagnostic Test | CEH-EUS will be conducted using a contrast agent to assess vascularity and enhancement patterns of the lesion for differentiation between GISTs and leiomyomas and risk stratification of GISTs. |
|
TIC-based quantitative CEH-EUS parameters will be measured and evaluated for their ability to distinguish GIST from leiomyoma and to predict GIST risk stratification, compared against final histopathology. |
| Within 1 month after histopathological diagnosis |
| Correlation of CEH-EUS Perfusion Parameters with Tumor Type and Risk Classification | CEH-EUS perfusion parameters such as enhancement intensity, wash-in rate, and wash-out rate will be analyzed for correlation with tumor type (GIST vs. leiomyoma) and with GIST risk levels based on NIH criteria. | Within 1 month after histopathological diagnosis |
| Result |
| Li J, Ye Y, Wang J, Zhang B, Qin S, Shi Y, He Y, Liang X, Liu X, Zhou Y, Wu X, Zhang X, Wang M, Gao Z, Lin T, Cao H, Shen L, Chinese Society Of Clinical Oncology Csco Expert Committee On Gastrointestinal Stromal Tumor. Chinese consensus guidelines for diagnosis and management of gastrointestinal stromal tumor. Chin J Cancer Res. 2017 Aug;29(4):281-293. doi: 10.21147/j.issn.1000-9604.2017.04.01. |
| 18076015 | Result | Dematteo RP, Gold JS, Saran L, Gonen M, Liau KH, Maki RG, Singer S, Besmer P, Brennan MF, Antonescu CR. Tumor mitotic rate, size, and location independently predict recurrence after resection of primary gastrointestinal stromal tumor (GIST). Cancer. 2008 Feb 1;112(3):608-15. doi: 10.1002/cncr.23199. |
| 18774375 | Result | Joensuu H. Risk stratification of patients diagnosed with gastrointestinal stromal tumor. Hum Pathol. 2008 Oct;39(10):1411-9. doi: 10.1016/j.humpath.2008.06.025. |
| 24444087 | Result | Chen H, Xu Z, Huo J, Liu D. Submucosal tunneling endoscopic resection for simultaneous esophageal and cardia submucosal tumors originating from the muscularis propria layer (with video). Dig Endosc. 2015 Jan;27(1):155-8. doi: 10.1111/den.12227. Epub 2014 Jan 20. |
| 28385194 | Result | Standards of Practice Committee; Faulx AL, Kothari S, Acosta RD, Agrawal D, Bruining DH, Chandrasekhara V, Eloubeidi MA, Fanelli RD, Gurudu SR, Khashab MA, Lightdale JR, Muthusamy VR, Shaukat A, Qumseya BJ, Wang A, Wani SB, Yang J, DeWitt JM. The role of endoscopy in subepithelial lesions of the GI tract. Gastrointest Endosc. 2017 Jun;85(6):1117-1132. doi: 10.1016/j.gie.2017.02.022. Epub 2017 Apr 3. No abstract available. |
| 30617491 | Result | Chen T, Xu L, Dong X, Li Y, Yu J, Xiong W, Li G. The roles of CT and EUS in the preoperative evaluation of gastric gastrointestinal stromal tumors larger than 2 cm. Eur Radiol. 2019 May;29(5):2481-2489. doi: 10.1007/s00330-018-5945-6. Epub 2019 Jan 7. |
| 31841880 | Result | Chen Z, Yang J, Sun J, Wang P. Gastric gastrointestinal stromal tumours (2-5 cm): Correlation of CT features with malignancy and differential diagnosis. Eur J Radiol. 2020 Feb;123:108783. doi: 10.1016/j.ejrad.2019.108783. Epub 2019 Dec 11. |
| 31410755 | Result | Kim GH, Ahn JY, Gong CS, Kim M, Na HK, Lee JH, Jung KW, Kim DH, Choi KD, Song HJ, Lee GH, Jung HY. Efficacy of Endoscopic Ultrasound-Guided Fine-Needle Biopsy in Gastric Subepithelial Tumors Located in the Cardia. Dig Dis Sci. 2020 Feb;65(2):583-590. doi: 10.1007/s10620-019-05774-5. Epub 2019 Aug 13. |
| 28511234 | Result | Dumonceau JM, Deprez PH, Jenssen C, Iglesias-Garcia J, Larghi A, Vanbiervliet G, Aithal GP, Arcidiacono PG, Bastos P, Carrara S, Czako L, Fernandez-Esparrach G, Fockens P, Gines A, Havre RF, Hassan C, Vilmann P, van Hooft JE, Polkowski M. Indications, results, and clinical impact of endoscopic ultrasound (EUS)-guided sampling in gastroenterology: European Society of Gastrointestinal Endoscopy (ESGE) Clinical Guideline - Updated January 2017. Endoscopy. 2017 Jul;49(7):695-714. doi: 10.1055/s-0043-109021. Epub 2017 May 16. |
| 36369879 | Result | Wu J, Zhuang M, Zhou Y, Zhan X, Xie W. The value of contrast-enhanced harmonic endoscopic ultrasound in differential diagnosis and evaluation of malignant risk of gastrointestinal stromal tumors (<50mm). Scand J Gastroenterol. 2023 May;58(5):542-548. doi: 10.1080/00365521.2022.2144437. Epub 2022 Nov 11. |
| 32350667 | Result | Yang YT, Shen N, Ao F, Chen WQ. Diagnostic value of contrast-enhanced harmonic endoscopic ultrasonography in predicting the malignancy potential of submucosal tumors: a systematic review and meta-analysis. Surg Endosc. 2020 Sep;34(9):3754-3765. doi: 10.1007/s00464-020-07585-6. Epub 2020 Apr 29. |
| 34272196 | Result | Lefort C, Gupta V, Lisotti A, Palazzo L, Fusaroli P, Pujol B, Gincul R, Fumex F, Palazzo M, Napoleon B. Diagnosis of gastric submucosal tumors and estimation of malignant risk of GIST by endoscopic ultrasound. Comparison between B mode and contrast-harmonic mode. Dig Liver Dis. 2021 Nov;53(11):1486-1491. doi: 10.1016/j.dld.2021.06.013. Epub 2021 Jul 14. |
| 30400724 | Result | Lee HS, Cho CM, Kwon YH, Nam SY. Predicting Malignancy Risk in Gastrointestinal Subepithelial Tumors with Contrast-Enhanced Harmonic Endoscopic Ultrasonography Using Perfusion Analysis Software. Gut Liver. 2019 Mar 15;13(2):161-168. doi: 10.5009/gnl18185. |
| 21874631 | Result | Piscaglia F, Nolsoe C, Dietrich CF, Cosgrove DO, Gilja OH, Bachmann Nielsen M, Albrecht T, Barozzi L, Bertolotto M, Catalano O, Claudon M, Clevert DA, Correas JM, D'Onofrio M, Drudi FM, Eyding J, Giovannini M, Hocke M, Ignee A, Jung EM, Klauser AS, Lassau N, Leen E, Mathis G, Saftoiu A, Seidel G, Sidhu PS, ter Haar G, Timmerman D, Weskott HP. The EFSUMB Guidelines and Recommendations on the Clinical Practice of Contrast Enhanced Ultrasound (CEUS): update 2011 on non-hepatic applications. Ultraschall Med. 2012 Feb;33(1):33-59. doi: 10.1055/s-0031-1281676. Epub 2011 Aug 26. No abstract available. |
| 37663113 | Result | Gomes RSA, de Oliveira GHP, de Moura DTH, Kotinda APST, Matsubayashi CO, Hirsch BS, Veras MO, Ribeiro Jordao Sasso JG, Trasolini RP, Bernardo WM, de Moura EGH. Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis. World J Gastrointest Endosc. 2023 Aug 16;15(8):528-539. doi: 10.4253/wjge.v15.i8.528. |
| 12038814 | Result | Brand B, Oesterhelweg L, Binmoeller KF, Sriram PV, Bohnacker S, Seewald S, De Weerth A, Soehendra N. Impact of endoscopic ultrasound for evaluation of submucosal lesions in gastrointestinal tract. Dig Liver Dis. 2002 Apr;34(4):290-7. doi: 10.1016/s1590-8658(02)80150-5. |
| ID | Term |
|---|---|
| D046152 | Gastrointestinal Stromal Tumors |
| D007889 | Leiomyoma |
| ID | Term |
|---|---|
| D009372 | Neoplasms, Connective Tissue |
| D018204 | Neoplasms, Connective and Soft Tissue |
| D009370 | Neoplasms by Histologic Type |
| D009369 | Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D009379 | Neoplasms, Muscle Tissue |
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| ID | Term |
|---|---|
| D019160 | Endosonography |
| ID | Term |
|---|---|
| D014463 | Ultrasonography |
| D003952 | Diagnostic Imaging |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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