Table · dataset · 2026
Table 4_Preoperative staging of gastric cancer: a prospective comparison of gastric filling ultrasonography and enhanced CT with implications for surgical decision-making.docx
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Background<p>Accurate preoperative staging is essential for optimizing treatment strategies in gastric cancer.
Description
While gastric-enhanced CT is widely used, its accuracy remains suboptimal, particularly for early-stage tumors. Gastric filling ultrasonography, a non-invasive technique using oral contrast to displace intraluminal gas, offers potential advantages in mural visualization.
This prospective study compared the diagnostic performance of gastric filling ultrasonography and gastric-enhanced CT against postoperative pathological staging.</p>Methods<p>We enrolled 406 patients with histologically confirmed gastric cancer who underwent both imaging modalities prior to surgery. Preoperative T and N stages assigned by each modality were compared with pathological results. Diagnostic accuracy, sensitivity, specificity, and area under the ROC curve (AUC) were calculated.
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McNemar's test was used for paired comparisons, DeLong test for AUC comparisons, and Kappa statistics for agreement assessment. Univariate logistic regression identified factors affecting ultrasound accuracy.</p>Results<p>For T-staging, overall accuracy was 72.7% (295/406) for ultrasound vs. 63.5% (258/406) for CT (P < 0.001). Ultrasound significantly outperformed CT in T1 (81.5% vs. 56.3%, P = 0.009) and T2 (81.1% vs. 67.9%, P < 0.001) stages.
For N-staging, accuracy was 82.0% (333/406) for ultrasound vs. 60.1% (244/406) for CT (P < 0.001). Kappa agreement with pathology was substantial for ultrasound T-staging (κ = 0.625) and N-staging (κ = 0.748), compared with moderate agreement for CT (κ = 0.508 and 0.395, respectively). In multivariate analysis, vascular infiltration was the only independent factor associated with ultrasound T-staging accuracy.</p>Conclusions<p>Gastric filling ultrasonography demonstrates superior accuracy over gastric-enhanced CT for preoperative T1/T2 and N-staging, with substantial agreement with pathological findings.
This non-invasive and radiation-free examination method can serve as an effective complement to CT, and is particularly suitable for gastric cancer at the T1 and T2 stages. We have proposed a complementary imaging protocol to assist in surgical decision-making, which is expected to enable clinicians to make more accurate preoperative staging assessments for patients with gastric cancer.</p>Registration<p>It was registered in the ClinicalTrials.gov (NCT05596864).</p>
Links
Where it is published
- DOI doi.org/10.3389/fsurg.2026.1925096.s004 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
- From keywords
- Astronomy & Astrophysics · Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Social Science · Surgery
- Inferred from text
- Cancer 75% · Computed tomography 50% · Imaging 75% · Tabular 65%
Provenance · 11 source records, 21 field assertions
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| HKU DataHub · removed upstream | oai:figshare.com:article/34044543 | 13 d ago | JSON v1 |
| Swinburne Figshare · removed upstream | oai:figshare.com:article/34044543 | 13 d ago | JSON v1 |
| DaYta Ya Rona · removed upstream | oai:figshare.com:article/34044543 | 13 d ago | JSON v1 |
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| figshare | oai:figshare.com:article/34044543 | 13 d ago | JSON v1 |
| Loughborough Research Repository · removed upstream | oai:figshare.com:article/34044543 | 13 d ago | JSON v1 |
| GRANTS Data · removed upstream | oai:figshare.com:article/34044543 | 12 d ago | JSON v1 |
| UP Research Data Repository · removed upstream | oai:figshare.com:article/34044543 | 12 d ago | JSON v1 |
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| concepts[field].local:field:chemistry | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare com | connector:figshare_com@1.0.0 | |
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