ArticleAnnals of translational medicine2021
Modified method to improve the diagnostic efficiency of
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 6 citations in OpenAlex.
- Evaluation of PET-detected nodal upstaging and planning target volume expansion in esophageal cancer radiotherapy planning.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
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- Value of Computed Tomography Scan for Detecting Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma.Annals of surgical oncology · 2025Article
- The Utility ofClinical Medicine Insights. Oncology · 2024Article
- Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRegional lymph node (LN) metastasis is a significant factor influencing the treatment choice of esophageal squamous cell carcinoma (ESCC). The performance PET/CT as an imaging evaluation method for regional LNs in ESCC, is unsatisfactory due to the lack of logical criterion. We explored how a modified criterion improved the diagnostic value of
methodsThe data from 111 patients with ESCC were analyzed retrospectively. All patients underwent preoperative PET/CT examination, resection of the cancer, and regional LN dissection. The PET/CT images were interpreted by two experienced diagnosticians. LNs were allocated to five subregions. Each LN was diagnosed by two diagnostic criteria of PET/CT (traditional criterion and the modified criterion) one by one across the same field, and the accuracy of PET/CT was determined using the histopathologic results as the reference standard.
resultsA total of 4,847 LNs were dissected, of which 147 were confirmed as metastases by postoperative pathology. A total of 656 LNs were screened by
conclusionsThe modified diagnostic criterion had better diagnostic efficiency because it combined PET and CT imaging data.
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