Evaluation of the Prognostic Value of Quantitative and Visual Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) Parameters in Superficial Esophageal Squamous Cell Carcinoma

定量和可视化氟代脱氧葡萄糖正电子发射断层扫描/计算机断层扫描(FDG PET/CT)参数在浅表食管鳞状细胞癌预后价值的评估

阅读:2

Abstract

INTRODUCTION: Early diagnosis is crucial for improving outcomes in esophageal cancer, as prognosis is strongly dependent on the stage at detection. This study evaluated the prognostic value of quantitative and visual 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) parameters in patients with superficial esophageal squamous cell carcinoma (SESCC). MATERIALS AND METHODS: A retrospective cohort of 95 patients with clinically confirmed SESCC who underwent pre-treatment FDG PET/CT was analyzed. Patients were stratified into FDG-positive and FDG-negative groups using both visual assessment and quantitative thresholds. Quantitative parameters included maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Associations with overall survival and pathological TNM classification were assessed. RESULTS: Quantitative analysis using SUVmax (threshold = 3.0) demonstrated significant prognostic stratification, with FDG-negative patients exhibiting superior overall survival compared to FDG-positive patients (p = 0.0264, log-rank test). Visual assessment did not yield significant survival discrimination (p = 0.3222). No significant correlations were identified between FDG-derived parameters and pathological or clinical TNM stages. CONCLUSION: Quantitative FDG PET/CT parameters, particularly SUVmax, provide superior prognostic information compared to visual assessment in SESCC. Incorporating quantitative metabolic imaging into the initial evaluation of early-stage esophageal cancer may enhance risk stratification and inform treatment planning.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。