Exploration of the evolving role of <sup>18</sup> F-FDG PET/CT in evaluating extrahepatic cholangiocarcinoma lymph node metastasis.

e16218 Background: The presence of lymph node metastases at diagnosis is one of the most relevant negative prognostic factors in patients with extrahepatic cholangiocarcinoma (eCCA). This study aims to identify the diagnostic criteria of 18 F-FDG PET/CT for lymph node metastasis in eCCA, and to develop a more accurate predictive model of lymph node metastasis based on these results. Methods: All pathologically diagnosed cases of 98 lymph nodes from 71 patients of extrahepatic cholangiocarcinoma preoperatively were retrospectively analyzed. The distributional differences between malignant and benign groups were compared. The variables for constructing the metastasis prediction model of the lymph nodes were determined through further univariate and multivariate analyses of the variables exhibiting distributional differences. Results: It was observed that lymph nodes with tumor metastasis displayed greater size and metabolism. Following multifactorial analysis, a lymph node metastasis prediction model comprising of three variables: short diameter, aspect ratio and SUVmax. This model demonstrated favorable outcomes in our cohort's validation (AUC 0.932, sensitivity 87.5%, specificity 90.3%). In addition, these factors were used to construct the nomogram model, which showed good concordance and accuracy. Conclusions: In this study, a lymph node metastasis prediction model for extrahepatic cholangiocarcinoma based on short diameter, aspect ratio, and SUVmax has been developed. However, a larger sample size and a multicenter study are necessary to authenticate the model's efficacy.

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.e16218
Primary Topic
Cholangiocarcinoma and Gallbladder Cancer Studies
Type
article
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article

Exploration of the evolving role of 18 F-FDG PET/CT in evaluating extrahepatic cholangiocarcinoma lymph node metastasis.

Hongcheng Shi, Jie Xiao, Houbao Liu, Sheng Shen et al.
Journal of Clinical Oncology
Cholangiocarcinoma and Gallbladder Cancer Studies
article

Exploration of the evolving role of 18 F-FDG PET/CT in evaluating extrahepatic cholangiocarcinoma lymph node metastasis.

Hongcheng Shi, Jie Xiao, Houbao Liu, Sheng Shen, Tao Suo, Xiaojian Ni, Zhihui Gao
article en

Abstract

e16218 Background: The presence of lymph node metastases at diagnosis is one of the most relevant negative prognostic factors in patients with extrahepatic cholangiocarcinoma (eCCA). This study aims to identify the diagnostic criteria of 18 F-FDG PET/CT for lymph node metastasis in eCCA, and to develop a more accurate predictive model of lymph node metastasis based on these results. Methods: All pathologically diagnosed cases of 98 lymph nodes from 71 patients of extrahepatic cholangiocarcinoma preoperatively were retrospectively analyzed. The distributional differences between malignant and benign groups were compared. The variables for constructing the metastasis prediction model of the lymph nodes were determined through further univariate and multivariate analyses of the variables exhibiting distributional differences. Results: It was observed that lymph nodes with tumor metastasis displayed greater size and metabolism. Following multifactorial analysis, a lymph node metastasis prediction model comprising of three variables: short diameter, aspect ratio and SUVmax. This model demonstrated favorable outcomes in our cohort's validation (AUC 0.932, sensitivity 87.5%, specificity 90.3%). In addition, these factors were used to construct the nomogram model, which showed good concordance and accuracy. Conclusions: In this study, a lymph node metastasis prediction model for extrahepatic cholangiocarcinoma based on short diameter, aspect ratio, and SUVmax has been developed. However, a larger sample size and a multicenter study are necessary to authenticate the model's efficacy.

Journal of Clinical OncologyVol. 43(16_suppl)
Sun Yat-sen University (CN), Fudan University (CN), Zhongshan Hospital (CN), The First Affiliated Hospital, Sun Yat-sen University (CN)
Openalex Percentile: Top 79%
Cholangiocarcinoma and Gallbladder Cancer Studies
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