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ORIGINAL RESEARCH article
Front. Oncol.
Sec. Thoracic Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1533569
This article is part of the Research Topic 3D Models in Cancer Research: Bridging Tumor Biology and Personalized Medicine View all 9 articles
The value of 18F-FDG PET/CT combined with 3D quantitative technology and clinicopathologic features in predicting prognosis of NSCLC
Provisionally accepted- 1 Zhuhai People's Hospital, Zhuhai, China
- 2 department of Nuclear Medicine, Zhuhai, China
Objective: To investigate the value of 18F-FDG PET/CT combined with 3D quantitative technology and clinicopathologic features in predicting the prognosis of non-small cell lung cancer (NSCLC).Methods: A retrospective review was performed for patients who undergoing PET/CT and curative resection of NSCLC between January 2016 and June 2019 in our hospital. PET/CT data, clinical features and pathology results were collected.Gross tumor volume (GTV) was delineated on CT images by ITK-SNAP software.The prognosis was followed up, and the study endpoint was progression-free survival (PFS). Receiver operating characteristic curve (ROC) was used to initially assess the relationship between each parameter and PFS, and parameters were grouped accordingly. Cox proportional hazards regression was used to develop models based on clinicopathologic features to predict prognosis of NSCLC patients. Kaplan-Meier method was used to draw the Survival curves.Results: A total of 128 patients were enrolled in the study with PFS of 8 to 96 months.Univariate analysis demonstrated that age, SUVindex (the ratio of SUVmax of lesion to SUVmax of liver), MTV(metabolic tumor volume), Dmax (the largest diameter), GTV, lymph node metastasis (LNM) and TNM staging are significantly related to recurrence (all P＜0.05). The multivariate analysis showed that only age, SUVindex and LNM were independent prognostic factor for PFS (all P＜0.05).Conclusions: Although 18F-FDG PET/CT combined with 3D quantitative techniques were helpful in predicting PFS in NSCLC, only age, SUVindex, and LNM were independent predictors for PFS.
Keywords: lung cancer, PET/CT, prognosis, 3D quantitative technology, NSCLC
Received: 24 Nov 2024; Accepted: 17 Mar 2025.
Copyright: © 2025 Su, Qiu and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yuling Su, Zhuhai People's Hospital, Zhuhai, China
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