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Background <p>Both ground-glass opacity (GGO) components on computed tomography (CT) and metabolic information derived from positron emission tomography (PET) are associated with prognosis in early‑stage non-small cell lung cancer (NSCLC) patients. The purpose of this study was to evaluate whether their combined assessment could improve risk stratification in surgically resected stage IA NSCLC.</p> Methods <p>We retrospectively analyzed 212 consecutive patients with stage IA NSCLC from two medical centers who underwent <sup>18</sup>F-FDG PET/CT before curative surgery between November 2012 and October 2024. The cohort was divided into feasibility evaluation (<i>n</i> = 152) and external validation (<i>n</i> = 60) groups. Primary tumor maximum standardized uptake values (SUV<sub>max</sub>), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured. Optimal PET parameter cutoffs for progression-free survival (PFS) were determined using receiver operating characteristic curve analysis in the feasibility cohort. A two-point prognostic scoring system combining GGO features and the multivariable-identified prognostic PET parameters was developed and validated in both cohorts using log-rank tests.</p> Results <p>For the feasibility cohort, the optimal cut-off values for the prediction of PFS were 6.2, 1.9 mL, and 11.7 for SUV<sub>max</sub>, MTV, and TLG, respectively. Both patients with primary tumors exceeding these metabolic parameters and those in the GGO-negative subgroup showed significantly shorter PFS (all <i>P</i> &lt; 0.05). Multivariable analysis identified GGO [hazard ratio (HR) = 8.137; 95% CI: 1.035–63.998; <i>P</i> = 0.046] and TLG (HR = 4.993; 95% CI: 1.831–13.612; <i>P</i> = 0.002) as independent prognostic factors, even after adjusting for histopathology and other PET parameters. The two-point prognostic scoring system, which consisted of GGO and TLG, stratified patients into low-, moderate-, and high-risk groups. In the feasibility cohort, PFS demonstrated statistically significant differences between the three groups (all <i>P</i> &lt; 0.05), with similar trends in the external validation cohort.</p> Conclusions <p>The two-point prognostic scoring system, combining morphological GGO features with volumetric metabolic parameters TLG, provided a simple yet effective method for enhancing prognostic stratification in patients with surgically resected stage IA NSCLC.</p>

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Prognostic value of integrating CT morphological features and PET volumetric metabolic parameters in surgically resected stage IA non-small cell lung cancer: a two-center retrospective study

  • 期刊论文

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  • 发表日期：

    2025年11月26日

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  • Jingjie Shang,
  • Xiaobei Duan,
  • Yingjun He,
  • Biao Wu,
  • Qijun Cai,
  • Xiaoling Cao,
  • Yongjin Tang,
  • Jinci Mai,
  • Simin Tan,
  • Huihu Li,
  • Xueying Ling,
  • Binhao Huang,
  • Hao Xu

摘要

Background

Both ground-glass opacity (GGO) components on computed tomography (CT) and metabolic information derived from positron emission tomography (PET) are associated with prognosis in early‑stage non-small cell lung cancer (NSCLC) patients. The purpose of this study was to evaluate whether their combined assessment could improve risk stratification in surgically resected stage IA NSCLC.

Methods

We retrospectively analyzed 212 consecutive patients with stage IA NSCLC from two medical centers who underwent 18F-FDG PET/CT before curative surgery between November 2012 and October 2024. The cohort was divided into feasibility evaluation (n = 152) and external validation (n = 60) groups. Primary tumor maximum standardized uptake values (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured. Optimal PET parameter cutoffs for progression-free survival (PFS) were determined using receiver operating characteristic curve analysis in the feasibility cohort. A two-point prognostic scoring system combining GGO features and the multivariable-identified prognostic PET parameters was developed and validated in both cohorts using log-rank tests.

Results

For the feasibility cohort, the optimal cut-off values for the prediction of PFS were 6.2, 1.9 mL, and 11.7 for SUVmax, MTV, and TLG, respectively. Both patients with primary tumors exceeding these metabolic parameters and those in the GGO-negative subgroup showed significantly shorter PFS (all P < 0.05). Multivariable analysis identified GGO [hazard ratio (HR) = 8.137; 95% CI: 1.035–63.998; P = 0.046] and TLG (HR = 4.993; 95% CI: 1.831–13.612; P = 0.002) as independent prognostic factors, even after adjusting for histopathology and other PET parameters. The two-point prognostic scoring system, which consisted of GGO and TLG, stratified patients into low-, moderate-, and high-risk groups. In the feasibility cohort, PFS demonstrated statistically significant differences between the three groups (all P < 0.05), with similar trends in the external validation cohort.

Conclusions

The two-point prognostic scoring system, combining morphological GGO features with volumetric metabolic parameters TLG, provided a simple yet effective method for enhancing prognostic stratification in patients with surgically resected stage IA NSCLC.