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Objective <p>To evaluate the diagnostic efficacy of a novel FAP-targeted tracer, [¹⁸F]F-FAPI-FUSCC-07, for solitary pulmonary nodules (SPNs) and to develop a reliable prediction model by integrating PET functional parameters with CT morphological features.</p> Methods <p>One hundred and thirty-seven patients with SPNs who underwent both [¹⁸F]F-FAPI-FUSCC-07 and [¹⁸F]F-FDG PET/CT were retrospectively enrolled in this study. Diagnostic performance of semi-quantitative parameters (SUVmax and TBR) for both tracers was evaluated and compared using ROC analysis. A multivariate logistic regression model was constructed in a training cohort (<i>n</i> = 100) and validated in an independent cohort (<i>n</i> = 37).</p> Results <p>Both [¹⁸F]F-FAPI-FUSCC-07 and [¹⁸F]F-FDG PET/CT were able to discriminate between benign and malignant SPNs effectively. Compared with [¹⁸F]F-FDG PET/CT, [¹⁸F]F-FAPI-FUSCC-07 PET/CT demonstrated significantly higher diagnostic accuracy (AUC for TBR of both tracers: 0.801 vs. 0.677, <i>p</i> &lt; 0.05). To better leverage the advantages of [¹⁸F]F-FAPI-FUSCC-07 PET/CT, a diagnostic model combining FAPI uptake and CT morphological features was constructed using logistic regression. The model was formulated as <i>P</i> = 1 / (1 + e^(-x)), where P represents the probability of malignancy, x = -1.223 + 0.502 × TBR<sub>FAPI</sub> + 1.959 × lobulation. The diagnostic model achieved superior performance with an AUC of 0.866. In the validation set, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the model were 87.50%, 69.23%, 81.08%, 84.00%, and 75.00%, respectively. Exploratory analysis revealed significantly lower [¹⁸F]F-FAPI-FUSCC-07 uptake in invasive mucinous adenocarcinoma than in other subtypes.</p> Conclusion <p>[¹⁸F]F-FAPI-FUSCC-07 PET/CT is a superior imaging tool for discriminating benign from malignant SPNs compared to [¹⁸F]F-FDG PET/CT. A prediction model combining its functional parameters with CT morphological features achieved satisfactory discriminatory ability (AUC: 0.866) in the training set and maintained good accuracy (81.08%) in an independent validation set, providing a promising non-invasive diagnostic strategy that warrants further validation in prospective studies.</p>

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Diagnostic performance of [18F]F-FAPI-FUSCC-07 PET/CT in characterizing solitary pulmonary nodules: a head-to-head comparison

  • 期刊论文

  • 发表日期：

    2026年2月17日

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  • Yuan Cheng,
  • Nan Li,
  • Bin Zhu,
  • Xiaosheng Liu,
  • Jianping Zhang,
  • Xiaoping Xu,
  • Silong Hu,
  • Shaoli Song

摘要

Objective

To evaluate the diagnostic efficacy of a novel FAP-targeted tracer, [¹⁸F]F-FAPI-FUSCC-07, for solitary pulmonary nodules (SPNs) and to develop a reliable prediction model by integrating PET functional parameters with CT morphological features.

Methods

One hundred and thirty-seven patients with SPNs who underwent both [¹⁸F]F-FAPI-FUSCC-07 and [¹⁸F]F-FDG PET/CT were retrospectively enrolled in this study. Diagnostic performance of semi-quantitative parameters (SUVmax and TBR) for both tracers was evaluated and compared using ROC analysis. A multivariate logistic regression model was constructed in a training cohort (n = 100) and validated in an independent cohort (n = 37).

Results

Both [¹⁸F]F-FAPI-FUSCC-07 and [¹⁸F]F-FDG PET/CT were able to discriminate between benign and malignant SPNs effectively. Compared with [¹⁸F]F-FDG PET/CT, [¹⁸F]F-FAPI-FUSCC-07 PET/CT demonstrated significantly higher diagnostic accuracy (AUC for TBR of both tracers: 0.801 vs. 0.677, p < 0.05). To better leverage the advantages of [¹⁸F]F-FAPI-FUSCC-07 PET/CT, a diagnostic model combining FAPI uptake and CT morphological features was constructed using logistic regression. The model was formulated as P = 1 / (1 + e^(-x)), where P represents the probability of malignancy, x = -1.223 + 0.502 × TBRFAPI + 1.959 × lobulation. The diagnostic model achieved superior performance with an AUC of 0.866. In the validation set, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the model were 87.50%, 69.23%, 81.08%, 84.00%, and 75.00%, respectively. Exploratory analysis revealed significantly lower [¹⁸F]F-FAPI-FUSCC-07 uptake in invasive mucinous adenocarcinoma than in other subtypes.

Conclusion

[¹⁸F]F-FAPI-FUSCC-07 PET/CT is a superior imaging tool for discriminating benign from malignant SPNs compared to [¹⁸F]F-FDG PET/CT. A prediction model combining its functional parameters with CT morphological features achieved satisfactory discriminatory ability (AUC: 0.866) in the training set and maintained good accuracy (81.08%) in an independent validation set, providing a promising non-invasive diagnostic strategy that warrants further validation in prospective studies.