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Biomedicines · 2025

Prognostic Value of Tumor Dissemination (Dmax) Derived from Basal 18F-FDG Positron Emission Tomography/Computed Tomography in Patients with Advanced Non-Small-Cell Lung Cancer.

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Pellegrino Sara, Fonti Rosa, Morra Rocco, Di Donna Erica, Servetto Alberto, Bianco Roberto, Del Vecchio Silvana

Аннотация

Objectives: The aim of the present study was to test whether a parameter reflecting tumor dissemination (Dmax), derived from basal 18F-FDG PET/CT, may predict clinical outcome in patients with advanced non-small-cell lung cancer (NSCLC). Methods: A total of 78 patients (55 men, 23 women) with stage III and IV NSCLC who had undergone whole-body 18F-FDG PET/CT scan at diagnosis were included in this study. Imaging parameters of primary lung tumors along with total MTV (MTVTOT) and whole-body TLG (TLGWB) of all malignant lesions were determined. Moreover, the largest distance between two 18F-FDG avid lesions (Dmax) in each patient was measured. Univariate and multivariate analyses of clinical and imaging variables were performed followed by overall survival (OS) curves. Results: A total of 441 lesions were analyzed, including 78 primary tumors, 174 metastatic lymph nodes, and 189 distant metastases. In primary tumors, the average values of SUVmax, SUVmean, MTV, and TLG were 11.80 ± 5.73, 5.37 ± 2.09, 60.61 ± 102.57 mL, and 340.36 ± 558.40 g, respectively. The mean value of Dmax was 29.98 ± 20.98 cm, whereas the average values of MTVTOT and TLGWB were 155.90 ± 176.94 mL and 851.08 ± 1032.17 g, respectively. In the univariate analysis, OS was predicted by MTVTOT (p = 0.0145), TLGWB (p = 0.0518), Dmax (p = 0.0031), and stage (p = 0.0130), whereas in the multivariate analysis, only Dmax was retained in the model (χ2 = 7.3130, p = 0.0068). In particular, a high Dmax value indicates a worse prognosis. Moreover, the combination of Dmax with MTVTOT was able to improve the prognostic stratification of patients with advanced stages of NSCLC. Conclusions: Dmax, by reflecting tumor dissemination throughout the body, can predict overall survival in NSCLC patients.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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