SUVmax to tumor perimeter distance: a robust radiomics prognostic biomarker in resectable non-small cell lung cancer patients.

Autor: Jiménez Londoño GA; Department of Nuclear Medicine, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain. gjimenez91@yahoo.com., García Vicente AM; Department of Nuclear Medicine, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain., Bosque JJ; Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), Universidad de Castilla-La Mancha, Ciudad Real, Spain., Amo-Salas M; Department of Mathematics, Universidad de Castilla-La Mancha, Ciudad Real, Spain., Pérez-Beteta J; Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), Universidad de Castilla-La Mancha, Ciudad Real, Spain., Honguero-Martinez AF; Department of Surgery, Hospital General Universitario de Albacete, Albacete, Spain., Pérez-García VM; Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), Universidad de Castilla-La Mancha, Ciudad Real, Spain., Soriano Castrejón ÁM; Department of Nuclear Medicine, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain.
Jazyk: angličtina
Zdroj: European radiology [Eur Radiol] 2022 Jun; Vol. 32 (6), pp. 3889-3902. Date of Electronic Publication: 2022 Feb 08.
DOI: 10.1007/s00330-021-08523-3
Abstrakt: Objective: The purpose of this study was to evaluate the prognostic value of novel geometric variables obtained from pre-treatment [ 18 F]FDG PET/CT with respect to classical ones in patients with non-small cell lung cancer (NSCLC).
Methods: Retrospective study including stage I-III NSCLC patients with baseline [ 18 F]FDG PET/CT. Clinical, histopathologic, and metabolic parameters were obtained. After tumor segmentation, SUV and volume-based variables, global texture, sphericity, and two novel parameters, normalized SUVpeak to centroid distance (nSCD) and normalized SUVmax to perimeter distance (nSPD), were obtained. Early recurrence (ER) and short-term mortality (STM) were used as end points. Univariate logistic regression and multivariate logistic regression with respect to ER and STM were performed.
Results: A cohort of 173 patients was selected. ER was detected in 49/104 of patients with recurrent disease. Additionally, 100 patients died and 53 had STM. Age, pathologic lymphovascular invasion, lymph nodal infiltration, TNM stage, nSCD, and nSPD were associated with ER, although only age (aOR = 1.06, p = 0.002), pathologic lymphovascular invasion (aOR = 3.40, p = 0.022), and nSPD (aOR = 0.02, p = 0.018) were significant independent predictors of ER in multivariate analysis. Age, lymph nodal infiltration, TNM stage, nSCD, and nSPD were predictors of STM. Age (aOR = 1.05, p = 0.006), lymph nodal infiltration (aOR = 2.72, p = 0.005), and nSPD (aOR = 0.03, p = 0.022) were significantly associated with STM in multivariate analysis. Coefficient of variation (COV) and SUVmean/SUVmax ratio did not show significant predictive value with respect to ER or STM.
Conclusion: The geometric variables, nSCD and nSPD, are robust biomarkers of the poorest outcome prediction of patients with NSCLC with respect to classical PET variables.
Key Points: • In NSCLC patients, it is crucial to find prognostic parameters since TNM system alone cannot explain the variation in lung cancer survival. • Age, lymphovascular invasion, lymph nodal infiltration, and metabolic geometrical parameters were useful as prognostic parameters. • The displacement grade of the highest point of metabolic activity towards the periphery assessed by geometric variables obtained from [ 18 F]FDG PET/CT was a robust biomarker of the poorest outcome prediction of patients with NSCLC.
(© 2022. The Author(s), under exclusive licence to European Society of Radiology.)
Databáze: MEDLINE
Externí odkaz: