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Role of Maximum Standardized Uptake Volume in Predicting Tumor Spread Through Air Spaces in Stage IA Lung Cancers
Massimiliano Bassi1, Beatrice Zacchini1, Rita Vaz Sousa1
1Thoracic Surgery Unit, Department of General Surgery, Surgical Specialties and Anestesiology, Policlinico Umberto I, Sapienza University of Rome, 00161 Rome, Italy.
Objective:
Recent guidelines suggest sublobar resection as a viable option for peripheral lung cancer smaller than 2 cm. However, the presence of Spread through Air Spaces (STAS) is a well-known poor prognostic factor in early-stage lung cancer treated with sublobar resections. The aim of this study is to analyze the potential correlation between STAS and maximum standardized uptake volume (SUVmax) in this subset of patients to help define the optimal resection.
Methods:
A retrospective monocentric study was performed including patients diagnosed with stage IA lung cancer undergoing surgical resection. Patients were divided into two groups according to the presence/absence of STAS. As further investigation, we also separately analyzed the subgroup of patients with a peripheral nodule smaller than 2 cm. A p-value ≤ 0.05 was considered statistically significant.
Results:
The study cohort consists of 121 patients, 76 (62.8%) male, with a mean age of 74.2 ± 8.8 years. STAS was observed in 67 (55.4%) cases. The STAS-positive group showed a higher SUVmax value compared to the STAS-negative one (mean 5.5 ± 4.4 vs. 3.9 ± 3.0; p-value 0.007) with an AUC of 0.65 and an optimum SUVmax cut-off value of 3.0. Moreover, patients with SUVmax ≥ 3 showed a 77% increase in risk of having STAS (RR = 1.77; 95%CI = 1.21-2.59, p-value 0.014). This association was confirmed also in the subgroup of patients with nodules ≤ 2 cm (mean SUVmax 5.3 ± 4.6 vs. 3.6 ± 2.7; p value = 0.014).
Conclusions:
In our study, an SUVmax ≥ 3 in preoperative 18-FDG-PET is associated with the presence of STAS in stage IA lung cancer and peripheral cancer smaller than 2 cm. These findings, integrated with other clinical and radiological data, may guide surgeons to optimize the surgical strategy.
