Prediction of Overall Survival and Progression-Free Survival by the 18F-FDG PETCT Radiomic Features in Patients with Primary Gastric Diffuse Large B-Cell Lymphoma

Abstract EN

Purpose.

To determine whether the radiomic features of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) contribute to prognosis prediction in primary gastric diffuse large B-cell lymphoma (PG-DLBCL) patients.

Methods.

This retrospective study included 35 PG-DLBCL patients who underwent PET/CT scans at West China Hospital before curative treatment.

The volume of interest (VOI) was drawn around the tumor, and radiomic analysis of the PET and CT images, within the same VOI, was conducted.

The metabolic and textural features of PET and CT images were evaluated.

Correlations of the extracted features with the overall survival (OS) and progression-free survival (PFS) were evaluated.

Univariate and multivariate analyses were conducted to assess the prognostic value of the radiomic parameters.

Results.

In the univariate model, many of the textural features, including kurtosis and volume, extracted from the PET and CT datasets were significantly associated with survival (5 for OS and 7 for PFS (PET); 7 for OS and 14 for PFS (CT)).

Multivariate analysis identified kurtosis (hazard ratio (HR): 28.685, 95% confidence interval (CI): 2.067–398.152, p=0.012), metabolic tumor volume (MTV) (HR: 26.152, 95% CI: 2.089–327.392, p=0.011), and gray-level nonuniformity (GLNU) (HR: 14.642, 95% CI: 2.661–80.549, p=0.002) in PET and sphericity (HR: 11.390, 95% CI: 1.360–95.371, p=0.025) and kurtosis (HR: 11.791, 95% CI: 1.583–87.808, p=0.016), gray-level nonuniformity (GLNU) (HR: 6.934, 95% CI: 1.069–44.981, p=0.042), and high gray-level zone emphasis (HGZE) (HR: 9.805, 95% CI: 1.359–70.747, p=0.024) in CT as independent prognostic factors.

Conclusion.

18F-FDG PET/CT radiomic features are potentially useful for survival prediction in PG-DLBCL patients.

However, studies with larger cohorts are needed to confirm the clinical prognostication of these parameters.