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

Abstract

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.

Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)

“…18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) can visibly and comprehensively assess the glucose metabolism of tissues and has been widely used in a variety of malignant tumors including gastric cancer and lymphoma. [ 14 – 16 ] Semi-quantitatively, the standard uptake value (SUV) and its derivatives, which correlate to the degree of FDG uptake in tissues, have been demonstrated to help differentiate gastric cancer from gastric lymphoma. [ 17 , 18 ] Nonetheless, FDG uptake has a wide range in both gastric cancer and gastric lymphoma, [ 15 , 17 , 19 ] which is partially due to the differences between pathological subtypes.…”

Texture Analysis Improves the Value of Pretreatment 18F-FDG PET/CT in Predicting Interim Response of Primary Gastrointestinal Diffuse Large B-Cell Lymphoma

“…The more often the pairs of pixels ( i , j ) with certain intensities and spatial relationships co-occur, the higher the energy is. A previous study including PET/CT images of 35 primary gastric DLBCL patients reported that energy GLCM failed to predict either the progression-free survival (PFS) or the overall survival (OS) [ 30 ]. However, this study focused on the prediction of the prognosis rather than the treatment response.…”

“…However, based on the limited evidence and the indeterminate choices of PET texture features, the value of PET TA in lymphoma remains unclear. Moreover, to the best of our knowledge, the application of PET TA in PGIL has been reported by only one study, which did not include intestinal PGIL-DLBCL [ 30 ].…”

A mesoscopic simulator to uncover heterogeneity and evolutionary dynamics in tumors

“…When S reg approaches zero the tumor will be highly irregular, resembling a fractal-like structure. This parameter receives different names in the literature and has been found to have prognostic value in lung cancer [ 39 , 40 ], head and neck cancer [ 41 , 42 ], esophageal cancer [ 43 ], breast cancer [ 44 ], lymphoma [ 45 ], and glioma [ 24 , 38 ].…”