Radiomic Features of 18F-FDG PET in Hodgkin Lymphoma Are Predictive of Outcomes

Purpose. In the present study, we aimed to investigate whether the radiomic features of baseline 18F-FDG PET can predict the prognosis of Hodgkin lymphoma (HL). Methods. A total 65 HL patients (training cohort: n = 49; validation cohort: n = 16) were retrospectively enrolled in the present study. A total of 47 radiomic features were extracted from pretreatment PET images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful prognostic features in the training cohort. The distance between the two lesions that were the furthest apart (Dmax) was recorded. The receiver operating characteristic (ROC) curve, Kaplan–Meier method, and Cox proportional hazards model were used to assess the prognostic factors. Results. Long-zone high gray-level emphasis extracted from a gray-level zone-length matrix (LZHGEGLZLM) (HR = 9.007; p = 0.044 ) and Dmax (HR = 3.641; p = 0.048 ) were independently correlated with 2-year progression-free survival (PFS). A prognostic stratification model was established based on both risk predictors, which could distinguish three risk categories for PFS ( p = 0.0002 ). The 2-year PFS was 100.0%, 64.7%, and 33.3%, respectively. Conclusions. LZHGEGLZLM and Dmax were independent prognostic factors for survival outcomes. Besides, we proposed a prognostic stratification model that could further improve the risk stratification of HL patients.

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Prognostic Value of Baseline Radiomic Features of 18F-FDG PET in Patients with Diffuse Large B-Cell Lymphoma

Diagnostics ◽

10.3390/diagnostics11010036 ◽

2020 ◽

Vol 11 (1) ◽

pp. 36

Author(s):

Kun-Han Lue ◽

Yi-Feng Wu ◽

Hsin-Hon Lin ◽

Tsung-Cheng Hsieh ◽

Shu-Hsin Liu ◽

...

Keyword(s):

Fdg Pet ◽

Validation Cohort ◽

Cell Lymphoma ◽

B Cell Lymphoma ◽

Survival Outcomes ◽

Training Cohort ◽

Large B Cell Lymphoma ◽

Prognostic Stratification ◽

18F Fdg ◽

Large B Cell

This study investigates whether baseline 18F-FDG PET radiomic features can predict survival outcomes in patients with diffuse large B-cell lymphoma (DLBCL). We retrospectively enrolled 83 patients diagnosed with DLBCL who underwent 18F-FDG PET scans before treatment. The patients were divided into the training cohort (n = 58) and the validation cohort (n = 25). Eighty radiomic features were extracted from the PET images for each patient. Least absolute shrinkage and selection operator regression were used to reduce the dimensionality within radiomic features. Cox proportional hazards model was used to determine the prognostic factors for progression-free survival (PFS) and overall survival (OS). A prognostic stratification model was built in the training cohort and validated in the validation cohort using Kaplan–Meier survival analysis. In the training cohort, run length non-uniformity (RLN), extracted from a gray level run length matrix (GLRLM), was independently associated with PFS (hazard ratio (HR) = 15.7, p = 0.007) and OS (HR = 8.64, p = 0.040). The International Prognostic Index was an independent prognostic factor for OS (HR = 2.63, p = 0.049). A prognostic stratification model was devised based on both risk factors, which allowed identification of three risk groups for PFS and OS in the training (p < 0.001 and p < 0.001) and validation (p < 0.001 and p = 0.020) cohorts. Our results indicate that the baseline 18F-FDG PET radiomic feature, RLNGLRLM, is an independent prognostic factor for survival outcomes. Furthermore, we propose a prognostic stratification model that may enable tailored therapeutic strategies for patients with DLBCL.

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Prognostic Significance of Metabolic Parameters by 18F-FDG PET/CT in Thymic Epithelial Tumors

Cancers ◽

10.3390/cancers13040712 ◽

2021 ◽

Vol 13 (4) ◽

pp. 712

Author(s):

Joohee Lee ◽

Young Seok Cho ◽

Jhingook Kim ◽

Young Mog Shim ◽

Kyung-Han Lee ◽

...

Keyword(s):

Multivariate Analysis ◽

Prognostic Factors ◽

Fdg Pet ◽

Univariate Analysis ◽

Thymic Epithelial Tumors ◽

Epithelial Tumors ◽

Masaoka Stage ◽

Pet Ct ◽

18F Fdg ◽

Fdg Pet Ct

Background: Imaging tumor FDG avidity could complement prognostic implication in thymic epithelial tumors. We thus investigated the prognostic value of volume-based 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/CT parameters in thymic epithelial tumors with other clinical prognostic factors. Methods: This is a retrospective study that included 83 patients who were diagnosed with thymic epithelial tumors and underwent pretreatment 18F-FDG PET/CT. PET parameters, including maximum and average standardized uptake values (SUVmax, SUVavg), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), were measured with a threshold of SUV 2.5. Univariate and multivariate analysis of PET parameters and clinicopathologic variables for time-to-progression was performed by using a Cox proportional hazard regression model. Results: There were 21 low-risk thymomas (25.3%), 27 high-risk thymomas (32.5%), and 35 thymic carcinomas (42.2%). Recurrence or disease progression occurred in 24 patients (28.9%). On univariate analysis, Masaoka stage (p < 0.001); histologic types (p = 0.009); treatment modality (p = 0.001); and SUVmax, SUVavg, MTV, and TLG (all p < 0.001) were significant prognostic factors. SUVavg (p < 0.001) and Masaoka stage (p = 0.001) were independent prognostic factors on multivariate analysis. Conclusion: SUVavg and Masaoka stage are independent prognostic factors in thymic epithelial tumors.

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