Will Baseline Total Lesion Glycolysis Play a Role in Improving the Prognostic Value of the NCCN-IPI in Primary Gastric Diffuse Large B-Cell Lymphoma Patients Treated With the R-CHOP Regimen?

Advances in diagnosis, treatment and prognostic factors of gastrointestinal DLBCL

Gastrointestinal diffuse large B-cell lymphoma (GI-DLBCL) is an extremely aggressive form of B-cell non-Hodgkin lymphoma (BNHL) which has complex histological characteristics and manifests a high degree of heterogeneity in terms of clinical, morphological, immunological, and genetic features. GI-DLBCL mainly spreads by infiltrating neighboring lymph nodes, and common gastrointestinal complications (GICS) such as obstruction, perforation, or bleeding, frequently arise during the progression of the disease, posing significant challenges in both diagnosing and treating the condition. Meanwhile, the incidence of GI-DLBCL has been gradually increasing in recent years, and its strong invasiveness makes it prone to being misdiagnosed or completely missed. In clinical practice, over half of the patients diagnosed with the disease are in stage III or stage IV. What makes it worse is that certain patients may not exhibit a favorable response to chemotherapy. All these lead to intricacies in management of this disease. Unfortunately, there is currently no large prospective study or evidence-based medical evidence to provide clear guidance on treatment decisions for this specific type of lymphoma. Neither do physicians have a consensus regarding the optimal approach to address this condition. Recent studies have identified the presence of various prognostic factors that significantly impact survival in GI-DLBCL, which demonstrates the unique particularity of GI-DLBCL, and could help optimize the clinical decision.

Staging and response assessment of lymphoma: a brief review of the Lugano classification and the role of FDG-PET/CT

The accurate assessment of initial disease status and therapeutic responses is critical to the optimal management of patients with lymphoma. Currently, staging and treatment response evaluation for lymphoma has been standardized into the Lugano classification. Lugano classification incorporates positron emission tomography (PET) into the existing response criteria, and response assessment using FDG-PET/CT has been proven to predict the prognosis in various lymphoma subtypes effectively. We will briefly review the current staging and response evaluation system and explore the role of functional imaging in the field of lymphoma.

Radiomics signature from [18F]FDG PET images for prognosis predication of primary gastrointestinal diffuse large B cell lymphoma

OBJECTIVES

To investigate the prognostic value of PET radiomics feature in the prognosis of patients with primary gastrointestinal diffuse large B cell lymphoma (PGI-DLBCL) treated with R-CHOP-like regimen.

METHODS

A total of 140 PGI-DLBCL patients who underwent pre-therapy [¹⁸F] FDG PET/CT were enrolled in this retrospective analysis. PET radiomics features obtained from patients in the training cohort were subjected to three machine learning methods and Pearson's correlation test for feature selection. Support vector machine (SVM) was used to build a radiomics signature classifier associated with progression-free survival (PFS) and overall survival (OS). A multivariate Cox proportional hazards regression model was established to predict survival outcomes.

RESULTS

A total of 1421 PET radiomics features were extracted and reduced to 5 features to build a radiomics signature which was significantly associated with PFS and OS (p < 0.05). The combined model incorporating radiomics signatures, metabolic metrics, and clinical risk factors showed high C-indices in both the training (PFS: 0.825, OS: 0.834) and validation sets (PFS: 0.831, OS: 0.877). Decision curve analysis (DCA) demonstrated that the combined models achieved the most net benefit across a wider reasonable range of threshold probabilities for predicting PFS and OS.

CONCLUSION

The newly developed radiomics signatures obtained by the ensemble strategy were independent predictors of PFS and OS for PGI-DLBCL patients. Moreover, the combined model with clinical and metabolic factors was able to predict patient prognosis and may enable personalized treatment decision-making.

KEY POINTS

• Radiomics signatures generated from the optimal radiomics feature set from the [¹⁸F]FDG PET images can predict the survival of PGI-DLBCL patients. • The optimal radiomics feature set is constructed by integrating the feature selection outputs of LASSO, RF, Xgboost, and PC methods. • Combined models incorporating radiomics signatures from¹⁸F-FDG PET images, metabolic parameters, and clinical factors outperformed clinical models, and NCCN-IPI.

Prognostic Impact of Pretreatment 2-[18F]-FDG PET/CT Parameters in Primary Gastric DLBCL

Background and Objectives: Primary gastric diffuse large-B cell lymphoma (DLBCL) is an aggressive lymphoma subtype with high ¹⁸F-FDG avidity but unclear criteria for 2-[¹⁸F]-FDG PET/CT in the evaluation of treatment response and prognostication. Our aim was to investigate whether the pretreatment 2-[¹⁸F]-FDG PET/CT variables may predict treatment response (at end of first-line therapy) and prognosis in primary gastric DLBCL. Materials and Methods: we included 57 patients with a diagnosis of primary gastric DLBCL and a baseline 2-[¹⁸F]-FDG PET/CT and an end of treatment PET/CT after 6 cycles of R-CHOP chemotherapy. We analyzed PET images qualitatively and semi-quantitatively by deriving the maximum standardized uptake value body weight (SUVbw), the maximum standardized uptake value lean body mass (SUVlbm), the maximum standardized uptake value body surface area (SUVbsa), lesion to liver SUVmax ratio (L-L SUV R), lesion to blood-pool SUVmax ratio (L-BP SUV R), metabolic tumor volume and total lesion glycolysis of gastric lesion (gMTV and gTLG), and total MTV (tMTV) and TLG. Survival curves were plotted according to the Kaplan–Meier analysis. Results: at a median follow up of 80 months, the median PFS and OS were 69 and 80 months. Baseline gMTV, gTLG, tMTV, and TLG were significantly higher in patients with incomplete response (partial response and progression) compared to complete response group. tMTV and TLG were confirmed to be independent prognostic factors both for PFS (p = 0.023 and p = 0.038) and OS (p = 0.038 and p = 0.026); instead, the other metabolic parameters were not related to outcome survival. Conclusions: high tMTV and TLG were significantly correlated with shorter survival (PFS and OS) and may predict incomplete response after therapy.