PURPOSE: Baseline metabolic tumor volume (MTV) is a promising biomarker in diffuse large B-cell lymphoma (DLBCL). Our aims were to determine the best statistical relationship between MTV and survival and to compare MTV with the International Prognostic Index (IPI) and its individual components to derive the best prognostic model. METHODS: PET scans and clinical data were included from five published studies in newly diagnosed diffuse large B-cell lymphoma. Transformations of MTV were compared with the primary end points of 3-year progression-free survival (PFS) and overall survival (OS) to derive the best relationship for further analyses. MTV was compared with IPI categories and individual components to derive the best model. Patients were grouped into three groups for survival analysis using Kaplan-Meier analysis; 10% at highest risk, 30% intermediate risk, and 60% lowest risk, corresponding with expected clinical outcome. Validation of the best model was performed using four studies as a test set and the fifth study for validation and repeated five times. RESULTS: The best relationship for MTV and survival was a linear spline model with one knot located at the median MTV value of 307.9 cm³. MTV was a better predictor than IPI for PFS and OS. The best model combined MTV with age as continuous variables and individual stage as I-IV. The MTV-age-stage model performed better than IPI and was also better at defining a high-risk group (3-year PFS 46.3% v 58.0% and 3-year OS 51.5% v 66.4% for the new model and IPI, respectively). A regression formula was derived to estimate individual patient survival probabilities. CONCLUSION: A new prognostic index is proposed using MTV, age, and stage, which outperforms IPI and enables individualized estimates of patient outcome.

Purpose: Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment. Methods: Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values. Results: The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUV_peak and the maximal distance between the largest lesion and any other lesion (Dmax_bulk, AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUV_peak and Dmax_bulk) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively). Conclusion: Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance. Trial registration number and date: EudraCT: 2006–005,174-42, 01–08-2008.

Interim 18F-fluorodeoxyglucose positron emission tomography (Interim-18F-FDG-PET, hereafter I-PET) has the potential to guide treatment of patients with diffuse large B-cell lymphoma (DLBCL) if the prognostic value is known. The aim of this study was to determine the optimal timing and response criteria for evaluating prognosis with I-PET in DLBCL. Individual patient data from 1692 patients with de novo DLBCL were combined and scans were harmonized. I-PET was performed at various time points during treatment with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) therapy. Scans were interpreted using the Deauville score (DS) and change in maximum standardized uptake value (ΔSUVmax). Multilevel Cox proportional hazards models corrected for International Prognostic Index (IPI) score were used to study the effects of timing and response criteria on 2-year progression-free survival (PFS). I-PET after 2 cycles (I-PET2) and I-PET4 significantly discriminated good responders from poor responders, with the highest hazard ratios (HRs) for I-PET4. Multivariable HRs for a PET-positive result at I-PET2 and I-PET4 were 1.71 and 2.95 using DS4-5, 4.91 and 6.20 using DS5, and 2.93 and 4.65 using ΔSUVmax, respectively. ΔSUVmax identified a larger proportion of poor responders than DS5 did. For all criteria, the negative predictive value was >80%, and positive predictive values ranged from 30% to 70% at I-PET2 and I-PET4. Unlike I-PET1, I-PET3 discriminated good responders from poor responders using DS4-5 and DS5 thresholds (HRs, 2.94 and 4.67, respectively). I-PET2 and I-PET4 predict good response equally during R-CHOP therapy in DLBCL. Optimal timing and response criteria depend on the clinical context. Good response at I-PET2 is suggested for de-escalation trials, and poor response using ΔSUVmax at I-PET4 is suggested for randomized trials that are evaluating new therapies.

Diffuse large B-cell lymphoma (DLBCL) represents the most common subtype of non-Hodgkin lymphoma. Most relapses occur in the first 2 years after diagnosis. Early response assessment with ¹⁸F-fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography (PET) may facilitate early change of treatment, thereby preventing ineffective treatment and unnecessary side effects. We aimed to assess the predictive value of visually-assessed interim ¹⁸F-FDG PET on progression-free survival (PFS) or event-free survival (EFS) in DLBCL patients treated with first-line immuno-chemotherapy regimens.

Purpose: Recently, updated EARL specifications (EARL2) have been developed and announced. This study aims at investigating the impact of the EARL2 specifications on the quantitative reads of clinical PET–CT studies and testing a method to enable the use of the EARL2 standards whilst still generating quantitative reads compliant with current EARL standards (EARL1). Methods: Thirteen non-small cell lung cancer (NSCLC) and seventeen lymphoma PET–CT studies were used to derive four image datasets—the first dataset complying with EARL1 specifications and the second reconstructed using parameters as described in EARL2. For the third (EARL2F6) and fourth (EARL2F7) dataset in EARL2, respectively, 6 mm and 7 mm Gaussian post-filtering was applied. We compared the results of quantitative metrics (MATV, SUVmax, SUVpeak, SUVmean, TLG, and tumor-to-liver and tumor-to-blood pool ratios) obtained with these 4 datasets in 55 suspected malignant lesions using three commonly used segmentation/volume of interest (VOI) methods (MAX41, A50P, SUV4). Results: We found that with EARL2 MAX41 VOI method, MATV decreases by 22%, TLG remains unchanged and SUV values increase by 23–30% depending on the specific metric used. The EARL2F7 dataset produced quantitative metrics best aligning with EARL1, with no significant differences between most of the datasets (p>0.05). Different VOI methods performed similarly with regard to SUV metrics but differences in MATV as well as TLG were observed. No significant difference between NSCLC and lymphoma cancer types was observed. Conclusions: Application of EARL2 standards can result in higher SUVs, reduced MATV and slightly changed TLG values relative to EARL1. Applying a Gaussian filter to PET images reconstructed using EARL2 parameters successfully yielded EARL1 compliant data.