Pre-treatment total metabolic tumour volumes in lymphoma: Does quantity matter?

Understandings 18 FDG PET radiomics and its application to lymphoma

The early identification of lymphoma patients who fail front-line treatment is crucial for optimizing disease management. Positron emission tomography, a well-established tool for staging and response evaluation in lymphoma, is typically assessed visually or semiquantitatively, leaving much of its latent information unexploited. Radiomic analysis, which employs mathematical descriptors, can enable the extraction of quantitative features from baseline images that correlate with the disease's biological characteristics. Emerging radiomic features such as metabolic tumour volume, total lesion glycolysis and markers of disease dissemination and metabolic heterogeneity are proving to be powerful prognostic biomarkers in lymphoma. Texture analysis, the most advanced area of radiomics, offers highly complex features that require further standardization and validation before being adopted as reliable biomarkers. Combining radiomic features with clinical risk factors and genomic data holds promising potential for improving clinical risk prediction. This review explores the current state of radiomic analysis, progress towards its standardization and its incorporation into clinical practice and trial designs. The integration of radiomic markers with circulating tumour DNA may provide a comprehensive approach to developing baseline and dynamic risk scores, facilitating the testing of novel treatments and advancing personalized treatment of aggressive lymphomas.

Clinical scoring systems, molecular subtypes and baseline [18F]FDG PET/CT image analysis for prognosis of diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous hematological malignancy resulting in a range of outcomes, and the early prediction of these outcomes has important implications for patient management. Clinical scoring systems provide the most commonly used prognostic evaluation criteria, and the value of genetic testing has also been confirmed by in-depth research on molecular typing. [18F]-fluorodeoxyglucose positron emission tomography / computed tomography ([18F]FDG PET/CT) is an invaluable tool for predicting DLBCL progression. Conventional baseline image-based parameters and machine learning models have been used in prognostic FDG PET/CT studies of DLBCL; however, numerous studies have shown that combinations of baseline clinical scoring systems, molecular subtypes, and parameters and models based on baseline FDG PET/CT image may provide better predictions of patient outcomes and aid clinical decision-making in patients with DLBCL.

The value of semiquantitative PET features and end-of-therapy PET in grade 3B follicular lymphoma

Grade 3B follicular lymphoma (G3BFL) is a rare lymphoma thought to sit on a continuum between low-grade FL and diffuse large B-cell lymphoma (DLBCL). The prognostic impact of quantitative positron emission tomography (PET) metrics such as total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), and maximum standard uptake value (SUVmax) have been extensively analysed in FL and DLBCL, but G3BFL data are lacking. Here, we describe PET outcomes and radiomic characteristics in 46 G3BFL cases uniformly treated with R-CHOP (like) chemotherapy. Central semi-automated PET TMTV, TLG, and SUVmax analyses, using MIM software, were correlated with clinical outcomes and compared with published results in low-grade FL and DLBCL. In G3BFL, the end-of-treatment complete metabolic response was associated with improved progression-free survival (PFS; p = 0.002) and overall survival (OS; p = 0.04). G3BFL median TLG (1455) and SUVmax (16.50) sit between published values for low-grade FL (TLG: 1112, SUVmax: 11.3) and DLBCL (TLG: 3004, SUVmax: 24.35). No association between TMTV (>350 cm3) and survival was seen (PFS: p = 0.24; OS: p = 0.40). High SUVmax (>19.2) and TLG (>2760) both conferred inferior PFS but not OS (PFS: SUVmax p = 0.004; TLG p = 0.05). These data support the routine incorporation of PET radiomics at baseline and treatment response for G3BFL.

International Benchmark for Total Metabolic Tumor Volume Measurement in Baseline 18F-FDG PET/CT of Lymphoma Patients: A Milestone Toward Clinical Implementation

Total metabolic tumor volume (TMTV) is prognostic in lymphoma. However, cutoff values for risk stratification vary markedly, according to the tumor delineation method used. We aimed to create a standardized TMTV benchmark dataset allowing TMTV to be tested and applied as a reproducible biomarker. Methods: Sixty baseline 18F-FDG PET/CT scans were identified with a range of disease distributions (20 follicular, 20 Hodgkin, and 20 diffuse large B-cell lymphoma). TMTV was measured by 12 nuclear medicine experts, each analyzing 20 cases split across subtypes, with each case processed by 3-4 readers. LIFEx or ACCURATE software was chosen according to reader preference. Analysis was performed stepwise: TMTV1 with automated preselection of lesions using an SUV of at least 4 and a volume of at least 3 cm3 with single-click removal of physiologic uptake; TMTV2 with additional removal of reactive bone marrow and spleen with single clicks; TMTV3 with manual editing to remove other physiologic uptake, if required; and TMTV4 with optional addition of lesions using mouse clicks with an SUV of at least 4 (no volume threshold). Results: The final TMTV (TMTV4) ranged from 8 to 2,288 cm3, showing excellent agreement among all readers in 87% of cases (52/60) with a difference of less than 10% or less than 10 cm3 In 70% of the cases, TMTV4 equaled TMTV1, requiring no additional reader interaction. Differences in the TMTV4 were exclusively related to reader interpretation of lesion inclusion or physiologic high-uptake region removal, not to the choice of software. For 5 cases, large TMTV differences (>25%) were due to disagreement about inclusion of diffuse splenic uptake. Conclusion: The proposed segmentation method enabled highly reproducible TMTV measurements, with minimal reader interaction in 70% of the patients. The inclusion or exclusion of diffuse splenic uptake requires definition of specific criteria according to lymphoma subtype. The publicly available proposed benchmark allows comparison of study results and could serve as a reference to test improvements using other segmentation approaches.

Metabolic tumor volume and the survival of patients with Non-Hodgkin lymphoma treated with chimeric antigen receptor T cell therapy: a meta-analysis

Background

Chimeric antigen receptor T cell (CAR-T) is a promising treatment for aggressive Non-Hodgkin lymphoma (NHL). The aim of the meta-analysis was to determine the association between metabolic tumor volumes (MTV) derived on positron emission tomography before CAR-T infusion and the survival of patients with NHL.

Methods

Relevant observational studies pertaining to the purpose of the meta-analysis were obtained through a search of PubMed, Web of Science, and Embase from inception of the databases to April 1, 2024. The data was combined using a random-effects model that accounted for the potential influence of between-study heterogeneity.

Results

Fifteen observational studies were included. Pooled results showed that compared to those with a lower MTV, the NHL patients with a higher MTV before CAR-T infusion were associated with a poor progression-free survival (hazard ratio [HR]: 1.73, 95% confidence interval [CI]: 1.48 to 2.02, p < 0.001; I2 = 20%) and overall survival (HR: 2.11, 95% CI: 1.54 to 2.89, p < 0.001; I2 = 58%). Subgroup analysis showed that the association between MTV and survival of NHL patients after CAR-T was not significantly impacted by study design, methods for determination of MTV cutoff, or analytic models (univariate or multivariate, p for each subgroup all < 0.05). Subgroup analysis suggested a stronger association between MTV and poor survival outcomes in patients with median of lines of previous treatment of 2 or 3 as compared to those of 4 (p for subgroup difference < 0.05). Further meta-regression analyses suggested that the association between MTV and survival was not significantly affected by sample size, age, proportion of men, cutoff value of MTV, follow-up duration, or study quality scores (p all > 0.05).

Conclusion

A high MTV at baseline is associated with a poor survival of NHL patients after CAR-T.

Systematic Review Registration

https://inplasy.com/, identifier INPLASY (INPLASY202450069).

TMTV-Net: fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images - a multi-center generalizability analysis

PURPOSE

Total metabolic tumor volume (TMTV) segmentation has significant value enabling quantitative imaging biomarkers for lymphoma management. In this work, we tackle the challenging task of automated tumor delineation in lymphoma from PET/CT scans using a cascaded approach.

METHODS

Our study included 1418 2-[18F]FDG PET/CT scans from four different centers. The dataset was divided into 900 scans for development/validation/testing phases and 518 for multi-center external testing. The former consisted of 450 lymphoma, lung cancer, and melanoma scans, along with 450 negative scans, while the latter consisted of lymphoma patients from different centers with diffuse large B cell, primary mediastinal large B cell, and classic Hodgkin lymphoma cases. Our approach involves resampling PET/CT images into different voxel sizes in the first step, followed by training multi-resolution 3D U-Nets on each resampled dataset using a fivefold cross-validation scheme. The models trained on different data splits were ensemble. After applying soft voting to the predicted masks, in the second step, we input the probability-averaged predictions, along with the input imaging data, into another 3D U-Net. Models were trained with semi-supervised loss. We additionally considered the effectiveness of using test time augmentation (TTA) to improve the segmentation performance after training. In addition to quantitative analysis including Dice score (DSC) and TMTV comparisons, the qualitative evaluation was also conducted by nuclear medicine physicians.

RESULTS

Our cascaded soft-voting guided approach resulted in performance with an average DSC of 0.68 ± 0.12 for the internal test data from developmental dataset, and an average DSC of 0.66 ± 0.18 on the multi-site external data (n = 518), significantly outperforming (p < 0.001) state-of-the-art (SOTA) approaches including nnU-Net and SWIN UNETR. While TTA yielded enhanced performance gains for some of the comparator methods, its impact on our cascaded approach was found to be negligible (DSC: 0.66 ± 0.16). Our approach reliably quantified TMTV, with a correlation of 0.89 with the ground truth (p < 0.001). Furthermore, in terms of visual assessment, concordance between quantitative evaluations and clinician feedback was observed in the majority of cases. The average relative error (ARE) and the absolute error (AE) in TMTV prediction on external multi-centric dataset were ARE = 0.43 ± 0.54 and AE = 157.32 ± 378.12 (mL) for all the external test data (n = 518), and ARE = 0.30 ± 0.22 and AE = 82.05 ± 99.78 (mL) when the 10% outliers (n = 53) were excluded.

CONCLUSION

TMTV-Net demonstrates strong performance and generalizability in TMTV segmentation across multi-site external datasets, encompassing various lymphoma subtypes. A negligible reduction of 2% in overall performance during testing on external data highlights robust model generalizability across different centers and cancer types, likely attributable to its training with resampled inputs. Our model is publicly available, allowing easy multi-site evaluation and generalizability analysis on datasets from different institutions.

Utility of FDG-PET in predicting the histology of relapsed or refractory lymphoma

ABSTRACT

18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) is a valuable prognostic tool in modern lymphoma care. In this study, we explored the use of quantitative FDG-PET parameters in predicting the histology of suspected relapsed or refractory (R/R) lymphoma. We retrospectively analyzed 290 FDG-PET scans performed for suspected R/R lymphoma. FDG-PET parameters measured were maximum and mean standardized uptake value (SUVMax and SUVMean), total metabolic tumor volume, and total lesion glycolysis (TLG). Receiver operating characteristic curve analysis was used to obtain the optimal thresholds that best discriminate (1) benign vs R/R lymphoma, (2) indolent vs aggressive non-Hodgkin lymphoma (NHL), and (3) aggressive transformation of indolent NHL. We found that although all 4 FDG-PET parameters discriminated R/R lymphoma from benign histology, TLG was the best performing parameter (optimal cut-off ≥245, sensitivity 63%, specificity 86%, positive predictive value [PPV] 97%, negative predictive value [NPV] 30%, area under the curve [AUC] 0.798, and P < .001). SUVMax discriminated aggressive from indolent NHL with modest accuracy (optimal threshold ≥15, sensitivity 46%, specificity 79%, PPV 82%, NPV 38%, AUC 0.638, and P < .001). In patients with a prior diagnosis of indolent NHL, SUVMax was a modest predictor of transformation (optimal cut-off ≥12, sensitivity 71%, specificity 61%, PPV 50%, NPV 78%, AUC 0.676, and P .006). Additionally, SUVMax ≥25 and an increase in SUVMax (ΔSUVMax) from baseline ≥150% were highly specific (96% and 94%, respectively). These FDG-PET thresholds can aid in identification of suspected R/R lymphoma cases with higher likelihood of R/R disease and aggressive transformation of indolent NHL, guiding the necessity and urgency of biopsy.

Metabolic bulk volume from FDG PET as an independent predictor of progression-free survival in follicular lymphoma

Background

Total metabolic tumor volume (TMTV) in 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) predicts patient outcome in follicular lymphoma (FL); however, it requires laborious segmentation of all lesions. We investigated the prognostic value of the metabolic bulk volume (MBV) obtained from the single largest lesion.

Methods

Pretreatment FDG PET/computed tomography (CT) scans of 201 patients were analyzed for TMTV and MBV using a 41% maximum standardized uptake value (SUVmax) threshold.

Results

During a median follow-up of 3.2 years, 54 events, including 14 deaths, occurred. Optimal cut-offs were 121.1 cm3 for TMTV and 24.8 cm3 for MBV. Univariable predictors of progression-free survival (PFS) included a high Follicular Lymphoma International Prognostic Index 2 (FLIPI2) score, TMTV, and MBV. In the multivariable analysis, high TMTV and MBV were independent predictors of worse PFS (P =0.015 and 0.033). Furthermore, in a sub-group with FLIP2 scores of 0-2 (n = 132), high MBV could identify patients with worse PFS (P = 0.007). .

Conclusion

Readily measurable MBV is useful for stratifying risk in FL patients.

Integration of PET in DLBCL

F-fluorodeoxyglucose positron emission tomography-computerized tomography (18FDG-PET/CT) is the gold-standard imaging modality for staging and response assessment for most lymphomas. This review focuses on the utility of 18FDG-PET/CT, and its role in staging, prognostication and response assessment in diffuse large B-cell lymphoma (DLBCL), including emerging possibilities for future use.

Prognostic Markers within the Tumour Microenvironment in Classical Hodgkin Lymphoma

Classical Hodgkin lymphoma (cHL) accounts for 0.4% of all new cancer cases globally. Despite high cure rates with standard treatment, approximately 15% of patients still experience relapsed or refractory (RR) disease, and many of these eventually die from lymphoma-related causes. Exciting new targeted agents such as anti-PD-1 agents and brentuximab vedotin have changed the therapeutic paradigm beyond chemotherapy and radiotherapy alone. Advances in understanding of the molecular biology are providing insights in the context of novel therapies. The signature histology of cHL requires the presence of scant malignant Hodgkin Reed-Sternberg cells (HRSCs) surrounded by a complex immune-rich tumour microenvironment (TME). The TME cellular composition strongly influences outcomes, yet knowledge of the precise characteristics of TME cells and their interactions with HRSCs is evolving. Novel high-throughput technologies and single-cell sequencing allow deeper analyses of the TME and mechanisms elicited by HRSCs to propagate growth and avoid immune response. In this review, we explore the evolution of knowledge on the prognostic role of immune cells within the TME and provide an up-to-date overview of emerging prognostic data on cHL from new technologies that are starting to unwind the complexity of the cHL TME and provide translational insights into how to improve therapy in the clinic.

Prognostic indices in diffuse large B-cell lymphoma: a population-based comparison and validation study of multiple models

Currently, the International Prognostic Index (IPI) is the most used and reported model for prognostication in patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL). IPI-like variations have been proposed, but only a few have been validated in different populations (e.g., revised IPI (R-IPI), National Comprehensive Cancer Network IPI (NCCN-IPI)). We aimed to validate and compare different IPI-like variations to identify the model with the highest predictive accuracy for survival in newly diagnosed DLBCL patients. We included 5126 DLBCL patients treated with immunochemotherapy with available data required by 13 different prognostic models. All models could predict survival, but NCCN-IPI consistently provided high levels of accuracy. Moreover, we found similar 5-year overall survivals in the high-risk group (33.4%) compared to the original validation study of NCCN-IPI. Additionally, only one model incorporating albumin performed similarly well but did not outperform NCCN-IPI regarding discrimination (c-index 0.693). Poor fit, discrimination, and calibration were observed in models with only three risk groups and without age as a risk factor. In this extensive retrospective registry-based study comparing 13 prognostic models, we suggest that NCCN-IPI should be reported as the reference model along with IPI in newly diagnosed DLBCL patients until more accurate validated prognostic models for DLBCL become available.

Advances in positron emission tomography and radiomics

Positron emission tomography is established for staging and response evaluation in lymphoma using visual evaluation and semi-quantitative analysis. Radiomic analysis involving quantitative imaging features at baseline, such as metabolic tumor volume and markers of disease dissemination and changes in the standardized uptake value during treatment are emerging as powerful biomarkers. The combination of radiomic features with clinical risk factors and genomic analysis offers the potential to improve clinical risk prediction. This review discusses the state of current knowledge, progress toward standardization of tumor delineation for radiomic analysis and argues that radiomic features, molecular markers and circulating tumor DNA should be included in clinical trial designs to enable the development of baseline and dynamic risk scores that could further advance the field to facilitate testing of novel treatments and personalized therapy in aggressive lymphomas.

PET/CT in Non-Hodgkin Lymphoma: An Update

Non-Hodgkin lymphomas represents a heterogeneous group of lymphoproliferative disorders characterized by different clinical courses, varying from indolent to highly aggressive. ¹⁸F-FDG-PET/CT is the current state-of-the-art diagnostic imaging, for the staging, restaging and evaluation of response to treatment in lymphomas with avidity for ¹⁸F-FDG, despite it is not routinely recommended for surveillance. PET-based response criteria (using five-point Deauville Score) are nowadays uniformly applied in FDG-avid lymphomas. In this review, a comprehensive overview of the role of ¹⁸F-FDG-PET in Non-Hodgkin lymphomas is provided, at each relevant point of patient management, particularly focusing on recent advances on diffuse large B-cell lymphoma and follicular lymphoma, with brief updates also on other histotypes (such as marginal zone, mantle cell, primary mediastinal- B cell lymphoma and T cell lymphoma). PET-derived semiquantitative factors useful for patient stratification and prognostication and emerging radiomics research are also presented.

Influence of the methodological aspects of the dichotomization of total metabolic tumor volume measured through baseline fluorine-18 fluorodeoxyglucose PET on survival prediction in lymphoma

OBJECTIVE

The total metabolic tumor volume (TMTV) measured from fluorine-18 fluorodeoxyglucose (18F-FDG) PET can be useful for determining the prognosis of patients with lymphoma. Stratifying patients into high- and low-TMTV risk groups requires a cutoff point, which is determined through the dichotomization method. This study investigated whether different TMTV dichotomization methods influenced survival prediction in patients with lymphoma.

METHODS

We retrospectively enrolled 129 patients with lymphoma who had undergone baseline 18F-FDG PET. TMTV was calculated using a fixed standardized uptake value threshold of 4.0. A total of six methods were employed to determine the optimal TMTV cutoff point using receiver-operating characteristic curve analyses, X-Tile bioinformatics software, and the Cutoff Finder web application. The prognostic performance of each method in survival prediction was examined.

RESULTS

The median (interquartile range) TMTV was 123 cm3 (21-335 cm3). The optimal TMTV cutoff values for predicting progression-free survival (PFS) and overall survival (OS) were in the range of 144-748 cm3. The cutoff points were used to dichotomize patients into two groups with distinct prognoses. All TMTV dichotomizations were significantly predictive of PFS and OS. The survival curves showed significant differences between the high- and low-TMTV groups. The C-indices of the survival models did not significantly differ in any of the dichotomizations.

CONCLUSION

The prognostic significance of TMTV was maintained regardless of the methodological aspects of dichotomization. However, the optimal TMTV cutoff point varied according to the chosen dichotomization method. Care should be taken when establishing an optimal TMTV cutoff point for clinical use.