Dynamic risk assessment based on positron emission tomography scanning in diffuse large B-cell lymphoma: Post-hoc analysis from the PETAL trial

Role of Novel Quantitative Imaging Techniques in Hematological Malignancies

Hematological malignancies exhibit a widespread distribution, necessitating evaluation of disease activity over the entire body. In clinical practice, visual analysis and semiquantitative parameters are used to assess 18F-FDGPET/CT imaging, which solely represents measurements of disease activity from limited area and may not adequately reflect global disease assessment. An efficient method for assessing the global disease burden of hematological malignancies is to employ PET/computed tomography based novel quantitative parameters. In this article, we explored novel quantitative parameters on PET/CT imaging for assessing global disease burden and the potential role of artificial intelligence (AI) to determine these parameters in evaluation of hematological malignancies.

Long-Axial Field-of-View PET Imaging in Patients with Lymphoma: Challenges and Opportunities

[18F]fluoro-2-deoxy-d-glucose PET/computed tomography has been implemented in the management of patients with lymphoma, offering real-time metabolic information on lymphoma with the promise of more accurate staging, treatment response assessment, prognostication, and early detection of disease recurrence. The clinical management of lymphoproliferative disease has recently, rapidly evolved from initial chemotherapeutic to the use of immunotherapy, targeted agents, and to the use of chimeric antigen receptor T-cell therapies. The implementation of these new systems and imaging protocols together with new tracer development creates, in the field of lymphoproliferative disease, both opportunities and challenges that will be detailed in this comprehensive literature review.

Metabolic parameters predict survival and toxicity in chimeric antigen receptor T-cell therapy-treated relapsed/refractory large B-cell lymphoma

CD19-targeted chimeric antigen receptor (CAR) T-cell therapy has revolutionized treatment for patients with relapsed/refractory large B-cell lymphoma (LBCL). However, data available concerning the impact of the prognostic value of quantitative 18F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT) parameters on the CAR T-related outcomes and toxicities are limited. Therefore, we aimed to evaluate the predictive value of pre- and post-CAR T metabolic parameters on survival and toxicities following CAR T-cell therapy. Fifty-nine patients with PET/CT scans done pre-and post-CAR T infusion were retrospectively identified and analyzed in a single institution database of LBCL patients treated with commercial CD19-targeted CAR T-cell therapy. The median follow-up was 10.7 months [interquartile range (IQR): 2.6-25.5 months]. The overall response (complete response-CR and partial response) and CR rates post-CAR T were 76% (n = 45) and 53% (n = 31), respectively. On univariate analysis, low pre-CAR T total lesion glycolysis (TLG) and metabolic tumor volume (MTV) predicted improved overall response post-CAR T (OR = 4.7, p = 0.01, OR = 9.5, p = 0.03, respectively) and CR post-CAR T (OR = 12.4, p = 0.0004, OR = 10.9, p = 0.0001, respectively). High TLG pre-CAR T was correlated with cytokine release syndrome (CRS, OR = 3.25, p = 0.04). High MTV pre-CAR T was correlated with developing immune effector cell neurotoxicity syndrome (ICANS) events (OR = 4.3, p = 0.01), and high SUV pre-CAR T was associated with grade 3-4 neurological events (OR = 12, p = 0.01). High MTV/TLG/SUVmax post-CAR T were significantly associated with inferior Overall survival (OS). On multivariate analysis, high TLG pre-CAR T (HR = 2.4, p = 0.03), age ≥60 (HR = 2.7, p = 0.03), and bulky disease (≥5 cm) at the time of apheresis (HR = 2.5, p = 0.02) were identified to be independent prognostic factors for inferior PFS. High MTV post-CAR T was identified as the most prognostic factor associated with inferior OS.

Outcome prediction by interim positron emission tomography and IgM monoclonal gammopathy in diffuse large B-cell lymphoma

In diffuse large B-cell lymphoma (DLBCL), a positive interim positron emission tomography (PET) scan predicts treatment failure, but the proportion of high-risk patients thus identified is small. To improve prediction, we combined the interim PET result with the presence or absence of an associated IgM gammopathy. Of 108 DLBCL patients participating in a prospective trial, nine (8%) were interim PET positive and 19 (18%) had an IgM gammopathy. The monoclonal protein was not associated with distinguishing genetic features, and its light chain restriction was not always concordant with the light chain restriction of the lymphoma. The information provided by interim PET and IgM gammopathy was combined to dichotomize the population into sizeable high-risk (1-2 adverse factors) and low-risk groups (no adverse factor) with widely different outcomes (population size, 25% vs. 75%; 3-year risk of progression, 51% vs. 10%; 3-year overall survival, 64% vs. 95%). Multivariable analyses including established risk factors revealed the interim PET result and the IgM gammopathy status to be the only factors significantly associated with outcome. Information about interim PET response and IgM gammopathy may be useful in studies testing risk-adapted treatment strategies.

Dissemination feature based on PET/CT is a risk factor for diffuse large B cell lymphoma patients outcome

BACKGROUND

18F-FDG PET/CT provides precise information about dissemination of lymphoma lesions. Dmax, defined as distance between the two lesions that were farthest apart by PET/CT, was found to be a promising predictor of Diffuse large B-cell lymphoma (DLBCL) outcome in a small size of clinical trial data. We analyzed the impact of Dmax on the outcome of a large real-world DLBCL cohort.

METHODS

Data of newly diagnosed DLBCL at the Third Affiliated Hospital of Soochow University were retrospectively collected. Baseline Dmax, clinical data and survival information were recorded. A metabolic parameter, metabolic bulk volume (MBV), was also measured to verify the independent impact of Dmax.

RESULTS

Optimal cut-off values for Dmax and MBV were 45.34 cm and 21.65 cm3. With a median follow-up of 32 months, Dmax significantly impacted progression-free survival (PFS) and overall survival (OS) in 253 DLBCL patients. For Dmaxlow and Dmaxhigh groups, estimated 3-year OS were 87.0% and 53.8% (p < 0.001), while 3-year PFS were 77.3% and 37.3% (p < 0.001). And for MBVlow and MBVhighgroups, 3-year OS were 84.5% and 58.8% (p < 0.001), and 3-year PFS were 68.7% and 50.4% (p = 0.003). Multivariate analysis identified Dmax and Eastern Cooperative Oncology Group performance status (ECOG PS) independently associated with PFS and OS, while MBV only independently associated with OS. A Dmax revised prognostic index (DRPI) combining Dmax and ECOG PS identified an ultra-risk DLBCL population with 3-year PFS of 31.7% and 3-year OS of 38.5%. The area under the curve (AUC) showed that this model performed better than International prognostic Index (IPI).

CONCLUSION

Dmax is a new and promising indicator to investigate dissemination of lymphoma lesions associated with the outcome of DLBCL. It significantly contributes to stratification of patients with disparate outcomes.

TRIAL REGISTRATION

This research has been retrospectively registered in the Ethics Committee institutional of the Third Affiliated Hospital of Soochow University, and the registration number was approval No. 155 (approved date: 31 May 2022).

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.

Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma in adults. Standard treatment includes chemoimmunotherapy with R-CHOP or similar regimens. Despite treatment advancements, many patients with DLBCL experience refractory disease or relapse. While baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) parameters have shown promise in predicting survival, they may not fully capture lesion heterogeneity. This study aimed to assess the prognostic value of baseline 18F-FDG PET radiomics features in comparison with clinical factors and metabolic parameters for assessing 2-year progression-free survival (PFS) and 5-year overall survival (OS) in patients with DLBCL.

RESULTS

A total of 201 patients with DLBCL were enrolled in this study, and 1328 radiomics features were extracted. The radiomics signatures, clinical factors, and metabolic parameters showed significant prognostic value for individualized prognosis prediction in patients with DLBCL. Radiomics signatures showed the lowest Akaike information criterion (AIC) value and highest Harrell's concordance index (C-index) value in comparison with clinical factors and metabolic parameters for both PFS (AIC: 571.688 vs. 596.040 vs. 576.481; C-index: 0.732 vs. 0.658 vs. 0.702, respectively) and OS (AIC: 339.843 vs. 363.671 vs. 358.412; C-index: 0.759 vs. 0.667 vs. 0.659, respectively). Statistically significant differences were observed in the area under the curve (AUC) values between the radiomics signatures and clinical factors for both PFS (AUC: 0.768 vs. 0.681, P = 0.017) and OS (AUC: 0.767 vs. 0.667, P = 0.023). For OS, the AUC of the radiomics signatures were significantly higher than those of metabolic parameters (AUC: 0.767 vs. 0.688, P = 0.007). However, for PFS, no significant difference was observed between the radiomics signatures and metabolic parameters (AUC: 0.768 vs. 0.756, P = 0.654). The combined model and the best-performing individual model (radiomics signatures) alone showed no significant difference for both PFS (AUC: 0.784 vs. 0.768, P = 0.163) or OS (AUC: 0.772 vs. 0.767, P = 0.403).

CONCLUSIONS

Radiomics signatures derived from PET images showed the high predictive power for progression in patients with DLBCL. The combination of radiomics signatures, clinical factors, and metabolic parameters may not significantly improve predictive value beyond that of radiomics signatures alone.

Development of a radiomic-clinical nomogram for prediction of survival in patients with diffuse large B-cell lymphoma treated with chimeric antigen receptor T cells

BACKGROUND

In our current work, an 18F-FDG PET/CT radiomics-based model was developed to assess the progression-free survival (PFS) and overall survival (OS) of patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who received chimeric antigen receptor (CAR)-T cell therapy.

METHODS

A total of 61 DLBCL cases receiving 18F-FDG PET/CT before CAR-T cell infusion were included in the current analysis, and these patients were randomly assigned to a training cohort (n = 42) and a validation cohort (n = 19). Radiomic features from PET and CT images were obtained using LIFEx software, and radiomics signatures (R-signatures) were then constructed by choosing the optimal parameters according to their PFS and OS. Subsequently, the radiomics model and clinical model were constructed and validated.

RESULTS

The radiomics model that integrated R-signatures and clinical risk factors showed superior prognostic performance compared with the clinical models in terms of both PFS (C-index: 0.710 vs. 0.716; AUC: 0.776 vs. 0.712) and OS (C-index: 0.780 vs. 0.762; AUC: 0.828 vs. 0.728). For validation, the C-index of the two approaches was 0.640 vs. 0.619 and 0.676 vs. 0.699 for predicting PFS and OS, respectively. Moreover, the AUC was 0.886 vs. 0.635 and 0.778 vs. 0.705, respectively. The calibration curves indicated good agreement, and the decision curve analysis suggested that the net benefit of radiomics models was higher than that of clinical models.

CONCLUSIONS

PET/CT-derived R-signature could be a potential prognostic biomarker for R/R DLBCL patients undergoing CAR-T cell therapy. Moreover, the risk stratification could be further enhanced when the PET/CT-derived R-signature was combined with clinical factors.

Sensitivity of an AI method for [18F]FDG PET/CT outcome prediction of diffuse large B-cell lymphoma patients to image reconstruction protocols

BACKGROUND

Convolutional neural networks (CNNs), applied to baseline [18F]-FDG PET/CT maximum intensity projections (MIPs), show potential for treatment outcome prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study is to investigate the robustness of CNN predictions to different image reconstruction protocols. Baseline [18F]FDG PET/CT scans were collected from 20 DLBCL patients. EARL1, EARL2 and high-resolution (HR) protocols were applied per scan, generating three images with different image qualities. Image-based transformation was applied by blurring EARL2 and HR images to generate EARL1 compliant images using a Gaussian filter of 5 and 7 mm, respectively. MIPs were generated for each of the reconstructions, before and after image transformation. An in-house developed CNN predicted the probability of tumor progression within 2 years for each MIP. The difference in probabilities per patient was then calculated between both EARL2 and HR with respect to EARL1 (delta probabilities or ΔP). We compared these to the probabilities obtained after aligning the data with ComBat using the difference in median and interquartile range (IQR).

RESULTS

CNN probabilities were found to be sensitive to different reconstruction protocols (EARL2 ΔP: median = 0.09, interquartile range (IQR) = [0.06, 0.10] and HR ΔP: median = 0.1, IQR = [0.08, 0.16]). Moreover, higher resolution images (EARL2 and HR) led to higher probability values. After image-based and ComBat transformation, an improved agreement of CNN probabilities among reconstructions was found for all patients. This agreement was slightly better after image-based transformation (transformed EARL2 ΔP: median = 0.022, IQR = [0.01, 0.02] and transformed HR ΔP: median = 0.029, IQR = [0.01, 0.03]).

CONCLUSION

Our CNN-based outcome predictions are affected by the applied reconstruction protocols, yet in a predictable manner. Image-based harmonization is a suitable approach to harmonize CNN predictions across image reconstruction protocols.

Quantitative PET-based biomarkers in lymphoma: getting ready for primetime

The use of functional quantitative biomarkers extracted from routine PET-CT scans to characterize clinical responses in patients with lymphoma is gaining increased attention, and these biomarkers can outperform established clinical risk factors. Total metabolic tumour volume enables individualized estimation of survival outcomes in patients with lymphoma and has shown the potential to predict response to therapy suitable for  risk-adapted treatment approaches in clinical trials. The deployment of machine learning tools in molecular imaging research can assist in recognizing complex patterns and, with image classification, in tumour identification and segmentation of data from PET-CT scans. Initial studies using fully automated approaches to calculate metabolic tumour volume and other PET-based biomarkers have demonstrated appropriate correlation with calculations from experts, warranting further testing in large-scale studies. The extraction of computer-based quantitative tumour characterization through radiomics can provide a comprehensive view of phenotypic heterogeneity that better captures the molecular and functional features of the disease. Additionally, radiomics can be integrated with genomic data to provide more accurate prognostic information. Further improvements in PET-based biomarkers are imminent, although their incorporation into clinical decision-making currently has methodological shortcomings that need to be addressed with confirmatory prospective validation in selected patient populations. In this Review, we discuss the current knowledge, challenges and opportunities in the integration of quantitative PET-based biomarkers in clinical trials and the routine management of patients with lymphoma.

Efficacy and safety of zanubrutinib plus R-CHOP in treatment of non-GCB DLBCL with extranodal involvement

Introduction

Treatment with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) shows poor response rates in non-germinal center B cell-like (non-GCB) diffuse large B-cell lymphoma (DLBCL) patients with multiple extranodal involvement. This study aims to evaluate anti-tumor activity and safety of zanubrutinib with R-CHOP (ZR-CHOP) in treatment naïve non-GCB DLBCL with extranodal involvement.

Methods

In this single-arm, phase 2, prospective, single-center study, patients with newly diagnosed non-GCB DLBCL with extranodal involvement enrolled between October 2020 to March 2022 received ZR-CHOP for 6 cycles followed by 2 cycles of maintenance treatment with rituximab and zanubrutinib. The primary endpoint included progression-free survival (PFS) in the intent-to-treat (ITT) population whereas the secondary endpoints included overall response rate (ORR), complete response (CR), and duration of response. Further, next-generation sequencing (NGS) was used for detection of different oncogenic mutations closely related to DLBCL pathogenesis.

Results

From October 2020 to March 2022, 26 patients were enrolled, and 23 of them were evaluated for efficacy after receiving 3 cycles of ZR-CHOP treatment. 1-year PFS and OS were 80.8% and 88.5% respectively while expected PFS and OS for 2-years are 74.0% and 88.5% respectively with median follow-up of 16.7 months and ORR was 91.3% (CR: 82.61%; PR: 8.70%). Oncogenic mutations closely related to DLBCL pathogenesis were assessed in 20 patients using NGS. B-cell receptor and NF-κB pathway gene mutations were detected in 10 patients, which occurred in MYD88 (7/19), CD79B (4/19), CARD11 (5/19), and TNFAIP3 (2/19). Hematological adverse events (AEs) ≥ grade 3 included neutropenia (50%), thrombocytopenia (23.1%), and anemia (7.7%) whereas non-hematological AEs ≥ grade 3 included pulmonary infection (19.2%).

Conclusion

ZR-CHOP is safe and effective for treating treatment naïve non-GCB DLBCL patients with extranodal involvement.

Clinical Trial Registration

Clinicaltrials.gov, NCT04835870.

An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients

Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to investigate the feasibility of a CNN using maximum intensity projection (MIP) images from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) baseline scans to predict the probability of time-to-progression (TTP) within 2 years and compare it with the International Prognostic Index (IPI), i.e. a clinically used score. 296 DLBCL 18F-FDG PET/CT baseline scans collected from a prospective clinical trial (HOVON-84) were analysed. Cross-validation was performed using coronal and sagittal MIPs. An external dataset (340 DLBCL patients) was used to validate the model. Association between the probabilities, metabolic tumour volume and Dmaxbulk was assessed. Probabilities for PET scans with synthetically removed tumors were also assessed. The CNN provided a 2-year TTP prediction with an area under the curve (AUC) of 0.74, outperforming the IPI-based model (AUC = 0.68). Furthermore, high probabilities (> 0.6) of the original MIPs were considerably decreased after removing the tumours (< 0.4, generally). These findings suggest that MIP-based CNNs are able to predict treatment outcome in DLBCL.

A novel prognostic index for diffuse large B-cell lymphoma combined baseline metabolic tumour volume with clinical and pathological risk factors

OBJECTIVES

This study aimed to develop a novel prognostic index integrating baseline metabolic tumour volume (MTV) along with clinical and pathological parameters for diffuse large B-cell lymphoma (DLBCL).

METHODS

This prospective trial enrolled 289 patients with newly diagnosed DLBCL. The predictive value of novel prognostic index was compared with Ann Arbor staging and National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI). We used the concordance index (C-index) and a calibration curve to determine its predictive capacity.

RESULTS

Multivariate analysis revealed high MTV (>191 cm 3 ), Ann Arbor stage (III-IV) and MYC/BCL2 double expression lymphoma (DEL) to be independently associated with inferior progression-free survival (PFS) and overall survival (OS). Ann Arbor stage and DEL could be stratified by MTV. Our index, combining MTV with Ann Arbor stage and DEL status, identified four prognostic groups: group 1 (no risk factors,), group 2 (one risk factor), group 3 (two risk factors), and group 4 (three risk factors). The 2-year PFS rates were 85.5, 73.9, 53.6, and 13.9%; 2-year OS rates were 94.6, 87.0, 67.5, and 24.2%, respectively. The C-index values of the novel index were 0.697 and 0.753 for PFS and OS prediction, which was superior to Ann Arbor stage and NCCN-IPI.

CONCLUSION

The novel index including tumour burden and clinicopathological features may help predict outcome of DLBCL (clinicaltrials.gov identifier: NCT02928861).

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.

Interim FDG-PET/CT for Response Assessment of Lymphoma

The clinical use and prognostic value of interim FDG-PET/CT (iPET/CT), which is performed after treatment initiation but prior to its completion, varies by lymphoma subtype. Evidence supporting the prognostic value of iPET/CT is more robust for classical Hodgkin lymphoma (cHL), and in this lymphoma subtype, response-adapted treatment approaches guided by iPET/CT are a widely used standard of care for first-line therapy. The data supporting use of iPET/CT among patients with non-Hodgkin lymphoma (NHL) is less well-established, but failure to achieve complete metabolic response on iPET/CT is generally considered a poor prognostic factor with likely consequences for progression free survival. This review will present the available evidence supporting use of iPET/CT in lymphoma patients, particularly as it relates to prognostication and the ability to inform response-adapted treatment strategies. The latter will be addressed through a discussion on the major iPET-response adapted clinical trials with mention of ongoing trials. Special attention will be given to cHL and a few subtypes of NHL, including diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), and peripheral T cell lymphoma (PTCL).

FDG-PET/CT in the Monitoring of Lymphoma Immunotherapy Response: Current Status and Future Prospects

Cancer immunotherapy has been extensively investigated in lymphoma over the last three decades. This new treatment modality is now established as a way to manage and maintain several stages and subtypes of lymphoma. The establishment of this novel therapy has necessitated the development of new imaging response criteria to evaluate and follow up with cancer patients. Several FDG PET/CT-based response criteria have emerged to address and encompass the various most commonly observed response patterns. Many of the proposed response criteria are currently being used to evaluate and predict responses. The purpose of this review is to address the efficacy and side effects of cancer immunotherapy and to correlate this with the proposed criteria and relevant patterns of FDG PET/CT in lymphoma immunotherapy as applicable. The latest updates and future prospects in lymphoma immunotherapy, as well as PET/CT potentials, will be discussed.

Interim FDG18-PET SUVmax Variation Adds Prognostic Value to Deauville 5-Point Scale in the Identification of Patients with Ultra-High-Risk Diffuse Large B Cell Lymphoma

INTRODUCTION

Interim response evaluation by ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (iPET) in diffuse large B cell lymphoma (DLBCL) could be important to rule out disease progression and has been suggested to be predictive of survival. However, treatment guidance by iPET is not yet recommended for DLBCL in clinical practice. We aimed to compare the predictive value of iPET when utilizing the visual Deauville 5-point scale (DS) and the semiquantitative variation of maximum standardized uptake value (ΔSUV_max).

MATERIALS AND METHODS

We included 85 patients diagnosed with DLBCL and uniformly treated with standard protocols. iPET with DS of 1-3 and/or ΔSUV_max ≥66% was defined as negative. Univariable and multivariable Cox regression analyses were performed to determine the independent factors affecting progression free survival (PFS) or overall survival (OS) and to estimate PFS and OS.

RESULTS

iPET positivity, measured by DS or ΔSUV_max, showed predictive value of disease refractoriness, improved by combining DS and ΔSUV_max. After a median follow-up of 50.1 months, iPET was an independent predictor for both PFS and OS when interpreted by DS, but only for PFS by ΔSUV_max. Combined visual and semiquantitative analysis (D4-5 & ΔSUV_max<66%) was an independent predictor of PFS and OS, and allowed to identify an ultra-high-risk subgroup of patients with very dismal outcome, increasing the discriminating capacity for iPET.

CONCLUSION

Our study suggests that combined DS and ΔSUV_max in iPET assessment predicts refractory disease and distinguishes ultra-high-risk DLBCL patients with a very dismal prognosis, who may benefit from PET-guided therapy adjustment.

Semi-automated 18F-FDG PET segmentation methods for tumor volume determination in Non-Hodgkin lymphoma patients: a literature review, implementation and multi-threshold evaluation

In the treatment of Non-Hodgkin lymphoma (NHL), multiple therapeutic options are available. Improving outcome predictions are essential to optimize treatment. The metabolic active tumor volume (MATV) has shown to be a prognostic factor in NHL. It is usually retrieved using semi-automated thresholding methods based on standardized uptake values (SUV), calculated from ¹⁸F-Fluorodeoxyglucose Positron Emission Tomography (¹⁸F-FDG PET) images. However, there is currently no consensus method for NHL. The aim of this study was to review literature on different segmentation methods used, and to evaluate selected methods by using an in house created software tool. A software tool, MUltiple SUV Threshold (MUST)-segmenter was developed where tumor locations are identified by placing seed-points on the PET images, followed by subsequent region growing. Based on a literature review, 9 SUV thresholding methods were selected and MATVs were extracted. The MUST-segmenter was utilized in a cohort of 68 patients with NHL. Differences in MATVs were assessed with paired t-tests, and correlations and distributions figures. High variability and significant differences between the MATVs based on different segmentation methods (p < 0.05) were observed in the NHL patients. Median MATVs ranged from 35 to 211 cc. No consensus for determining MATV is available based on the literature. Using the MUST-segmenter with 9 selected SUV thresholding methods, we demonstrated a large and significant variation in MATVs. Identifying the most optimal segmentation method for patients with NHL is essential to further improve predictions of toxicity, response, and treatment outcomes, which can be facilitated by the MUST-segmenter.

18F-FDG PET Maximum-Intensity Projections and Artificial Intelligence: A Win-Win Combination to Easily Measure Prognostic Biomarkers in DLBCL Patients

Total metabolic tumor volume (TMTV) and tumor dissemination (Dmax) calculated from baseline ¹⁸F-FDG PET/CT images are prognostic biomarkers in diffuse large B-cell lymphoma (DLBCL) patients. Yet, their automated calculation remains challenging. The purpose of this study was to investigate whether TMTV and Dmax features could be replaced by surrogate features automatically calculated using an artificial intelligence (AI) algorithm from only 2 maximum-intensity projections (MIPs) of the whole-body ¹⁸F-FDG PET images. Methods: Two cohorts of DLBCL patients from the REMARC (NCT01122472) and LNH073B (NCT00498043) trials were retrospectively analyzed. Experts delineated lymphoma lesions from the baseline whole-body ¹⁸F-FDG PET/CT images, from which TMTV and Dmax were measured. Coronal and sagittal MIP images and associated 2-dimensional reference lesion masks were calculated. An AI algorithm was trained on the REMARC MIP data to segment lymphoma regions. The AI algorithm was then used to estimate surrogate TMTV (sTMTV) and surrogate Dmax (sDmax) on both datasets. The ability of the original and surrogate TMTV and Dmax to stratify patients was compared. Results: Three hundred eighty-two patients (mean age ± SD, 62.1 y ± 13.4 y; 207 men) were evaluated. sTMTV was highly correlated with TMTV for REMARC and LNH073B datasets (Spearman r = 0.878 and 0.752, respectively), and so were sDmax and Dmax (r = 0.709 and 0.714, respectively). The hazard ratios for progression free survival of volume and MIP-based features derived using AI were similar, for example, TMTV: 11.24 (95% CI: 2.10-46.20), sTMTV: 11.81 (95% CI: 3.29-31.77), and Dmax: 9.0 (95% CI: 2.53-23.63), sDmax: 12.49 (95% CI: 3.42-34.50). Conclusion: Surrogate TMTV and Dmax calculated from only 2 PET MIP images are prognostic biomarkers in DLBCL patients and can be automatically estimated using an AI algorithm.

Interim FDG-PET analysis to identify patients with aggressive non-Hodgkin lymphoma who benefit from treatment intensification: a post-hoc analysis of the PETAL trial

The randomized PETAL trial failed to demonstrate a benefit of interim FDG-PET (iPET)-based treatment intensification over continued standard therapy with CHOP (plus rituximab (R) in CD20-positive lymphomas). We hypothesized that PET analysis of all lymphoma manifestations may identify patients who benefitted from treatment intensification. A previously developed neural network was employed for iPET analysis to identify the highest pathological FDG uptake (max-SUVAI) and the mean FDG uptake of all lymphoma manifestations (mean-SUVAI). High mean-SUVAI uptake was determined separately for iPET-positive and iPET-negative patients. The endpoint was time-to-progression (TTP). There was a significant interaction of additional rituximab and mean-SUVAI in the iPET-negative group (HR = 0.6, p < 0.05). Patients with high mean-SUVAI had significantly prolonged TTP when treated with 6xR-CHOP + 2 R (not reached versus 52 months, p < 0.05), whereas max-SUVmanual failed to show an impact of additional rituximab. In the iPET-positive group, patients with high mean-SUVAI had a significantly longer TTP with (R-)CHOP than with the Burkitt protocol (14 versus 4 months, p < 0.01). Comprehensive iPET evaluation may provide new prognosticators in aggressive lymphoma. Additional application of rituximab was associated with prolonged TTP in iPET-negative patients with high mean-SUVAI. Comprehensive iPET interpretation could identify high-risk patients who benefit from study-specific interventions.

Baseline radiomics features and MYC rearrangement status predict progression in aggressive B-cell lymphoma

We investigated whether the outcome prediction of patients with aggressive B-cell lymphoma can be improved by combining clinical, molecular genotype, and radiomics features. MYC, BCL2, and BCL6 rearrangements were assessed using fluorescence in situ hybridization. Seventeen radiomics features were extracted from the baseline positron emission tomography-computed tomography of 323 patients, which included maximum standardized uptake value (SUVmax), SUVpeak, SUVmean, metabolic tumor volume (MTV), total lesion glycolysis, and 12 dissemination features pertaining to distance, differences in uptake and volume between lesions, respectively. Logistic regression with backward feature selection was used to predict progression after 2 years. The predictive value of (1) International Prognostic Index (IPI); (2) IPI plus MYC; (3) IPI, MYC, and MTV; (4) radiomics; and (5) MYC plus radiomics models were tested using the cross-validated area under the curve (CV-AUC) and positive predictive values (PPVs). IPI yielded a CV-AUC of 0.65 ± 0.07 with a PPV of 29.6%. The IPI plus MYC model yielded a CV-AUC of 0.68 ± 0.08. IPI, MYC, and MTV yielded a CV-AUC of 0.74 ± 0.08. The highest model performance of the radiomics model was observed for MTV combined with the maximum distance between the largest lesion and another lesion, the maximum difference in SUVpeak between 2 lesions, and the sum of distances between all lesions, yielding an improved CV-AUC of 0.77 ± 0.07. The same radiomics features were retained when adding MYC (CV-AUC, 0.77 ± 0.07). PPV was highest for the MYC plus radiomics model (50.0%) and increased by 20% compared with the IPI (29.6%). Adding radiomics features improved model performance and PPV and can, therefore, aid in identifying poor prognosis patients.

Metabolic Imaging in B-Cell Lymphomas during CAR-T Cell Therapy

Simple Summary

Chimeric antigen receptor–engineered T cells are an innovative therapy in hematologic malignancies, especially in patients with refractory/relapsed B-cell lymphomas. Few studies have analyzed the role of [¹⁸F]FDG PET/CT in this field; this review aims to illustrate the literature data and the major findings related to [¹⁸F]FDG PET/CT use during CAR-T cell therapy in B-cell lymphomas, focusing on the prognostic value of metabolic parameters, as well as on response assessment. Furthermore, this work shows in detail the specific adverse events during CAR-T cell therapy and the role of [¹⁸F]FDG PET/CT imaging in their occurrence.

Abstract

Chimeric antigen receptor–engineered (CAR) T cells are emerging powerful therapies for patients with refractory/relapsed B-cell lymphomas. [¹⁸F]FDG PET/CT plays a key role during staging and response assessment in patients with lymphoma; however, the evidence about its utility in CAR-T therapies for lymphomas is limited. This review article aims to provide an overview of the role of PET/CT during CAR-T cell therapy in B-cell lymphomas, focusing on the prognostic value of metabolic parameters, as well as on response assessment. Data from the literature report on the use of [¹⁸F]FDG PET/CT at the baseline with two scans performed before treatment started focused on the time of decision (TD) PET/CT and time of transfusion (TT) PET/CT. Metabolic tumor burden is the most studied parameter associated with disease progression and overall survival, making us able to predict the occurrence of adverse effects. Instead, for post-therapy evaluation, 1 month (M1) PET/CT seems the preferable time slot for response assessment and in this setting, the Deauville 5-point scale (DS), volumetric analyses, SUVmax, and its variation between different time points (∆SUVmax) have been evaluated, confirming the usefulness of M1 PET/CT, especially in the case of pseudoprogression. Additionally, an emerging role of PET/CT brain scans is reported for the evaluation of neurotoxicity related to CAR-T therapies. Overall, PET/CT results to be an accurate method in all phases of CAR-T treatment, with particular interest in assessing treatment response. Moreover, PET parameters have been reported to be reliable predictors of outcome and severe toxicity.

A tumor volume and performance status model to predict outcome before treatment in diffuse large B-cell lymphoma

Aggressive large B-cell lymphoma (LBCL) has variable outcomes. Current prognostic tools use factors for risk stratification that inadequately identify patients at high risk of refractory disease or relapse before initial treatment. A model associating 2 risk factors, total metabolic tumor volume (TMTV) >220 cm3 (determined by fluorine-18 fluorodeoxyglucose positron emission tomography coupled with computed tomography) and performance status (PS) ≥2, identified as prognostic in 301 older patients in the REMARC trial (#NCT01122472), was validated in 2174 patients of all ages treated in 2 clinical trials, PETAL (Positron Emission Tomography-Guided Therapy of Aggressive Non-Hodgkin Lymphomas; N = 510) and GOYA (N = 1315), and in real-world clinics (N = 349) across Europe and the United States. Three risk categories, low (no factors), intermediate (1 risk factor), and high (2 risk factors), significantly discriminated outcome in most of the series. Patients with 2 risk factors had worse outcomes than patients with no risk factors in the PETAL, GOYA, and real-world series. Patients with intermediate risk also had significantly worse outcomes than patients with no risk factors. The TMTV/Eastern Cooperative Oncology Group-PS combination outperformed the International Prognostic Index with a positive C-index for progression-free survival and overall survival in most series. The combination of high TMTV > 220 cm3 and ECOG-PS ≥ 2 is a simple clinical model to identify aggressive LBCL risk categories before treatment. This combination addresses the unmet need to better predict before treatment initiation for aggressive LBCL the patients likely to benefit the most or not at all from therapy.

The value of FDG PET/CT imaging in outcome prediction and response assessment of lymphoma patients treated with immunotherapy: a meta-analysis and systematic review

PURPOSE

Treatment strategies of lymphoid malignancies have been revolutionized by immunotherapy. Because of the inherent property of Hodgkin lymphoma and some subtypes of non-Hodgkin lymphoma as a highly FDG-avid tumor, functional ¹⁸F-FDG PET/CT imaging is already embedded in their routine care. Nevertheless, the question is whether it is still valuable in the context of these tumors being treated with immunotherapy. Herein, we will review the value of ¹⁸F-FDG PET/CT imaging lymphoid tumors treated with immunotherapy regimens.

METHODS

A comprehensive literature search of the PubMed database was conducted on the value of the ¹⁸F-FDG PET/CT for immunotherapy response monitoring of patients with malignant lymphoma. The articles were considered eligible if they met all of the following inclusion criteria: (a) clinical studies on patients with different types of malignant lymphoma, (b) treatment with anti-CD20 antibodies, immune checkpoint inhibitors or immune cell therapies, (c) and incorporated PET/CT with ¹⁸F-FDG as the PET tracer.

RESULTS

From the initial 1488 papers identified, 91 were ultimately included in our study. In anti-CD20 therapy, the highest pooled hazard ratios (HRs) of baseline, early, and late response monitoring parameters for progression-free survival (PFS) belong to metabolic tumor volume (MTV) (3.19 (95%CI: 2.36-4.30)), maximum standardized uptake value (SUVmax) (3.25 (95%CI: 2.08-5.08)), and Deauville score (DS) (3.73 (95%CI: 2.50-5.56)), respectively. These measurements for overall survival (OS) were MTV (4.39 (95%CI: 2.71-7.08)), DS (3.23 (95%CI: 1.87-5.58)), and DS (3.64 (95%CI: 1.40-9.43)), respectively. Early and late ¹⁸F-FDG PET/CT response assessment in immune checkpoint inhibitors (ICI) and immune cell therapy might be an effective tool for prediction of clinical outcome.

CONCLUSION

For anti-CD20 therapy of lymphoma, the MTV as a baseline ¹⁸F-FDG PET/CT-derived parameter has the highest HRs for PFS and OS. The DS as visual criteria in early and late response assessment has higher HRs for PFS and OS compared to the international harmonization project (IHP) visual criteria in anti-CD20 therapy. Early changes in ¹⁸F-FDG PET parameters may be predictive of response to ICIs and cell therapy in lymphoma patients.

Baseline Total Metabolic Tumor Volume is Prognostic for Refractoriness to Immunochemotherapy in DLBCL: Results From GOYA

INTRODUCTION

A good response to initial therapy is key to maximizing survival in patients with diffuse large B-cell lymphoma (DLBCL), but patients with chemorefractory disease and early progression have poor outcomes.

PATIENTS AND METHODS

Data from the GOYA study in patients with DLBCL who received first-line rituximab or obinutuzumab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) were analyzed. Positron emission tomography/computed tomography (PET/CT)-derived characteristics associated with total metabolic tumor volume (TMTV) and clinical risk factors for primary chemorefractory disease and disease progression within 12 months (POD12) were explored.

RESULTS

Of those patients fulfilling the criteria for analysis, 108/1126 (10%) were primary chemorefractory and 147/1106 (13%) had POD12. Primary chemorefractory and POD12 status were strongly associated with reduced overall survival. After multivariable analysis of clinical and imaging-based risk factors by backward elimination, only very high TMTV (quartile [Q] 1 vs. Q4 odds ratio [OR]: 0.45; P = .006) and serum albumin levels (low vs. normal OR of 1.86; P = .004) were associated with primary chemorefractoriness. After additionally accounting for BCL2/MYC translocation in a subset of patients, TMTV and BCL2/MYC double-hit status remained as significant predictors of primary chemorefractoriness (Q1 vs. Q4 OR: 0.32, P = .01 and double-hit vs. no-hit OR of 4.47, P = .02, respectively). Risk factors including very high TMTV, high sum of the product of the longest diameters (SPD), geographic region (Asia), short time since diagnosis, extranodal involvement and low serum albumin were retained for POD12.

CONCLUSION

PET-derived TMTV has prognostic value in identifying patients at risk of early treatment failure.

Proposed New Dynamic Prognostic Index for Diffuse Large B-Cell Lymphoma: International Metabolic Prognostic Index

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.

18F-FDG PET Improves Baseline Clinical Predictors of Response in Diffuse Large B-Cell Lymphoma: The HOVON-84 Study

We aimed to determine the added value of baseline metabolic tumor volume (MTV) and interim PET (I-PET) to the age-adjusted international prognostic index (aaIPI) to predict 2-y progression-free survival (PFS) in diffuse large B-cell lymphoma. Secondary objectives were to investigate optimal I-PET response criteria (using Deauville score [DS] or quantitative change in SUV_max [ΔSUV_max] between baseline and I-PET4 [observational I-PET scans after 4 cycles of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone administered in 2-wk intervals with intensified rituximab in the first 4 cycles [R(R)-CHOP14]). Methods: I-PET4 scans in the HOVON-84 (Hemato-Oncologie voor Volwassenen Nederland [Haemato Oncology Foundation for Adults in the Netherlands]) randomized clinical trial (EudraCT 2006-005174-42) were centrally reviewed using DS (cutoff, 4-5). Additionally, ΔSUV_max (prespecified cutoff, 70%) and baseline MTV were measured. Multivariable hazard ratio (HR), positive predictive value (PPV), and negative predictive value (NPV) were obtained for 2-y PFS. Results: In total, 513 I-PET4 scans were reviewed according to DS, and ΔSUV_max and baseline MTV were available for 367 and 296 patients. The NPV of I-PET ranged between 82% and 86% for all PET response criteria. Univariate HR and PPV were better for ΔSUV_max (4.8% and 53%, respectively) than for DS (3.1% and 38%, respectively). aaIPI and ΔSUV_max independently predicted 2-y PFS (HR, 3.2 and 5.0, respectively); adding MTV brought about a slight improvement. Low or low-intermediate aaIPI combined with a ΔSUV_max of more than 70% (37% of patients) yielded an NPV of 93%, and the combination of high-intermediate or high aaIPI and a ΔSUV_max of 70% or less yielded a PPV of 65%. Conclusion: In this study on diffuse large B-cell lymphoma, I-PET after 4 cycles of R(R)-CHOP14 added predictive value to aaIPI for 2-y PFS, and both were independent response biomarkers in a multivariable Cox model. We externally validated that ΔSUV_max outperformed DS in 2-y PFS prediction.

Risk Assessment in Diffuse Large B-Cell Lymphoma by Combining Baseline Metabolic Tumor Volume and Peking Criteria When Evaluating Series 18F-Fluorodeoxyglucose Positron Emission Tomography Scans

This study aimed to determine the predictive and prognostic value of baseline metabolic tumor volume (MTV) and the Peking criteria from serial positron emission tomography (PET) scans in diffuse large B-cell lymphoma, including 300 newly diagnosed patients who were prospectively treated with 2–4 cycles of standard first-line treatment (clinicaltrials.gov identifier: NCT02928861). PET/computed tomography (CT) examinations were performed at baseline, after two (PET-2) or four cycles (PET-4). PET during the interim was evaluated using Deauville 5-point scales (5-PS), ΔSUV_max criteria, and the Peking criteria which interpreted based on the maximum standard uptake of the liver (SUV_max-liver). Peking criteria had better accuracy, positive predictive value (PPV), and specificity than other two methods. The MTV and Peking criteria both significantly predicted progression-free survival (PFS) and overall survival (OS). An MTV > 191 cm² and Peking criteria of PET-2 and PET-4 > 1.6-fold SUV_max-liver was used as the cutoff for a positive result. PET-4 achieved higher accuracy, PPV, and specificity for 2-year PFS (83.3%, 86.7%, and 98.4%, respectively) and OS (92.6%, 73.3%, and 97.2%, respectively) than PET-2. Various prognostic models containing different risk factors were established via Cox regression analysis. The MTV and PET-2/PET-4 results were used to categorized patients into low-risk, intermediate-risk, and high-risk prognostic groups (with 0, 1, and 2 risk factors, respectively) (P < 0.0001). High burden MTV and positive PET-2 and PET-4 (>1.6-fold SUV_max-liver) could identify high-risk patients with 2-year PFS and OS of 0.0% and 26.3% (95% confidence interval [CI]: N/A to 54.3%). When PET-2 and PET-4 were evaluated by 5-PS, the 2-year PFS and OS from high risk patients of three-parameters model achieved 31.4% (95%CI: 6.9%–55.9%) and 42.7% (95%CI: 14.6%–70.7%). In conclusion, combining baseline MTV and any regular response on PET/CT evaluated using the Peking criteria can improve prognostic value. Serial PET/CT from baseline MTV to PET-4 may have relatively greater predictive power for poor prognosis in diffuse large B-cell lymphoma.

Clinical Perspectives for 18F-FDG PET Imaging in Pediatric Oncology: Μetabolic Tumor Volume and Radiomics

Pediatric cancer, although rare, requires the most optimized treatment approach to obtain high survival rates and minimize serious long-term side effects in early adulthood. 18F-FDG PET/CT is most helpful and widely used in staging, recurrence detection, and response assessment in pediatric oncology. The well-known 18F-FDG PET metabolic indices of metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) have already revealed an independent significant prognostic value for survival in oncologic patients, although the corresponding cut-off values remain study-dependent and not validated for use in clinical practice. Advanced tumor “radiomic” analysis sheds new light into these indices. Numerous patterns of texture 18F-FDG uptake features can be extracted from segmented PET tumor images due to new powerful computational systems supporting complex “deep learning” algorithms. This high number of “quantitative” tumor imaging data, although not decrypted in their majority and once standardized for the different imaging systems and segmentation methods, could be used for the development of new “clinical” models for specific cancer types and, more interestingly, for specific age groups. In addition, data from novel techniques of tumor genome analysis could reveal new genes as biomarkers for prognosis and/or targeted therapies in childhood malignancies. Therefore, this ever-growing information of “radiogenomics”, in which the underlying tumor “genetic profile” could be expressed in the tumor-imaging signature of “radiomics”, possibly represents the next model for precision medicine in pediatric cancer management. This paper reviews 18F-FDG PET image segmentation methods as applied to pediatric sarcomas and lymphomas and summarizes reported findings on the values of metabolic and radiomic features in the assessment of these pediatric tumors.

Prognostic Value of Radiomic Features of 18F-FDG PET/CT in Patients With B-Cell Lymphoma Treated With CD19/CD22 Dual-Targeted Chimeric Antigen Receptor T Cells

Objective

In the present study, we aimed to evaluate the prognostic value of PET/CT-derived radiomic features for patients with B-cell lymphoma (BCL), who were treated with CD19/CD22 dual-targeted chimeric antigen receptor (CAR) T cells. Moreover, we explored the relationship between baseline radiomic features and the occurrence probability of cytokine release syndrome (CRS).

Methods

A total of 24 BCL patients who received 18F-FDG PET/CT before CAR T-cell infusion were enrolled in the present study. Radiomic features from PET and CT images were extracted using LIFEx software, and the least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful predictive features of progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic curves, Cox proportional hazards model, and Kaplan-Meier curves were conducted to assess the potential prognostic value.

Results

Contrast extracted from neighbourhood grey-level different matrix (NGLDM) was an independent predictor of PFS (HR = 15.16, p = 0.023). MYC and BCL2 double-expressor (DE) was of prognostic significance for PFS (HR = 7.02, p = 0.047) and OS (HR = 10.37, p = 0.041). The combination of NGLDM_ContrastPET and DE yielded three risk groups with zero (n = 7), one (n = 11), or two (n = 6) factors (p &lt; 0.0001 and p = 0.0004, for PFS and OS), respectively. The PFS was 85.7%, 63.6%, and 0%, respectively, and the OS was 100%, 90.9%, and 16.7%, respectively. Moreover, there was no significant association between PET/CT variables and CRS.

Conclusions

In conclusion, radiomic features extracted from baseline 18F-FDG PET/CT images in combination with genomic factors could predict the survival outcomes of BCL patients receiving CAR T-cell therapy.

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

Positron emission tomography/computed tomography (PET/CT) is used for the staging of lymphomas. Clinical information, such as Ann Arbor stage and number of involved sites, is derived from baseline staging and correlates with tumour volume. With modern imaging software, exact measures of total metabolic tumour volumes (tMTV) can be determined, in a semi- or fully-automated manner. Several technical factors, such as tumour segmentation and PET/CT technology influence tMTV and there is no consensus on a standardized uptake value (SUV) thresholding method, or how to include the volumes in the bone marrow and spleen. In diffuse large B-cell lymphoma, follicular lymphoma, peripheral T-cell lymphoma, and Hodgkin lymphoma, tMTV has been shown to predict progression-free survival and/or overall survival, after adjustments for clinical risk scores. However, most studies have used receiver operating curves to determine the optimal cut-off for tMTV and many studies did not include a training-validation approach, which led to the risk of overestimation of the independent prognostic value of tMTV. The identified cut-off values are heterogeneous, even when the same SUV thresholding method is used. Future studies should focus on testing tMTV in homogeneously-treated cohorts and seek to validate identified cut-off values externally so that a prognostic value can be documented, over and above currently used clinical surrogates for tumour volume.

Twenty Years On: RECIST as a Biomarker of Response in Solid Tumours an EORTC Imaging Group - ESOI Joint Paper

Response evaluation criteria in solid tumours (RECIST) v1.1 are currently the reference standard for evaluating efficacy of therapies in patients with solid tumours who are included in clinical trials, and they are widely used and accepted by regulatory agencies. This expert statement discusses the principles underlying RECIST, as well as their reproducibility and limitations. While the RECIST framework may not be perfect, the scientific bases for the anticancer drugs that have been approved using a RECIST-based surrogate endpoint remain valid. Importantly, changes in measurement have to meet thresholds defined by RECIST for response classification within thus partly circumventing the problems of measurement variability. The RECIST framework also applies to clinical patients in individual settings even though the relationship between tumour size changes and outcome from cohort studies is not necessarily translatable to individual cases. As reproducibility of RECIST measurements is impacted by reader experience, choice of target lesions and detection/interpretation of new lesions, it can result in patients changing response categories when measurements are near threshold values or if new lesions are missed or incorrectly interpreted. There are several situations where RECIST will fail to evaluate treatment-induced changes correctly; knowledge and understanding of these is crucial for correct interpretation. Also, some patterns of response/progression cannot be correctly documented by RECIST, particularly in relation to organ-site (e.g. bone without associated soft-tissue lesion) and treatment type (e.g. focal therapies). These require specialist reader experience and communication with oncologists to determine the actual impact of the therapy and best evaluation strategy. In such situations, alternative imaging markers for tumour response may be used but the sources of variability of individual imaging techniques need to be known and accounted for. Communication between imaging experts and oncologists regarding the level of confidence in a biomarker is essential for the correct interpretation of a biomarker and its application to clinical decision-making. Though measurement automation is desirable and potentially reduces the variability of results, associated technical difficulties must be overcome, and human adjudications may be required.

Interobserver Agreement on Automated Metabolic Tumor Volume Measurements of Deauville Score 4 and 5 Lesions at Interim 18F-FDG PET in Diffuse Large B-Cell Lymphoma

Metabolic tumor volume (MTV) on interim PET (I-PET) is a potential prognostic biomarker for diffuse large B-cell lymphoma (DLBCL). Implementation of MTV on I-PET requires a consensus on which semiautomated segmentation method delineates lesions most successfully with least user interaction. Methods used for baseline PET are not necessarily optimal for I-PET because of lower lesional SUVs at I-PET. Therefore, we aimed to evaluate which method provides the best delineation quality for Deauville score (DS) 4-5 DLBCL lesions on I-PET at the best interobserver agreement on delineation quality and, second, to assess the effect of lesional SUVmax on delineation quality and performance agreement. Methods: DS 4-5 lesions from 45 I-PET scans were delineated using 6 semiautomated methods: a fixed SUV threshold of 2.5 g/cm3, a fixed SUV threshold of 4.0 g/cm3, an adaptive threshold corrected for source-to-local background activity contrast at 50% of the SUVpeak, 41% of SUVmax per lesion, a majority vote including voxels detected by at least 2 methods, and a majority vote including voxels detected by at least 3 methods (MV3). Delineation quality per MTV was rated by 3 independent observers as acceptable or nonacceptable. For each method, observer scores on delineation quality, specific agreement, and MTV were assessed for all lesions and per category of lesional SUVmax (<5, 5-10, >10). Results: In 60 DS 4-5 lesions on I-PET, MV3 performed best, with acceptable delineation in 90% of lesions and a positive agreement of 93%. Delineation quality scores and agreement per method strongly depended on lesional SUV: the best delineation quality scores were obtained using MV3 in lesions with an SUVmax of less than 10 and using SUV4.0 in more 18F-FDG-avid lesions. Consequently, overall delineation quality and positive agreement improved by applying the most preferred method per SUV category instead of using MV3 as the single best method. The MV3- and SUV4.0-derived MTVs of lesions with an SUVmax of more than 10 were comparable after exclusion of visually failed MV3 contouring. For lesions with an SUVmax of less than 10, MTVs using different methods correlated poorly. Conclusion: On I-PET, MV3 performed best and provided the highest interobserver agreement regarding acceptable delineations of DS 4-5 DLBCL lesions. However, delineation-method preference strongly depended on lesional SUV. Therefore, we suggest exploration of an approach that identifies the optimal delineation method per lesion as a function of tumor 18F-FDG uptake characteristics, that is, SUVmax.

Generation and validation of a PET radiomics model that predicts survival in diffuse large B cell lymphoma treated with R-CHOP14: A SAKK 38/07 trial post-hoc analysis

Functional parameters from positron emission tomography (PET) seem promising biomarkers in various lymphoma subtypes. This study investigated the prognostic value of PET radiomics in diffuse large B-cell lymphoma (DLBCL) patients treated with R-CHOP given either every 14 (testing set) or 21 days (validation set). Using the PyRadiomics Python package, 107 radiomics features were extracted from baseline PET scans of 133 patients enrolled in the Swiss Group for Clinical Cancer Research 38/07 prospective clinical trial (SAKK 38/07) [ClinicalTrial.gov identifier: NCT00544219]. The international prognostic indices, the main clinical parameters and standard PET metrics, together with 52 radiomics uncorrelated features (selected using the Spearman correlation test) were included in a least absolute shrinkage and selection operator (LASSO) Cox regression to assess their impact on progression-free (PFS), cause-specific (CSS), and overall survival (OS). A linear combination of the resulting parameters generated a prognostic radiomics score (RS) whose area under the curve (AUC) was calculated by receiver operating characteristic analysis. The RS efficacy was validated in an independent cohort of 107 DLBCL patients. LASSO Cox regression identified four radiomics features predicting PFS in SAKK 38/07. The derived RS showed a significant capability to foresee PFS in both testing (AUC, 0.709; p < 0.001) and validation (AUC, 0.706; p < 0.001) sets. RS was significantly associated also with CSS and OS in testing (CSS: AUC, 0.721; p < 0.001; OS: AUC, 0.740; p < 0.001) and validation (CSS: AUC, 0.763; p < 0.0001; OS: AUC, 0.703; p = 0.004) sets. The RS allowed risk classification of patients with significantly different PFS, CSS, and OS in both cohorts showing better predictive accuracy respect to clinical international indices. PET-derived radiomics may improve the prediction of outcome in DLBCL patients.

Impact of germline polymorphisms in genes regulating glucose uptake on positron emission tomography findings and outcome in diffuse large B-cell lymphoma: results from the PETAL trial

Background

[¹⁸F]Fluoro-deoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is the standard imaging procedure in diffuse large B-cell lymphoma (DLBCL). Disease presentation, FDG-PET/CT performance, and outcome may be influenced by germline single nucleotide polymorphisms (SNP) in genes regulating glucose uptake.

Methods

Clinical variables, FDG-PET findings, and outcome were analysed in relation to SNPs in 342 DLBCL patients participating in the ‘Positron Emission Tomography-Guided Therapy of Aggressive Non-Hodgkin Lymphomas’ (PETAL) trial. Genes analysed included SLC2A1 (SNPs rs1385129, referred to as HaeIII; rs710218, HpyCH4V; rs841853, XbaI), VEGFA (rs3025039), HIF1A (rs11549465, P582S; rs11549467, A588T), and APEX1 (rs1130409, D148E). Statistical significance was assumed at p ≤ 0.05.

Results

The SLC2A1 HaeIII and HpyCH4V SNPs were tightly linked and statistically significantly associated with baseline maximum standardized uptake value (SUV_max) and Ann Arbor stage, with slightly lower SUV_max (HaeIII, median 18.9, interquartile range [IQR] 11.5–26.6, versus 21.6, IQR 14.4–29.7; p = 0.019) and more frequent stage IV disease (HaeIII, 44.5% versus 30.8%; p = 0.011) in minor allele carriers. As previously reported for lung cancer, the association was dependent upon the coexistent APEX1 D148E genotype. The HIF1A A588T SNP was associated with total metabolic tumour volume (TMTV) and time-to-progression, with significantly lower TMTV (median 16 cm³, IQR 7–210, versus 146 cm³, IQR 34–510; p = 0.034) and longer time-to-progression in minor allele carriers (log-rank p = 0.094). Time-to-progression was also associated with the SLC2A1 XbaI and APEX1 D148E SNPs, with shorter time-to-progression in homozygous and heterozygous SLC2A1 XbaI (HR 1.456; CI 0.930–2.280; p = 0.099) and homozygous APEX1 D148E minor allele carriers (HR 1.6; CI 1.005–2.545; p = 0.046). In multivariable analyses including SNPs, International Prognostic Index factors, sex, and B symptoms, HIF1A A588T, SLC2A1 XbaI, and APEX1 D148E retained statistical significance for time-to-progression, and SLC2A1 XbaI was also significantly associated with overall survival.

Conclusions

Common SNPs in genes regulating glucose uptake may impact SUV_max, tumour distribution, tumour volume, and outcome in DLBCL. The effects on SUV_max are of low magnitude and appear clinically negligible. The results are consistent with findings in other types of cancer. They need to be confirmed in an independent DLBCL population of sufficient size.

Trial registration

Trial registration: ClinicalTrials.gov NCT00554164; EudraCT 2006-001641-33. Registration date November 5, 2007, https://www.clinicaltrials.gov/ct2/show/NCT00554164

Supplementary Information

The online version contains supplementary material available at 10.1007/s00432-021-03796-z.

Prognostication of diffuse large B-cell lymphoma patients with Deauville score of 3 or 4 at end-of-treatment PET evaluation: a comparison of the Deauville 5-point scale and the ΔSUVmax method

Diffuse large B-cell lymphoma is treated with anti-CD 20 and multi-drug chemotherapy for cure. Positron emission tomography (PET) scans are performed at end of treatment (EOT) to assess response. EOT Deauville scores (DS) are equivocal for treatment response in some situations, requiring physicians to determine the need for further investigations or treatment. Studies have suggested the delta maximum standardised uptake value (ΔSUVmax) to be superior to DS for assessment of metabolic response at interim PET, although its use at EOT PET, especially in cases of equivocal response, has yet to be established. We investigated whether ΔSUVmax could better discriminate prognosis than DS 3 or 4 at EOT. ΔSUVmax did not outperform DS. Combination of DS 3 and International Prognostic Index (IPI) <3 selects for patients with extremely low risk of disease progression (HR 0.06, 95% CI 0.01 to 0.62, p 0.018) compared to DS 4 and IPI ≥3.

FDG-PET/CT in Lymphoma: Where Do We Go Now?

18F-fluorodeoxyglucose positron emission tomography combined with computed tomography (FDG-PET/CT) is an essential part of the management of patients with lymphoma at staging and response evaluation. Efforts to standardize PET acquisition and reporting, including the 5-point Deauville scale, have enabled PET to become a surrogate for treatment success or failure in common lymphoma subtypes. This review summarizes the key clinical-trial evidence that supports PET-directed personalized approaches in lymphoma but also points out the potential place of innovative PET/CT metrics or new radiopharmaceuticals in the future.

[18F]FDG PET-CT in patients with DLBCL treated with CAR-T cell therapy: a practical approach of reporting pre- and post-treatment studies

PURPOSE

The introduction of CD19-specific chimeric antigen receptor T-cell therapy (CAR-T) for treatment of relapsed/refractory diffuse large B cell lymphoma (R/R DLBCL) gives hope to patients with otherwise dismal prognosis. Therapy outcomes, however, depend upon selection of patients and accurate early identification of non-responders. Patients treated with CAR-T usually undergo [¹⁸F]FDG PET-CT at time of decision (TD), time of CAR-T transfusion (TT), 1 month (M1), and 3 months (M3) post-therapy. The purpose of the current study was to identify the specific parameters that should be addressed when reporting PET-CT studies in the clinical setting of CAR-T therapy.

METHODS

A total of 138 PET-CT scans (30 TD, 42 TT, 44 M1, 22 M3) of 48 patients treated with CAR-T were included. SUVmax, TMTV, and TLG were calculated in all scans. Response was assessed using the Deauville scale and ΔSUVmax method. Overall survival (OS) was the primary endpoint. Median follow-up was 12.8 (IQR 6.4-16.0) months from CAR-T infusion.

RESULTS

In a univariate analysis, TD-SUVmax > 17.1 and TT-SUVmax > 12.1 were associated with shorter OS (Pv < 0.05). In a multivariate analysis, three factors were significantly associated with shorter OS: TD-SUVmax > 17.1 (HR 10.3; Pv < 0.01), LDH > 450 U/l (HR 7.7; Pv < 0.01), and ECOG score > 1 (HR 5.5; Pv = 0.04). Data from TD and TT PET-CT scans were not predictive of toxicity. On M1-PET-CT, patients with a Deauville score > 3 had significantly shorter OS (median 7.9 months, versus not reached, Pv < 0.01). ΔSUVmax ≤ 66% on M1-PET-CT predicted shorter OS when M1-SUVmax was compared to TD-SUVmax (Pv = 0.02) but not to TT-SUVmax (Pv = 0.38).

CONCLUSION

Pre-treatment SUVmax may guide patient selection for CAR-T therapy. On M1-PET-CT, Deauville score and ΔSUVmax from TD may identify early therapy failure. These parameters are easy to obtain and should be included in the PET-CT report.

18F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma

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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05480-3.

Total tumor burden in lymphoma - an evolving strong prognostic parameter

Total metabolic tumor volume (TMTV), a new parameter extracted from baseline FDG-PET/CT, has been recently proposed by several groups as a prognosticator in lymphomas before first-line treatment. TMTV, the sum of the metabolic volume of each lesion, is an index of the metabolically most active part of the tumor and highly correlates with the total tumor burden. TMTV measurement is obtained from PET images processed with different software and techniques, many being now freely available. In the various lymphoma subtypes where it has been measured, such as diffuse large B-cell lymphoma, Hodgkin lymphoma, Follicular Lymphoma, and Peripheral T-cell lymphoma, TMTV has been reported as a strong predictor of outcome (progression-free survival and overall survival) often outperforming the clinical scores, molecular predictors, and results of interim PET. Combined with these scores, TMTV improves the stratification of the populations into risk groups with different outcomes. TMTV cut-off separating the high-risk from the low-risk population impacts the outcome whatever the technique used for its measurement and an international harmonization is ongoing. TMTV is a unique and easy tool that could replace the surrogate of tumor burden included in the prognostic indexes used in lymphoma and help tailor therapy. Other parameters extracted from the baseline PET may give an information on the dissemination of this total tumor volume such as the maximum distance between the lesions. Trials based on TMTV would probably demonstrate its predictive value.

New Approaches in Characterization of Lesions Dissemination in DLBCL Patients on Baseline PET/CT

Dissemination, expressed recently by the largest Euclidian distance between lymphoma sites (SDmax), appeared a promising risk factor in DLBCL patients. We investigated alternative distance metrics to characterize the robustness of the dissemination information. In 290 patients from the REMARC trial (NCT01122472), the Euclidean (Euc), Manhattan (Man), and Tchebychev (Tch) distances between the furthest lesions, firstly based on the centroid of each lesion and then directly from the two most distant tumor voxels and the Travelling Salesman Problem distance (TSP) were calculated. For PFS, the areas under the ROC curves were between 0.63 and 0.64, and between 0.62 and 0.65 for OS. Patients with high SDmax whatever the method of calculation or high SD_TSP had a significantly poorer outcome than patients with low SDmax or SD_TSP (p < 0.001 for both PFS and OS), with significance maintained in Ann Arbor advanced-stage patients. In multivariate analysis with total metabolic tumor volume and ECOG, each distance feature had an independent prognostic value for PFS. For OS, only SDmax_Tch, SDmax_Euc _Vox, and SDmax_Man _Vox reached significance. The spread of DLBCL lesions measured by the largest distance between lymphoma sites is a strong independent prognostic factor and could be measured directly from tumor voxels, allowing its development in the area of the deep learning segmentation methods.

Interim PET in Diffuse Large B-Cell Lymphoma

In diffuse large B-cell lymphoma, early assessment of treatment response by 18F-FDG PET may trigger treatment modification. Reliable identification of good and poor responders is important. We compared 3 competing methods of interim PET evaluation. Methods: Images from 449 patients participating in the "PET-Guided Therapy of Aggressive Non-Hodgkin Lymphomas" trial were reanalyzed by applying the visual Deauville score and the SUV-based qPET (q = quantitative) and ΔSUVmax scales to interim PET scans performed after 2 cycles of chemotherapy. qPET relates residual lymphoma 18F-FDG uptake to physiologic liver uptake, converting the ordinal Deauville scale into a continuous scale and permitting a direct comparison with the continuous ΔSUVmax scale, which is based on SUVmax changes between baseline and interim scans. Positive and negative predictive values were calculated for progression-free survival. Results: When established thresholds were used to distinguish between good and poor responders (visual Deauville score 1-3 vs. 4-5; ΔSUVmax > 66% vs. ≤ 66%), the positive predictive value was significantly lower with Deauville than ΔSUVmax (38.4% vs. 56.6%; P = 0.03). qPET and ΔSUVmax were strongly correlated on the log scale (Pearson r = 0.75). When plotted along corresponding percentiles, the positive predictive value curves for qPET and ΔSUVmax were superimposable, with low values up to the 85th percentile and a steep rise thereafter. The recommended threshold of 66% SUVmax reduction for the identification of poor responders was equivalent to qPET = 2.26, corresponding to score 5 on the visual Deauville scale. The negative predictive value curves were also superimposable but remained flat between 80% and 70%. Conclusion: Continuous scales are better suited for interim PET-based outcome prediction than the ordinal Deauville scale. qPET and ΔSUVmax essentially carry the same information. The proportion of poor-risk patients identified is less than 15%.

Liquid biopsy in lymphoma: Is it primed for clinical translation?

The simultaneous growth in our understanding of lymphoma biology and the burgeoning therapeutic options has come with a renewed drive for precision-based approaches and how best to incorporate them into contemporary and future patient care. In the hunt for accurate and sensitive biomarkers, liquid biopsies, particularly circulating tumour DNA, have come to the forefront as a promising tool in multiple cancer types including lymphomas, with considerable implications for clinical practice. Liquid biopsy analyses could supplement existing tissue biopsies with distinct advantages including the minimally invasive nature and the ease with which it can be repeated during a patient's clinical journey. Circulating tumour DNA (ctDNA) analyses has been and continues to be evaluated across lymphoma subtypes with potential applications as a diagnostic, disease monitoring and treatment selection tool. To make the leap into the clinic, these assays must demonstrate accuracy, reliability and a quick turnaround to be employed in the real-time clinical management of lymphoma patients. Here, we review the available ctDNA assays and discuss key practical and technical issues around improving sensitivity. We then focus on their potential roles in several lymphoma subtypes exemplified by recent studies and provide a glimpse of different features that can be analysed beyond ctDNA.

Improved prediction of chemoresistance in patients with diffuse large B-cell lymphoma through a new interim positron emission tomography-computed tomography evaluation model

OBJECTIVES

The positron emission tomography (PET) could predict the prognosis of DLBCL patients, but the exact procedure on interim PET (iPET) to determine chemoresistant patients remains elusive.

METHODS

We retrospectively analyzed 593 newly diagnosed DLBCL patients uniformly treated with R-CHOP regimen. Among them, 352 patients diagnosed from August 2010 to December 2016 were included in the test cohort and 241 patients diagnosed from January 2017 to December 2019 were included in the validation cohort. The iPET was evaluated with Deauville criteria and ΔSUVmax method. The reduction of maximal SUV between baseline and after 4 cycles of chemotherapy were defined as ΔSUVmax. The survival functions were depicted using the Kaplan-Meier method and compared with the log-rank test.

RESULTS

Patients with iPET Deauville 4 had heterogeneous outcome and end of treatment complete response rates (eCRR). Combined Deauville with ΔSUVmax method, we proposed a modified-Deauville model: patients with Deauville 4 and ΔSUVmax > 70%, as well as those with Deauville 1-3, were reclassified into the modified-Deauville negative group, while patients with Deauville 4 and ΔSUVmax ≤ 70%, as well as those with Deauville 5, into the modified-Deauville positive group. In the test cohort, 3-year PFS, OS and eCRR of modified-Deauville negative group were 80.2%, 89.9% and 91.8%, significantly higher than those of positive group (12.5%, 27.3% and 29.2%, p ≤ .001). Similar results were found in the validation cohort, that 3-year PFS, OS and eCRR were 87.8%, 95.4%, 96.3% in modified-Deauville negative group, and 27.4%, 32.5%, 13.5% in positive group. Through modified-Deauville model, patients in iPET positive group had very low eCRR and were resistant to conventional chemotherapy.

CONCLUSIONS

The modified-Deauville model could better distinguish DLBCL patients with poor response to chemotherapy. Accordingly, these patients could be recognized early and provided with alternative therapeutic agents, which might improve the clinical outcome of refractory DLBCL patients.

Optimal timing and criteria of interim PET in DLBCL: a comparative study of 1692 patients

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.