Risk stratification in diffuse large B-cell lymphoma using lesion dissemination and metabolic tumor burden calculated from baseline PET/CT†

2-deoxy-2-[18F]FDG PET Imaging for Therapy Assessment in Hodgkin's and Non-Hodgkin Lymphomas

The 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography combined with computed tomography (PET/CT) has contributed to outcome improvement of patients with lymphoma. The use of [18F]FDG PET/CT for staging and response assessment is successfully applied both in routine clinical practice and in clinical trials. The challenges lie in enhancing the outcomes of lymphoma patients, particularly those with advanced or refractory/relapsed disease, and to minimize the long-term toxicity associated with treatments, including radiation therapy. The objective of this review article is to present contemporary data on the use of [18F]FDG PET/CT for treatment assessment of aggressive lymphomas.

Lymphoma: The Added Value of Radiomics, Volumes and Global Disease Assessment

Lymphoma represents a condition that holds promise for cure with existing treatment modalities; nonetheless, the primary clinical obstacle lies in advancing therapeutic outcomes by pinpointing high-risk individuals who are unlikely to respond favorably to standard therapy. In this article, the authors will delineate the significant strides achieved in the lymphoma field, with a particular emphasis on the 3 prevalent subtypes: Hodgkin lymphoma, diffuse large B-cell lymphomas, and follicular lymphoma.

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.

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 from baseline [18 F]FDG PET/CT at diagnosis improves the IPI stratification in patients with diffuse large B-cell lymphoma

PURPOSE

Although several different parameters of PET/CT were reported to be predictive of survival in DLBCL, the best parameter remains to be elucidated and whether it could improve the risk stratification of IPI in patients with DLBCL.

PROCEDURES

262 DLBCL patients including in the training and validation cohort were retrospectively analyzed in this study.

RESULTS

Among different parameters, MTV was identified as the optimal prognostic parameter with a maximum area under the curve (AUC) of 0.652 ± 0.112 than TLG and SDmax (0.645 ± 0.113 and 0.600 ± 0.117, respectively). Patients with high MTV were associated with inferior PFS (p < 0.001 and p = 0.021, respectively) and OS (p < 0.001 and p < 0.001, respectively) in both the training and validation cohort. The multivariate analysis revealed that high MTV was an unfavorable factor for PFS (relative ratio [RR], 2.295; 95% confidence interval [CI], 1.457-3.615; p < 0.01) and OS (RR, 2.929; 95% CI 1.679-5.109; p < 0.01) independent of IPI.

CONCLUSIONS

Further analysis showed MTV could improve the risk stratification of IPI for both PFS and OS (p < 0.01 and p < 0.01, respectively). In conclusion, our study suggests that MTV was an optimal prognostic parameter of PET/CT for survival and it could improve the risk stratification of IPI in DLBCL, which may help to guide treatment in clinical trial.

Baseline SUVmax is correlated with tumor hypoxia and patient outcomes in nasopharyngeal carcinoma

To evaluate the prognostic significance of the maximum standardized uptake value (SUVmax) in nasopharyngeal carcinoma (NPC), establish a gene signature that correlates with SUVmax, and explore the underlying biological behaviors associated with these correlations for the prediction of clinical outcomes. A cohort of 726 patients with NPC was examined to identify correlations between SUVmax and various clinical variables. RNA sequencing was performed to identify genes related to SUVmax, and these genes were used to develop an SUV signature. Additionally, transcriptome enrichment analysis was conducted to investigate the potential biological behaviors underlying the observed correlations. Higher SUVmax was associated with an increased tumor burden and worse prognosis. The SUV signature, which consisted of 10 genes, was positively correlated with SUVmax, and it predicted worse survival outcomes. This signature was highly expressed in malignant epithelial cells and associated with hypoxia and resistance to radiotherapy. Additionally, the signature was negatively correlated with immune function. SUVmax is a valuable prognostic indicator in NPC, with higher values predicting worse outcomes. The SUV signature offers further prognostic insights, linking glucose metabolism to tumor aggressiveness, treatment resistance, and immune function, and it could represent a potential biomarker for NPC.

RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models

Explaining the decisions made by a radiomic model is of significant interest, as it can provide valuable insights into the information learned by complex models and foster trust in well-performing ones, thereby facilitating their clinical adoption. Promising radiomic approaches that aggregate information from multiple regions within an image currently lack suitable explanation tools that could identify the regions that most significantly influence their decisions. Here we present a model- and modality-agnostic tool (RadShap, https://github.com/ncaptier/radshap), based on Shapley values, that explains the predictions of multiregion radiomic models by highlighting the contribution of each individual region. Methods: The explanation tool leverages Shapley values to distribute the aggregative radiomic model's output among all the regions of interest of an image, highlighting their individual contribution. RadShap was validated using a retrospective cohort of 130 patients with advanced non-small cell lung cancer undergoing first-line immunotherapy. Their baseline PET scans were used to build 1,000 synthetic tasks to evaluate the degree of alignment between the tool's explanations and our data generation process. RadShap's potential was then illustrated through 2 real case studies by aggregating information from all segmented tumors: the prediction of the progression-free survival of the non-small cell lung cancer patients and the classification of the histologic tumor subtype. Results: RadShap demonstrated strong alignment with the ground truth, with a median frequency of 94% for consistently explained predictions in the synthetic tasks. In both real-case studies, the aggregative models yielded superior performance to the single-lesion models (average [±SD] time-dependent area under the receiver operating characteristic curve was 0.66 ± 0.02 for the aggregative survival model vs. 0.55 ± 0.04 for the primary tumor survival model). The tool's explanations provided relevant insights into the behavior of the aggregative models, highlighting that for the classification of the histologic subtype, the aggregative model used information beyond the biopsy site to correctly classify patients who were initially misclassified by a model focusing only on the biopsied tumor. Conclusion: RadShap aligned with ground truth explanations and provided valuable insights into radiomic models' behaviors. It is implemented as a user-friendly Python package with documentation and tutorials, facilitating its smooth integration into radiomic pipelines.

Metabolic tumour area: a novel prognostic indicator based on 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma in the R-CHOP era

BACKGROUND

The metabolic tumour area (MTA) was found to be a promising predictor of prostate cancer. However, the role of MTA based on 18F-FDG PET/CT in diffuse large B-cell lymphoma (DLBCL) prognosis remains unclear. This study aimed to elucidate the prognostic significance of MTA and evaluate its incremental value to the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) for DLBCL patients treated with first-line R-CHOP regimens.

METHODS

A total of 280 consecutive patients with newly diagnosed DLBCL and baseline 18F-FDG PET/CT data were retrospectively evaluated. Lesions were delineated via a semiautomated segmentation method based on a 41% SUVmax threshold to estimate semiquantitative metabolic parameters such as total metabolic tumour volume (TMTV) and MTA. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off values. Progression-free survival (PFS) and overall survival (OS) were the endpoints that were used to evaluate the prognosis. PFS and OS were estimated via Kaplan‒Meier curves and compared via the log-rank test.

RESULTS

Univariate analysis revealed that patients with high MTA, high TMTV and NCCN-IPI ≥ 4 were associated with inferior PFS and OS (P < 0.0001 for all). Multivariate analysis indicated that MTA remained an independent predictor of PFS and OS [hazard ratio (HR), 2.506; 95% confidence interval (CI), 1.337-4.696; P = 0.004; and HR, 1.823; 95% CI, 1.005-3.310; P = 0.048], whereas TMTV was not. Further analysis using the NCCN-IPI model as a covariate revealed that MTA and NCCN-IPI were still independent predictors of PFS (HR, 2.617; 95% CI, 1.494-4.586; P = 0.001; and HR, 2.633; 95% CI, 1.650-4.203; P < 0.0001) and OS (HR, 2.021; 95% CI, 1.201-3.401; P = 0.008; and HR, 3.869; 95% CI, 1.959-7.640; P < 0.0001; respectively). Furthermore, MTA was used to separate patients with high NCCN-IPI risk scores into two groups with significantly different outcomes.

CONCLUSIONS

Pre-treatment MTA based on 18F-FDG PET/CT and NCCN-IPI were independent predictor of PFS and OS in DLBCL patients treated with R-CHOP. MTA has additional predictive value for the prognosis of patients with DLBCL, especially in high-risk patients with NCCN-IPI ≥ 4. In addition, the combination of MTA and NCCN-IPI may be helpful in further improving risk stratification and guiding individualised treatment options.

TRIAL REGISTRATION

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

Baseline and early 18F-FDG PET/CT evaluations as predictors of progression-free survival in metastatic breast cancer patients treated with targeted anti-CDK therapy

BACKGROUND

Exploring the value of baseline and early 18F-FDG PET/CT evaluations in prediction PFS in ER+/HER2- metastatic breast cancer patients treated with a cyclin-dependent kinase inhibitor in combination with an endocrine therapy.

METHODS

Sixty-six consecutive breast cancer patients who underwent a pre-therapeutic 18F-FDG PET/CT and a second PET/CT within the first 6 months of treatment were retrospectively included. Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) and Dmax, which represents tumour dissemination and is defined as the distance between the two most distant lesions, were computed. The variation in these parameters between baseline and early evaluation PET as well as therapeutic evaluation using PERCIST were assessed as prognosticators of PFS at 18 months.

RESULTS

The median follow-up was equal to 22.5 months. Thirty progressions occurred (45.4%). The average time to event was 17.8 ± 10.4 months. At baseline, Dmax was the only predictive metabolic parameter. Patients with a baseline Dmax ≤ 18.10 cm had a significantly better 18 m-PFS survival than the others: 69.2% (7.7%) versus 36.7% (8.8%), p = 0.017. There was no association between PERCIST evaluation and 18 m-PFS status (p = 0.149) and there was no difference in 18 m-PFS status between patients classified as complete, partial metabolic responders or having stable metabolic disease.

CONCLUSION

Disease spread at baseline PET, as assessed by Dmax, is predictive of an event occurring within 18 months. In the absence of early metabolic progression, which occurs in 15% of patients, treatment should be continued regardless of the quality of the initial response to treatment.

Impact of therapeutic inhibition of oncogenic cell signaling tyrosine kinase on cell metabolism: in vivo-detectable metabolic biomarkers of inhibition

BACKGROUND

Inhibition of kinases is the ever-expanding therapeutic approach to various types of cancer. Typically, assessment of the treatment response is accomplished by standard, volumetric imaging procedures, performed weeks to months after the onset of treatment, given the predominantly cytostatic nature of the kinase inhibitors, at least when used as single agents. Therefore, there is a great clinical need to develop new monitoring approaches to detect the response to kinase inhibition much more promptly. Noninvasive 1H magnetic resonance spectroscopy (MRS) can measure in vitro and in vivo concentration of key metabolites which may potentially serve as biomarkers of response to kinase inhibition.

METHODS

We employed mantle cell lymphoma (MCL) cell lines demonstrating markedly diverse sensitivity of inhibition of Bruton's tyrosine kinase (BTK) regarding their growth and studied in-depth effects of the inhibition on various aspects of cell metabolism including metabolite synthesis using metabolomics, glucose and oxidative metabolism by Seahorse XF technology, and concentration of index metabolites lactate, alanine, total choline and taurine by 1H MRS.

RESULTS

Effective BTK inhibition profoundly suppressed key cell metabolic pathways, foremost pyrimidine and purine synthesis, the citrate (TCA) cycle, glycolysis, and pyruvate and glutamine/alanine metabolism. It also inhibited glycolysis and amino acid-related oxidative metabolism. Finally, it profoundly and quickly decreased concentration of lactate (a product of mainly glycolysis) and alanine (an indicator of amino acid metabolism) and, less universally total choline both in vitro and in vivo, in the MCL xenotransplant model. The decrease correlated directly with the degree of inhibition of lymphoma cell expansion and tumor growth.

CONCLUSIONS

Our results indicate that BTK inhibition exerts a broad and profound suppressive effect on cell metabolism and that the affected index metabolites such as lactate, alanine may serve as early, sensitive, and reliable biomarkers of inhibition in lymphoma patients detectable by noninvasive MRS-based imaging method. This kind of imaging-based detection may also be applicable to other kinase inhibitors, as well as diverse lymphoid and non-lymphoid malignancies.

Comparative analysis of F-18 FDG PET/CT images between scrub typhus and systemic lupus erythematosus

This study evaluated the use of F-18 fluorodeoxyglucose (FDG) PET/CT imaging to differentiate between scrub typhus and systemic lupus erythematosus (SLE) in patients presenting with lymphadenopathy. We carried out a retrospective analysis of 18 scrub typhus patients and seven SLE patients, using various imaging parameters, including lymph node size, spleen and liver lengths, the distance between the two farthest lesions (Dmax), and assessments of glucose metabolism. On FDG PET images, we measured the maximum standardized uptake value (SUVmax) of the lymph nodes, spleen, and liver and the mean standardized uptake value (SUVmean) of the liver and spleen. The Dmax values of scrub typhus patients were significantly longer than those of SLE patients, indicating that lymphadenopathy is more generalized in the patients with scrub typhus. The SUVmax values for the lymph node, spleen, and liver were also higher in patients with scrub typhus, while the SUVmean of the liver and spleen did not differ between the two groups. This study is the first to compare FDG PET/CT images between these two conditions, suggesting the potential of this imaging modality to provide critical diagnostic distinctions.

The Art of Bioimmunogenomics (BIGs) 5.0 in CAR-T Cell Therapy for Lymphoma Management

Purpose

Lymphoma, the most predominant neoplastic disorder, is divided into Hodgkin and Non-Hodgkin Lymphoma classifications. Immunotherapeutic modalities have emerged as essential methodologies in combating lymphoid malignancies. Chimeric Antigen Receptor (CAR) T cells exhibit promising responses in chemotherapy-resistant B-cell non-Hodgkin lymphoma cases.

Methods

This comprehensive review delineates the advancement of CAR-T cell therapy as an immunotherapeutic instrument, the selection of lymphoma antigens for CAR-T cell targeting, and the conceptualization, synthesis, and deployment of CAR-T cells. Furthermore, it encompasses the advantages and disadvantages of CAR-T cell therapy and the prospective horizons of CAR-T cells from a computational research perspective. In order to improve the design and functionality of artificial CARs, there is a need for TCR recognition investigation, followed by the implementation of a quality surveillance methodology.

Results

Various lymphoma antigens are amenable to CAR-T cell targeting, such as CD19, CD20, CD22, CD30, the kappa light chain, and ROR1. A notable merit of CAR-T cell therapy is the augmentation of the immune system's capacity to generate tumoricidal activity in patients exhibiting chemotherapy-resistant lymphoma. Nevertheless, it also introduces manufacturing impediments that are laborious, technologically demanding, and financially burdensome. Physical, physicochemical, and physiological limitations further exacerbate the challenge of treating solid neoplasms with CAR-T cells.

Conclusion

While the efficacy and safety of CAR-T cell immunotherapy remain subjects of fervent investigation, the promise of this cutting-edge technology offers valuable insights for the future evolution of lymphoma treatment management approaches. Moreover, CAR-T cell therapies potentially benefit patients, motivating regulatory bodies to foster international collaboration.

2-[18]F FDG PET/CT dissemination features in adult burkitt lymphoma Are predictive of outcome

This retrospective study investigated the prognostic role of disease dissemination features (Dmax and Dmaxbsa) measured by 2-[18F]FDG PET/CT in newly diagnosed Burkitt Lymphoma (BL) patients, comparing their performance with other metabolic parameters. We included 78 patients diagnosed with BL between 2010 and 2022 with an available baseline PET, interim PET/CT (iPET) and end of treatment PET/CT (eotPET) and with a minimum of two 2-[18F]FDG avid lesions present at the baseline scan. Dmax was calculated from the three-dimensional coordinates of the baseline metabolic tumor volume (MTV) by using LIFEx software; Dmaxbsa was calculated as Dmax normalized for body surface area according to the Du Bois method. We evaluated their effect on metabolic treatment response evaluated by PET, on progression free survival (PFS) and on overall survival (OS). Dmaxbsa was significantly associated with tumor stage, bulky and extranodal disease, MTV and TLG. At a median follow-up of 49 months, the median PFS and OS were 45 and 48 months. Dmax and Dmaxbsa were significantly higher in not complete metabolic response than complete metabolic response group at iPET and eotPET.As far as PFS, parameters including iPET/CT, eotPET/CT outcomes, MTV and TLG showed to be independent prognostic factors while Dmax and Dmaxbsa were not significantly associated with the outcome. Dissemination features, together with eotPET/CT results, MTV and TLG, demonstrated to be significantly correlated with OS. In conclusion, in this study we demonstrated that dissemination features derived by 2[18F]-FDG PET/CT were significantly correlated with response to treatment and long-term outcome, independently from other PET features.

Axicabtagene ciloleucel vs standard of care in second-line large B-cell lymphoma: outcomes by metabolic tumor volume

ABSTRACT

Metabolic tumor volume (MTV) assessed using 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography, a measure of tumor burden, is a promising prognostic indicator in large B-cell lymphoma (LBCL). This exploratory analysis evaluated relationships between baseline MTV (categorized as low [median or less] vs high [greater than median]) and clinical outcomes in the phase 3 ZUMA-7 study (NCT03391466). Patients with LBCL relapsed within 12 months of or refractory to first-line chemoimmunotherapy were randomized 1:1 to axicabtagene ciloleucel (axi-cel; autologous anti-CD19 chimeric antigen receptor T-cell therapy) or standard care (2-3 cycles of chemoimmunotherapy followed by high-dose chemotherapy with autologous stem cell transplantation in patients who had a response). All P values are descriptive. Within high- and low-MTV subgroups, event-free survival (EFS) and progression-free survival (PFS) were superior with axi-cel vs standard care. EFS in patients with high MTV (vs low MTV) was numerically shorter with axi-cel and was significantly shorter with standard care. PFS was shorter in patients with high MTV vs low MTV in both the axi-cel and standard-care arms, and median MTV was lower in patients in ongoing response at data cutoff vs others. Median MTV was higher in patients treated with axi-cel who experienced grade ≥3 neurologic events or cytokine release syndrome (CRS) than in patients with grade 1/2 or no neurologic events or CRS, respectively. Baseline MTV less than or equal to median was associated with better clinical outcomes in patients receiving axi-cel or standard care for second-line LBCL. The trial was registered at www.clinicaltrials.gov as #NCT03391466.

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.

Diagnosis of bone marrow involvement in angioimmunoblastic T-cell lymphoma should be based on both [18F]FDG-PET/CT and bone marrow biopsy findings

OBJECTIVE

During the initial staging of certain lymphoma subtypes, 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) has become an alternative to bone marrow biopsy (BMB) for detecting bone marrow (BM) involvement. However, whether [18F]FDG-PET/CT can accurately detect BM involvement in angioimmunoblastic T-cell lymphoma (AITL) remains unknown. Our study aimed to assess the diagnostic and prognostic capability of [18F]FDG-PET/CT for detecting BM involvement in AITL. Methods: This retrospective study included 84 individuals newly diagnosed with AITL who underwent baseline BMB and [18F]FDG-PET/CT. "BM involvement" was defined as one or both of the following: 1) angioimmunoblastic T-cells detected in the BM; or 2) initially heightened focal uptake having disappeared on follow-up [18F]FDG-PET/CT. The ability of [18F]FDG-PET/CT to detect BM cancerous lesions was respectively analyzed by BM involvement confirmed by BMB or the aforementioned definition as the reference standard. The patients' clinical characteristics and survival and prognostic outcomes were respectively analyzed.

RESULTS

Of the 84 participants, five (6.0%) displayed positive BMB and PET/BM results, 17 (20.2%) had BMB-positive but PET/BM-negative results, eight (9.5%) showed BMB-negative but PET/BM-positive outcomes, and 54 (64.3%) displayed negative BMB and PET/BM outcomes. Using pre-defined BM involvement as the reference standard, [18F]FDG-PET/CT exhibited a specificity of 100%, sensitivity of 40%, negative predictive value (NPV) of 75%, and positive predictive value (PPV) of 100%. In contrast, using BMB-detected BM involvement as reference, [18F]FDG-PET/CT exhibited a sensitivity, specificity, PPV, and NPV of 38.5%, 76.1%, 22.7%, and 87.1%, respectively. Among patients with PET/BM-positive and BMB-negative outcomes, 62.5% (5/8) underwent upstaging from III to IV. In 58.8% (10/17) of patients who were initially diagnosed with stage II/III disease based on the [18F]FDG-PET/CT results, repeat BMB resulted in upstaging to IV. PET/BM-negative patients had a higher 3-year progression-free survival rate (38.3% vs. 22.8%, p = 0.018) and 3-year overall survival rate (64.4% vs. 34.6%, p = 0.011) than PET/BM-positive patients.

CONCLUSION

In AITL patients, PET/BM-positive results may obviate the necessity for repeat BMB to ascertain confirm BM involvement. PET/BM-negative results do not definitively exclude BM involvement. The combined use of [18F]FDG-PET/CT and BMB can increase the diagnostic accuracy of BM involvement for AITL patients.

Prognostic value of the combination of volume, massiveness and fragmentation parameters measured on baseline FDG pet in high-burden follicular lymphoma

The prognostic value of radiomic quantitative features measured on pre-treatment 18F-FDG PET/CT was investigated in patients with follicular lymphoma (FL). We conducted a retrospective study of 126 FL patients (grade 1-3a) diagnosed between 2006 and 2020. A dozen of PET/CT-derived features were extracted via a software (Oncometer3D) from baseline 18F-FDG PET/CT images. The receiver operating characteristic (ROC) curve, Kaplan-Meier method and Cox analysis were used to assess the prognostic factors for progression of disease within 24 months (POD24) and progression-free survival at 24 months. Four different clusters were identified among the twelve PET parameters analyzed: activity, tumor burden, fragmentation-massiveness and dispersion. On ROC analyses, TMTV, the total metabolic tumor volume, had the highest AUC (0.734) followed by medPCD, the median distance between the centroid of the tumors and their periphery (AUC: 0.733). Patients with high TMTV (HR = 4.341; p < 0.001), high Tumor Volume Surface Ratio (TVSR) (HR = 3.204; p < 0.003) and high medPCD (HR = 4.507; p < 0.001) had significantly worse prognosis in both Kaplan-Meier and Cox univariate analyses. Furthermore, a synergistic effect was observed in Kaplan-Meier and Cox analyses combining these three PET/CT-derived parameters (HR = 12.562; p < 0.001). Having two or three high parameters among TMTV, TVSR and medPCD was able to predict POD24 status with a specificity of 68% and a sensitivity of 75%. TMTV, TVSR and baseline medPCD are strong prognostic factors in FL and their combination better predicts disease prognosis.

Investigator choice of standard therapy versus sequential novel therapy arms in the treatment of relapsed follicular lymphoma (REFRACT): study protocol for a multi-centre, open-label, randomised, phase II platform trial

BACKGROUND

Relapsed or refractory follicular lymphoma (rrFL) is an incurable disease associated with shorter remissions and survival after each line of standard therapy. Many promising novel, chemotherapy-free therapies are in development, but few are licensed as their role in current treatment pathways is poorly defined.

METHODS

The REFRACT trial is an investigator-initiated, UK National Cancer Research Institute, open-label, multi-centre, randomised phase II platform trial aimed at accelerating clinical development of novel therapies by addressing evidence gaps. The first of the three sequential novel therapy arms is epcoritamab plus lenalidomide, to be compared with investigator choice standard therapy (ICT). Patients aged 18 years or older with biopsy proven relapsed or refractory CD20 positive, grade 1-3a follicular lymphoma and assessable disease by PET-CT are eligible. The primary outcome is complete metabolic response by PET-CT at 24 weeks using the Deauville 5-point scale and Lugano 2014 criteria. Secondary outcomes include overall metabolic response, progression-free survival, overall survival, duration of response, and quality of life assessed by EQ-5D-5 L and FACT-Lym. The trial employs an innovative Bayesian design with a target sample size of 284 patients: 95 in the ICT arm and 189 in the novel therapy arms.

DISCUSSION

Whilst there are many promising novel drugs in early clinical development for rrFL, understanding the relative efficacy and safety of these agents, and their place in modern treatment pathways, is limited by a lack of randomised trials and dearth of published outcomes for standard regimens to act as historic controls. Therefore, the aim of REFRACT is to provide an efficient platform to evaluate novel agents against standard therapies for rrFL. The adaptive Bayesian power prior methodology design will minimise patient numbers and accelerate trial delivery.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT05848765; 08-May-2023.

EUDRACT

2022-000677-75; 10-Feb-2022.

Indicators describing the tumor lesion aggregation and dissemination and their impact on the prognosis of patients with diffuse large B cell lymphoma receiving chimeric antigen receptor T cell therapy

INTRODUCTION

Chimeric antigen receptor (CAR) T cell therapy has markedly improved the prognosis of patients with diffuse large B-cell lymphoma (DLBCL). The relative positioning of tumor lesions in lymphoma varies among patients, manifesting as either aggregation (clumped together) or dissemination (spread throughout the body). Prognostic significance of factors indicating the relative positioning of tumor lesions in CAR T cell therapy remains underexplored. For aggregation, prior research proposed the tumor volume surface ratio (TVSR), linking it to prognosis in chemotherapy. Regarding dissemination, indicators such as disease stage or extranodal involvement, commonly used in clinical practice, have not demonstrated prognostic significance in CAR T cell therapy. This study aims to analyze current indicators of tumor aggregation or dissemination and introduce a novel indicator to assess the prognostic value of tumor lesions' relative positioning in DLBCL patients undergoing CAR T cell therapy.

METHODS

This retrospective study included 42 patients receiving CAR T cell therapy. Lesion image information was obtained from the last PET/CT scan prior to CAR T cell infusion, including total metabolic tumor volume, total tumor surface, diameter of lymphoma masses, and the sites of tumor lesions. We evaluated TVSR and bulky disease as descriptors of tumor aggregation. We refined existing indicators, stage III&IV and >1 site extranodal involvement, to distill a new indicator, termed 'extra stage', to better represent tumor dissemination. The study examined the prognostic significance of tumor aggregation and dissemination.

RESULTS

Our findings indicate that TVSR, while prognostically valuable in chemotherapy, lacks practical prognostic value in CAR T cell therapy. Conversely, bulky disease emerged as an optimal prognostic indicator of tumor aggregation. Both bulky disease and extra stage were associated with poor prognosis and exhibiting synergistic prognostic impact in CAR T cell therapy.

CONCLUSIONS

Overall, the relative positioning of tumor lesions significantly influences the prognosis of patients with DLBCL receiving CAR T cell therapy. The ideal scenario involves tumors with minimal dissemination and no aggregation.

A different perspective on PET/CT before treatment in patients with Hodgkin lymphoma: importance of volumetric and dissemination parameters

The aim of this study is to investigate the role of the combination of volumetric and dissemination parameters obtained from pretreatment 18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting the interim response and progression status in patients with Hodgkin lymphoma (HL). Pretreatment PET/CT images of HL patients were analyzed with LIFEx software, and volumes of interest (VOIs) were drawn with a fixed SUV 4.0 threshold. MTV, SUVmax, and TLG values were obtained from each VOI. Total MTV (tMTV) was calculated by summing the MTV values in all VOIs, and similarly, total TLG (tTLG) was obtained by summing the TLG values. The distance between the centers of the lesions was noted as Dmax, and the distance between the outermost voxels of the lesions as DmaxVox. tMTV/DmaxVox was calculated by dividing the tMTV value by the DmaxVox value, and tTLG/DmaxVox was calculated by dividing the tTLG value by the DmaxVox value. The correlation of pretreatment PET parameters with response groups (complete/poor) and relapse/progression status (stable/progressive) was statistically evaluated. A total of 52 patients were included in the study. Bulky disease, tMTV, tTLG, and tMTV/DmaxVox values were found to be significantly higher in the poor response group. tMTV > 190.60 ml was found to be the only prognostic factor predicting interim PET response. The tMTV/DmaxVox and tTLG/DmaxVox showed statistically significant differences between the groups with and without progression. tMTV/DmaxVox > 7.70 was found to be the only prognostic factor in predicting relapse/progression. The evaluation of tumor burden and dissemination together in 18F-FDG PET/CT before treatment in patients with HL can help us to predict the results of the patients.

Optimization of Metabolic Tumor Volume as a Prognostic Marker in CAR T-Cell Therapy for Aggressive Large B-cell NHL

BACKGROUND

CD19-targeted chimeric antigen receptor (CAR) T-cell therapy has become a standard of care in relapsed/refractory (R/R) aggressive large B-cell non-Hodgkin lymphomas (B-NHL) though the majority of recipients do not receive durable disease benefit, prompting the need to better define risk factors for relapse/progression.

OBJECTIVES

We performed a single-center, retrospective analysis of patients treated with commercial CAR T-cell therapy to evaluate the impact of tumor burden, as measured by whole-body metabolic tumor volume (MTV) from 18F fluorodeoxyglucose PET imaging, on treatment outcomes.

STUDY DESIGN

Sixty-one patients treated with CAR T-cell therapy for R/R B-NHL between May 2016 and November 2021 were included.

RESULTS

Using a receiver operating characteristic curve-based MTV optimization cutoff of 450 mL, 1-year progression-free survival (PFS) was 22% for high MTV versus 54% for low MTV (P < .01), and 1-year overall survival (OS) was 37% and 73%, respectively (P = .01). In a subset of 46 patients, residual MTV of less than 106 mL at the day 30 (D30) disease assessment was associated with significantly improved outcomes (1-year OS 85% vs. 13%, P < .01). Incorporation of pretreatment MTV to the International Prognostic Index (IPI) scoring system significantly distinguished 2-year PFS and OS outcomes by 3 risk groups.

CONCLUSIONS

Our findings suggest that both pretreatment and D30 MTV are predictive of outcomes among R/R B-NHL patients treated with CAR T-cell therapy. These data indicate that efforts to reduce pretreatment tumor burden may improve longitudinal clinical outcomes. Furthermore, D30 postinfusion MTV quantification may aid clinicians in optimally identifying patients at high-risk for progression, and in whom closer disease monitoring should be considered. MTV also adds prognostic value to patients with high-risk IPI and holds promise for incorporation in novel risk scoring systems which can identify patients prior to CAR T-cell therapy at highest risk of adverse outcomes.

Tumor Location Relative to the Spleen Is a Prognostic Factor in Lymphoma Patients: A Demonstration from the REMARC Trial

Baseline [18F]FDG PET/CT radiomic features can improve the survival prediction in patients with diffuse large B-cell lymphoma (DLBCL). The purpose of this study was to investigate whether characterizing tumor locations relative to the spleen location in baseline [18F]FDG PET/CT images predicts survival in patients with DLBCL and improves the predictive value of total metabolic tumor volume (TMTV) and age-adjusted international prognostic index (IPI). Methods: This retrospective study included 301 DLBCL patients from the REMARC (NCT01122472) cohort. Physicians delineated the tumor regions, whereas the spleen was automatically segmented using an open-access artificial intelligence algorithm. We systematically measured the distance between the centroid of the spleen and all other lesions, defining the SD of these distances as the lesion spread (SpreadSpleen). We calculated the maximum distance between the spleen and another lesion (Dspleen) for each patient and normalized it with the body surface area, resulting in standardized Dspleen (sDspleen). The predictive value of each PET/CT feature for progression-free survival (PFS) and overall survival (OS) was evaluated through univariate and multivariate time-dependent Cox models and Kaplan-Meier analysis. Results: In total, 282 patients (mean age, 68.33 ± 5.41 y; 164 men) were evaluated. The artificial intelligence algorithm successfully segmented the spleen in 96% of the patients. SpreadSpleen, Dspleen, and sDspleen were correlated neither with TMTV (Pearson ρ < 0.23) nor with IPI (Pearson ρ < 0.15). When median values were used as the cutoff, SpreadSpleen, Dspleen, and sDspleen all significantly classified patients into 2 risk groups for PFS and OS (P < 0.001). They complemented TMTV and IPI to classify the patients into 3 risk groups for PFS and OS (P < 0.001). Integrating SpreadSpleen, Dspleen, or sDspleen into a Cox model on the basis of TMTV, IPI, and TMTV combined with IPI significantly improved the concordance index for PFS and OS (P < 0.05). Conclusion: Baseline PET/CT features that characterize tumor spread and dissemination relative to the spleen strongly predicted survival in patients with DLBCL. Integrating these features with TMTV and IPI further improved survival prediction.

PET/CT Biomarkers Enable Risk Stratification of Patients with Relapsed/Refractory Diffuse Large B-cell Lymphoma Enrolled in the LOTIS-2 Clinical Trial

PURPOSE

Significant progress has occurred in developing quantitative PET/CT biomarkers in diffuse large B-cell lymphoma (DLBCL). Total metabolic tumor volume (MTV) is the most extensively studied, enabling assessment of FDG-avid tumor burden associated with outcomes. However, prior studies evaluated the outcome of cytotoxic chemotherapy or chimeric antigen receptor T-cell therapy without data on recently approved FDA agents. Therefore, we aimed to assess the prognosis of PET/CT biomarkers in patients treated with loncastuximab tesirine.

EXPERIMENTAL DESIGN

We centrally reviewed screening PET/CT scans of patients with relapsed/refractory DLBCL enrolled in the LOTIS-2 (NCT03589469) study. MTV was obtained by computing individual volumes using the SUV ≥4.0 threshold. Other PET/CT metrics, clinical factors, and the International Metabolic Prognostic Index (IMPI) were evaluated. Logistic regression was used to assess the association between biomarkers and treatment response. Cox regression was used to determine the effect of biomarkers on time-to-event outcomes. We estimated biomarker prediction as continuous and binary variables defined by cutoff points.

RESULTS

Across 138 patients included in this study, MTV with a cutoff point of 96 mL was the biomarker associated with the highest predictive performance in univariable and multivariable models to predict failure to achieve complete metabolic response (OR, 5.42; P = 0.002), progression-free survival (HR, 2.68; P = 0.002), and overall survival (HR, 3.09; P < 0.0001). IMPI demonstrated an appropriate performance, however, not better than MTV alone.

CONCLUSIONS

Pretreatment MTV demonstrated robust risk stratification, with those patients demonstrating high MTV achieving lower responses and survival to loncastuximab tesirine in relapsed/refractory DLBCL.

Baseline [18F]FDG PET features are associated with survival and toxicity in patients treated with CAR T cells for large B cell lymphoma

PURPOSE

Chimeric antigen receptor (CAR) T cells have established themselves as an effective treatment for refractory or relapsed large B cell lymphoma (LBCL). Recently, the sDmax, which corresponds to the distance separating the two farthest lesions standardized by the patient's body surface area, has appeared as a prognostic factor in LBCL. This study aimed to identify [18F]FDG-PET biomarkers associated with prognosis and predictive of adverse events in patients treated with CAR T cells.

METHODS

Patients were retrospectively included from two different university hospitals. They were being treated with CAR T cells for LBCL and underwent [18F]FDG-PET just before CAR T cell infusion. Lesions were segmented semi-automatically with a threshold of 41% of the maximal uptake. In addition to clinico-biological features, sDmax, total metabolic tumor volume (TMTV), SUVmax, and uptake intensity of healthy lymphoid organs and liver were collected. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. The occurrence of adverse events, such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), was reported.

RESULTS

Fifty-six patients were included. The median follow-up was 9.7 months. Multivariate analysis showed that TMTV (cut-off of 36 mL) was an independent prognostic factor for PFS (p < 0.001) and that sDmax (cut-off of 0.15 m-1) was an independent prognostic factor for OS (p = 0.008). Concerning the occurrence of adverse events, a C-reactive protein level > 35 mg/L (p = 0.006) and a liver SUVmean > 2.5 (p = 0.027) before CAR T cells were associated with grade 2 to 4 CRS and a spleen SUVmean > 1.9 with grade 2 to 4 ICANS.

CONCLUSION

TMTV and sDmax had independent prognostic values, respectively, on PFS and OS. Regarding adverse events, the mean liver and spleen uptakes were associated with the occurrence of grade 2 to 4 CRS and ICANS, respectively. Integrating these biomarkers into the clinical workflow could be useful for early adaptation of patients management.

Metabolic tumor volume predicts outcome in patients with advanced stage follicular lymphoma from the RELEVANCE trial

BACKGROUND

We investigated the prognostic value of baseline positron emission tomography (PET) parameters for patients with treatment-naïve follicular lymphoma (FL) in the phase III RELEVANCE trial, comparing the immunomodulatory combination of lenalidomide and rituximab (R2) versus R-chemotherapy (R-chemo), with both regimens followed by R maintenance therapy.

PATIENTS AND METHODS

Baseline characteristics of the entire PET-evaluable population (n = 406/1032) were well balanced between treatment arms. The maximal standard uptake value (SUVmax) and the standardized maximal distance between tow lesions (SDmax) were extracted, the standardized distance between two lesions the furthest apart, were extracted. The total metabolic tumor volume (TMTV) was computed using the 41% SUVmax method.

RESULTS

With a median follow-up of 6.5 years, the 6-year progression-free survival (PFS) was 57.8%, the median TMTV was 284 cm3, SUVmax was 11.3 and SDmax was 0.32 m-1, with no significant difference between arms. High TMTV (>510 cm3) and FLIPI were associated with an inferior PFS (P = 0.013 and P = 0.006, respectively), whereas SUVmax and SDmax were not (P = 0.08 and P = 0.12, respectively). In multivariable analysis, follicular lymphoma international prognostic index (FLIPI) and TMTV remained significantly associated with PFS (P = 0.0119 and P = 0.0379, respectively). These two adverse factors combined stratified the overall population into three risk groups: patients with no risk factors (40%), with one factor (44%), or with both (16%), with a 6-year PFS of 67.7%, 54.5%, and 41.0%, respectively. No significant interaction between treatment arms and TMTV or FLIPI (P = 0.31 or P = 0.59, respectively) was observed. The high-risk group (high TMTV and FLIPI 3-5) had a similar PFS in both arms (P = 0.45) with a median PFS of 68.4% in the R-chemo arm versus 71.4% in the R2 arm.

CONCLUSIONS

Baseline TMTV is predictive of PFS, independently of FLIPI, in patients with advanced FL even in the context of antibody maintenance.

Prognostic Value of Baseline Tumor Burden and Tumor Dissemination Extracted From 18 F-FDG PET/CT in a Cohort of Adult Patients With Early or Advanced Hodgkin Lymphoma

PURPOSE

We aimed to assess the prognostic value of baseline tumor burden and dissemination parameters extracted from 18 F-FDG PET/CT in patients with early or advanced Hodgkin lymphoma (HL) treated with ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) or escalated BEACOPP (increased bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone).

PATIENTS AND METHODS

Patients aged ≥18 years with classical Hodgkin lymphoma were retrospectively included. Progression-free survival (PFS) analysis of dichotomized clinicobiological and PET/CT parameters (SUV max , TMTV, TLG, D max , and D bulk ) was performed. Optimal cutoff values for quantitative metrics were defined as the values maximizing the Youden index from receiver operating characteristic analysis. PFS rates were estimated with Kaplan-Meier curves, and the log-rank test was used to assess statistical significance. Hazard ratios were calculated using Cox proportional hazards models.

RESULTS

With a median age of 32 years, 166 patients were enrolled. A total of 111 patients had ABVD or ABVD-like treatment with or without radiotherapy and 55 patients with escalated BEACOPP treatment. The median follow-up was 55 months. Only International Prognostic Score (IPS >1), TMTV >107 cm 3 , and TLG >1628 were found to be significant prognostic factors for PFS on univariate analysis. Multivariate analysis revealed that IPS and TLG were independently prognostic and, combined, identified 4 risk groups ( P < 0.001): low (low TLG and low IPS; 4-year PFS, 95%), intermediate-low (high IPS and low TLG; 4-year PFS, 79%), intermediate-high (low IPS and high TLG; 4-year PFS, 78%), and high (high TLG and high IPS; 4-year PFS, 71%).

CONCLUSIONS

Combining baseline TLG with IPS could improve PFS prediction.

FDG PET/CT Tumor Dissemination Characteristic Predicts the Outcome of First-Line Systemic Therapy in Non-small Cell Lung Cancer

RATIONALE AND OBJECTIVES

To explore the correlation between the tumor dissemination characteristic at 18F-fluoro-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images and the outcome of first-line systemic therapy for stage IV non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

The current retrospective study included 101 NSCLC patients receiving first-line systemic therapy with baseline 18F-FDG PET/CT images available. The distance between the two lesions that were the farthest apart was defined as Dmax to calculate the tumor dissemination. The tumor metabolic volume (MTV) of the primary tumor and the MTV of the whole-body tumor lesions (MTVwb) were calculated using 18F-FDG PET/CT imaging. The Kaplan-Meier survival analyses and Cox predictive model were performed to assess the relationship between the parameters and survival.

RESULTS

Dmax and MTVwb were independent prognostic factors for overall survival (OS) (p = 0.019 and p = 0.011, respectively) and progression-free survival (PFS) (p = 0.043 and p = 0.009, respectively). Poor PFS and OS were associated with high MTVwb (>54.0 cm3) and high Dmax (>48.5 cm) (p = 0.006 and p = 0.008, respectively). When MTVwb and Dmax were combined, three risk groups were stratified with no (score 0), one (score 1), or two (score 2) factors (p < 0.001 for PFS, p < 0.001 for OS). The group with a score of 0 had a considerably longer PFS and OS than those who received a score of 1 or 2 (PFS: 61.1%, 43.5%, and 21.1%, respectively, OS: 77.8%, 54.3%, and 36.8%, respectively).

CONCLUSION

The combination of tumor dissemination characteristic (Dmax) and tumor burden (MTVwb) can further improve the prognosis stratification of NSCLC.

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.

Predictive value of Dmax and %ΔSUVmax of 18F-FDG PET/CT for the prognosis of patients with diffuse large B-cell lymphoma

PURPOSE

To investigate the prognosis value of a combined model based on 18F-fluoro-deoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) baseline and interim parameters in patients with diffuse large B-cell lymphoma (DLBCL).

METHODS

We retrospectively analyzed the PET metabolic parameters and clinical data of 154 DLBCL patients between December 2015 and October 2020. All of these patients underwent 18F-FDG PET/CT scan before treatment and after three or four courses of chemotherapy. The optimal cut-off values for quantitative variables were determined by the receiver operating characteristic (ROC) curve. The baseline and interim PET/CT parameters, which respectively included maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax) and total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%ΔSUVmax), and clinical characteristics were analyzed by chi-squared test, Kaplan-Meier survival curve, and Cox regression analysis.

RESULTS

Of 154 patients, 35 exhibited disease progression or recurrence. ROC analysis revealed that baseline 18F-FDG PET/CT metabolic parameters, including maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax), along with interim 18F-FDG PET/CT metabolic parameters such as total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%ΔSUVmax), were predictive of relapse or progression in DLBCL patients (P < 0.05). The chi-squared test showed that TMTV0, STMTV0, Dmax, SUVmax1, TMTV1, TTLG1, %ΔSUVmax, Deauville score, IPI, Ann Arbor stage, and LDH were associated with patient prognosis (P < 0.05). Multivariate Cox regression analysis showed that Dmax (P = 0.021) and %ΔSUVmax (P = 0.030) were independent predictors of prognosis in DLBCL patients. There were statistically significant differences in PFS among the three groups with high, intermediate, and low risk according to the combination model (P < 0.001). The combination model presented higher predictive efficacy than single indicators.

CONCLUSION

The combined model of baseline parameter Dmax and intermediate parameter %ΔSUVmax of 18F-FDG PET/CT improved the predictive efficacy of PFS and contributed to the risk stratification of patients, providing a reference for clinical individualization and precision treatment.

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.

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.

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 nomogram for predicting the rapid progression of diffuse large B-cell lymphoma established by combining baseline PET/CT total metabolic tumor volume, lesion diffusion, and TP53 mutations

OBJECTIVES

This study aimed to integrate positron emission tomography/computed tomography (PET/CT) metrics and genetic mutations to optimize the risk stratification for diffuse large B-cell lymphoma (DLBCL) patients.

METHODS

The data of 94 primary DLBCL patients with baseline PET/CT examination completed in the Shandong Cancer Hospital and Institute (Jinan, China) were analyzed to establish a training cohort. An independent cohort of 45 DLBCL patients with baseline PET/CT examination from other hospitals was established for external validation. The baseline total metabolic tumor volume (TMTV) and the largest distance between two lesions (Dmax) standardized by patient body surface area (SDmax) were calculated. The pretreatment pathological tissues of all patients were sequenced by a lymphopanel including 43 genes.

RESULTS

The optimal TMTV cutoff was 285.3 cm3 and the optimal SDmax cutoff was 0.135 m-1 . TP53 status was found as an independent predictive factor significantly affecting complete remission (p = 0.001). TMTV, SDmax, and TP53 status were the main factors of the nomogram and could stratify the patients into four distinct subgroups based on their predicted progression-free survival (PFS). The calibration curve demonstrated satisfactory agreement between the predicted and actual 1-year PFS of the patients. The receiver operating characteristic curves showed this nomogram based on PET/CT metrics and TP53 mutations had a better predictive ability than the clinic risk scores. Similar results were identified upon external validation.

CONCLUSIONS

The nomogram based on imaging factors and TP53 mutations could lead to a more accurate selection of DLBCL patients with rapid progression, to increase tailor therapy.

Radiomics predictive modeling from dual-time-point FDG PET Ki parametric maps: application to chemotherapy response in lymphoma

BACKGROUND

To investigate the use of dynamic radiomics features derived from dual-time-point (DTP-feature) [¹⁸F]FDG PET metabolic uptake rate K_i parametric maps to develop a predictive model for response to chemotherapy in lymphoma patients.

METHODS

We analyzed 126 lesions from 45 lymphoma patients (responding n = 75 and non-responding n = 51) treated with chemotherapy from two different centers. Static and DTP radiomics features were extracted from baseline static PET images and DTP K_i parametric maps. Spearman's rank correlations were calculated between static and DTP features to identify features with potential additional information. We first employed univariate analysis to determine correlations between individual features, and subsequently utilized multivariate analysis to derive predictive models utilizing DTP and static radiomics features before and after ComBat harmonization. For multivariate modeling, we utilized both the minimum redundancy maximum relevance feature selection technique and the XGBoost classifier. To evaluate our model, we partitioned the patient datasets into training/validation and testing sets using an 80/20% split. Different metrics for classification including area under the curve (AUC), sensitivity (SEN), specificity (SPE), and accuracy (ACC) were reported in test sets.

RESULTS

Via Spearman's rank correlations, there was negligible to moderate correlation between 32 out of 65 DTP features and some static features (ρ < 0.7); all the other 33 features showed high correlations (ρ ≥ 0.7). In univariate modeling, no significant difference between AUC of DTP and static features was observed. GLRLM_RLNU from static features demonstrated a strong correlation (AUC = 0.75, p value = 0.0001, q value = 0.0007) with therapy response. The most predictive DTP features were GLCM_Energy, GLCM_Entropy, and Uniformity, each with AUC = 0.73, p value = 0.0001, and q value < 0.0005. In multivariate analysis, the mean ranges of AUCs increased following harmonization. Use of harmonization plus combining DTP and static features was shown to provide significantly improved predictions (AUC = 0.97 ± 0.02, accuracy = 0.89 ± 0.05, sensitivity = 0.92 ± 0.09, and specificity = 0.88 ± 0.05). All models depicted significant performance in terms of AUC, ACC, SEN, and SPE (p < 0.05, Mann-Whitney test).

CONCLUSIONS

Our results demonstrate significant value in harmonization of radiomics features as well as combining DTP and static radiomics models for predicting response to chemotherapy in lymphoma patients.

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.

Risk Factors of Progression in Low-tumor Burden Follicular Lymphoma Initially Managed by Watch and Wait in the Era of PET and Rituximab

Patients (pts) with asymptomatic low-burden follicular lymphoma (FL) are usually observed at diagnosis. Time to lymphoma treatment (TLT) initiation can however be very heterogeneous and risk factors of progression are poorly studied. Our study evaluated 201 pts with grade 1-3a low-tumor burden FL diagnosed in four French centers between 2010 and 2020 and managed by a watch and wait strategy in real-life settings. After a median follow-up of 4.8 years, the median TLT was 4.2 years (95% confidence interval, 3.1-5.5). On multivariate analysis, elevated lactate dehydrogenase (hazard ratio [HR] = 2.2; P = 0.02), more than 4 nodal areas involved (HR = 1.7; P = 0.02) and more than 1 extranodal involvement (HR = 2.7; P = 0.01) were identified as independent predictors of TLT. The median TLT was 5.8 years for pts with no risk factor, 2.4 years for 1 risk factor, and 1.3 years for >1 risk factors (P < 0.01). In a subanalysis of 75 pts staged with positron emission tomography-computed tomography (PET-CT), total metabolic tumor volume (TMTV) ≥14 cm³ and standardized Dmax (reflecting tumor dissemination) >0.32 m^-1 were also associated with shorter TLT (HR = 3.4; P = 0.004 and HR = 2.4; P = 0.007, respectively). In multivariate models combining PET-CT parameters and clinical variables, TMTV remained independent predictor of shorter TLT. These simple parameters could help to identify FL patients initially observed at higher risk of early progression. The role of PET-CT (extranodal sites and PET metrics) in low-burden FL appears promising and warrants further assessment in large cohorts.

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.

Molecular Imaging of Lymphoma: Future Directions and Perspectives

More than 250,000 patients die from Hodgkin or non-Hodgkin lymphoma each year. Currently, molecular imaging with ¹⁸F-FDG-PET/CT is the standard of care for lymphoma staging and therapy response assessment. In this review, we will briefly summarize the role of molecular imaging for lymphoma diagnosis, staging, outcome prediction, and prognostication. We discuss future directions in response assessment and surveillance with quantitative PET parameters, the utility of interim assessment, and the differences with response assessment to immunomodulatory therapy. Lastly, we will cover innovations in the field regarding novel tracers and artificial intelligence.

European Association of Nuclear Medicine (EANM) Focus 4 consensus recommendations: molecular imaging and therapy in haematological tumours

Given the paucity of high-certainty evidence, and differences in opinion on the use of nuclear medicine for hematological malignancies, we embarked on a consensus process involving key experts in this area. We aimed to assess consensus within a panel of experts on issues related to patient eligibility, imaging techniques, staging and response assessment, follow-up, and treatment decision-making, and to provide interim guidance by our expert consensus. We used a three-stage consensus process. First, we systematically reviewed and appraised the quality of existing evidence. Second, we generated a list of 153 statements based on the literature review to be agreed or disagreed with, with an additional statement added after the first round. Third, the 154 statements were scored by a panel of 26 experts purposively sampled from authors of published research on haematological tumours on a 1 (strongly disagree) to 9 (strongly agree) Likert scale in a two-round electronic Delphi review. The RAND and University of California Los Angeles appropriateness method was used for analysis. Between one and 14 systematic reviews were identified on each topic. All were rated as low to moderate quality. After two rounds of voting, there was consensus on 139 (90%) of 154 of the statements. There was consensus on most statements concerning the use of PET in non-Hodgkin and Hodgkin lymphoma. In multiple myeloma, more studies are required to define the optimal sequence for treatment assessment. Furthermore, nuclear medicine physicians and haematologists are awaiting consistent literature to introduce volumetric parameters, artificial intelligence, machine learning, and radiomics into routine practice.

18F-FDG PET/CT Maximum Tumor Dissemination (Dmax) in Lymphoma: A New Prognostic Factor?

Recently, several studies introduced the potential prognostic usefulness of maximum tumor dissemination (Dmax) measured by 2-deoxy-2-fluorine-18-fluoro-D-glucose positron-emission tomography/computed tomography (¹⁸F-FDG PET/CT). Dmax is a simple three-dimensional feature that represents the maximal distance between the two farthest hypermetabolic PET lesions. A comprehensive computer literature search of PubMed/MEDLINE, Embase, and Cochrane libraries was conducted, including articles indexed up to 28 February 2023. Ultimately, 19 studies analyzing the value of ¹⁸F-FDG PET/CT Dmax in patients with lymphomas were included. Despite their heterogeneity, most studies showed a significant prognostic role of Dmax in predicting progression-free survival (PFS) and overall survival (OS). Some articles showed that the combination of Dmax with other metabolic features, such as MTV and interim PET response, proved to better stratify the risk of relapse or death. However, some methodological open questions need to be clarified before introducing Dmax into clinical practice.

Are dynamic or fixed FDG-PET measures of disease of greater prognostic value in patients with relapsed/refractory diffuse large B-cell lymphoma undergoing autologous haematopoietic stem cell transplantation?

Positron emission tomography (PET) response assessment using the Deauville score has prognostic utility in relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) undergoing autologous stem-cell transplantation (ASCT). Improved predictive methods are required to identify patients with poor outcomes who may be better considered for other salvage options. We investigated the prognostic value of mean tumour volume (MTV) and maximum standardised uptake value (SUVmax) at pre-salvage and pre-ASCT time-points, and the quantitative changes between scans (∆MTV and ∆SUVmax). One hundred and twenty-five patients with R/R DLBCL underwent salvage immunochemotherapy and ASCT: 80 patients had pre-salvage PET and 90 had pre-ASCT PET available. With a median follow-up of 5.6 years, 5-year progression-free survival (PFS) and overall survival (OS) were 52% and 65%, respectively. For patients with PET-positive residual disease after salvage therapy, pre-ASCT MTV was a significant negative prognosticator for PFS (HR 1.19 per 100 ml, p < 0.001) and OS (HR 1.78 per 100 ml, p < 0.001). Similarly, pre-ASCT SUVmax was negatively associated with PFS (HR 1.08, p < 0.001) and OS (HR 1.08, p < 0.001). Notably, pre-salvage MTV and SUVmax and ∆MTV and ∆SUVmax were not associated with PFS or OS. In conclusion, pre-ASCT MTV and SUVmax appear to be of greater predictive value than the degree of response. Potential application may exist for PET-directed management of R/R DLBCL patients.

Prognostic Value of 18F-FDG PET/CT in Diffuse Large B-Cell Lymphoma Treated with a Risk-Adapted Immunochemotherapy Regimen

Early identification of patients with diffuse large B-cell lymphoma (DLBCL) who are likely to experience disease recurrence or refractory disease after rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) would be useful for improving risk-adapted treatment strategies. We aimed to assess the prognostic value of 18F-FDG PET/CT parameters at baseline, interim, and end of treatment (EOT). Methods: We analyzed the prognostic impact of 18F-FDG PET/CT in 166 patients with DLBCL treated with a risk-adapted immunochemotherapy regimen. Scans were obtained at baseline, after 4 cycles of R-CHOP or 3 cycles of RR-CHOP (double dose of R) and 1 cycle of CHOP alone (interim) and 6 wk after completing therapy (EOT). Progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan-Meier and the impact of clinical/PET factors assessed with Cox models. We also assessed the predictive ability of the recently proposed International Metabolic Prognostic Index (IMPI). Results: The median follow-up was 7.9 y. International Prognostic Index (IPI), baseline metabolic tumor volume (MTV), and change in maximum SUV (ΔSUVmax) at interim scans were statistically significant predictors for OS. Baseline MTV, interim ΔSUVmax, and EOT Deauville score were statistically significant predictors of PFS. Combining interim PET parameters demonstrated that patients with Deauville 4-5 and positive ΔSUVmax ≤ 70% at restaging (∼10% of the cohort) had extremely poor prognosis. The IMPI had limited discrimination and slightly overestimated the event rate in our cohort. Conclusion: Baseline MTV and interim ΔSUVmax predicted both PFS and OS with this sequential immunochemotherapy program. Combining interim Deauville score with interim ΔSUVmax may identify an extremely high-risk DLBCL population.

Role of 18F-fluorodeoxyglucose PET/computed tomography in the diagnosis and treatment response assessment of primary bone lymphoma

OBJECTIVE

Primary bone lymphoma (PBL) is a rare type of extranodal lymphoma, and the clinical application value of 18F-fluorodeoxyglucose PET/computed tomography ( 18 F-FDG PET/CT) in PBL has not been fully evaluated. This study aimed to determine the imaging characteristics of PBL and investigate the value of 18 F-FDG PET/CT parameters.

METHODS

A total of 25 patients with PBL who underwent PET/CT examination before treatment were included in this study. The clinicopathological parameters and PET/CT parameters were analyzed.

RESULTS

Among the 25 patients, 7 patients had single lesions, 15 patients had nonsingle lesions (≥2) and 3 patients had diffuse distribution in the medullary cavity. The bone destruction types included osteolytic, osteogenic, normal density, mixed lytic and osteogenic. All patients showed increased FDG uptake, and the CT detection rate was 88%. Five patients underwent PET/CT assessment mid-treatment, and when assessed using the Deauville five-point scale, four patients were PET-negative and one patient was PET-positive. There were two PET-positive and three PET-negative patients when assessed using the Δ maximum standardized uptake value (SUV max ) method. Six patients underwent PET/CT imaging at the end of treatment. When assessed using the Deauville five-point scale, five patients (83%) were PET-negative and one patient (17%) was PET-positive. The same results were obtained when evaluated by the ΔSUV max method.

CONCLUSION

PET/CT plays a substantial role in the diagnosis and treatment efficacy evaluation of PBL, and it should be recognized by clinicians and radiologists. Changes in metabolic parameters such as SUV, metabolic tumor volume and total lesion glycolysis have considerable potential for application in PBL diagnostics and treatment efficacy evaluation.

Prognostic value of metabolic tumor volume and lesion dissemination from baseline PET/CT in patients with diffuse large B-cell lymphoma: further risk stratification of the group with low-risk and high-risk NCCN-IPI

PURPOSE

The purpose of this study was to determine the prognostic value of metabolic tumor volume and lesion dissemination from baseline PET/CT in patients with diffuse large B-cell lymphoma (DLBCL) and the prognostic value of them in the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) subgroups.

METHODS

A total of 113 patients who underwent ¹⁸F-FDG PET/CT examination in our institution were retrospectively collected. The MTV was measured by iterative adaptive algorithm. The location of the lesion was obtained according to its three-dimensional coordinates, and Dmax was obtained. SDmax is derived from Dmax standardized by body surface area (BSA). The X-tile method was used to determine the optimal cut-off values for MTV, Dmax and SDmax. Cox regression analysis was used to perform univariate and multivariate analyses. Patient survival rates were derived from Kaplan-Meier curves and compared using the log-rank test.

RESULTS

The median follow-up time was 24 months. The median of MTV was 196.86 cm³ (range 2.54-2925.37 cm³), and the optimal cut-off value was 489 cm³. The median of SDmax was 0.25 m^-1 (range 0.12-0.51 m^-1), and the best cut-off value was 0.31 m^-1. MTV and SDmax were independent prognostic factors of PFS (all P < 0.001). Combined with MTV and SDmax, the patients were divided into three groups, and the difference of PFS among the groups was statistically significant (P < 0.001), and was able to stratify the risk of NCCN-IPI patients in the low-risk (NCCN-IPI < 4) and high-risk (NCCN-IPI ≥ 4) groups (P = 0.001 and P = 0.031).

CONCLUSION

MTV and SDmax are independent prognostic factors for PFS in DCBCL patients, which describe tumor burden and tumor dissemination characteristics, respectively. The combination of the two could facilitate risk stratification between the low-risk and high-risk NCCN-IPI groups.

Prognostic value of baseline 18F-FDG PET/CT in patients with esophageal squamous cell carcinoma treated with definitive (chemo)radiotherapy

PURPOSE

To investigate the prognostic value of baseline ¹⁸F-FDG PET/CT in patients with esophageal squamous cell carcinoma (ESCC) treated with definitive (chemo)radiotherapy.

METHODS

A total of 98 ESCC patients with cTNM stage T1-4, N1-3, M0 who received definitive (chemo)radiotherapy after ¹⁸F-FDG PET/CT examination from December 2013 to December 2020 were retrospectively analyzed. Clinical factors included age, sex, histologic differentiation grade, tumor location, clinical stage, and treatment strategies. Parameters obtained by ¹⁸F-FDG PET/CT included SUV_max of primary tumor (SUV_Tumor), metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUV_max of lymph node (SUV_LN), PET positive lymph nodes (PLNS) number, the shortest distance between the farthest PET positive lymph node and the primary tumor in three-dimensional space after the standardization of the patient BSA (SD_max(LN-T)). Univariate and multivariate analysis was conducted by Cox proportional hazard model to explore the significant factors affecting overall survival (OS) and progression-free survival (PFS) in ESCC patients.

RESULTS

Univariate analysis showed that tumor location, SUV_Tumor, MTV, TLG, PLNS number, SD_{max (LN-T)} were significant predictors of OS and tumor location, and clinical T stage, SUV_Tumor, MTV, TLG, SD_{max (LN-T)} were significant predictors of PFS (all p < 0.1). Multivariate analysis showed that MTV and SD_{max (LN-T)} were independent prognostic factors for OS (HR = 1.018, 95% CI 1.006-1.031; p = 0.005; HR = 6.988, 95% CI 2.119-23.042; p = 0.001) and PFS (HR = 1.019, 95% CI 1.005-1.034; p = 0.009; HR = 5.819, 95% CI 1.921-17.628; p = 0.002). Combined with independent prognostic factors MTV and SD_{max (LN-T)}, we can further stratify patient risk.

CONCLUSIONS

Before treatment, ¹⁸F-FDG PET/CT has important prognostic value for patients with ESCC treated with definitive (chemo)radiotherapy. The lower the value of MTV and SD_{max (LN-T)}, the better the prognosis of patients.

Prognostic value of 18F-FDG lesion dissemination features in patients with peripheral T-cell lymphoma (PTCL)

PURPOSE

To explore the prognostic value of the distance between the two lesions that were farthest apart (Dmax) on baseline 18F-FDG PET/CT in peripheral T lymphoma (PTCL) and establish a new prognostic model for predicting the survival outcomes of patients with PTCL.

METHODS

In this study, a retrospective analysis of 95 patients with PTCL who underwent baseline 18F-FDG PET/CT was performed to assess the predictive value of Dmax. The total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), standardized uptake value (SUV), and Dmax were calculated with LIFEx software. Progression-free survival (PFS) and overall survival (OS) were used as endpoints. The prognostic model was developed based on the results of the multivariate analysis. The time-dependent area under the ROC curve (tdAUC), calibration curves, Harrell C-index, and decision curve analysis (DCA) were used to assess the model.

RESULTS

Patients were followed up for a median of 17.0 months. Multivariate analysis showed that bone marrow biopsy (BMB) and Dmax were independent predictors of PFS (HR: 1.889, P = 0.039; HR: 1.965, P = 0.047) and OS (HR: 1.923, P = 0.031; HR: 1.982, P = 0.034). The model consisting of Dmax, TMTV, and BMB had substantial prognostic value for survival outcomes of PTCL and could successfully identify four groups of patients with significantly different prognoses (χ² = 13.731, P = 0.003 for PFS; χ² = 11.841, P = 0.008 for OS). The tdAUC, C-index, calibration curves, and DCA supported that the model was superior to the prognostic index for T-cell lymphoma (PIT) and International Prognostic Index (IPI) scores.

CONCLUSION

BMB and Dmax were independent predictors of PTCL in our study. Moreover, a prognostic model based on the Dmax, TMTV, and BMB could be useful for predicting the survival outcomes of patients with PTCL.