Baseline SUVmax is related to tumor cell proliferation and patient outcome in follicular lymphoma

End-of-treatment 18[F]-FDG PET can predict early progression in patients receiving bendamustine-rituximab for follicular lymphoma in first relapse: a prospective West Japan hematology Study Group (W-JHS) NHL01 trial

Response determined by 18[F]-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET)-CT after induction therapy can predict progression-free survival (PFS) in follicular lymphoma (FL). However, little prospective research has examined the significance of PET after second-line therapy. We conducted a prospective multicenter phase II trial (W-JHS NHL01) of bendamustine plus rituximab (BR) without rituximab maintenance for FL in first relapse. This study aimed to evaluate the usefulness of end-of-treatment (EOT)-PET for predicting PFS in FL patients in first relapse. EOT-PET examinations were performed between 6 and 8 weeks from the start of the last BR cycle. The primary endpoint was 1-year PFS. Key secondary endpoints were overall response rate (ORR), complete response rate (CRR), and 1-year overall survival (OS). Seventy-five patients were enrolled, and 8 were excluded from analysis. ORR was 86.6% and CRR was 59.7%. One-year PFS was 88.9% (95% confidence interval [CI] 80.7-94.3%) and 1-year OS in 75 patients was 97.3% (95% CI 89.6-99.3%). One-year PFS was significantly inferior in EOT-PET-positive patients (n = 9) compared with PET-negative patients (n = 58) (77.8% vs. 93.1%; p = 0.02). We confirmed that EOT-PET after second-line BR therapy could predict early progression in FL patients in first relapse.

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.

Involvement of spleen is associated with shorter survival in patients with angioimmunoblastic T cell lymphoma

BACKGROUND

The prognosis of patients with angioimmunoblastic T cell lymphoma (AITL) remains dismal, with their 5-year overall survival (OS) and progression-free survival (PFS) rates of 32-41% and 18-38%, respectively. Spleen involvement occurs in a proportion of patients with AITL. But still, it is unclear whether spleen involvement impacts the prognosis of AITL patients. In this study, we aim to establish new prognostic indicators for the identification of high-risk patients to draft optimal treatment regimens.

METHODS

We collected and counted the clinical data of 54 patients with AITL treated with CHOP-based first-line chemotherapy regimen between 2010 and 2021 at Hubei Cancer Hospital and Hunan Cancer Hospital. In addition, all patients received PET-CT scan prior to receiving treatment. We performed univariate and multivariate analyses to assess the predictive role of tumor characteristics, laboratory, and radiographic data for the prognosis of AITL.

RESULTS

We observed that PFS and OS are worse in patients with high ECOG scores, spleen involvement, and low serum albumin levels in patients with AITL. In univariate analysis, stage (HR 3.515 [1.142-10.822], p = 0.028) and spleen involvement (HR 8.378 [1.085-64.696, p = 0.042) were correlated with PFS in patients with AITL. Besides, stage (HR 3.439 [1.108-10.674], p = 0.033) and spleen involvement (HR 11.002 [1.420-85.254], p = 0.022) were significantly correlated with OS. Consistently, spleen involvement was correlated with OS (HR 16.571 [1.350-203.446], p = 0.028) and PFS (HR 10.905 [1.037-114.690], p = 0.047) in AITL patients in a multivariate analysis.

CONCLUSION

This study demonstrates that spleen involvement might be used as a prognostic indicator for AITL patients.

Evaluation of Semiautomatic and Deep Learning-Based Fully Automatic Segmentation Methods on [18F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization

The objective is to assess the performance of seven semiautomatic and two fully automatic segmentation methods on [18F]FDG PET/CT lymphoma images and evaluate their influence on tumor quantification. All lymphoma lesions identified in 65 whole-body [18F]FDG PET/CT staging images were segmented by two experienced observers using manual and semiautomatic methods. Semiautomatic segmentation using absolute and relative thresholds, k-means and Bayesian clustering, and a self-adaptive configuration (SAC) of k-means and Bayesian was applied. Three state-of-the-art deep learning-based segmentations methods using a 3D U-Net architecture were also applied. One was semiautomatic and two were fully automatic, of which one is publicly available. Dice coefficient (DC) measured segmentation overlap, considering manual segmentation the ground truth. Lymphoma lesions were characterized by 31 features. Intraclass correlation coefficient (ICC) assessed features agreement between different segmentation methods. Nine hundred twenty [18F]FDG-avid lesions were identified. The SAC Bayesian method achieved the highest median intra-observer DC (0.87). Inter-observers' DC was higher for SAC Bayesian than manual segmentation (0.94 vs 0.84, p < 0.001). Semiautomatic deep learning-based median DC was promising (0.83 (Obs1), 0.79 (Obs2)). Threshold-based methods and publicly available 3D U-Net gave poorer results (0.56 ≤ DC ≤ 0.68). Maximum, mean, and peak standardized uptake values, metabolic tumor volume, and total lesion glycolysis showed excellent agreement (ICC ≥ 0.92) between manual and SAC Bayesian segmentation methods. The SAC Bayesian classifier is more reproducible and produces similar lesion features compared to manual segmentation, giving the best concordant results of all other methods. Deep learning-based segmentation can achieve overall good segmentation results but failed in few patients impacting patients' clinical evaluation.

Personalised therapy in follicular lymphoma - is the dial turning?

Follicular lymphoma is the most common indolent lymphoma accounting for approximately 20%-25% of all new non-Hodgkin lymphoma diagnoses in western countries. Whilst outcomes are mostly favorable, the spectrum of clinical phenotypes includes high-risk groups with significantly inferior outcomes. This review discusses recent updates in risk stratification and treatment approaches from upfront treatment for limited and advanced stage follicular lymphoma to the growing options for relapsed, refractory disease with perspectives on how to approach this from a personalized lens. Notable gaps remain on how one can precisely and prospectively select optimal treatment for patients based on varying risks, with an anticipation that an increased understanding of the biology of these different phenotypes and increasing refinement of imaging- and biomarker-based tools will, in time, allow these gaps to be closed.

Ki67 proliferation index in follicular lymphoma is associated with favorable outcome in patients treated with R-CHOP

Follicular lymphoma (FL) is a common, indolent small B-cell lymphoma. While the Follicular Lymphoma International Prognostic Index is widely used, reliable prognostic and predictive biomarkers are needed. A recent study suggested that architectural patterns of CD10, BCL6, and Ki67 expression may correlate with progression-free survival (PFS) in FL patients treated with chemotherapy-free regimens. We examined the prognostic and predictive utility of architectural patterns of CD10, BCL6, Ki67, and FOXP1 in 90 patients treated with immunochemotherapy (bendamustine-rituximab [BR] and R-cyclophosphamide, doxorubicin, vincristine, prednisone [CHOP]). We found that high follicular Ki67 (≥30%) was associated with longer PFS in the subgroup of patients treated with R-CHOP but not among those treated with BR. Validation of this biomarker may support routine use of Ki67 as a predictive marker in FL.

Diagnostic and prognostic value of pretreatment PET/CT in extranodal natural killer/T-cell lymphoma: a retrospective multicenter study

PURPOSE

The objective of this research was to assess the utility of positron emission tomography combined with computed tomography (PET/CT) to detect bone marrow invasion (BMI) and the predictive value of PET/CT in extranodal natural killer/T-cell lymphoma (ENKTL) patients.

PATIENTS AND METHODS

This multicentre study enrolled ENKTL patients who underwent pretherapy PET/CT and bone marrow biopsy (BMB). The specificity, sensitivity, negative predictive value (NPV), and positive predictive value (PPV) of PET/CT and BMB for BMI were evaluated. Multivariate analysis was used to identify predictive parameters for constructing a nomogram.

RESULTS

Seven hundred and forty-eight patients were identified from four hospitals, with eighty (10.7%) having focal skeletal lesions on PET/CT and fifty (6.7%) having positive BMB. When BMB is considered as the gold standard, the specificity, sensitivity, PPV, and NPV of PET/CT for diagnosing BMI were found to be 93.8%, 74.0%, 46.3%, and 98.1%, respectively. PET/CT-positive individuals showed significantly worse OS than PET/CT-negative patients in the subgroup of BMB-negative cases. The nomogram model created according to the significant risk factors from multivariate analysis performed well in predicting survival probability.

CONCLUSION

PET/CT offers a superior degree of precision for determining BMI in ENKTL. A nomogram model including the parameters of PET/CT can predict survival probability and may help in applying appropriate personalized therapy.

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.

Achieving the Cure of Follicular Lymphoma: is it Time to Finalize Treatment Strategies to Reach This Goal in a Subset of Patients?

NO ABSTRACT AVAILABLE

Improving the prognostic ability of PET/CT SUVmax to identify follicular lymphoma with early treatment failure

Follicular lymphoma (FL) has a high degree of heterogeneity both clinically and molecularly. Early treatment failure (ETF), progression or relapse within 24 months of frontline immunochemotherapy is associated with a poor prognosis in FL. However, the clinical utility of ETF at diagnosis is limited. The maximum standardized uptake value (SUVmax) is a metabolic parameter for positron emission tomography/computed tomography (PET/CT); nevertheless, the relationship between SUVmax and ETF remains unclear. Thus, identifying early biomarkers that incorporate SUVmax and other clinical correlative variables could be helpful in identifying patients at high risk of ETF. A nomogram consisted of three independent variables, including SUVmax ≥ 12, beta-2 microglobulin > 3 mg/L, and Ki67 > 40%, was established to predict ETF in 127 patients with grade 1, 2, or 3a FL from the First Hospital of Jilin University (training cohort) and was validated using data from the Duke University Medical Center (validation cohort, n=95). The nomogram demonstrated prognostic accuracy in predicting ETF (sensitivity 70.8% and specificity 83.5% in the training cohort; sensitivity 84.2% and specificity 68.4% in the validation cohort). The patients were stratified into three groups: low-, intermediate-, and high-risk. In the training cohort, the corresponding 5-year progression-free survival (PFS) rates were 81.7%, 73.4%, and 34.9%, and the 5-year overall survival (OS) rates were 97.4%, 87.4%, and 62.3%, respectively. In the validation cohort, the 5-year PFS rates were 77.7%, 52.9%, and 34.8%, and the 5-year OS rates were 96.4%, 94.1%, and 73.7%, respectively. This was the first study to use a nomogram with SUVmax to predict ETF in FL to identify a subset of patients who might benefit from individualized targeted therapy.

High baseline total lesion glycolysis predicts early progression of disease within 24 months in patients with high-tumor-burden follicular lymphoma

Despite the introduction of rituximab-containing regimens, approximately 20% of patients with follicular lymphoma (FL) still experience progression of disease within 24 months (POD24) and have poor overall survival. Therefore, a more accurate risk assessment tool is required. We investigated the predictive value of two new volume-based parameters determined from baseline 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT), baseline total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG), in 45 patients with high-tumor-burden FL who underwent baseline PET/CT. We observed that high TMTV, high TLG, and poor initial treatment response (less than complete [metabolic] response [non-CR/CMR] at the end of induction therapy) independently predicted poor PFS. Notably, POD24-positive patients were more common in the high-TLG group than in the high-TMTV group, which suggests that TLG is a stronger predictor of outcomes than TMTV. Combining baseline TLG and initial treatment response showed that patients with both high TLG and non-CR/CMR experienced significantly poorer outcomes, with a 2 year PFS of 0% (hazard ratio 60.39, P = 0.000002). This combination had 56% sensitivity and 100% specificity for detecting patients who would experience POD24. Baseline TLG and initial treatment response can precisely identify patients at high risk of POD24.

Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas

The total metabolic tumor volume (TMTV) is a new prognostic factor in lymphomas that could benefit from automation with deep learning convolutional neural networks (CNN). Manual TMTV segmentations of 1218 baseline 18FDG-PET/CT have been used for training. A 3D V-NET model has been trained to generate segmentations with soft dice loss. Ground truth segmentation has been generated using a combination of different thresholds (TMTVprob), applied to the manual region of interest (Otsu, relative 41% and SUV 2.5 and 4 cutoffs). In total, 407 and 405 PET/CT were used for test and validation datasets, respectively. The training was completed in 93 h. In comparison with the TMTVprob, mean dice reached 0.84 in the training set, 0.84 in the validation set and 0.76 in the test set. The median dice scores for each TMTV methodology were 0.77, 0.70 and 0.90 for 41%, 2.5 and 4 cutoff, respectively. Differences in the median TMTV between manual and predicted TMTV were 32, 147 and 5 mL. Spearman’s correlations between manual and predicted TMTV were 0.92, 0.95 and 0.98. This generic deep learning model to compute TMTV in lymphomas can drastically reduce computation time of TMTV.

Significance of initial, interim and end-of-therapy 18F-FDG PET/CT for predicting transformation risk in follicular lymphoma

Background

Histological transformation (HT) of follicular lymphoma to a more aggressive lymphoma is a serious event affecting patients’ outcomes. To date, no strong clinical HT predictors present at diagnosis have yet been identified. The fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) is highlighted as a non-invasive diagnostic tool for the detection of HT, but its ability to predict HT at early stage of disease has not been clear. Therefore, this study investigated the predictive values of the pre-transformation standardized uptake value (SUV_max) for the risk of transformation in FL.

Methods

This retrospective study involved 219 patients with FL between June 2008 and October 2019 who had undergone ¹⁸F-FDG PET/CT scan. One hundred and thirty-two, 64, and 78 patients underwent PET at baseline (PET_baseline), interim (PET_interim) and end-of-induction therapy (PET_end), respectively. Qualitative assessment was performed using the 5-point Deauville scale. Statistical analysis was done using Cox regression models, receiver operating characteristic (ROC) analysis, and Kaplan–Meir survival curves.

Results

Of the 219 patients included, 128 had low-grade FL (grade 1–2) and 91 had high-grade FL (grade 3a). HT eventually occurred in 30 patients. The median time to HT was 13.6 months. Among clinical indicators, advance pathological grade was shown as the most significant predictor of HT (HR = 4.561, 95% CI 1.604–12.965). We further assessed the relationship between PET and HT risk in FL. Univariate Cox regression determined that SUV_baseline and SUV_end were significant predictors for HT, while neither SUV_interim nor qualitative assessment of Deauville score has predictive value for HT. Due to the noticeable impact of high pathological grade on the HT risk, we conducted the subgroup analysis in patients with low/high pathological grade, and found SUV_baseline could still predict HT risk in both low-grade and high-grade subgroups. Multivariate analysis adjusted by FLIPI2 score showed the SUV_baseline (HR 1.065, 95% CI 1.020–1.111) and SUV_end (HR 1.261, 95% CI 1.076–1.478) remained as significant predictors independently of the FLIPI2 score. According to the cut-off determined from the ROC analysis, increased SUV_baseline with a cutoff value of 14.3 and higher SUV_end with a cutoff value of 7.3 were highly predictive of a shorter time to HT.

Conclusions

In follicular lymphoma, quantitative assessment used SUV_max at the pre-treatment and end-of-treatment PET/CT scan may be helpful for early screen out patients at high risk of transformation and guide treatment decisions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02094-5.

An Immune-Clinical Prognostic Index (ICPI) for Patients With De Novo Follicular Lymphoma Treated With R-CHOP/CHOP Chemotherapy

Purpose

Although the role of tumor-infiltrating T cells in follicular lymphoma (FL) has been reported previously, the prognostic value of peripheral blood T lymphocyte subsets has not been systematically assessed. Thus, we aim to incorporate T-cell subsets with clinical features to develop a predictive model of clinical outcome.

Methods

We retrospectively screened a total of 1,008 patients, including 252 newly diagnosed de novo FL patients with available peripheral blood T lymphocyte subsets who were randomized to different sets (177 in the training set and 75 in the internal validation set). A nomogram and a novel immune-clinical prognostic index (ICPI) were established according to multivariate Cox regression analysis for progression-free survival (PFS). The concordance index (C-index), Akaike’s information criterion (AIC), and likelihood ratio chi-square were employed to compare the ICPI’s discriminatory capability and homogeneity to that of FLIPI, FLIPI2, and PRIMA-PI. Additional external validation was performed using a dataset (n = 157) from other four centers.

Results

In the training set, multivariate analysis identified five independent prognostic factors (Stage III/IV disease, elevated lactate dehydrogenase (LDH), Hb <120g/L, CD4+ <30.7% and CD8+ >36.6%) for PFS. A novel ICPI was established according to the number of risk factors and stratify patients into 3 risk groups: high, intermediate, and low-risk with 4-5, 2-3, 0-1 risk factors respectively. The hazard ratios for patients in the high and intermediate-risk groups than those in the low-risk were 27.640 and 2.758. The ICPI could stratify patients into different risk groups both in the training set (P < 0.0001), internal validation set (P = 0.0039) and external validation set (P = 0.04). Moreover, in patients treated with RCHOP-like therapy, the ICPI was also predictive (P < 0.0001). In comparison to FLIPI, FLIPI2, and PRIMA-PI (C-index, 0.613-0.647), the ICPI offered adequate discrimination capability with C-index values of 0.679. Additionally, it exhibits good performance based on the lowest AIC and highest likelihood ratio chi-square score.

Conclusions

The ICPI is a novel predictive model with improved prognostic performance for patients with de novo FL treated with R-CHOP/CHOP chemotherapy. It is capable to be used in routine practice and guides individualized precision therapy.

Intratumoral T cells have a differential impact on FDG-PET parameters in follicular lymphoma

Data on the prognostic impact of pretherapy 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in follicular lymphoma (FL) is conflicting. The predictive utility of pretherapy total metabolic tumor volume (TMTV) and maximum standardized uptake value (SUVmax) on outcome appears to vary between regimens. Chemoimmunotherapies vary in the extent of T-cell depletion they induce. The role of intratumoral T cells on pretherapy FDG-PET parameters is undefined. We assessed pretherapy FDG-PET parameters and quantified intratumoral T cells by multiple methodologies. Low intratumoral T cells associated with approximately sixfold higher TMTV, and FL nodes from patients with high TMTV showed increased malignant B-cell infiltration and fewer clonally expanded intratumoral CD8+ and CD4+ T-follicular helper cells than those with low TMTV. However, fluorescently labeled glucose uptake was higher in CD4+ and CD8+ T cells than intratumoral B cells. In patients with FDG-PET performed prior to excisional biopsy, SUVmax within the subsequently excised node associated with T cells but not B cells. In summary, TMTV best reflects the malignant B-cell burden in FL, whereas intratumoral T cells influence SUVmax. This may contribute to the contradictory results between the prognostic role of different FDG-PET parameters, particularly between short- and long-term T-cell-depleting chemoimmunotherapeutic regimens. The impact of glucose uptake in intratumoral T cells should be considered when interpreting pretherapy FDG-PET in FL.

High Basal Maximal Standardized Uptake Value (SUVmax) in Follicular Lymphoma Identifies Patients with a Low Risk of Long-Term Relapse

BACKGROUND

Despite that the unfavorable prognostic role of a high Total Metabolic Tumor Volume (TMTV) in Follicular Lymphoma has been demonstrated, the role of SUV_max alone at baseline PET/CT could have a different prognostic role.

PATIENTS AND METHODS

We performed a retrospective observational monocentric cohort study. All patients affected by FL who underwent a basal PET/CT were included. Two subgroups were identified and compared in terms of PFS and OS: (A) Basal SUV_max ≤ 6; and (B) Basal SUV_max > 6.

RESULTS

Ninety-four patients were included, 34 in group A (36.2%) and 60 in group B (63.8%). The PFS at two years was comparable in the two groups (97%). The five-year PFS was 73.5% for group A and 95% for group B (p 0.005). The five-year PFS in the whole cohort was 87.5%. A clear advantage was confirmed in group A in the absence of other risk factors. Patients with SUV_max ≤ 6 and no risk factors showed a 5-year PFS of 73% against 83% for patients with SUV_max > 6 and at least two risk factors.

CONCLUSION

A high FDG uptake favorably correlated with PFS. A low basal SUV_max reflected a higher rate of late relapse requiring a prolonged follow-up. The basal SUV_max is an approachable parameter with prognostic implications.