Prognostic value of metabolic tumour volume on baseline 18F-FDG PET/CT in addition to NCCN-IPI in patients with diffuse large B-cell lymphoma: further stratification of the group with a high-risk NCCN-IPI

Development and validation of prognostic models based on 18F-FDG PET radiomics, metabolic parameters, and clinical factors for elderly DLBCL patients

This study aimed to assess the predictive value of baseline 18F-FDG PET radiomics features, metabolic parameters, and clinical factors for PFS and OS in elderly DLBCL patients. Using LASSO COX regression, we derived Radscore from PET radiomics features. We constructed and externally validated prognostic models, evaluating their performance through various metrics. From 341 training set patients and 83 external validation set patients revealed significant correlations between PET radiomics features and survival outcomes. Multivariate COX analysis identified associations of radiomics features (Radscore), metabolic parameters (TMTV, Dmax), and clinical factors (ECOG PS, hemoglobin level) with PFS and OS. In external validation, the combined model incorporating radiomic features, metabolic parameters, and clinical factors showed superior predictive performance for PFS and OS compared to other models. The combined model had higher C-index values for both PFS and OS, and its td-ROC curves exhibited significantly higher AUCs. Calibration curves demonstrated good consistency, and DCA revealed a higher net benefit for the combined model. In conclusion, the combined model that incorporated 18F-FDG PET radiomics features, metabolic parameters, and clinical factors demonstrated superior prognostic predictive ability, providing a useful tool for personalized treatment decisions in elderly DLBCL patients.

Survival prediction in diffuse large B-cell lymphoma patients: multimodal PET/CT deep features radiomic model utilizing automated machine learning

PURPOSE

We sought to develop an effective combined model for predicting the survival of patients with diffuse large B-cell lymphoma (DLBCL) based on the multimodal PET-CT deep features radiomics signature (DFR-signature).

METHODS

369 DLBCL patients from two medical centers were included in this study. Their PET and CT images were fused to construct the multimodal PET-CT images using a deep learning fusion network. Then the deep features were extracted from those fused PET-CT images, and the DFR-signature was constructed through an Automated machine learning (AutoML) model. Combined with clinical indexes from the Cox regression analysis, we constructed a combined model to predict the progression-free survival (PFS) and the overall survival (OS) of patients. In addition, the combined model was evaluated in the concordance index (C-index) and the time-dependent area under the ROC curve (tdAUC).

RESULTS

A total of 1000 deep features were extracted to build a DFR-signature. Besides the DFR-signature, the combined model integrating metabolic and clinical factors performed best in terms of PFS and OS. For PFS, the C-indices are 0.784 and 0.739 in the training cohort and internal validation cohort, respectively. For OS, the C-indices are 0.831 and 0.782 in the training cohort and internal validation cohort.

CONCLUSIONS

DFR-signature constructed from multimodal images improved the classification accuracy of prognosis for DLBCL patients. Moreover, the constructed DFR-signature combined with NCCN-IPI exhibited excellent potential for risk stratification of DLBCL patients.

The impact of initial tumor bulk in DLBCL treated with DA-EPOCH-R vs. R-CHOP: a secondary analysis of alliance/CALGB 50303

The ideal treatment paradigm for bulky diffuse large B-cell lymphoma (DLBCL) remains uncertain. We investigated the impact of tumor bulk in patients treated with systemic therapy alone through Alliance/CALGB 50303. Data from this trial were obtained from the National Cancer Institute's NCTN/NCORP Data Archive. The study assessed the size of nodal sites and estimated progression-free survival (PFS) using Cox proportional hazards models. Stratified analysis factored in International Prognostic Index (IPI) risk scores. Out of 524 patients, 155 had pretreatment scans. Using a 7.5 cm cutoff, 44% were classified as bulky. Bulk did not significantly impact progression-free survival (PFS), whether measured continuously or at thresholds of >5 or >7.5 cm (p = 0.10-p = 0.99). Stratified analyses by treatment group and IPI risk group were also non-significant. In this secondary analysis, a significant association between bulk and PFS was not identified.

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).

The prognostic value of bone marrow retention index and bone marrow-to-liver ratio of baseline 18F-FDG PET/CT in diffuse large B-cell lymphoma

OBJECTIVE

To determine prognostic value of bone marrow retention index (RI-bm) and bone marrow-to-liver ratio (BLR) measured on baseline dual-phase 18F-FDG PET/CT in a series of newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL) treated homogeneously with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) chemotherapy.

PATIENTS AND METHODS

This prospective study enrolled 135 patients with newly diagnosed DLBCL. All patients underwent dual-phase 18F-FDG PET/CT. The following PET parameters were calculated for both tumor and bone marrow: maximum standardized uptake value (SUVmax) at both time points (SUVmax early and SUVmax delayed), SUVmax increment (SUVinc), RI, and BLR. Patients were treated with R-CHOP regimen and response at end of treatment was assessed.

RESULTS

The final analysis included 98 patients with complete remission. At a median follow-up of 22 months, 57 patients showed no relapse, 74 survived, and 24 died. The 2-year relapse-free survival (RFS) values for patients with higher and lower RI-bm were 20% and 65.1%, respectively (p < 0.001), and for patients with higher and lower BLR were 30.2% and 69.6%, respectively (p < 0.001). The 2-year overall survival (OS) values for patients with higher and lower RI-bm were 60% and 76.3%, respectively (p = 0.023), and for patients with higher and lower BLR were 57.3% and 78.6%, respectively (p = 0.035). Univariate analysis revealed that RI-bm and BLR were independent significant prognostic factors for both RFS and OS (hazard ratio [HR] = 4.02, p < 0.001, and HR = 3.23, p < 0.001, respectively) and (HR = 2.83, p = 0.030 and HR = 2.38, p = 0.041, respectively).

CONCLUSION

Baseline RI-bm and BLR were strong independent prognostic factors in DLBCL patients.

CLINICAL RELEVANCE STATEMENT

Bone marrow retention index (RI-bm) and bone marrow-to-liver ratio (BLR) could represent suitable and noninvasive positron emission tomography/computed tomography (PET/CT) parameters for predicting pretreatment risk in patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) who were treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) chemotherapy.

KEY POINTS

• Bone marrow retention index (RI-bm) and bone marrow-to-liver ratio (BLR) are powerful prognostic variables in diffuse large B-cell lymphoma (DLBCL) patients. • High BLR and RI-bm are significantly associated with poor overall survival (OS) and relapse-free survival (RFS). • RI-bm and BLR represent suitable and noninvasive risk indicators in DLBCL patients.

Predictive Value of Corrected 18 F-FDG PET/CT Baseline Parameters for Primary DLBCL Prognosis: A Single-center Study

Objective  The purpose of this study was to evaluate the prognostic significance of corrected baseline metabolic parameters in fluorodeoxyglucose positron emission tomography imaging ( 18 F-FDG PET/CT) for 3-year progression-free survival (PFS) in patients with primary diffuse large B cell lymphoma (DLBCL). Patients and Methods  Retrospective clinical and pathological data were collected for 199 patients of DLBCL diagnosed between January 2018 and January 2021. All patients underwent 18 F-FDG PET/CT scans without any form of treatment. The corrected maximum standardized uptake value (corSUVmax), corrected mean standardized uptake value (corSUVmean), corrected whole-body tumor metabolic volume sum (corMTVsum), and corrected total lesion glycolysis of whole body (corTLGtotal) were corrected using the SUVmean in a 1-cm diameter mediastinal blood pool (MBP) from the descending thoracic aorta of patients. Kaplan-Meier survival curves and Cox regression were used to examine the predictive significance of corrected baseline metabolic parameters on 3-year PFS of patients. The incremental values of corrected baseline metabolic parameters were evaluated by using Harrell's C-indices, receiver operating characteristic, and Decision Curve Analysis. Results  The multivariate analysis revealed that only the National Comprehensive Cancer Network (NCCN)-International Prognostic Index (IPI) and corMTVsum had an effect on 3-year PFS of patients ( p  < 0.05, respectively). The Kaplan-Meier survival analysis demonstrated significant differences in PFS between the risk groups classified by corSUVsum, corMTVsum, and corTLGtotal (log-rank test, p  < 0.05). The predictive model composed of corMTVsum and corTLGtotal surpasses the predictive performance of the model incorporating MTVsum and TLGtotal. The optimal performance was observed when corMTVsum was combined with NCCN-IPI, resulting in a Harrell's C index of 0.785 and area under the curve values of 0.863, 0.891, and 0.947 for the 1-, 2-, and 3-year PFS rates, respectively. Conclusion  The corMTVsum offers significant prognostic value for patients with DLBCL. Furthermore, the combination of corMTVsum with the NCCN-IPI can provide an accurate prediction of the prognosis.

Optimizing the prognostic capacity of baseline 18F-FDG PET/CT metabolic parameters in extranodal natural killer/T-cell lymphoma by using relative and absolute thresholds

Objectives

To investigate the prognostic capacity of baseline 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters in extranodal natural killer/T-cell lymphoma (ENKTCL), and the influence of relative thresholds (RT) and absolute thresholds (AT) selection on prognostic capacity.

Materials and methods

Metabolic tumor volume (MTV)-based parameters were defined using RTs (41 % or 25 % of maximum standardized uptake value [SUVmax]), ATs (SUV 2.5, 3.0, 4.0, or mean liver uptake) in 133 patients. Metabolic parameters were classified into avidity-related parameters (SUVmax, mean SUV [SUVmean], standard deviation of SUV [SUVsd]), volume-related parameters (RT-MTV), and avidity- and volume-related parameters (total lesion glycolysis [TLG] and AT-MTV). The prognostic capacity of the metabolic parameters and the effects of different threshold types (RT vs. AT) were evaluated.

Results

All metabolic parameters were moderately associated with prognosis. However, the area under the receiver operating characteristic curve of MTV and TLG was slightly higher than that of avidity-related parameters for predicting 5-year progression-free survival (PFS) (0.614-0.705 vs. 0.563-0.609) and overall survival (OS) (0.670-0.748 vs. 0.562-0.593). Correlations of MTV and avidity-related parameters differed between RTs (r < 0.06, P = 0.324-0.985) and ATs (r 0.56-0.84, P ≤ 0.001). AT-MTV was the optimal predictor for PFS and OS, while RT-TLG was the optimal predictor for PFS, and the combination of RT-MTV with SUVmax was the optimal predictor for OS.

Conclusion

The incorporation of volume and avidity significantly improved the prognostic capacity of PET in ENKTCL. Composite parameters that encompassed both avidity and volume were recommended.

Robust deep learning-based PET prognostic imaging biomarker for DLBCL patients: a multicenter study

OBJECTIVE

To develop and independently externally validate robust prognostic imaging biomarkers distilled from PET images using deep learning techniques for precise survival prediction in patients with diffuse large B cell lymphoma (DLBCL).

METHODS

A total of 684 DLBCL patients from three independent medical centers were included in this retrospective study. Deep learning scores (DLS) were generated from PET images using deep convolutional neural network architecture known as VGG19 and DenseNet121. These DLSs were utilized to predict progression-free survival (PFS) and overall survival (OS). Furthermore, multiparametric models were designed based on results from the Cox proportional hazards model and assessed through calibration curves, concordance index (C-index), and decision curve analysis (DCA) in the training and validation cohorts.

RESULTS

The DLSPFS and DLSOS exhibited significant associations with PFS and OS, respectively (P<0.05) in the training and validation cohorts. The multiparametric models that incorporated DLSs demonstrated superior efficacy in predicting PFS (C-index: 0.866) and OS (C-index: 0.835) compared to competing models in training cohorts. In external validation cohorts, the C-indices for PFS and OS were 0.760 and. 0.770 and 0.748 and 0.766, respectively, indicating the reliable validity of the multiparametric models. The calibration curves displayed good consistency, and the decision curve analysis (DCA) confirmed that the multiparametric models offered more net clinical benefits.

CONCLUSIONS

The DLSs were identified as robust prognostic imaging biomarkers for survival in DLBCL patients. Moreover, the multiparametric models developed in this study exhibited promising potential in accurately stratifying patients based on their survival risk.

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.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Tumor Volume on PSMA PET as a Prognostic Biomarker in Prostate Cancer Patients Treated With Cabazitaxel

PURPOSE

The aim of this study was to evaluate the prognostic value of 68Ga-labeled prostate-specific membrane antigen (PSMA) PET/CT in metastatic castration-resistant prostate cancer patients receiving second-line chemotherapy with cabazitaxel.

METHODS

All patients with metastatic castration-resistant prostate cancer who underwent a PSMA PET/CT within 8 weeks before initiating the cabazitaxel treatment were retrospectively evaluated. The whole-body PSMA total tumor volume (PSMA-TV) was measured for each patient. Other factors such as prostate-specific antigen, hemoglobin, lactate dehydrogenase, and alkaline phosphatase were recorded. A log-rank cutoff finder was used to define the PSMA-TV optimal cutoff. Survival analyses were performed using Cox regression and Kaplan-Meier methods.

RESULTS

In total, 32 patients were included, receiving a median of 6 cycles of cabazitaxel (range, 2-10). After a median follow-up of 12 months, 28 patients presented disease progression, and 18 died. Baseline PSMA-TV presented a significant association with progression-free survival (PFS) and overall survival (OS; P = 0.035 and P = 0.002, respectively). Optimal PSMA-TV cutoffs were 515 mL for PFS and 473 mL for OS. Patients with low volume presented longer PFS and OS than those with high volume: median PFS, 21 versus 12 weeks, respectively (hazard ratio, 0.33; P = 0.017); and median OS, 24 versus 8.5 months, respectively (hazard ratio, 0.21; P = 0.002). On the multivariable analyses, PSMA-TV remained an independent predictor of OS (P = 0.016).

CONCLUSION

Our results show that total tumor volume measured on PSMA PET/CT is a prognostic biomarker in patients treated with cabazitaxel. High PSMA-TV before treatment initiation is associated with shorter PFS and OS.

A preliminary investigation of the relationship between 18F-FDG PET/CT metabolic parameters and prognosis in angioimmunoblastic T-cell lymphoma

Purpose

The goal of the study was to determine the prognostic significance of metabolic parameters in baseline ¹⁸F-FDG PET/CT images obtained from patients with angioimmunoblastic T-cell lymphoma (AITL).

Methods

Forty patients with pathologically diagnosed AITL who had baseline ¹⁸F-FDG PET/CT between May 2014 and May 2021 were assessed as part of this study. Maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), and total metabolic tumor volume (TMTV) were obtained and analyzed. In addition, many relevant features were evaluated, including sex, age, staging, International Prognostic Index (IPI), prediction index for T-cell lymphoma (PIT), Ki-67, and so on. Estimates of progression-free survival (PFS) and overall survival (OS) were determined using the log-rank test and Kaplan-Meier.

Results

The median follow-up was 30.2 months (interquartile range 9.82-43.03). Throughout the follow-up period, 29 (72.5%) deaths occurred and 22 (55.0%) patients made progress. The rates for 2- and 3-year PFS were 43.6% and 26.4%, respectively. The 3- and 5-year OS were 42.6% and 21.5%. For TMTV, TLG, and SUVmax, the cut-off values were 87.0 cm3, 711.1, and 15.8, respectively. Poorer PFS and OS were substantially correlated with high SUVmax and TLG. An increased TMTV suggested a shorter OS. TLG performed independently as OS predictors in multivariate analysis. The risk score for predicting the prognosis of AITL includes the TMTV, TLG, SUVmax, and IPI scores, with 4.5 for TMTV, 2 for TLG, 1.5 for IPI scores, and 1 for SUVmax. Three risk categories of patients with AITL had 3-year OS rates of 100.0%, 43.3%, and 25.0%, respectively.

Conclusion

Baseline TLG was a strong predictor of OS. Here a new prognostic scoring system for AITL based on the clinical indicators and PET/CT metabolic parameters was constructed, which might make stratification of prognosis easy and also help to individualize treatment.

Metabolic bulk volume predicts survival in a homogeneous cohort of stage II/III diffuse large B-cell lymphoma patients undergoing R-CHOP treatment

Purpose

Accurate risk stratification can improve lymphoma management, but current volumetric ¹⁸F-fluorodeoxyglucose (FDG) indicators require time-consuming segmentation of all lesions in the body. Herein, we investigated the prognostic values of readily obtainable metabolic bulk volume (MBV) and bulky lesion glycolysis (BLG) that measure the single largest lesion.

Methods

The study subjects were a homogeneous cohort of 242 newly diagnosed stage II or III diffuse large B-cell lymphoma (DLBCL) patients who underwent first-line R-CHOP treatment. Baseline PET/CT was retrospectively analyzed for maximum transverse diameter (MTD), total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), MBV, and BLG. Volumes were drawn using 30% SUVmax as threshold. Kaplan-Meier survival analysis and the Cox proportional hazards model assessed the ability to predict overall survival (OS) and progression-free survival (PFS).

Results

During a median follow-up period of 5.4 years (maximum of 12.7 years), events occurred in 85 patients, including progression, relapse, and death (65 deaths occurred at a median of 17.6 months). Receiver operating characteristic (ROC) analysis identified an optimal TMTV of 112 cm³, MBV of 88 cm³, TLG of 950, and BLG of 750 for discerning events. Patients with high MBV were more likely to have stage III disease; worse ECOG performance; higher IPI risk score; increased LDH; and high SUVmax, MTD, TMTV, TLG, and BLG. Kaplan-Meier survival analysis showed that high TMTV (p = 0.005 and < 0.001), MBV (both p < 0.001), TLG (p < 0.001 and 0.008), and BLG (p = 0.018 and 0.049) were associated with significantly worse OS and PFS. On Cox multivariate analysis, older age (> 60 years; HR, 2.74; 95% CI, 1.58-4.75; p < 0.001) and high MBV (HR, 2.74; 95% CI, 1.05-6.54; p = 0.023) were independent predictors of worse OS. Older age (hazard ratio [HR], 2.90; 95% CI, 1.74-4.82; p < 0.001) and high MBV (HR, 2.36; 95% CI, 1.15-6.54; p = 0.032) were also independent predictors of worse PFS. Furthermore, among subjects ≤60 years, high MBV remained the only significant independent predictor of worse OS (HR, 4.269; 95% CI, 1.03-17.76; p = 0.046) and PFS (HR, 6.047; 95% CI, 1.73-21.11; p = 0.005). Among subjects with stage III disease, only greater age (HR, 2.540; 95% CI, 1.22-5.30; p = 0.013) and high MBV (HR, 6.476; 95% CI, 1.20-31.9; p = 0.030) were significantly associated with worse OS, while greater age was the only independent predictor of worse PFS (HR, 6.145; 95% CI, 1.10-4.17; p = 0.024).

Conclusions

MBV easily obtained from the single largest lesion may provide a clinically useful FDG volumetric prognostic indicator in stage II/III DLBCL patients treated with R-CHOP.

Targeting positive cofactor 4 induces autophagic cell death in MYC-expressing diffuse large B-cell lymphoma

MYC-expressing diffuse large B-cell lymphoma (DLBCL) is one of the refractory lymphomas. Currently, the pathogenesis of MYC-expressing DLBCL is still unclear, and there is a lack of effective therapy. We characterized positive cofactor 4 (PC4) as an upstream regulator of c-Myc, and PC4 is overexpressed in DLBCL and is closely related to clinical staging, prognosis, and c-Myc expression. Furthermore, our in vivo and in vitro studies revealed that PC4 knockdown can induce autophagic cell death and enhance the therapeutic effect of doxorubicin in MYC-expressing DLBCL. Inhibition of c-Myc-mediated aerobic glycolysis and activation of the AMPK/mTOR signaling pathway are responsible for the autophagic cell death induced by PC4 knockdown in MYC-expressing DLBCL. Using dual-luciferase reporter assay and electrophoretic mobility shift assay assays, we also found that PC4 exerts its oncogenic functions by directly binding to c-Myc promoters. To sum up, our study provides novel insights into the functions and mechanisms of PC4 in MYC-expressing DLBCL and suggests that PC4 may be a promising therapeutic target for MYC-expressing DLBCL.

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.

Evaluation of a convolution neural network for baseline total tumor metabolic volume on [18F]FDG PET in diffuse large B cell lymphoma

OBJECTIVES

New PET data-processing tools allow for automatic lesion selection and segmentation by a convolution neural network using artificial intelligence (AI) to obtain total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) routinely at the clinical workstation. Our objective was to evaluate an AI implemented in a new version of commercial software to verify reproducibility of results and time savings in a daily workflow.

METHODS

Using the software to obtain TMTV and TLG, two nuclear physicians applied five methods to retrospectively analyze data for 51 patients. Methods 1 and 2 were fully automated with exclusion of lesions ≤ 0.5 mL and ≤ 0.1 mL, respectively. Methods 3 and 4 were fully automated with physician review. Method 5 was semi-automated and used as reference. Time and number of clicks to complete the measurement were recorded for each method. Inter-instrument and inter-observer variation was assessed by the intra-class coefficient (ICC) and Bland-Altman plots.

RESULTS

Between methods 3 and 5, for the main user, the ICC was 0.99 for TMTV and 1.0 for TLG. Between the two users applying method 3, ICC was 0.97 for TMTV and 0.99 for TLG. Mean processing time (± standard deviation) was 20 s ± 9.0 for method 1, 178 s ± 125.7 for method 3, and 326 s ± 188.6 for method 5 (p < 0.05).

CONCLUSION

AI-enabled lesion detection software offers an automated, fast, reliable, and consistently performing tool for obtaining TMTV and TLG in a daily workflow.

KEY POINTS

• Our study shows that artificial intelligence lesion detection software is an automated, fast, reliable, and consistently performing tool for obtaining total metabolic tumor volume and total lesion glycolysis in a daily workflow.

Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

Objective

In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy.

Methods

This study retrospectively recruited 129 cases with DLBCL. Among them, PET/CT scans were conducted and baseline images were collected for radiomics features along with their clinicopathological features. Radiomics features related to recurrence were screened for survival analysis using univariate Cox regression analysis with p < 0.05. Next, a weighted Radiomics-score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Furthermore, the nomogram was tested for their ability to predict PFS using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results

Blood platelet, Rad-score, and gender were included in the nomogram as independent DLBCL risk factors for PFS. We found that the training cohort areas under the curve (AUCs) were 0.79, 0.84, and 0.88, and validation cohort AUCs were 0.67, 0.83, and 0.72, respectively. Further, the DCA and calibration curves confirmed the predictive nomogram’s clinical relevance.

Conclusion

Using Rad-score, blood platelet, and gender of the DLBCL patients, a PET/CT radiomics-based nomogram was developed to guide cases’ recurrence risk assessment prior to treatment. The developed nomogram can help provide more appropriate treatment plans to the cases.

Key Points

• DLBCL cases can be classified into low- and high-risk groups using PET/CT radiomics based Rad-score.

• When combined with other clinical characteristics (gender and blood platelet count), Rad-score can be used to predict the outcome of the pretreatment of DLBCL cases with a certain degree of accuracy.

• A prognostic nomogram was established in this study in order to aid in assessing prognostic risk and providing more accurate treatment plans for DLBCL cases.

The usefulness of the total metabolic tumor volume for predicting the postoperative recurrence of thoracic esophageal squamous cell carcinoma

Background

Induction or adjuvant therapies are not always beneficial for thoracic esophageal squamous cell carcinoma (ESCC) patients, and it is thus important to identify patients at high risk for postoperative ESCC recurrence. We investigated the usefulness of the total metabolic tumor volume (TMTV) for predicting the postoperative recurrence of thoracic ESCC.

Methods

We retrospectively analyzed the cases of 163 thoracic ESCC patients (135 men, 28 women; median age of 66 [range 34–82] years) treated at our hospital in 2007–2012. The TMTV was calculated from the fluorine-18 fluorodeoxyglucose (18F-FDG) uptake in the primary lesion and lymph node metastases. The optimal cut-off values for relapse and non-relapse were obtained by the time-dependent receiver operating curve analyses. Relapse-free survival (RFS) was evaluated by the Kaplan-Meier method, and between-subgroup differences in survival were analyzed by log-rank test. The prognostic significance of metabolic parameters and clinicopathological variables was assessed by a Cox proportional hazard regression analysis. The difference in the failure patterns after surgical resection was evaluated using the χ2-test.

Results

The optimal cut-off value of TMTV for discriminating relapse from non-relapse was 3.82. The patients with a TMTV ≥3.82 showed significantly worse prognoses than those with low values (p < 0.001). The TMTV was significantly related to RFS (model 1 for preoperative risk factors: TMTV: hazard ratio [HR] =2.574, p = 0.004; model 2 for preoperative and postoperative risk factors: HR = 1.989, p = 0.044). The combination of the TMTV and cN0–1 or pN0–1 stage significantly stratified the patients into low-and high-risk recurrence groups (TMTV cN0–1, p < 0.001; TMTV pN0–1, p = 0.004). The rates of hematogenous and regional lymph node metastasis were significantly higher in the patients with TMTV ≥3.82 than those with low values (hematogenous metastasis, p < 0.001, regional lymph node metastasis, p = 0.011).

Conclusions

The TMTV was a more significantly independent prognostic factor for RFS than any other PET parameter in patients with resectable thoracic ESCC. The TMTV may be useful for the identifying thoracic ESCC patients at high risk for postoperative recurrence and for deciding the patient management.

The role of 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma after radioimmunotherapy using 131I-rituximab as consolidation therapy

Purpose

To evaluate the prognostic value of pretreatment ¹⁸F-FDG PET/CT after consolidation therapy of ¹³¹I-rituximab in patients with diffuse large B-cell lymphoma (DLBCL) who had acquired complete remission after receiving chemotherapy.

Methods

Patients who were diagnosed with DLBCL via histologic confirmation were retrospectively reviewed. All patients had achieved complete remission after 6 to 8 cycles of R-CHOP (rituximab, cyclophosphamide, vincristine, doxorubicin, and prednisolone) chemotherapy after which they underwent consolidation treatment with ¹³¹I-rituximab. ¹⁸F-FDG PET/CT scans were performed before R-CHOP for initial staging. The largest diameter of tumor, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained from pretreatment ¹⁸F-FDG PET/CT scans. Receiver-operating characteristic curves analysis was introduced for assessing the optimal criteria. Kaplan-Meier curve survival analysis was performed to evaluate both relapse free survival (RFS) and overall survival (OS).

Results

A total of 15 patients (12 males and 3 females) with a mean age of 56 (range, 30–73) years were enrolled. The median follow-up period of these patients was 73 months (range, 11–108 months). Four (27%) patients relapsed. Of them, three died during follow-up. Median values of the largest tumor size, highest SUVmax, MTV, and TLG were 5.3 cm (range, 2.0–16.4 cm), 20.2 (range, 11.1–67.4), 231.51 (range, 15–38.34), and 1277.95 (range, 238.37–10341.04), respectively. Patients with SUVmax less than or equal to 16.9 showed significantly worse RFS than patients with SUVmax greater than 16.9 (5-year RFS rate: 60% vs. 100%, p = 0.008). Patients with SUVmax less than or equal to 16.9 showed significantly worse OS than patients with SUVmax greater than 16.9 (5-year OS rate: 80% vs. 100% p = 0.042).

Conclusion

Higher SUVmax at pretreatment ¹⁸F-FDG PET/CT was associated with better relapse free survival and overall survival in DLBCL patients after consolidation therapy with ¹³¹I-rituximab. However, because this study has a small number of patients, a phase 3 study with a larger number of patients is needed for clinical application in the future.

Total metabolic tumor volume as a survival predictor for patients with diffuse large B-cell lymphoma in the GOYA study

This retrospective analysis of the phase III GOYA study investigated the prognostic value of baseline metabolic tumor volume parameters and maximum standardized uptake values for overall and progression-free survival (PFS) in treatment-naïve diffuse large B-cell lymphoma. Baseline total metabolic tumor volume (determined for tumors >1 mL using a threshold of 1.5 times the mean liver standardized uptake value +2 standard deviations), total lesion glycolysis, and maximum standardized uptake value positron emission tomography data were dichotomized based on receiver operating characteristic analysis and divided into quartiles by baseline population distribution. Of 1,418 enrolled patients, 1,305 had a baseline positron emission tomography scan with detectable lesions. Optimal cut-offs were 366 cm3 for total metabolic tumor volume and 3,004 g for total lesion glycolysis. High total metabolic tumor volume and total lesion glycolysis predicted poorer PFS, with associations retained after adjustment for baseline and disease characteristics (high total metabolic tumor volume hazard ratio: 1.71, 95% confidence interval [CI]: 1.35- 2.18; total lesion glycolysis hazard ratio: 1.46; 95% CI: 1.15-1.86). Total metabolic tumor volume was prognostic for PFS in subgroups with International Prognostic Index scores 0-2 and 3-5, and those with different cell-of-origin subtypes. Maximum standardized uptake value had no prognostic value in this setting. High total metabolic tumor volume associated with high International Prognostic Index or non-germinal center B-cell classification identified the highest-risk cohort for unfavorable prognosis. In conclusion, baseline total metabolic tumor volume and total lesion glycolysis are independent predictors of PFS in patients with diffuse large B-cell lymphoma after first-line immunochemotherapy.

Radiomics signature from [18F]FDG PET images for prognosis predication of primary gastrointestinal diffuse large B cell lymphoma

OBJECTIVES

To investigate the prognostic value of PET radiomics feature in the prognosis of patients with primary gastrointestinal diffuse large B cell lymphoma (PGI-DLBCL) treated with R-CHOP-like regimen.

METHODS

A total of 140 PGI-DLBCL patients who underwent pre-therapy [¹⁸F] FDG PET/CT were enrolled in this retrospective analysis. PET radiomics features obtained from patients in the training cohort were subjected to three machine learning methods and Pearson's correlation test for feature selection. Support vector machine (SVM) was used to build a radiomics signature classifier associated with progression-free survival (PFS) and overall survival (OS). A multivariate Cox proportional hazards regression model was established to predict survival outcomes.

RESULTS

A total of 1421 PET radiomics features were extracted and reduced to 5 features to build a radiomics signature which was significantly associated with PFS and OS (p < 0.05). The combined model incorporating radiomics signatures, metabolic metrics, and clinical risk factors showed high C-indices in both the training (PFS: 0.825, OS: 0.834) and validation sets (PFS: 0.831, OS: 0.877). Decision curve analysis (DCA) demonstrated that the combined models achieved the most net benefit across a wider reasonable range of threshold probabilities for predicting PFS and OS.

CONCLUSION

The newly developed radiomics signatures obtained by the ensemble strategy were independent predictors of PFS and OS for PGI-DLBCL patients. Moreover, the combined model with clinical and metabolic factors was able to predict patient prognosis and may enable personalized treatment decision-making.

KEY POINTS

• Radiomics signatures generated from the optimal radiomics feature set from the [¹⁸F]FDG PET images can predict the survival of PGI-DLBCL patients. • The optimal radiomics feature set is constructed by integrating the feature selection outputs of LASSO, RF, Xgboost, and PC methods. • Combined models incorporating radiomics signatures from¹⁸F-FDG PET images, metabolic parameters, and clinical factors outperformed clinical models, and NCCN-IPI.

Value of CT-Textural Features and Volume-Based PET Parameters in Comparison to Serologic Markers for Response Prediction in Patients with Diffuse Large B-Cell Lymphoma Undergoing CD19-CAR-T Cell Therapy

The goal of this study was to investigate the value of CT-textural features and volume-based PET parameters in comparison to serologic markers for response prediction in patients with diffuse large B-cell lymphoma (DLBCL) undergoing cluster of differentiation (CD19)-chimeric antigen receptor (CAR)-T cell therapy. We retrospectively analyzed the whole-body (WB)-metabolic tumor volume (MTV), the WB-total lesion glycolysis (TLG) and first order textural features derived from 18F-FDG-PET/CT, as well as serologic parameters (C-reactive protein [CRP] and lactate dehydrogenase [LDH], leucocytes) prior and after CAR-T cell therapy in 21 patients with DLBCL (57.7 ± 14.7 year; 7 female). Interleukin 6 (IL-6) and IL-2 receptor peaks were monitored after treatment onset and compared with patient outcome judged by follow-up 18F-FDG-PET/CT. In 12/21 patients (57%), complete remission (CR) was observed, whereas 9/21 patients (43%) showed partial remission (PR). At baseline, WB-MTV and WB-TLG were lower in patients achieving CR (35 ± 38 mL and 319 ± 362) compared to patients achieving PR (88 ± 110 mL and 1487 ± 2254; p < 0.05). The “entropy” proved lower (1.81 ± 0.09) and “uniformity” higher (0.33 ± 0.02) in patients with CR compared to PR (2.08 ± 0.22 and 0.28 ± 0.47; p < 0.05). Patients achieving CR had lower levels of CRP, LDH and leucocytes at baseline compared to patients achieving PR (p < 0.05). In the entire cohort, WB-MTV and WB-TLG decreased after therapy onset (p < 0.01) becoming not measurable in the CR-group. Leucocytes and CRP significantly dropped after therapy (p < 0.01). The IL-6 and IL-2R peaks after therapy were lower in patients with CR compared to PR (p > 0.05). In conclusion, volume-based PET parameters derived from PET/CT and CT-textural features have the potential to predict therapy response in patients with DLBCL undergoing CAR-T cell therapy.

Integration of Baseline Metabolic Parameters and Mutational Profiles Predicts Long-Term Response to First-Line Therapy in DLBCL Patients: A Post Hoc Analysis of the SAKK38/07 Study

Accurate estimation of the progression risk after first-line therapy represents an unmet clinical need in diffuse large B-cell lymphoma (DLBCL). Baseline (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) parameters, together with genetic analysis of lymphoma cells, could refine the prediction of treatment failure. We evaluated the combined impact of mutation profiling and baseline PET/CT functional parameters on the outcome of DLBCL patients treated with the R-CHOP14 regimen in the SAKK38/07 clinical trial (NCT00544219). The concomitant presence of mutated SOCS1 with wild-type CREBBP and EP300 defined a group of patients with a favorable prognosis and 2-year progression-free survival (PFS) of 100%. Using an unsupervised recursive partitioning approach, we generated a classification-tree algorithm that predicts treatment outcomes. Patients with elevated metabolic tumor volume (MTV) and high metabolic heterogeneity (MH) (15%) had the highest risk of relapse. Patients with low MTV and favorable mutational profile (9%) had the lowest risk, while the remaining patients constituted the intermediate-risk group (76%). The resulting model stratified patients among three groups with 2-year PFS of 100%, 82%, and 42%, respectively (p < 0.001).

Deep learning-based tumour segmentation and total metabolic tumour volume prediction in the prognosis of diffuse large B-cell lymphoma patients in 3D FDG-PET images

OBJECTIVES

To demonstrate the effectiveness of automatic segmentation of diffuse large B-cell lymphoma (DLBCL) in 3D FDG-PET scans using a deep learning approach and validate its value in prognosis in an external validation cohort.

METHODS

Two PET datasets were retrospectively analysed: 297 patients from a local centre for training and 117 patients from an external centre for validation. A 3D U-Net architecture was trained on patches randomly sampled within the PET images. Segmentation performance was evaluated by six metrics, including the Dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), sensitivity (Se), positive predictive value (PPV), Hausdorff distance 95 (HD 95), and average symmetric surface distance (ASSD). Finally, the prognostic value of predictive total metabolic tumour volume (pTMTV) was validated in real clinical applications.

RESULTS

The mean DSC, JSC, Se, PPV, HD 95, and ASSD (with standard deviation) for the validation cohort were 0.78 ± 0.25, 0.69 ± 0.26, 0.81 ± 0.27, 0.82 ± 0.25, 24.58 ± 35.18, and 4.46 ± 8.92, respectively. The mean ground truth TMTV (gtTMTV) and pTMTV were 276.6 ± 393.5 cm³ and 301.9 ± 510.5 cm³ in the validation cohort, respectively. Perfect homogeneity in the Bland-Altman analysis and a strong positive correlation in the linear regression analysis (R² linear = 0.874, p < 0.001) were demonstrated between gtTMTV and pTMTV. pTMTV (≥ 201.2 cm³) (PFS: HR = 3.097, p = 0.001; OS: HR = 6.601, p < 0.001) was shown to be an independent factor of PFS and OS.

CONCLUSIONS

The FCN model with a U-Net architecture can accurately segment lymphoma lesions and allow fully automatic assessment of TMTV on PET scans for DLBCL patients. Furthermore, pTMTV is an independent prognostic factor of survival in DLBCL patients.

KEY POINTS

•The segmentation model based on a U-Net architecture shows high performance in the segmentation of DLBCL patients on FDG-PET images. •The proposed method can provide quantitative information as a predictive TMTV for predicting the prognosis of DLBCL patients.

Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma

PURPOSE

To develop and externally validate models incorporating a PET radiomics signature (R-signature) obtained by the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma (DLBCL).

METHODS

A total of 383 patients with DLBCL from two medical centres between 2011 and 2019 were included. The cross-combination method was used on three types of PET radiomics features from the training cohort to generate 49 feature selection-classification candidates based on 7 different machine learning models. The R-signature was then built by selecting the optimal candidates based on their progression-free survival (PFS) and overall survival (OS). Cox regression analysis was used to develop the survival prediction models. The calibration, discrimination, and clinical utility of the models were assessed and externally validated.

RESULTS

The R-signatures determined by 12 and 31 radiomics features were significantly associated with PFS and OS, respectively (P<0.05). The combined models that incorporated R-signatures, metabolic metrics, and clinical risk factors exhibited significant prognostic superiority over the clinical models, PET-based models, and the National Comprehensive Cancer Network International Prognostic Index in terms of both PFS (C-index: 0.801 vs. 0.732 vs. 0.785 vs. 0.720, respectively) and OS (C-index: 0.807 vs. 0.740 vs. 0.773 vs. 0.726, respectively). For external validation, the C-indices were 0.758 vs. 0.621 vs. 0.732 vs. 0.673 and 0.794 vs. 0.696 vs. 0.781 vs. 0.708 in the PFS and OS analyses, respectively. The calibration curves showed good consistency, and the decision curve analysis supported the clinical utility of the combined model.

CONCLUSION

The R-signature could be used as a survival predictor for DLBCL, and its combination with clinical factors may allow for accurate risk stratification.

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

Objective

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

Methods

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

Results

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

Conclusions

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

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

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

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

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

A novel analytic approach for outcome prediction in diffuse large B-cell lymphoma by [18F]FDG PET/CT

PURPOSE

This study aimed to develop a novel analytic approach based on 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography/computed tomography ([¹⁸F]FDG PET/CT) radiomic signature (RS) and International Prognostic Index (IPI) to predict the progression-free survival (PFS) and overall survival (OS) of patients with diffuse large B-cell lymphoma (DLBCL).

METHODS

We retrospectively enrolled 152 DLBCL patients and divided them into a training cohort (n = 100) and a validation cohort (n = 52). A total of 1245 radiomic features were extracted from the total metabolic tumor volume (TMTV) and the metabolic bulk volume (MBV) of pre-treatment PET/CT images. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to develop the RS. Cox regression analysis was used to construct hybrid nomograms based on different RS and clinical variables. The performances of hybrid nomograms were evaluated using the time-dependent receiver operator characteristic (ROC) curve and the Hosmer-Lemeshow test. The clinical utilities of prediction nomograms were determined via decision curve analysis. The predictive efficiency of different RS, clinical variables, and hybrid nomograms was compared.

RESULTS

The RS and IPI were identified as independent predictors of PFS and OS, and were selected to construct hybrid nomograms. Both TMTV- and MBV-based hybrid nomograms had significantly higher values of area under the curve (AUC) than IPI in training and validation cohorts (all P < 0.05), while no significant difference was found between TMTV- and MBV-based hybrid nomograms (P > 0.05). The Hosmer-Lemeshow test showed that both TMTV- and MBV-based hybrid nomograms calibrated well in the training and validation cohorts (all P > 0.05). Decision curve analysis indicated that hybrid nomograms had higher net benefits than IPI.

CONCLUSION

The hybrid nomograms combining RS with IPI could significantly improve survival prediction in DLBCL. Radiomic analysis on MBV may serve as a potential approach for prognosis assessment in DLBCL.

TRIAL REGISTRATION

NCT04317313. Registered March 16, 2020. Public site: https://clinicaltrials.gov/ct2/show/NCT04317313.

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

Purpose

Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment.

Methods

Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values.

Results

The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUV_peak and the maximal distance between the largest lesion and any other lesion (Dmax_bulk, AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUV_peak and Dmax_bulk) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively).

Conclusion

Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance.

Trial registration number and date

EudraCT: 2006–005,174-42, 01–08-2008.

Supplementary Information

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

18F-FDG cerebellum/liver index as a prognostic factor for progression-free survival in diffuse large B-cell lymphoma

OBJECTIVE

18F-FDG PET/CT provides valuable informations regarding the prognosis of DLBCL. The aim of this study is to test a novel index based on cerebellar uptake to predict progression free survival in DLBCL patients.

METHODS

Data from patients with de novo DLBCL between January 2011 and December 2018 were retrospectively collected and PFS was determined. The conventional PET parameters (SUVmax and total metabolic tumor volume) and the CLIP, corresponding to the ratio of the cerebellum SUVmax over the liver SUVmean, were extracted from baseline 18F-FDG PET.

RESULTS

Ninety-five patients were included. When using a threshold of 3.24, CLIP was a significant predictor of PFS on univariate analysis (HR 3.4, p < 0.001) with different 5-year survival rates: 68% (CLIP ≥ 3.24) versus 32% (CLIP < 3.24). Multivariate analysis confirmed the prognostic value of CLIP, as it is one of the two factors remaining significant with β2-microglobulin (HR 2.1 and 2.5 respectively, p = 0.04 and p = 0.03). A score associating β2-microglobulin and CLIP allowed to separate the population into three groups of different outcome in terms of 5-year PFS: low risk (80%), intermediate risk (42%) and high risk (17%).

CONCLUSIONS

The CLIP derived from pre-therapeutic 18F-FDG PET seems to be an interesting predictive marker of PFS in DLBCL treated by immunochemotherapy.

Value of total lesion glycolysis and cell-of-origin subtypes for prognostic stratification of diffuse large B-cell lymphoma patients

Background

This study aimed to explore the added prognostic value of baseline metabolic volumetric parameters and cell of origin subtypes to the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) in nodal diffuse large B-cell lymphoma (DLBCL) patients.

Methods

A total of 184 consecutive de novo nodal DLBCL patients who underwent baseline positron emission tomography/computed tomography (PET/CT) were included in this study. Kaplan-Meier estimates were generated to evaluate the clinical, biological, and PET/CT parameters' prognostic value. The Cox proportional hazards model was performed to examine the potential independent predictors for progression-free survival (PFS) and overall survival (OS).

Results

With a median follow-up of 35 months, the 3-year PFS and OS were 65.2% and 73.0%, respectively. In univariate analysis, total lesion glycolysis (TLG), cell-of-origin subtypes, and NCCN-IPI were both PFS and OS predictors. High TLG (≥1,852), non-germinal center B (non-GCB), as well as high NCCN-IPI (≥4), were shown to be independently significantly associated with inferior PFS and OS after multivariate analysis. Based on the number of risk factors (high TLG, non-GCB, and high NCCN-IPI), a revised risk model was designed, and the participants were divided into four risk groups with very different outcomes, in which the PFS rates were 89.7%, 66.2%, 51.7%, and 26.7% (χ²=30.179, P<0.001), and OS rates were 93.1%, 73.8%, 56.7%, and 43.3%, respectively (χ²=23.649, P<0.001), respectively. Compared with the NCCN-IPI alone, the revised risk model showed a stronger ability to reveal further discrimination among subgroups, especially for participants with very unfavorable survival outcomes (PFS: χ²=9.963, P=0.002; OS: χ²=4.166, P=0.041, respectively).

Conclusions

The TLG, cell-of-origin subtypes, and NCCN-IPI are independent prognostic survival factors in DLBCL patients. Moreover, the revised risk model composed of the number of risk factors (high TLG, non-GCB, and high NCCN-IPI) can stratify patients better than the NCCN-IPI, especially for patients at high risk, which suggests its potential integration into decision making for personalized medicine.

Prognostic Impact of Pretreatment 2-[18F]-FDG PET/CT Parameters in Primary Gastric DLBCL

Background and Objectives: Primary gastric diffuse large-B cell lymphoma (DLBCL) is an aggressive lymphoma subtype with high ¹⁸F-FDG avidity but unclear criteria for 2-[¹⁸F]-FDG PET/CT in the evaluation of treatment response and prognostication. Our aim was to investigate whether the pretreatment 2-[¹⁸F]-FDG PET/CT variables may predict treatment response (at end of first-line therapy) and prognosis in primary gastric DLBCL. Materials and Methods: we included 57 patients with a diagnosis of primary gastric DLBCL and a baseline 2-[¹⁸F]-FDG PET/CT and an end of treatment PET/CT after 6 cycles of R-CHOP chemotherapy. We analyzed PET images qualitatively and semi-quantitatively by deriving the maximum standardized uptake value body weight (SUVbw), the maximum standardized uptake value lean body mass (SUVlbm), the maximum standardized uptake value body surface area (SUVbsa), lesion to liver SUVmax ratio (L-L SUV R), lesion to blood-pool SUVmax ratio (L-BP SUV R), metabolic tumor volume and total lesion glycolysis of gastric lesion (gMTV and gTLG), and total MTV (tMTV) and TLG. Survival curves were plotted according to the Kaplan–Meier analysis. Results: at a median follow up of 80 months, the median PFS and OS were 69 and 80 months. Baseline gMTV, gTLG, tMTV, and TLG were significantly higher in patients with incomplete response (partial response and progression) compared to complete response group. tMTV and TLG were confirmed to be independent prognostic factors both for PFS (p = 0.023 and p = 0.038) and OS (p = 0.038 and p = 0.026); instead, the other metabolic parameters were not related to outcome survival. Conclusions: high tMTV and TLG were significantly correlated with shorter survival (PFS and OS) and may predict incomplete response after therapy.

Comparison of clinical and PET-derived prognostic factors in patients with non-Hodgkin lymphoma: a special emphasis on bone marrow involvement

OBJECTIVE

In patients with non-Hodgkin lymphoma (NHL), we investigated F FDG PET/computed tomography (CT) parameters, clinical findings, laboratory parameters, and bone marrow involvement (BMI) status for predictive methods in progression-free survival (PFS) and overall survival (OS), and whether F FDG PET/CT could take the place of bone marrow biopsy (BMB).

METHODS

The performance of F FDG PET/CT (BMPET) was evaluated. The prognostic value of maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), stage, international prognostic index (IPI) score, IPI risk, lactate dehydrogenase (LDH), B2 microglobulin, Ki67 proliferation index, and the presence of BMI was evaluated for OS and PFS. Kaplan-Meier curves were drawn for each designated cutoff value, and 5-year PFS and 7-year OS were evaluated using log-rank analysis.

RESULTS

The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of BMPET and BMB to identify BMI were 69, 100, 86.1, 80, 100%, and 81.6, 100, 92.5, 89, 100%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of BMPET in patients with Ki67- proliferation index >25% were all 100%. BMPET, IPI risk, MTV, and LDH were found to be independent prognostic predictors for PFS, whereas BMPET, SUVmax, and MTV for OS. Five-year PFS analysis estimated as follows: BMPET (+) = 22%, BMPET (-) = 80%, LDH ≤ 437 (U/L) = 86%, LDH > 437 (U/L) = 51%, MTV ≤ 56 (cm) = 87%, MTV > 56 (cm) = 49%, low IPI risk = 87%, intermediate IPI risk = 69%, high IPI risk = 25%. Seven-year OS analysis was found as: SUVmax ≤ 17.6 = 80%, SUVmax > 17.6 = 48%, MTV ≤ 56 (cm) = 84.4%, MTV > 56 (cm) = 45.8%, BMPET (-) = 72.5%, BMPET (+) = 42%.

CONCLUSION

In the Ki-67 proliferation index > 25% group, F FDG PET/CT was able to differentiate BMI independently from NHL subgroups. We recommend using this method with large patient groups. MTV and BMPET were independent prognostic indicators for OS and PFS and may help to determine high-risk patients.

Application of 18F-fluorodeoxyglucose positron emission tomography/computerized tomography in mantle cell lymphoma

OBJECTIVE

The study is to investigate the application of F-fluorodeoxyglucose (F-FDG) PET/computerized tomography (CT) for the evaluation of mantle cell lymphoma (MCL).

METHODS

We retrospectively analyzed 39 patients who were pathologically diagnosed with MCL and underwent F-FDG PET/CT before treatment between August 2007 and August 2018. We compared the clinical information and PET/CT imaging characteristics in different groups based on bone marrow invasion, spleen invasion or International Prognostic Index (IPI) score. We also assessed the efficacy of PET/CT evaluation basing on the follow-up PET CT findings of 21 MCL patients and their biopsies.

RESULTS

Thirty-five patients were stage IV according to the Revised Ann Arbor Staging System. Lymph node involvement was observed in all 39 cases. The maximum diameter of the affected lymph nodes (4.33 ± 3.09 cm) and maximum standardized uptake value (SUVmax) (8.38 ± 4.99) was positively correlated (r = 0.486, P = 0.002). Extranodal invasion was identified in 38 patients with MCL, and the SUVmax of extranodal invasion was 7.34 ± 3.31. Extranodal invasion was most common in the spleen (25/38) and bone marrow (18/38). The group with bone marrow invasion was more prone to nasopharyngeal, lung and renal invasions (all P < 0.05). The groups with bone marrow invasion or spleen invasion were more likely to have decreased hemoglobin (Hgb) and platelets (all P < 0.01). The IPI high-risk group was more prone to lung involvement, elevated LDH and CRP, and decreased Hgb (all P < 0.05). Among the follow-up of 30 MCL patients, the 2-year progression-free survival and overall survival rates were 73.33 and 87.50%, respectively. PET/CT reexaminations of 21 MCL patients after treatment showed that the sensitivity, specificity, negative predictive value, positive predictive value and accuracy of the efficacy evaluation were 80, 90.91, 88.89, 83.33 and 85.71%, respectively.

CONCLUSION

F-FDG PET/CT imaging has important application value in the diagnosis, staging, treatment efficacy assessment and prognosis monitoring of MCL, especially in the systemic assessment of advanced MCL.

Prognostic value of the baseline 18F-FDG PET/CT metabolic tumour volume (MTV) and further stratification in low-intermediate (L-I) and high-intermediate (H-I) risk NCCNIPI subgroup by MTV in DLBCL MTV predict prognosis in DLBCL

INTRODUCTION

In the era of rituximab, the NCCNIPI is widely used in clinical practice as a tool for the prognosis and risk stratification of diffuse large B-cell lymphoma (DLBCL). In recent years, FDG PET/CT has also shown unique prognostic value. We try to further confirm the prognostic role of metabolic parameters in the overall and subgroups patients.

METHODS

We retrospectively analysed 87 DLBCL patients who underwent baseline FDG PET/CT and followed the R-CHOP or R-CHOP-like strategy. The clinical parameters and PET-related metabolic parameters were evaluated.

RESULTS

For all patients, the 2-year PFS rate was 65.5% and the 2-year OS rate was 66.7%. According to Cox multivariate analysis, a high NCCNIPI score (4-8 points) and an MTV greater than 64.1 cm3 (defined by ROC) were independent prognostic factors for PFS and OS. The patients were divided into low, low-intermediate, high-intermediate and high-risk groups by NCCNIPI score. The 2-year PFS rates in each group were 90.9%, 71.3%, 33.2% and 16.7%, and the 2-year OS rates were 100%, 81.6%, 48.4% and 16.7%. In the subsequent subgroup analysis by MTV, it could further stratified low-intermediate and high-intermediate NCCNIPI groups, the P value was 0.068 and 0.069 for PFS, 0.078 and 0.036 for OS.

CONCLUSIONS

MTV, as a tumor metabolic volume parameter, and the NCCNIPI score were independent predictors of prognosis in general DLBCL patients. In the low-intermediate and high-intermediate NCCNIPI subgroup, we further confirm the risk stratification abilities of MTV, which could add the prognostic value of NCCNIPI.

Will Baseline Total Lesion Glycolysis Play a Role in Improving the Prognostic Value of the NCCN-IPI in Primary Gastric Diffuse Large B-Cell Lymphoma Patients Treated With the R-CHOP Regimen?

PURPOSE

The aim was to explore whether baseline total lesion glycolysis (TLG) can improve the prognostic value of the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) in primary gastric diffuse large B-cell lymphoma (PG-DLBCL) patients treated with an R-CHOP-like regimen.

MATERIALS AND METHODS

Ninety-four PG-DLBCL patients who underwent baseline PET/CT between July 2010 and May 2019 were included in this retrospective study. FDG-avid lesions in each patient were segmented to calculate the SUVmax, total metabolic tumor volume (TMTV), and TLG. Progression-free survival (PFS) and overall survival (OS) were used as end points to evaluate prognosis.

RESULTS

During the follow-up period of 5 to 108 months (35.3 ± 23.5 months), high TLG and a high NCCN-IPI were significantly associated with poor PFS and OS. Total lesion glycolysis and the NCCN-IPI were independent predictors of PFS and OS. Patients were stratified into 3 groups according to the combination of TLG and the NCCN-IPI for PFS (P < 0.001) and OS (P < 0.001): high-risk group (TLG > 1159.1 and NCCN-IPI 4-8) (PFS and OS, 57.7% and 61.5%, respectively, n = 42), intermediate-risk group (TLG > 1159.1 or NCCN-IPI 4-8) (PFS and OS, both 76.9%, n = 26), and low-risk group (TLG ≤ 1159.1 and NCCN-IPI 0-3) (PFS and OS, 97.6% and 100.0%, respectively, n = 26).

CONCLUSIONS

Both TLG and the NCCN-IPI are independent predictors of PG-DLBCL patient survival. Moreover, the combination of TLG and the NCCN-IPI improved patient risk stratification and might help personalize therapeutic regimens.

Semi-automatic evaluation of baseline whole-body tumor burden as an imaging biomarker of 68Ga-PSMA-11 PET/CT in newly diagnosed prostate cancer

OBJECTIVES

The prognostic value of baseline tumor burden of prostate cancer was rarely studied. We aimed to evaluate the whole-body tumor burden of ⁶⁸Ga- prostate specific membrane antigen-HBED-CC (⁶⁸Ga-PSMA-11) PET/CT in newly diagnosed prostate cancer semi-automatically, and explore its preliminary application in predicting prognosis.

METHODS

Similar to metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of ¹⁸F-FDG PET/CT, ⁶⁸Ga-PSMA-11 PET/CT tumor burden parameters including whole-body PSMA tumor volume (wbPSMA-TV) and whole-body total lesions PSMA uptake (wbTL-PSMA) were acquired semi-automatically. The intra-observer and inter-observer reliability was analyzed. The relationship between tumor burden and prostate-specific antigen (PSA) value or Gleason score was investigated. The preliminary application of tumor burden in predicting progression-free survival (PFS) was explored.

RESULTS

Fifty-nine newly diagnosed prostate cancer patients were retrospectively analyzed. Semi-automatic quantification of whole-body tumor burden had excellent intra-observer and inter-observer consistency [all intra-class correlation coefficient (ICC) > 0.990]. wbPSMA-TV and wbTL-PSMA were 32.6 (range 1.0-3968.2) cm³ and 161.9 (range 6.0-24971.7), respectively. wbPSMA-TV and wbTL-PSMA correlated with PSA (r = 0.858, p < 0.001; r = 0.879, p < 0.001) and Gleason score (r = 0.793, p < 0.001; r = 0.805, p < 0.001) significantly. In univariate analysis, wbPSMA-TV, wbTL-PSMA, SUV_max, SUV_peak, SUV_mean, PSMA-TV, TL-PSMA of primary tumor, fPSA and Gleason score were independent significant predictors of PFS (all p < 0.05). Moreover, in multivariate analysis, wbTL-PSMA [hazard ratio (HR): 1.001, p = 0.014] and Gleason score (HR: 5.124, p = 0.031) can significantly predict progression-free prognosis.

CONCLUSIONS

As imaging biomarkers, wbPSMA-TV and wbTL-PSMA correlated with clinical characteristics significantly. High wbTL-PSMA or Gleason score was associated with shorter PFS of newly diagnosed prostate cancer independently.

Value of 18F-FDG PET/CT for prognostic stratification in patients with primary intestinal diffuse large B cell lymphoma treated with an R-CHOP-like regimen

PURPOSE

The prognostic value of ¹⁸F-FDG PET/CT for primary intestinal diffuse large B-cell lymphoma (PI-DLBCL) patients has not been determined. This prompted us to explore the value of ¹⁸F-FDG PET/CT for prognostic stratification in patients with PI-DLBCL treated with an R-CHOP-like regimen.

MATERIALS AND METHODS

Seventy-three PI-DLBCL patients who underwent baseline PET/CT between January 2010 and May 2019 were included in this retrospective study. Total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) were computed using the 41% SUV_max thresholding method. Progression-free survival (PFS) and overall survival (OS) were used as endpoints to evaluate prognosis.

RESULTS

During the follow-up period of 3-117 months (29.0 ± 25.5 months), high TLG, non-germinal center B-cell-like (non-GCB) and high National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) were significantly associated with inferior PFS and OS. TLG, cell-of-origin and NCCN-IPI were independent predictors of PFS, and both TLG and NCCN-IPI were independent predictors of OS. The grading system was based on the number of risk factors (high TLG, non-GCB, high NCCN-IPI) and patients were divided into 4 risk groups (PFS: χ² = 33.858, P < 0.001; OS: χ² = 29.435, P < 0.001): low-risk group (none of the 3 risk factors, 18 patients); low-intermediate risk group (1 risk factor, 24 patients); high-intermediate risk group (2 risk factors, 16 patients); and high-risk group (all 3 risk factors, 15 patients).

CONCLUSIONS

High TLG, non-GCB and high NCCN-IPI can identify a subset of PI-DLBCL patients with inferior survival outcomes. Furthermore, the grading system can identify PI-DLBCL patient groups with markedly different prognoses, which might contribute to the adjustment of the therapeutic regime.

Prognostic models integrating quantitative parameters from baseline and interim positron emission computed tomography in patients with diffuse large B-cell lymphoma: post-hoc analysis from the SAKK38/07 clinical trial

Positron emission computed tomography (PET/CT) in patients with diffuse large B-cell lymphoma (DLBCL) enrolled in a prospective clinical trial were reviewed to test the impact of quantitative parameters from interim PET/CT scans on overall (OS) and progression-free (PFS) survival. We centrally reviewed baseline and interim PET/CT scans of 138 patients treated with rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone given every 14 days (R-CHOP14) in the SAKK38/07 trial (ClinicalTrial.gov identifier: NCT00544219). Cutoff values for maximum standardized uptake value (SUV_max ), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and metabolic heterogeneity (MH) were defined by receiver operating characteristic analysis. Responses were scored using the Deauville scale (DS). Patients with DS 5 at interim PET/CT (defined by uptake >2 times higher than in normal liver) had worse PFS (P = 0.014) and OS (P < 0.0001). A SUV_max reduction (Δ) greater than 66% was associated with longer PFS (P = 0.0027) and OS (P < 0.0001). Elevated SUV_max , MTV, TLG, and MH at interim PET/CT also identified patients with poorer outcome. At multivariable analysis, ΔSUV_max and baseline MTV appeared independent outcome predictors. A prognostic model integrating ΔSUV_max and baseline MTV discriminated three risk groups with significantly (log-rank test for trend, P < 0.0001) different PFS and OS. Moreover, the integration of MH and clinical prognostic indices could further refine the prediction of OS. PET metrics-derived prognostic models perform better than the international indices alone. Integration of baseline and interim PET metrics identified poor-risk DLBCL patients who might benefit from alternative treatments.

Baseline total metabolic tumor volume combined with international peripheral T-cell lymphoma project may improve prognostic stratification for patients with peripheral T-cell lymphoma (PTCL)

Purpose

The aim of this study was to explore the prognostic value of total metabolic tumor volume (TMTV) at baseline ¹⁸F-FDG PET/CT in patients diagnosed with peripheral T-cell lymphoma (PTCL).

Materials and methods

Eighty-four newly diagnosed PTCL patients who underwent baseline ¹⁸F-FDG PET/CT prior to treatment between March 2009 and January 2019 were enrolled in this retrospective study. The FDG-avid lesions in each patient were segmented using semiautomated software to calculate the maximum standardized uptake value (SUVmax), total metabolic tumor volume (TMTV), and total lesion glycolysis (TLG) values using the boundaries of voxels presenting with the 41% SUVmax threshold method. Progression-free survival (PFS) and overall survival (OS) were used as end points to evaluate patient prognosis. The log-rank test and Cox regression analyses were used to evaluate PFS and OS.

Results

ROC curve analysis indicated an ideal TMTV cut-off value of 228.8 cm³. During the 4–131 months (29.2 ± 28.5 months) follow-up period, high TMTV was significantly associated with worse PFS and OS. TMTV and the international peripheral T-cell lymphoma project score (IPTCLP) were independent predictors of PFS and OS with multivariate analysis. The combination of TMTV and the IPTCLP may provide significantly better risk substratification in PFS and OS of PTCL patients.

Conclusions

Both TMTV and IPTCLP are independent predictors of PTCL patient survival outcomes. Moreover, the combination of TMTV and IPTCLP improved patient risk stratification and may contribute to personalized therapeutic regimens.

Texture Analysis Improves the Value of Pretreatment 18F-FDG PET/CT in Predicting Interim Response of Primary Gastrointestinal Diffuse Large B-Cell Lymphoma

Objectives

To explore the application of pretreatment 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) texture analysis (TA) in predicting the interim response of primary gastrointestinal diffuse large B-cell lymphoma (PGIL-DLBCL).

Methods

Pretreatment 18F-FDG PET/CT images of 30 PGIL-DLBCL patients were studied retrospectively. The interim response was evaluated after 3-4 cycles of chemotherapy. The complete response (CR) rates in patients with different clinicopathological characteristics were compared by Fisher's exact test. The differences in the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and texture features between the CR and non-CR groups were compared by the Mann-Whitney U test. Feature selection was performed according to the results of the Mann-Whitney U test and feature categories. The predictive efficacies of the SUVmax, MTV, and the selected texture features were assessed by receiver operating characteristic (ROC) analysis. A prediction probability was generated by binary logistic regression analysis.

Results

The SUVmax, MTV, some first-order texture features, volume, and entropy were significantly higher in the non-CR group. The energy was significantly lower in the non-CR group. The SUVmax, volume, and entropy were excellent predictors of the interim response, and the areas under the curves (AUCs) were 0.850, 0.805, and 0.800, respectively. The CR rate was significantly lower in patients with intestinal involvement. The prediction probability generated from the combination of the SUVmax, entropy, volume, and intestinal involvement had a higher AUC (0.915) than all single parameters.

Conclusions

TA has potential in improving the value of pretreatment PET/CT in predicting the interim response of PGIL-DLBCL. However, prospective studies with large sample sizes and validation analyses are needed to confirm the current results.

Combination of baseline total metabolic tumor volume measured on FDG-PET/CT and β2-microglobulin have a robust predictive value in patients with primary breast lymphoma

The aim was to build a prognostic model to stratify patients at diagnosis into different risk categories. We investigated the prognostic value of functional PET parameters and clinical features in 64 primary breast lymphoma (PBL) patients. With a median follow-up of 60 months, 5-year progression-free survival (PFS) and overall survival (OS) was 62.5% and 73.4%. In multivariate analysis, baseline total metabolic tumor volume (TMTV0) and β2-microglobulin remained more reliable predictors of survival than other prognostic factors. The optimal TMTV0 cut-off value was 90 cm³ . Among 29 patients with high TMTV0, 5-year PFS and OS were 44.8% and 62.1%, respectively, while 5-year PFS and OS of 35 patients with low TMTV0 were 74.3% and 85.7%, respectively. TMTV0 combined with β2-microglobulin identified three groups with very different prognosis, including low-risk group with low TMTV0 and β2-microglobulin≤normal (n = 30), intermediate-risk group with high TMTV0 or β2-microglobulin>normal (n = 20), and high-risk group with high TMTV0 and β2-microglobulin>normal (n = 14). In the three groups, 5-year PFS rates were 80%, 55% and 28.6% (P = .003), and 5-year OS rates were 90%, 65%, and 50% (P = .023) respectively. We established a new prognostic model through TMTV0 and β2-microglobulin, and can divide PBL at diagnosis into different risk categories.

SAKK38/07 study: integration of baseline metabolic heterogeneity and metabolic tumor volume in DLBCL prognostic model

Several functional parameters from baseline (18)F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography have been proposed as promising biomarkers of treatment efficacy in diffuse large B-cell lymphoma (DLBCL). We tested their ability to predict outcome in 2 cohorts of DLBCL patients receiving conventional immunochemotherapy (rituximab, cyclophosphamide, doxorubicin hydrochloride, vincristine sulfate, and prednisone [R-CHOP] regimen), either every 14 (R-CHOP14) or 21 days (R-CHOP21). Baseline PET analysis was performed in 141 patients with DLBCL treated with R-CHOP14 in the prospective SAKK38/07 study (NCT00544219) of the Swiss Group for Clinical Cancer Research (testing set). Reproducibility was examined in a validation set of 113 patients treated with R-CHOP21. In the SAKK38/07 cohort, progression-free survival (PFS) at 5 years was 83% for patients with low metabolic tumor volume (MTV) and 59% for those with high MTV (hazard ratio [HR], 3.4; 95% confidence interval [CI], 1.6-7.0; P = .0005), whereas overall survival (OS) was 91% and 64%, respectively (HR, 4.4; 95% CI, 1.9-10; P = .0001). MTV was the most powerful predictor of outcome also in the validation set. Elevated metabolic heterogeneity (MH) significantly predicted poorer outcomes in the subgroups of patients with elevated MTV. A model integrating MTV and MH identified high-risk patients with shorter PFS (testing set: HR, 5.6; 95% CI, 1.8-17; P < .0001; validation set: HR, 5.6; 95% CI, 1.7-18; P = .0002) and shorter OS (testing set: HR, 9.5; 95% CI, 1.7-52; P < .0001; validation set: HR, 7.6; 95% CI, 2.0-28; P = .0003). This finding was confirmed by an unsupervised regression tree analysis indicating that prognostic models based on MTV and MH may allow early identification of refractory patients who might benefit from treatment intensification. This trial was registered at www.clinicaltrials.gov as #NCT00544219.

Prognostic Values of Baseline 18F-FDG PET/CT in Patients with Peripheral T-Cell Lymphoma

Purpose

In the present study, we aimed to investigate whether the metabolic parameters on baseline ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) could be used to predict prognosis in peripheral T-cell lymphomas (PTCL).

Methods

A total of 51 nodal PTCL patients who underwent baseline ¹⁸F-FDG PET/CT were retrospectively evaluated in the present study. Total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and maximum standardized uptake value (SUV_max) were also assessed. Besides, the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) was also included. Log-rank test and Cox regression analysis were used to evaluate progression-free survival (PFS) and overall survival (OS).

Results

The median follow-up was 18 months. Patients with low TLG, TMTV, and SUV_max levels had a significantly better clinical outcome than those with high TLG, TMTV, and SUV_max levels. The 2-year PFS rates of the high- and low-TMTV groups were 34.62% and 80%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively,

Conclusions

Baseline TMTV and TLG were independent predictors of PFS and OS in PTCL patients, and SUV_max and NCCN-IPI scores were also independent predictors of OS. Moreover, the combination of TMTV and NCCN-IPI scores improved patient risk-stratification at the initial stage and might contribute to the adjustment of the therapeutic regime. This trial is registered with ChiCTR1900025526.

A better prediction of progression-free survival in diffuse large B-cell lymphoma by a prognostic model consisting of baseline TLG and %ΔSUVmax

In the era of rituximab, the International Prognostic Index (IPI) has been inefficient in initial risk stratification for patients with R‐CHOP‐treated diffuse large B‐cell lymphoma (DLBCL). To estimate the predictive values of PET/CT quantitative parameters and three prognostic models consisting of baseline and interim parameters for three‐year progression‐free survival (PFS), we conducted an analysis of 85 patients in China with DLBCL underwent baseline and interim PET/CT scans and treated at the Department of Hematology of Peking University Third Hospital from November 2012 to November 2017. The PET/CT parameters, viz. the baseline and interim values of standardized uptake value (SUV_max), total metabolic tumor volume (TMTV), and total lesion glycolysis (TLG), and their rates of change, were analyzed by a receiver operating characteristics curve, Kaplan‐Meier analysis, and log‐rank test. Besides, the National Comprehensive Cancer Network International Prognostic Index (NCCN‐IPI) was also included in the multivariate Cox hazards model. Owing to the strong correlation between TMTV and TLG at baseline and interim (Pearson's correlation coefficient, r = 0.823, P‐value = 0.000, and 0.988, P‐value = 0.000, respectively), only TLG was included in the multivariate Cox hazards model, where TLG₀ > 1036.61 g and %ΔSUV_max < 86.02% showed predictive value independently (HR = 10.42, 95% CI 2.35‐46.30, P = 0.002, and HR = 4.86, 95% CI 1.27‐18.54, P = 0.021, respectively). Replacing TLG in the equation, TMTV₀ and TMTV₁ both showed significantly predictive abilities like TLG (HR = 8.22, 95% CI 1.86‐32.24, P = 0.005, and HR = 2.96, 95% CI 1.16‐7.54, P = 0.023, respectively). After dichotomy, NCCN‐IPI also gave a significant performance (P = 0.035 and P = 0.010, respectively, in TLG and TMTV models). The baseline variables, that is, TMTV₀, TLG₀ and dichotomized NCCN‐IPI, and the interim variables TMTV₁ and %ΔSUV_max, presented independent prognostic value for PFS. In prognostic model 2 (TLG₀ + %ΔSUV_max), the group with TLG₀ > 1036.61 g and %ΔSUV_max < 86.02% recognized 19 (82.6%) of the relapse or progression events, which showed the best screening ability among three models consisting of baseline and interim PET/CT parameters.