Prognosis Prediction of Diffuse Large B-Cell Lymphoma in 18F-FDG PET Images Based on Multi-Deep-Learning Models.

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based methods. In this paper, a new flexible ensemble deep learning model is proposed for the prognosis prediction of the DLBCL in 18F-FDG PET images. This study proposes the multi-R-signature construction through selected pre-trained deep learning models for predicting progression-free survival (PFS) and overall survival (OS). The proposed method is trained and validated on two datasets from different imaging centers. Through analyzing and comparing the results, the prediction models, including Age, Ann abor stage, Bulky disease, SUVmax, TMTV, and multi-R-signature, achieve the almost best PFS prediction performance (C-index: 0.770, 95% CI: 0.705-0.834, with feature adding fusion method and C-index: 0.764, 95% CI: 0.695-0.832, with feature concatenate fusion method) and OS prediction (C-index: 0.770 (0.692-0.848) and 0.771 (0.694-0.849)) on the validation dataset. The developed multiparametric model could achieve accurate survival risk stratification of DLBCL patients. The outcomes of this study will be helpful for the early identification of high-risk DLBCL patients with refractory relapses and for guiding individualized treatment strategies.

Venetoclax plus dose-adjusted R-EPOCH (VR-DA-EPOCH) or G-EPOCH bridging to subsequent cellular therapy for the patients with transformed lymphoma a single center clinical experience.

Indolent lymphoma, including chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) and follicular lymphoma (FL), can undergo histological transformation into an aggressive subtype, typically diffuse large B-cell lymphoma (DLBCL). The prognosis of transformed lymphoma is poor. In this study, we reported the efficacy and toxicity of a combination of venetoclax, dose-adjusted rituximab or obinutuzumab, etoposide, prednisone, vincristine, doxorubicin, and cyclophosphamide (VR-DA-EPOCH or VG-DA-EPOCH) in 11 patients with biopsy-proven histology transformation into DLBCL, including 8 patients with RT and 3 with transformed FL (tFL). The study was conducted between October 2019 and March 2023 at our single center. The median age of participants at enrolment was 53 years. Six patients (85.7%, 6/7) achieved complete remission (CR) at the end of treatment. The best overall response rate (ORR) and CR rate were both 72.7%, respectively. Two patients received autologous hemopoietic stem cell transplant (ASCT) while two patients received ASCT concurrently with CAR-T therapy for consolidation. With a median follow-up of 13.5 (range, 2.4-29.8) months after enrollment, the median event-free survival, progression-free survival, and overall survival were 9.4, 11.5, and 17.5 months, respectively. Hematologic toxicities of grade ≥3 consisted of neutropenia (90.9%, 10/11), thrombocytopenia (63.6%, 7/11), and febrile neutropenia (54.5%, 6/11). In conclusion, VR-DA-EPOCH or VG-DA-EPOCH was a promising strategy to achieve an early remission, bridging to cellular therapy within this population.

[18F-FDG PET/CT Metabolic Parameters and Circulating Tumour DNA Mutation Abundance in Diffuse Large B-Cell Lymphoma: Correlation and Survival Analysis].

OBJECTIVE: To investigate the correlation between 18Fluoro-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters and peripheral blood circulating tumour DNA (ctDNA) in patients with diffuse large B-cell lymphoma (DLBCL), and the prognostic value of these two types of parameters in predicting progression-free survival (PFS). METHODS: Clinical, PET/CT and ctDNA data of DLBCL patients who underwent peripheral blood ctDNA testing and corresponding PET/CT scans during the same period were retrospectively analyzed. At the time of ctDNA sampling and PET scan, patients were divided into baseline and relapsed/refractory (R/R) groups according to different disease conditions. CtDNA mutation abundance was expressed as variant allele frequency (VAF), including maximum VAF (maxVAF) and mean VAF (meanVAF). Total metabolic tumour volume (TMTV) and total lesion glycolysis (TLG) were obtained by the 41% maximum normalized uptake value method, and the distance between the two farthest lesions (Dmax) was used to assess the correlation between PET parameters and ctDNA mutation abundance using Spearman correlation analysis. The receiver operating characteristic (ROC) curves were used to obtain the optical cut-off values of those parameters in predicting PFS in the baseline and R/R groups, respectively. Survival curves were outlined using the Kaplan-Meier method and log-rank test was performed to compare survival differences. RESULTS: A total of 67 DLBCL patients ï¼»28 males and 39 females, median age 56.0(46.0, 67.0) yearsï¼½ were included and divided into baseline group (29 cases) and R/R group (38 cases). Among these PET parameters, baseline TMTV, TLG, and Dmax were significantly correlated with baseline ctDNA mutation abundance, except for maximum standardized uptake value (SUVmax) (maxVAF vs TMTV: r=0.711; maxVAF vs TLG: r=0.709; maxVAF vs Dmax: r=0.672; meanVAF vs TMTV: r=0.682; meanVAF vs TLG: r=0.677; meanVAF vs Dmax: r=0.646). While in all patients, these correlations became weaker significantly. Among R/R patients, only TMTV had a weak correlation with meanVAF (r=0.376). ROC analysis showed that, the specificity of TMTV, TLG and Dmax in predicting PFS was better than mutation abundance, while the sensitivity of ctDNA mutation abundance was better. Except R/R patients, TMTV, TLG, Dmax, and VAF were significantly different at normal/elevated lactate dehydrogenase in baseline group and all patients (all P<0.05). Survival curves indicated that high TMTV (>109.5 cm3), high TLG (>2 141.3), high Dmax (>33.1 cm) and high VAF (maxVAF>7.74%, meanVAF>4.39%) were risk factors for poor PFS in baseline patients, while only high VAF in R/R patients (both maxVAF and meanVAF >0.61%) was a risk factor for PFS. CONCLUSION: PET-derived parameters correlate well with ctDNA mutation abundance, especially in baseline patients. VAF of ctDNA predicts PFS more sensitively than PET metabolic parameters, while PET metabolic tumour burden with better specificity. TMTV, TLG and VAF all have good prognostic value for PFS. PET/CT combined with ctDNA has potential for further studies in prognostic assessment and personalized treatment.

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.

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

PURPOSE: To explore the prognostic value of the distance between the two lesions that were farthest apart (Dmax) on baseline 18F-FDG PET/CT in peripheral T lymphoma (PTCL) and establish a new prognostic model for predicting the survival outcomes of patients with PTCL. METHODS: In this study, a retrospective analysis of 95 patients with PTCL who underwent baseline 18F-FDG PET/CT was performed to assess the predictive value of Dmax. The total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), standardized uptake value (SUV), and Dmax were calculated with LIFEx software. Progression-free survival (PFS) and overall survival (OS) were used as endpoints. The prognostic model was developed based on the results of the multivariate analysis. The time-dependent area under the ROC curve (tdAUC), calibration curves, Harrell C-index, and decision curve analysis (DCA) were used to assess the model. RESULTS: Patients were followed up for a median of 17.0 months. Multivariate analysis showed that bone marrow biopsy (BMB) and Dmax were independent predictors of PFS (HR: 1.889, P = 0.039; HR: 1.965, P = 0.047) and OS (HR: 1.923, P = 0.031; HR: 1.982, P = 0.034). The model consisting of Dmax, TMTV, and BMB had substantial prognostic value for survival outcomes of PTCL and could successfully identify four groups of patients with significantly different prognoses (χ2 = 13.731, P = 0.003 for PFS; χ2 = 11.841, P = 0.008 for OS). The tdAUC, C-index, calibration curves, and DCA supported that the model was superior to the prognostic index for T-cell lymphoma (PIT) and International Prognostic Index (IPI) scores. CONCLUSION: BMB and Dmax were independent predictors of PTCL in our study. Moreover, a prognostic model based on the Dmax, TMTV, and BMB could be useful for predicting the survival outcomes of patients with PTCL.

The added prognostic values of baseline PET dissemination parameter in patients with angioimmunoblastic T-cell lymphoma.

To explore the prognostic values of baseline 2-deoxy-2-[18F] fluoro-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) dissemination parameter in angioimmunoblastic T-cell lymphoma (AITL) and its added values to total metabolic tumour volume (TMTV). Eighty-one AITL patients with at least two FDG-avid lesions in baseline PET/CT were retrospectively included. PET parameters including TMTV and the distance between the two lesions that are the furthest apart (Dmax) were obtained. Univariate Cox analysis showed that both Dmax and TMTV were risk factors for progression-free survival (PFS) and overall survival (OS). Multivariate Cox analysis models of different combinations showed that high Dmax (> 65.7 cm) could independently predict both PFS and OS, while high TMTV (>456.6 cm3) was only significant for OS. A concise PET model based on TMTV and Dmax can effectively risk-stratify patients. PFS and OS rates were significantly lower in patients with high Dmax and high TMTV than in patients with low Dmax and low TMTV (3-year PFS rate: 15.0% vs. 48.7%, p = 0.001; 3-year OS rate: 27.6% vs. 79.0%, p < 0.001). Dmax can directly reflect the disease dissemination characteristic and has a significant prognostic value for FDG-avid AITL patients. It has the potential to be introduced into new risk stratification models for tailored treatment.

18F-FDG PET/CT and clinicopathological characteristics of neurolymphomatosis in lymphoma patients.

OBJECTIVE: Neurolymphomatosis (NL) is a rare but serious manifestation defined as invasion of peripheral nervous system by malignant lymphocytes. Thus, this study investigated fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) and clinicopathological characteristics of NL in lymphoma patients. SUBJECTS AND METHODS: Clinicopathological and 18F-FDG PET/CT findings and treatment regimens were retrospectively investigated in 20 lymphoma patients with NL, and analyzed their correlation with progression-free survival (PFS) and overall survival (OS). RESULTS: These 20 lymphoma patients (11 males, 9 females; median age, 49 years) included 10 primary and 10 secondary NL patients. Non-Hodgkin's lymphoma (NHL) was noted in 19 patients, B-cell NHL was associated with 18 cases, and diffuse large B-cell lymphoma was the most common. Notably, 18 patients were aggressive lymphoma while 2 were indolent lymphoma. The affected neural structures included nerve roots (n=17), peripheral nerves (n=3), cranial nerves (n=3), and neural plexus (n=2). Fluorine-18-FDG was avid in all cases, and the median maximum standardized uptake value (SUVmax) of neural and all lesions was 12.2 (range, 3.3-25.6) and 15.0 (range, 4.4-34.2), respectively. The median PFS and OS of all patients were 9.3 and 14.3 months. The 12-month OS rate of 18 patients with aggressive lymphoma receiving intrathecal chemotherapy/autologous stem cell transplants (IT chem/ASCT) was significantly higher than who did not (64.8% vs 15.9%). CONCLUSION: The majority of NL occurred in patients with aggressive lymphoma, of which B-cell NHL were the predominant subtypes. Fluorine-18-FDG PET/CT imaging of NL was mainly characterized by intense glucose accumulation alongside peripheral nerves, and IT chem/ASCT was suggested to improve the outcomes of NL.

Clinical and prognostic role of 2-[18F]FDG PET/CT and sarcopenia in treatment-naïve patients with T-cell lymphoblastic lymphoma.

T-cell lymphoblastic lymphoma (T-LBL) is a rare and highly aggressive non-Hodgkin lymphoma. This study aimed to explore the role of 2-[18F]FDG PET/CT, sarcopenia, clinical features, and treatment regimens in 49 treatment-naïve patients with T-LBL, and assess their predictive value in the prognosis. Sarcopenia was measured as skeletal muscle index (SMI) at L3 level from the CT component of PET/CT images. All 49 patients (35 males, 14 females; median age, 26 years [range, 3-66 years]) were enrolled in this study, including 36 adult patients and 13 pediatric patients. Lymph nodes, thymus, bone marrow, and pleura were the most common involved sites of T-LBL. The median SUVmax, MTV, and TLG of all lesions in these 49 patients were 12.4 (range, 4.2-40.5), 532.6 (17.4-3518.1), and 2112.2 (53.9-18,699.2), respectively. Eighteen out of 49 patients (36.7%) were diagnosed with sarcopenia. Sarcopenia patients had lower BMI and SUVmax of muscle at L3 level than non-sarcopenia patients (P < 0.05). Univariate Cox regression analysis indicated that higher MTV and TLG and intrathecal therapy (IT) were associated with longer progression-free survival (PFS) and overall survival (OS), while multivariate Cox regression analysis showed that TLG and IT were independent predictors for PFS, and only IT was an independent predictor for OS. In conclusion, low BMI and SUVmax of muscle at L3 level correlated with sarcopenia in T-LBL patients. Higher initial MTV and TLG and receiving IT were associated with better prognosis in T-LBL patients. TLG and IT, but not sarcopenia, were independent prognostic factors.

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.

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.

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.

Prognostic value of baseline total metabolic tumour volume of 18F-FDG PET/CT imaging in patients with angioimmunoblastic T-cell lymphoma.

PURPOSE: The aim of this study was to explore the prognostic value of baseline metabolic parameters of 18F-FDG PET/CT imaging in patients with angioimmunoblastic T-cell lymphoma (AITL). MATERIALS AND METHODS: Fifty-six AITL patients (average age 64.0 ± 1.3 years) diagnosed pathologically from August 2009 to August 2019 were enrolled in this retrospective study. The total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), maximum standardized uptake value (SUVmax), and correlated clinical characteristics were collected and analysed. TMTV was computed with the 41% SUVmax threshold method. The chi-square test or Fisher's exact probability method was used to compare clinical characteristics. Kaplan-Meier curves were used to describe progression-free survival (PFS) and overall survival (OS). The log-rank test was used to analyse the difference within groups. The statistically significant factors in the univariate regression analysis were incorporated into the Cox risk proportional regression model for multivariate survival analysis. RESULTS: The TMTV cut-off value was 514.6 cm3 from the ROC curve analysis. Forty (71.4%) patients progressed and 31 (55.4%) patients died within a median follow-up time of 19.1 (interquartile range 7.8-34.6) months. The 1-year and 3-year PFS rates were 42.9% and 30.1%, and the 3-year and 5-year OS rates were 45.9% and 34.4%, respectively. Univariate survival analysis showed that high TMTV and TLG may be the factors contributing to poor PFS and OS. Multivariate analysis showed that TMTV and prognostic index for T-cell lymphoma (PIT) were independent parameters for PFS and OS in AITL patients. TMTV, combined with PIT, may have better risk stratification performance than TMTV alone. CONCLUSIONS: Baseline TMTV and PIT were independent prognostic predictors in AITL patients. The combination of TMTV and PIT can facilitate prognostic stratification and contribute to personalized therapy.

Regional Brain Glucose Metabolism and Its Prognostic Value in Pretreatment Extranodal Natural Killer/T-Cell Lymphoma Patients.

OBJECTIVE: To explore regional brain glucose metabolic abnormalities of pretreatment stage I/II extranodal natural killer/T-cell lymphoma (ENKTL) patients using positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed tomography (18F-FDG PET/CT) and assess its prognostic value. METHODS: Sixty pretreatment stage I/II ENKTL patients were enrolled in this retrospective study and divided into survival (n = 45) and death (n = 15) groups according to their status at the end of follow-up. A control group consisted of 60 healthy subjects. Regional cerebral glucose metabolism was evaluated on a voxel-by-voxel basis using statistical parametric mapping (SPM8) under a certain significance level (P < 0. 001) and voxel threshold (K = 100 voxels). RESULTS: Decreased metabolism was noted in patients, involving the bilateral prefrontal and orbitofrontal cortex, partial parietal and occipital cortex, cingulate gyrus and cerebellum; the sensorimotor cortex was largely spared. Increased metabolism was observed in the bilateral putamen, amygdala, and parahippocampal gyrus. Compared with the survival group, the death group had higher metabolism in the bilateral amygdala, putamen, left thalamus, uncus, and parahippocampal gyrus. Only B symptoms were associated with the increased metabolism of basal ganglia and thalamus (BGT). Patients with high metabolic tumor volume, total lesion glycolysis (TLG) and BGT metabolism had a poor prognosis. TLG and maximum standardized uptake value (SUVmax) LBGT/SUVmaxRight cerebellum were associated with Eastern Cooperative Oncology Group (ECOG) and prognostic index of natural killer lymphoma and Epstein-Barr virus-DNA (PINKE) scores. In multivariate analysis, only ECOG was an independent prognostic factor of both progression-free survival (PFS) and overall survival (OS). PINKE was an independent prognostic factor of OS. CONCLUSION: Pretreatment stage I/II ENKTL patients exhibited abnormal regional cerebral glucose metabolism. Higher pretreatment glucose metabolism in BGT could predict a relatively poor prognosis but did not surpass the predictive values of ECOG and PINKE in stage I/II ENKTL patients.

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.

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% SUVmax 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.

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.

[Roles of PET/CT in Predicting the Prognosis of Diffuse Large B Cell Lymphoma Patients Treated with Chimeric Antigen Receptor T Cell Therapy].

OBJECTIVE: To investigate the prognosis prediction value of PET/CT in DLBCL patients treated with CAR-T therapy. METHODS: The effects of PET/CT were retrospectively explored on 13 R/R DLBCL patients who were treated with CAR-T therapy. Parameters reflecting tumor metabolic burden, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured before and after CAR-T treatment. RESULTS: Patients with larger baseline MTV or longer sum of longest diameters showed shorter overall survival (OS) time than those with low tumor burden. Patients achieved complete remission (CR), partial remission (PR) and minor remission (MR) determined by response evaluation criteria in lymphoma (RECIL) in 12 weeks showed progression-free survival and OS time superior to those of patients with no remission. In addition, it was found that 2 patients with residual masses classified as PR by contrast-enhanced CT of patients were evaluated as complete metabolic response by PET/CT imaging. CONCLUSION: PET/CT shows a great value in the evaluation of prognosis and response in CAR-T-treated R/R DLBCL patients.

Interim response in diffuse large B cell lymphoma on CT: what is the optimal size reduction (ΔSPD) for predicting outcome?

OBJECTIVES: To investigate whether there was an optimal interim size reduction (iΔSPD) cutoff value that could discriminate diffuse large B cell lymphoma (DLBCL) patients with poor prognosis. METHODS: This retrospective study enrolled 265 newly diagnosed DLBCL patients with baseline and interim (after 3 cycles) contrast-enhanced computed tomographic scan (CECT) available. Two radiologists evaluated CECT images and selected target lesions according to the Lugano Response Criteria. Lymph nodes greater than 15 mm in longest diameter (LDi) and extra-nodal lesions with LDi greater than 10 mm could be chosen as target lesions and used to calculate iΔSPD. A software tool, X-Tile, was used to calculate the optimal iΔSPD cutoff value to differentiate patients with good vs. poor prognosis. Receiver operating characteristic curve analysis, Cox regression analysis, and Kaplan-Meier analyses were further used to validate the optimal cutoff value. RESULTS: The optimal cutoff value of iΔSPD calculated by X-tile was 80%. Compared with 50% and 100%, 80% cutoff value had the intermediate sensitivity and specificity (57.75% and 86.69% for overall survival (OS), 48.98% and 92.22% for progression-free survival (PFS), respectively), but the maximal Youden index (0.4744 for OS, 0.4120 for PFS, respectively) and areas under the curve (0.737 [0.680, 0.789] for OS). Cox regression analysis also revealed that iΔSPD < 80% could independently predict an inferior OS and PFS (both p < 0.001) while neither iΔSPD < 50% nor iΔSPD = 100% could. CONCLUSIONS: iΔSPD with the cutoff value 80% is an independent predictor of PFS and OS for patients with DLBCL. Results suggest that treatment should be modified for patients with iΔSPD < 80%. KEY POINTS: • The aim of interim response assessment is to identify patients whose disease has not responded to or has progressed on induction therapy. • A cutoff value of 80% in size reduction (ΔSPD) is an independent predictor of PFS and OS for DLBCL patients and is better than 50%. • In DLBCL patients with interim ΔSPD < 80%, a change to a more efficient therapy should be considered.

The prognostic role of 18F-FDG PET/CT baseline quantitative metabolic parameters in peripheral T-cell lymphoma.

Objectives: The aim of this study is to investigate the prognostic significance of baseline maximum standard uptake value (SUVmax), whole body SUVmax (WBSUVmax), whole body metabolic tumor volume (WBMTV) and whole body total lesion glycolysis (WBTLG) in patients with peripheral T-cell lymphoma (PTCL). Methods: Eighty patients with PTCL who underwent pretreatment 18F-PET/CT were enrolled in this study. WBMTV and WBTLG were computed by using the margin threshold of SUV>3.0. WBSUVmax was obtained by summing of SUVmax of the whole-body SUVmax of 11 nodal and 10 extra-nodal lesions. Results: Median SUVmax was 13.8 (range, 4.6-35.5), median WBSUVmax was 24.6 (range, 4.6-153.4), median WBMTV was 149 cm3 (range, 4-4545 cm3) and median WBTLG was 1017 (range, 16.5-23739). Six patients with anaplastic large cell lymphoma, ALK positive were excluded in the following statistical analysis for their unique pathological types and good prognosis. The receiver operating curve (ROC) analysis showed that the optimal cut-off values of WBSUVmax, WBMTV and WBTLG with overall survival (OS) were 22.2, 169.5 cm3 and 746.1, respectively. Patients with high WBSUVmax, WBMTV and WBTLG had a poor prognosis. WBSUVmax, WBMTV and WBTLG were associated with international prognostic index (IPI) and prognostic index for T-cell lymphoma (PIT). In multivariate analysis, WBTLG and PIT were independent prognostic factors of both progression free survival (PFS) and OS. Conclusions: Our study shows that high WBTLG, WBMTV and WBSUVmax could predict a relatively poor prognosis, and has a highly significant association with PIT and IPI.WBTLG could be an independent predictive factor for survival outcomes in patients with PTCL.