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Tumor Burden Measured by 18F-FDG PET/CT in Predicting Efficacy and Adverse Effects of Chimeric Antigen Receptor T-Cell Therapy in Non-Hodgkin Lymphoma.

ABSTRACT: Chimeric antigen receptor (CAR) T-cell therapy has exhibited promising clinical outcomes in treating relapsed/refractory (R/R) B-cell hematologic malignancies. Current studies have shown a close correlation between baseline tumor burden and therapeutic response in CAR-T cell therapy. However, the roles of PET/CT metabolic parameters, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), remain unclear in this setting. In this study, we retrospectively reviewed 41 R/R NHL patients. 18F-FDG PET/CT was used to measure the average standardized uptake value (SUV_avg), MTV, and TLG of the lymphomatous lesions. These patients were divided into two groups according to the optimal cutoff values of respective PET/CT metabolic parameters. The multivariate analysis depicted that early post-therapy SUV_avg (HR: 1.418, 95% CI: 1.029, 1.955; p = 0.033) and MTV (HR: 1.001, 95% CI: 1.000, 1.002; p = 0.041) were independent risk factors associated with OS and PFS, respectively. Patients with baseline SUV_avg < 4.36 achieved a superior 1-year OS rate than the SUV_avg ≥ 4.36 group (100.0% vs. 44.9%, p = 0.019). For the patients with lower values in early post-therapy SUV_avg (<2.60) (51.1% vs. 0%, p < 0.001), MTV (<0.55 cm³) (53.6% vs. 0.0%, p = 0.001), and TLG (<1.54) (53.6% vs. 0.0%, p = 0.001), their 1-year PFS rates were higher than the compared groups. Moreover, patients with higher baseline tumor burdens were found to have significantly increased CRS incidence and cytokine levels. In conclusion, the PET/CT metabolic parameters are closely related to OS, PFS, and CRS in R/R NHL patients treated with CAR-T cells. This study may pave the way for building a comprehensive assessment system of tumor burden using 18F-FDG PET/CT, which can optimize therapeutic and supportive approaches in CAR-T cell therapy.

SUBMITTER: Hong R

PROVIDER: S-EPMC8371710 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundTo investigate the diagnostic and prognostic performances of 18F-FDG PET/CT measures of metabolic tumour burden in patients with neurofibromatosis type-1 (NF1), suspect of malignant transformation.MethodsThis retrospective study included 49 patients (15-60 years old, 30 women) with a diagnosis of NF1, followed in our Reference Centre for Rare Neuromuscular Diseases, who presented clinical signs of tumour progression (pain, neurological deficit, tumour growth). Quantitative metabolic parameters were measured on 149 tumoral targets, using semi-automatic software and the best cut off values to predict transformation was assessed by Receiver Operating Characteristics (ROC) analysis. Prognostic value of PET/CT metabolic parameters was assessed by Kaplan-Meier estimates of overall survival.ResultsLesions were histologically documented in 40 patients: a sarcomatous transformation was found in 16, a dysplastic neurofibroma (NF) in 7, and a benign NF in 17; in the remaining 9 patients, a minimal follow-up of 12 mo (median 59 mo) confirmed the absence of transformation. The optimal cut off values for detection of malignant transformation were, in decreasing order of area under the ROC curves, a tumour-to-liver (T/L) ratio >2.5, SUVmax > 4.5, total lesion glycolysis (TLG) > 377, total metabolic tumour volume (TMTV) > 88 cm3, and heterogeneity index (HIsuv) > 1.69. The best prognostic marker was the TLG: the 4-y estimates of survival were 97% [95% CI, 90% - 100%] in patients with TLG ? 377 vs. 27% [95% CI, 5% - 49%] in patients with TLG > 377 (P < 0.0001; ?2 27.85; hazard ratio 13.27 [95% CI, 3.72-47.35]). T/L ratio, SUVmax and TMTV demonstrated slightly lower performance to predict survival, with ?2 ranging 14.41-19.12. The HIsuv index was not predictive of survival.ConclusionOur study demonstrates that TLG and TMTV, as PET/CT measures of metabolic tumour burden, may be used clinically to identify sarcomatous transformation in patients with NF1 and predict overall survival, with a higher specificity for the TLG. Conventional measures such as the SUVmax, and T/L ratio also demonstrate high prognostic value.

Project description:PurposeFor pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma.Methods18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson's correlation coefficient and relative percent differences were calculated between automated and physician-extracted features.ResultsMedian Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78-0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson's correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of - 4.3% (- 10.0-5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of - 0.4% (- 5.2-7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6-4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR - 7.5-40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically.ConclusionsAn automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.

Dataset Information

Tumor Burden Measured by 18F-FDG PET/CT in Predicting Efficacy and Adverse Effects of Chimeric Antigen Receptor T-Cell Therapy in Non-Hodgkin Lymphoma.

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