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

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

SUBMITTER: Nath K

PROVIDER: S-EPMC8270658 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:At present, 18F-fluorodesoxyglucose (18FDG) positron emission tomography (PET)/computed tomography (CT) cannot be used to omit a bone marrow biopsy (BMB) among initial staging procedures in follicular lymphoma (FL). The additional diagnostic value of skeletal textural features on baseline 18FDG-PET/CT in diffuse large B-cell lymphoma (DLBCL) patients has given promising results. The aim of this study is to evaluate the value of 18FDG-PET/CT radiomics for the diagnosis of bone marrow involvement (BMI) in FL patients. This retrospective bicentric study enrolled newly diagnosed FL patients addressed for baseline 18FDG PET/CT. For visual assessment, examinations were considered positive in cases of obvious bone focal uptakes. For textural analysis, the skeleton volumes of interest (VOIs) were automatically extracted from segmented CT images and analysed using LifeX software. BMB and visual assessment were taken as the gold standard: BMB -/PET - patients were considered as bone-NEGATIVE patients, whereas BMB +/PET -, BMB -/PET + and BMB +/PET + patients were considered bone-POSITIVE patients. A LASSO regression algorithm was used to select features of interest and to build a prediction model. Sixty-six consecutive patients were included: 36 bone-NEGATIVE (54.5%) and 30 bone-POSITIVE (45.5%). The LASSO regression found variance_GLCM, correlation_GLCM, joint entropy_GLCM and busyness_NGLDM to have nonzero regression coefficients. Based on ROC analysis, a cut-off equal to - 0.190 was found to be optimal for the diagnosis of BMI using PET pred.score. The corresponding sensitivity, specificity, PPV and NPV values were equal to 70.0%, 83.3%, 77.8% and 76.9%, respectively. When comparing the ROC AUCs with using BMB alone, visual PET assessment or PET pred.score, a significant difference was found between BMB versus visual PET assessments (p = 0.010) but not between BMB and PET pred.score assessments (p = 0.097). Skeleton texture analysis is worth exploring to improve the performance of 18FDG-PET/CT for the diagnosis of BMI at baseline in FL patients.

Project description:PurposeDelineation of tumour boundaries is important for quantification of [(18)F]fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) studies and for definition of biological target volumes in radiotherapy. Several (semi-)automatic tumour delineation methods have been proposed, but these methods differ substantially in estimating tumour volume and their performance may be affected by imaging parameters. The main purpose of this study was to explore the performance dependence of various (semi-)automatic tumour delineation methods on different imaging parameters, i.e. reconstruction parameters, noise levels and tumour characteristics, and thereby the need for standardization or inter-institute calibration.MethodsSix different types of delineation methods were evaluated by assessing accuracy and precision in estimating tumour volume from simulations and phantom experiments. The evaluated conditions were various tumour sizes, iterative reconstruction algorithm settings and image filtering, tumour to background ratios (TBR), noise levels and region growing initializations.ResultsThe accuracy of all automatic delineation methods was influenced when imaging parameters were varied. The performance of all tumour delineation methods depends on variation of TBR, image resolution and image noise level, and to a lesser extent on number of iterations during image reconstruction or the initialization method of the region generation. For sphere sizes larger than 20 mm diameter a contrast-oriented method provided the most accurate results, on average, over all simulated conditions. For threshold-based methods the accuracy of tumour delineation improved after image denoising/filtering.ConclusionThe accuracy and precision of all studied tumour delineation methods was affected by physiological and imaging parameters. The latter illustrates the need for optimizing imaging parameters and/or for careful calibration and optimization of delineation methods.

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

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