Dataset Information

Baseline ¹⁸F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.

ABSTRACT: Post-transplant lymphoproliferative disorder (PTLD) is a rare complication of immunosuppression. Sequential treatment is commonly proposed, combining induction with rituximab (R-induction) followed by either continuation of treatment or addition of chemotherapy depending on response. Response to R-induction, often assessed by CT scan, is a major predictor of overall survival (OS). The aim of the study was to analyze predictive factors of R-induction response, including total metabolic tumor volume (TMTV), and investigate the role of ¹⁸F-FDG PET/CT in response assessment. This retrospective multicenter study is based on patients with PTLD included in the K-VIROGREF cohort. Only patients treated by R-induction with a baseline ¹⁸F-FDG PET/CT were included. Response to R-induction was assessed by ¹⁸F-FDG PET/CT. The optimal threshold of TMTV for rituximab response was determined using receiver operating characteristic curves. Univariate and multivariate analyses were conducted to identify predictive factors of response. A total of 67 patients were included. Survival characteristics were similar to those previously reported: the complete response rate to R-induction was 30%, the 3-year OS estimate was 66%, and the treatment-related mortality was 4%. The optimal threshold for TMTV to predict R-induction response was 135 cm³. The response rate to R-induction was 38% in the 21 patients with TMTV ≥ 135 cm³ and 72% in the 46 patients with TMTV < 135 cm³. TMTV was a significant predictor of response, both at univariate and multivariate analyses (odd ratios = 3.71, P = 0.022). Baseline TMTV is predictive of response to R-induction. Early assessment of patient response is feasible with ¹⁸F-FDG PET/CT.

SUBMITTER: Morland D

PROVIDER: S-EPMC9875954 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Baseline <sup>18</sup>F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.

Morland David D Kanagaratnam Lukshe L Hubelé Fabrice F Toussaint Elise E Choquet Sylvain S Kas Aurélie A Caquot Pierre-Ambroise PA Haioun Corinne C Itti Emmanuel E Leprêtre Stéphane S Decazes Pierre P Bijou Fontanet F Schwartz Paul P Jacquet Caroline C Chauchet Adrien A Matuszak Julien J Kamar Nassim N Payoux Pierre P Durot Eric E

HemaSphere 20230124 2

Post-transplant lymphoproliferative disorder (PTLD) is a rare complication of immunosuppression. Sequential treatment is commonly proposed, combining induction with rituximab (R-induction) followed by either continuation of treatment or addition of chemotherapy depending on response. Response to R-induction, often assessed by CT scan, is a major predictor of overall survival (OS). The aim of the study was to analyze predictive factors of R-induction response, including total metabolic tumor volu ...[more]

PMID: 36713354

Similar Datasets

Project description:BackgroundPost-transplant lymphoproliferative disorder (PTLD) is a significant complication after liver transplantation. Research on the diagnostic value of the Fluorine-18 fluorodeoxyglucose positron emission tomography/computerized tomography (18F-FDG PET/CT) metabolic parameters of PTLD in pediatric liver transplantation (pLT) recipients is limited. This study sought to evaluate the diagnostic efficacy of 18F-FDG PET/CT in differentiating between PTLD and non-PTLD lymphadenopathy in pLT recipients.MethodsThis retrospective study collected the 18F-FDG PET/CT scans with clinical and pathological information of all consecutive children who were clinically suspected of PTLD from November 2016 to September 2022 at the Beijing Friendship Hospital. The 18F-FDG PET/CT metabolic parameters of the two groups were analyzed. We then established a diagnostic model composed of the clinical characteristics and metabolic parameters.ResultsIn total, 57 eligible patients were enrolled in this study, of whom 40 had PTLD and 17 had non-PTLD lymphadenopathy. Of the metabolic parameters examined in this study, total lesion glycolysis (TLG) had the highest area under the curve (AUC) value [0.757, 95% confidence interval (CI): 0.632-0.883, P=0.002]. The AUCs of the other metabolic parameters were all less than the AUC of TLG, including the maximum standardized uptake value (SUVmax) (AUC: 0.725, 95% CI: 0.597-0.853, P=0.008), mean standardized uptake value (SUVmean) (AUC: 0.701, 95% CI: 0.568-0.834, P=0.017), metabolic tumor volume total (MTVtotal) (AUC: 0.688, 95% CI: 0.549-0.827, P=0.040), TLG total (AUC: 0.674, 95% CI: 0.536-0.812, P=0.026). The diagnostic model, which was composed of clinical characteristics (digestive symptoms), the SUVmax, TLG, and the MTVtotal, showed excellent performance in the differential diagnosis (sensitivity: 0.675, 95% CI: 0.508-0.809; specificity: 0.941, 95% CI: 0.692-0.997; positive predictive value: 0.964, 95% CI: 0.798-0.998; and negative predictive value: 0.552, 95% CI: 0.360-0.730).ConclusionsThe 18F-FDG PET/CT metabolic parameters can be used to distinguishing between PTLD and non-PTLD lymphadenopathy in pLT recipients.

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:BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma in adults. Standard treatment includes chemoimmunotherapy with R-CHOP or similar regimens. Despite treatment advancements, many patients with DLBCL experience refractory disease or relapse. While baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) parameters have shown promise in predicting survival, they may not fully capture lesion heterogeneity. This study aimed to assess the prognostic value of baseline 18F-FDG PET radiomics features in comparison with clinical factors and metabolic parameters for assessing 2-year progression-free survival (PFS) and 5-year overall survival (OS) in patients with DLBCL.ResultsA total of 201 patients with DLBCL were enrolled in this study, and 1328 radiomics features were extracted. The radiomics signatures, clinical factors, and metabolic parameters showed significant prognostic value for individualized prognosis prediction in patients with DLBCL. Radiomics signatures showed the lowest Akaike information criterion (AIC) value and highest Harrell's concordance index (C-index) value in comparison with clinical factors and metabolic parameters for both PFS (AIC: 571.688 vs. 596.040 vs. 576.481; C-index: 0.732 vs. 0.658 vs. 0.702, respectively) and OS (AIC: 339.843 vs. 363.671 vs. 358.412; C-index: 0.759 vs. 0.667 vs. 0.659, respectively). Statistically significant differences were observed in the area under the curve (AUC) values between the radiomics signatures and clinical factors for both PFS (AUC: 0.768 vs. 0.681, P = 0.017) and OS (AUC: 0.767 vs. 0.667, P = 0.023). For OS, the AUC of the radiomics signatures were significantly higher than those of metabolic parameters (AUC: 0.767 vs. 0.688, P = 0.007). However, for PFS, no significant difference was observed between the radiomics signatures and metabolic parameters (AUC: 0.768 vs. 0.756, P = 0.654). The combined model and the best-performing individual model (radiomics signatures) alone showed no significant difference for both PFS (AUC: 0.784 vs. 0.768, P = 0.163) or OS (AUC: 0.772 vs. 0.767, P = 0.403).ConclusionsRadiomics signatures derived from PET images showed the high predictive power for progression in patients with DLBCL. The combination of radiomics signatures, clinical factors, and metabolic parameters may not significantly improve predictive value beyond that of radiomics signatures alone.

Project description:BackgroundNever-smokers with lung cancer usually have a higher survival rate than that of smokers. The high metabolic activity of lung cancer on 18F-2-Fluoro-2-deoxyglucose (18F-FDG) PET/CT generally indicates a poor outcome. However, there is a lack of reports on the association between cigarette smoking and 18F-FDG metabolic activity in patients with lung cancer. In this study, we aimed to investigate the effects of cigarette smoking on metabolic activity of lung cancer on 18F-FDG PET/CT.Materials and methodsA total of 338 patients (230 males, 108 females; mean age: 66.3, range 34-86) with pathologically diagnosed lung cancer were enrolled from September 2019 to April 2021. All patients underwent baseline 18F-FDG PET/CT and the maximum standard uptake value (SUVmax) of the primary tumor (pSUVmax), lymph node (nSUVmax) and distant metastasis (mSUVmax) were measured. The associations between cigarette smoking status, clinical stage, pathological subtypes and metabolic parameters on 18F-FDG PET/CT were analyzed.ResultsOf the 338 patients, cigarette smoking was identified in 153 patients (45.3%) and the remaining 185 (54.7%) were never-smokers. Smoking was found more frequently in males, squamous cell carcinoma (SCC) and stage III-IV diseases. The pSUVmax in smokers was significantly higher than that in never-smokers (t = 3.386, P < 0.001), but the nSUVmax and mSUVmax revealed no statistically significant differences (t = 0.399, P = 0.690 and t = 0.057, P = 0.955; respectively). With the increase of cumulative smoking dose, pSUVmax increased significantly (r = 0.217, P < 0.001). In addition, the pSUVmax in patients with stage III-IV was significantly higher than that in stage I-II (t = 8.509, P < 0.001). Smokers showed a higher pSUVmax than never-smokers for patients with stage I-II (t = 3.106, P = 0.002), but not in stage III-IV (t = 0.493, P = 0.622). The pSUVmax was significantly different among patients with different pathological subtypes of lung cancer (F = 11.45, P < 0.001), while only the adenocarcinoma (ADC) and SCC groups showed a difference in pSUVmax (t = 6.667, P < 0.001). Smokers with ADC showed a higher pSUVmax when compared to never-smokers, but not in SCC. There were no significant differences of pSUVmax between smokers and never-smokers at stage I-II ADC or SCC and stage III-IV ADC or SCC.ConclusionsThis study demonstrated a close association between cigarette smoking and the metabolic activity of lung cancer and suggests that smoking may be a potential risk factor of higher pSUVmax in early lung cancer on 18F-FDG PET/CT.

Project description:Knowledge of the within-subject variability of 18F-FDG PET/MRI measurements is necessary for proper interpretation of quantitative PET or MRI metrics in the context of therapeutic efficacy assessments with integrated PET/MRI scanners. The goal of this study was to determine the test-retest repeatability of these metrics on PET/MRI, with comparison to similar metrics acquired by PET/CT. Methods: This prospective study enrolled subjects with pathology-proven pelvic malignancies. Baseline imaging consisted of PET/CT immediately followed by PET/MRI, using a single 370-MBq 18F-FDG dose. Repeat imaging was performed within 7 d using an identical imaging protocol, with no oncologic therapy between sessions. PET imaging on both scanners consisted of a list-mode acquisition at a single pelvic station. The MRI consisted of 2-point Dixon imaging for attenuation correction, standard sequences for anatomic correlation, and diffusion-weighted imaging. PET data were statically reconstructed using various frame durations and minimizing uptake time differences between sessions. SUV metrics were extracted for both PET/CT and PET/MRI in each imaging session. Apparent diffusion coefficient (ADC) metrics were extracted for both PET/MRI sessions. Results: The study cohort consisted of 14 subjects (13 female, 1 male) with various pelvic cancers (11 cervical, 2 rectal, 1 endometrial). For SUVmax, the within-subject coefficient of variation (wCV) appeared higher for PET/CT (8.5%-12.8%) than PET/MRI (6.6%-8.7%) across all PET reconstructions, though with no significant repeatability differences (all P values ≥ 0.08) between modalities. For lean body mass-adjusted SUVpeak, the wCVs appeared similar for PET/CT (9.9%-11.5%) and PET/MRI (9.2%-11.3%) across all PET reconstructions, again with no significant repeatability differences (all P values ≥ 0.14) between modalities. For PET/MRI, the wCV for ADCmedian of 3.5% appeared lower than the wCVs for SUVmax (6.6%-8.7%) and SULpeak (9.2%-11.3%), though without significant repeatability differences (all P values ≥ 0.23). Conclusion: For solid tumors of the pelvis, the repeatability of the evaluated SUV and ADC metrics on 18F-FDG PET/MRI is both acceptably high and similar to previously published values for 18F-FDG PET/CT and MRI, supporting the use of 18F-FDG PET/MRI for quantitative oncologic treatment response assessments.

Dataset Information

Baseline ¹⁸F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.

Publications

Baseline <sup>18</sup>F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Baseline 18F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.

Publications

Baseline <sup>18</sup>F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Baseline ¹⁸F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.