[en] Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics. PET/CT scans from 34 lymphoma patients were used to calculate SUVmax${}^{liver}$, SUVpeak${}^{liver}$ and SUVmean${}^{liver}$ as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans. Generally, SUVmax${}^{liver}$ and SUVpeak${}^{liver}$ were 38% and 16% higher compared to SUVmean${}^{liver}$. SUVmax${}^{liver}$ and SUVpeak${}^{liver}$ increased up to 31% and 15% with VOI size while SUVmean${}^{liver}$ remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15-18% and 9-18% higher at interim and EoT PET, respectively. SUV${}^{liver}$ decreased with larger total MTVs. SUVmax${}^{liver}$ and SUVpeak${}^{liver}$ were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images. SUVmean${}^{liver}$ was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmean${}^{liver}$ values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmean${}^{liver}$ measurements in future studies.

[en] Biomarkers that can accurately predict outcome in DLBCL patients are urgently needed. Radiomics features extracted from baseline [${}^{18}$F]-FDG PET/CT scans have shown promising results. This study aims to investigate which lesion- and feature-selection approaches/methods resulted in the best prediction of progression after 2 years. A total of 296 patients were included. 485 radiomics features (n = 5 conventional PET, n = 22 morphology, n = 50 intensity, n = 408 texture) were extracted for all individual lesions and at patient level, where all lesions were aggregated into one VOI. 18 features quantifying dissemination were extracted at patient level. Several lesion selection approaches were tested (largest or hottest lesion, patient level [all with/without dissemination], maximum or median of all lesions) and compared to the predictive value of our previously published model. Several data reduction methods were applied (principal component analysis, recursive feature elimination (RFE), factor analysis, and univariate selection). The predictive value of all models was tested using a fivefold cross-validation approach with 50 repeats with and without oversampling, yielding the mean cross-validated AUC (CV-AUC). Additionally, the relative importance of individual radiomics features was determined. Models with conventional PET and dissemination features showed the highest predictive value (CV-AUC: 0.72-0.75). Dissemination features had the highest relative importance in these models. No lesion selection approach showed significantly higher predictive value compared to our previous model. Oversampling combined with RFE resulted in highest CV-AUCs. Regardless of the applied lesion selection or feature selection approach and feature reduction methods, patient level conventional PET features and dissemination features have the highest predictive value.

[en] 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. Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value $\ge <!--\; ???\; -->$ 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. 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). Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance. EudraCT: 2006-005,174-42, 01-08-2008.

[en] Purpose: The use of radiotherapy in patients with advanced Hodgkin's lymphoma (HL) is controversial. The purpose of this study was to describe the role of radiotherapy in patients with advanced HL who were in partial remission (PR) after chemotherapy. Methods: In a prospective randomized trial, patients <70 years old with previously untreated Stage III-IV HL were treated with six to eight cycles of mechlorethamine, vincristine, procarbazine, prednisone/doxorubicin, bleomycine, vinblastine hybrid chemotherapy. Patients in complete remission (CR) after chemotherapy were randomized between no further treatment and involved-field radiotherapy (IF-RT). Those in PR after six cycles received IF-RT (30 Gy to originally involved nodal areas and 18-24 Gy to extranodal sites with or without a boost). Results: Of 739 enrolled patients, 57% were in CR and 33% in PR after chemotherapy. The median follow-up was 7.8 years. Patients in PR had bulky mediastinal involvement significantly more often than did those in CR after chemotherapy. The 8-year event-free survival and overall survival rate for the 227 patients in PR who received IF-RT was 76% and 84%, respectively. These rates were not significantly different from those for CR patients who received IF-RT (73% and 78%) or for those in CR who did not receive IF-RT (77% and 85%). The incidence of second malignancies in patients in PR who were treated with IF-RT was similar to that in nonirradiated patients. Conclusion: Patients in PR after six cycles of mechlorethamine, vincristine, procarbazine, prednisone/doxorubicine, bleomycine, vinblastine treated with IF-RT had 8-year event-free survival and overall survival rates similar to those of patients in CR, suggesting a definite role for RT in these patients