Communicating threats and stress via biological signaling is common in animals. In humans, androstadienone (ANDR), a synthetic male steroid, is a socially relevant chemosignal exhibited to increase positive mood and cortisol levels specifically in (periovulatory) females in positively arousing contexts. In a negative context, we expected that such effects of ANDR could amplify social evaluative threat depending on the stress sensitivity, which differs between menstrual cycle phases. Therefore, this fMRI study aimed to examine psychosocial stress reactions on behavioral, hormonal and neural levels in 31 naturally cycling females, between 15 early follicular (EF) and 16 mid-luteal (ML) females tested with ANDR and placebo treatment in a repeated-measures design. Regardless of odor stimulation, psychosocial stress (i.e., mental arithmetic task with social evaluative threat) led to elevated negative mood and anxiety in all females. A negative association of social threat related amygdala activation and competence ratings appeared in ML-females, indicating enhanced threat processing by ANDR, particularly in ML-females who felt less competent early in the stress experience. Further, ML-females showed reduced performance and stronger stress-related hippocampus activation compared to EF-females under ANDR. Hippocampal activation in ML-females also correlated positively with post-stress subjective stress. Contrarily, such patterns were not observed in EF-females or under placebo in either group. Strikingly, unlike passive emotional processing, ANDR in a stressful context decreased cortisol concentration in all females. This points to a more complex interaction of ovarian/gonadal hormones in social threat processing and stress reactivity. Our findings suggest that ANDR enhanced initial evaluation of self-related social threat in ML-females. Female stress reactions are related to stress sensitivity through enhanced awareness and processing of social cues in a stressful context, with menstrual cycle phase being a critical factor.

BackgroundTo assess the additive value of dual-energy CT (DECT) over single-energy CT (SECT) to radiomics-based response prediction in patients with metastatic melanoma preceding immunotherapy.Material and methodsA total of 140 consecutive patients with melanoma (58 female, 63±16 years) for whom baseline DECT tumor load assessment revealed stage IV and who were subsequently treated with immunotherapy were included. Best response was determined using the clinical reports (81 responders: 27 complete response, 45 partial response, 9 stable disease). Individual lesion response was classified manually analogous to RECIST 1.1 through 1291 follow-up examinations on a total of 776 lesions (6.7±7.2 per patient). The patients were sorted chronologically into a study and a validation cohort (each n=70). The baseline DECT was examined using specialized tumor segmentation prototype software, and radiomic features were analyzed for response predictors. Significant features were selected using univariate statistics with Bonferroni correction and multiple logistic regression. The area under the receiver operating characteristic curve of the best subset was computed (AUROC). For each combination (SECT/DECT and patient response/lesion response), an individual random forest classifier with 10-fold internal cross-validation was trained on the study cohort and tested on the validation cohort to confirm the predictive performance.ResultsWe performed manual RECIST 1.1 response analysis on a total of 6533 lesions. Multivariate statistics selected significant features for patient response in SECT (min. brightness, R²=0.112, padj. ≤0.001) and DECT (textural coarseness, R²=0.121, padj. ≤0.001), as well as lesion response in SECT (mean absolute voxel intensity deviation, R²=0.115, padj. ≤0.001) and DECT (iodine uptake metrics, R²≥0.12, padj. ≤0.001). Applying the machine learning models to the validation cohort confirmed the additive predictive power of DECT (patient response AUROC SECT=0.5, DECT=0.75; lesion response AUROC SECT=0.61, DECT=0.85; p<0.001).ConclusionThe new method of DECT-specific radiomic analysis provides a significant additive value over SECT radiomics approaches for response prediction in patients with metastatic melanoma preceding immunotherapy, especially on a lesion-based level. As mixed tumor response is not uncommon in metastatic melanoma, this lends a powerful tool for clinical decision-making and may potentially be an essential step toward individualized medicine.

Background Retroperitoneal fibrosis is a rare disease with an incidence of 0–1/100 000 inhabitants per year and is associated with chronic inflammatory fibrosis of the retroperitoneum and the abdominal aorta. This article sheds light on the role of radiological imaging in retroperitoneal fibrosis, names various differential diagnoses and provides an overview of drug and surgical treatment options. Methods A literature search for the keywords “retroperitoneal fibrosis” and “Ormond’s disease” was carried out in the PubMed database between January 1, 1995 and December 31, 2019 (n = 1806). Mainly original papers were selected, but also reviews, in English and German language, with a focus on publications in the last 10 years, without excluding older publications that the authors believe are relevant to the topic discussed in the review (n = 40). Results and Conclusion Ormond’s disease is a rare but important differential diagnosis for nonspecific back and flank pain. Imaging diagnostics using CT or MRI show a retroperitoneal mass, which must be differentiated from lymphoma, sarcoma, multiple myeloma and Erdheim-Chester disease. Patients have an excellent prognosis under adequate therapy. FDG-PET/CT or FDG-PET/MRT should be considered as potential modalities, as hybrid imaging can evaluate both the morphological changes and the inflammation. Key Points:  Citation Format

Background: This study investigated whether a machine-learning-based combination of radiomics and clinical parameters was superior to the use of clinical parameters alone in predicting therapy response after three months, and overall survival after six and twelve months, in stage-IV malignant melanoma patients undergoing immunotherapy with PD-1 checkpoint inhibitors and CTLA-4 checkpoint inhibitors. Methods: A random forest model using clinical parameters (demographic variables and tumor markers = baseline model) was compared to a random forest model using clinical parameters and radiomics (extended model) via repeated 5-fold cross-validation. For this purpose, the baseline computed tomographies of 262 stage-IV malignant melanoma patients treated at a tertiary referral center were identified in the Central Malignant Melanoma Registry, and all visible metastases were three-dimensionally segmented (n = 6404). Results: The extended model was not significantly superior compared to the baseline model for survival prediction after six and twelve months (AUC (95% CI): 0.664 (0.598, 0.729) vs. 0.620 (0.545, 0.692) and AUC (95% CI): 0.600 (0.526, 0.667) vs. 0.588 (0.481, 0.629), respectively). The extended model was not significantly superior compared to the baseline model for response prediction after three months (AUC (95% CI): 0.641 (0.581, 0.700) vs. 0.656 (0.587, 0.719)). Conclusion: The study indicated a potential, but non-significant, added value of radiomics for six-month and twelve-month survival prediction of stage-IV melanoma patients undergoing immunotherapy.

Objectives To evaluate the predictive performance of the modified hepatoma arterial embolisation prognostic II (mHAP-II) score in a real-life western hepatocellular carcinoma (HCC) cohort treated with drug-eluting bead-TACE and compare the mHAP-II with other scores in this cohort. Methods One hundred seventy-nine HCC patients (mean age 77 (± 9) years, 87% male) with one or more drug-eluting bead (DEB)-TACE sessions using 100-300 μm microspheres were retrospectively analysed. Performance analysis of the mHAP-II score was based on Mann-Whitney U tests, the Kaplan-Meier method, log-rank tests, receiver operating characteristics, Akaike's information criterion and Cox regression models. Results In this population, HCC risk factors were mainly alcohol abuse (31%) and hepatitis C (28%). The median survival of the entire cohort was 29.4 months. mHAP-II classification of the cohort was mHAP-II B (30%), C (41%) and D (23%) respectively. Survival of all subgroups differed significantly from each other (each p < 0.05). Area under the curve for receiver operating characteristic was 0.60 and Akaike's information criterion was 21.8 (p = 0.03), indicating a superior performance of mHAP-II score compared with HAP score and BCLC. Tumour number ≥ two (HR 1.54), alpha-fetoprotein > 400 μg/l (HR 1.14), serum albumin < 3.6 g/dl (HR 1.63) and total bilirubin > 0.9 mg/dl (HR 1.58) contributed significantly in Cox proportional hazards regression (each p < 0.05). Conclusion The mHAP-II score can predict survival outcomes of western HCC patients undergoing DEB-TACE and further subdivide this heterogeneous group; however, certain limitations concerning the predictive power of mHAP-II score must be taken into account. Key Points • This retrospective study evaluated the predictive performance of the modified hepatoma arterial embolisation prognostic II (mHAP-II) score in a real-life western HCC cohort treated with drug-eluting bead-TACE. • Survival of all mHAP-II subgroups differed significantly, area under the curve for mHAP-II was 0.60 and Akaike's information criterion was 21.8. • The mHAP-II score can predict survival outcomes of western HCC patients undergoing DEB-TACE and further subdivide this heterogeneous group. However, because the study is underpowered, true survival prediction may be more difficult to infer.