Artificial Intelligence in Pancreatic Intraductal Papillary Mucinous Neoplasm Imaging: A Systematic Review.

Background: Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive in detecting high-risk IPMN, they lack specificity, resulting in surgical overtreatment. Artificial Intelligence (AI)-based medical image analysis has the potential to augment the clinical management of IPMNs by improving diagnostic accuracy.

Prognostic significance of immune reconstitution following CD19 CAR T-cell therapy for relapsed/refractory B-cell lymphoma.

Immune deficits after CD19 chimeric antigen receptor (CAR) T-cell therapy can be long-lasting, predisposing patients to infections and non-relapse mortality. In B-cell non-Hodgkin lymphoma (B-NHL), the prognostic impact of immune reconstitution (IR) remains ill-defined, and detailed cross-product comparisons have not been performed to date. In this retrospective observational study, we longitudinally characterized lymphocyte subsets and immunoglobulin levels in 105 B-NHL patients to assess patterns of immune recovery arising after CD19 CAR-T.

Identifying genetic differences between bipolar disorder and major depression through multiple genome-wide association analyses.

Background: Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

Aims: We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Weather-Related Factors and Patient-Reported Outcomes (PROs) in Cancer Patients: Results from the ExPRO Study.

Objective: The ExPRO (External factors influencing patient reported outcomes of patients with malignant diseases) study explored associations between QoL data and environmental factors on the day of questionnaire completion: mean temperature, sunshine hours, season, and lunar phase.

Methods: We undertook a cross-sectional analysis of baseline data in the prospective cohort study at two cancer centers in eastern Germany. From December 2020 to December 2021, cancer patients completed the EORTC QLQ-C30 questionnaire upon admission.