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Multiple myeloma (MM) is one of the most common hematological malignancies affecting the bone marrow. Radiomics analysis has been employed in the literature in an attempt to evaluate the bone marrow of MM patients. This manuscript aimed to systematically review radiomics research on MM while employing a radiomics quality score (RQS) to accurately assess research quality in the field. A systematic search was performed on Web of Science, PubMed, and Scopus. The selected manuscripts were evaluated (data extraction and RQS scoring) by three independent readers (R1, R2, and R3) with experience in radiomics analysis. A total of 23 studies with 2682 patients were included, and the median RQS was 10 for R1 (IQR 5.5–12) and R3 (IQR 8.3–12) and 11 (IQR 7.5–12.5) for R2. RQS was not significantly correlated with any of the assessed bibliometric data (impact factor, quartile, year of publication, and imaging modality) (p > 0.05). Our results demonstrated the low quality of published radiomics research in MM, similarly to other fields of radiomics research, highlighting the need to tighten publication standards.

Objectives Post - mortem interval (PMI) estimation has long been relying on sequential post - mortem changes on the body as a function of extrinsic, intrinsic, and environmental factors. Such factors are difficult to account for in complicated death scenes; thus, PMI estimation can be compromised. Herein, we aimed to evaluate the use of post-mortem CT (PMCT) radiomics for the differentiation between early and late PMI. Methods Consecutive whole-body PMCT examinations performed between 2016 and 2021 were retrospectively included ( n  = 120), excluding corpses without an accurately reported PMI ( n  = 23). Radiomics data were extracted from liver and pancreas tissue and randomly split into training and validation sets (70:30%). Following data preprocessing, significant features were selected (Boruta selection) and three XGBoost classifiers were built (liver, pancreas, combined) to differentiate between early (< 12 h) and late (> 12 h) PMI. Classifier performance was assessed with receiver operating characteristics (ROC) curves and areas under the curves (AUC), which were compared by bootstrapping. Results A total of 97 PMCTs were included, representing individuals (23 females and 74 males) with a mean age of 47.1 ± 23.38 years. The combined model achieved the highest AUC reaching 75% (95%CI 58.4–91.6%) ( p = 0.03 compared to liver and p  = 0.18 compared to pancreas). The liver-based and pancreas-based XGBoost models achieved AUCs of 53.6% (95%CI 34.8–72.3%) and 64.3% (95%CI 46.7–81.9%) respectively ( p  > 0.05 for the comparison between liver- and pancreas-based models). Conclusion The use of radiomics analysis on PMCT examinations differentiated early from late PMI, unveiling a novel image-based method with important repercussions in forensic casework. Clinical relevance statement This paper introduces the employment of radiomics in forensic diagnosis by presenting an effective automated alternative method of estimating post-mortem interval from targeted tissues, thus paving the way for improvement in speed and quality of forensic investigations. Key Points • A combined liver-pancreas radiomics model differentiated early from late post-mortem intervals (using a 12-h threshold) with an area under the curve of 75% (95%CI 58.4–91.6%). • XGBoost models based on liver-only or pancreas-only radiomics demonstrated inferior performance to the combined model in predicting the post-mortem interval.

Atlases of normal genomics, transcriptomics, proteomics, and metabolomics have been published in an attempt to understand the biological phenotype in health and disease and to set the basis of comprehensive comparative omics studies. No such atlas exists for radiomics data. The purpose of this study was to systematically create a radiomics dataset of normal abdominal and pelvic radiomics that can be used for model development and validation. Young adults without any previously known disease, aged > 17 and ≤ 36 years old, were retrospectively included. All patients had undergone CT scanning for emergency indications. In case abnormal findings were identified, the relevant anatomical structures were excluded. Deep learning was used to automatically segment the majority of visible anatomical structures with the TotalSegmentator model as applied in 3DSlicer. Radiomics features including first order, texture, wavelet, and Laplacian of Gaussian transformed features were extracted with PyRadiomics. A Github repository was created to host the resulting dataset. Radiomics data were extracted from a total of 531 patients with a mean age of 26.8 ± 5.19 years, including 250 female and 281 male patients. A maximum of 53 anatomical structures were segmented and used for subsequent radiomics data extraction. Radiomics features were derived from a total of 526 non-contrast and 400 contrast-enhanced (portal venous) series. The dataset is publicly available for model development and validation purposes.

Background Elderly patients are underrepresented in the studies concerning anticoagulation therapy (AT) in atrial fibrillation (AF), while patients’ frailty status is lacking in most of the studies. Objective Our objective was to evaluate AT in AF elderly patients and study the effect of patients’ frailty status on their long-term AT. Methods We conducted an observational prospective study that enrolled consecutive AF patients (≥ 75 years) who were hospitalized in the Department of Internal Medicine of the University Hospital of Heraklion, Crete, Greece from 1 June 2015 to 1 June 2016. We recorded the AT on admission and at discharge, all-cause mortality, and hospital readmission in a follow-up period of 1 year after hospital discharge. Frailty status was assessed by pre-established scores. Results One hundred and four consecutive patients (49% male; median age 87 years) were enrolled, 78 (78.8%) of whom received AT at discharge. Patients who did not receive AT at discharge had a higher HEMORR 2 HAGES (Hepatic or renal disease, Ethanol abuse, Malignancy, Older age, Reduced platelet count or function, Re-bleeding, Hypertension, Anemia, Genetic factors, Excessive fall risk and Stroke) score (5.5 ± 1.15 vs. 4.79 ± 1.68; p  = 0.032), a lower Katz score (2.48 ± 2.23 vs. 4.08 ± 2.25; p  = 0.006), and a higher Clinical Frailty Scale score (7 ± 1.95 vs. 5.57 ± 2.05; p  = 0.006). Sixty-five patients (62.5%) were readmitted to a hospital during the follow-up period. In-hospital death occurred in five patients (4.8%) and 57 patients (57.6%) died within the follow-up period. Conclusion A high percentage of the elderly AF patients did not receive AT, even at discharge. Patients who did not receive AT at discharge had higher bleeding and frailty scores. In the 1-year follow-up period after hospital discharge, high all-cause mortality and a high number of hospital readmissions were recorded.

The rapid developments in artificial intelligence (AI) research in radiology have produced numerous models that are scattered across various platforms and sources, limiting discoverability, reproducibility and clinical translation. Herein, OpenRad was created, a curated, standardized, open-access repository that aggregates radiology AI models and providing details such as the availability of pretrained weights and interactive applications. Retrospective analysis of peer reviewed literature and preprints indexed in PubMed, arXiv and Scopus was performed until Dec 2025 (n = 5239 records). Model records were generated using a locally hosted LLM (gpt-oss:120b), based on the RSNA AI Roadmap JSON schema, and manually verified by ten expert reviewers. Stability of LLM outputs was assessed on 225 randomly selected papers using text similarity metrics. A total of 1694 articles were included after review. Included models span all imaging modalities (CT, MRI, X-ray, US) and radiology subspecialties. Automated extraction demonstrated high stability for structured fields (Levenshtein ratio > 90%), with 78.5% of record edits being characterized as minor during expert review. Statistical analysis of the repository revealed CNN and transformer architectures as dominant, while MRI was the most commonly used modality (in 621 neuroradiology AI models). Research output was mostly concentrated in China and the United States. The OpenRad web interface enables model discovery via keyword search and filters for modality, subspecialty, intended use, verification status and demo availability, alongside live statistics. The community can contribute new models through a dedicated portal. OpenRad contains approx. 1700 open access, curated radiology AI models with standardized metadata, supplemented with analysis of code repositories, thereby creating a comprehensive, searchable resource for the radiology community.

Thyroid nodules, prevalent in 2% to 65% of the general population depending on diagnostic methodology, represent a significant clinical concern despite a low malignancy rate, typically 1% to 5%. A substantial proportion of thyroid cancers are small, indolent lesions, allowing for conservative management with favorable prognoses. Nodule detection commonly occurs via palpation, clinical examination, or incidental radiological findings. Established risk factors include advanced age, female gender, obesity, metabolic syndrome, and estrogen dominance. Despite conservative management potential, a considerable number of thyroid nodules in Europe are unnecessarily referred for surgery, incurring unfavorable risk-to-benefit ratios and increased costs. Minimally invasive techniques (MITs), encompassing ethanol and thermal ablation modalities (e.g., laser, radiofrequency, microwave), offer outpatient, nonsurgical management for symptomatic or cosmetically concerning thyroid lesions. These procedures, performed under ultrasound guidance without general anesthesia, are associated with low complication rates. MITs effectively achieve substantial and sustained nodule volume reduction (57–77% at 5 years), correlating with improved local symptoms. Thermal ablation (TA) is particularly favored for solid thyroid lesions due to its precise and predictable tissue destruction. Optimal TA balances near-complete nodule eradication to prevent recurrence with careful preservation of adjacent anatomical structures to minimize complications. Radiofrequency ablation (RFA) is widely adopted, while microwave ablation (MWA) presents a promising alternative addressing RFA limitations. Percutaneous laser ablation (LA), an early image-guided thyroid ablation technique, remains a viable option for benign, hyperfunctioning, and malignant thyroid pathologies. This review comprehensively evaluates RFA, MWA, and LA for thyroid nodule treatment, assessing current evidence regarding their efficacy, safety, comparative outcomes, side effects, and outlining future research directions.

Cardiopulmonary bypass (CPB) is one of the most groundbreaking medical innovations in history, enabling safe and effective heart surgery by temporarily replacing the function of the heart and lungs. This review starts with ancient concepts of cardiopulmonary function and then traces the evolution of CPB through important physiological and anatomical discoveries, culminating in the development of the modern heart–lung machine. In addition to examining the contributions of significant figures like Galen, Ibn al-Nafis, William Harvey, and John Gibbon, we also examine the ethical and technical challenges faced in the early days of open heart surgery. Modern developments are also discussed, such as miniature extracorporeal systems, off-pump surgical techniques, and the increasing importance of extracorporeal membrane oxygenation (ECMO) and extracorporeal life support (ECLS), while the evolving role of perfusionists in diverse cardiac teams and the variations in global access to CPB technology are also given special attention. We look at recent advancements in CPB, including customized methods, nanotechnology, artificial intelligence-guided perfusion, and organ-on-chip testing, emphasizing CPB’s enduring significance as a technological milestone and a living example of the cooperation of science, medicine, and human inventiveness because it bridges the gap between the past and the future.

We are grateful to Dr. Al Ebrahim for his thoughtful and constructive commentary on our historical review of cardiopulmonary bypass (CPB) [...].We are grateful to Dr. Al Ebrahim for his thoughtful and constructive commentary on our historical review of cardiopulmonary bypass (CPB) [...].

Nitrogen nutrition is one of the most effective cultural practices in vineyards. The vine nitrogen status influences the berries’ quality characteristics and the produced wines. The current study investigated the effect of traditional nitrogen fertilization in the form of ammonium sulfate compared to nitrogen fertilization coupled with the nitrification inhibitor 3,4-Dimethylpyrazole phosphate (DMPP) on the agronomic characteristics of grapes and the produced wines of the white variety Savvatiano from a productive vineyard in the Attiki region. Must and wine quality was evaluated by a chemical analysis and sensorial evaluation by trained panelists. The different forms of nitrogen fertilizers did not significantly affect the aroma and sensory profile in contrast to unfertilized grapevines. In addition, the applied fertilization increased some important aroma compounds in the wine, compared to no fertilization. The significance of this work is to add information about the effect of nitrogen fertilization on the wine volatile composition of the Greek white grapevine Savvatiano.

The association of low-density lipoprotein cholesterol lowering with outcomes in embolic stroke of undetermined source (ESUS) patients is unclear. In these patients we aimed to assess the effect of statin on stroke recurrence, major adverse cardiovascular events (MACE) and death rates. Consecutive ESUS patients in the Athens Stroke Registry were prospectively followed-up to 10 years for stroke recurrence, MACE, and death. The Nelson–Aalen estimator was used to estimate the cumulative probability by statin allocation at discharge and cox-regression analyses to investigate whether statin at discharge was a predictor of outcomes. Among 264 ESUS patients who were discharged and followed for 4 years, 89 (33.7%) were treated with statin at discharge. Patients who were discharged on statin had lower rates of stroke recurrence (3.58 vs. 7.23/100 patient-years, HR: 0.48; 95% CI 0.26–0.90), MACE (4.98 vs. 9.89/100 patient-years, HR: 0.49; 95% CI 0.29–0.85), and death (3.93 vs. 8.21/100 patient-years, HR: 0.50; 95% CI: 0.28–0.89). In the multivariate analysis, statin treatment at discharge was an independent predictor of stroke recurrence (adjusted HR: 0.48; 95% CI 0.26–0.91), MACE (adjusted HR: 0.48; 95% CI 0.28–0.82), and death (adjusted HR: 0.50; 95% CI 0.27–0.93). Patients with ESUS discharged on statins have lower rates of stroke recurrence, MACE, and death compared to those not receiving statin therapy.