Artificial Intelligence (AI) has become one of the most transformative technologies of the 21st century. It is poised to reshape medicine, as almost every field of hospital treatment has seen an increase in AI’s presence. In this article, we focus on its impact in the field of anesthesia. We discuss its possible influence on difficult airway management, as it remains one of the most critical and potentially hazardous aspects of anesthesia, often leading to life-threatening complications. The accurate prediction of difficult airways can significantly improve patient safety. We covered the available literature on AI-based models for difficult airway prediction in comparison to traditional forms of airway assessment, as well as the predictive value of ultrasonography. We also address the narrative that AI-based algorithms show high sensitivity and specificity, with which they significantly outperform classical tests based on complex scales and indices.

The diagnostic process in Intensive Care Units has been revolutionized by ultrasonography and accelerated by artificial intelligence. Patients in critical condition are often sonoanatomically challenging, with time constraints being an additional stress factor. In this paper, we describe the technology behind the development of AI systems to support diagnostic ultrasound in intensive care units. Among the AI-based solutions, the focus was placed on systems supporting cardiac ultrasound, such as Smart-VTI, Auto-VTI, SmartEcho Vue, AutoEF, Us2.ai, and Real Time EF. Solutions to assist hemodynamic assessment based on the evaluation of the inferior vena cava, such as Smart-IVC or Auto-IVC, as well as to facilitate ultrasound assessment of the lungs, such as Smart B-line or Auto B-line, and to help in the estimation of gastric contents, such as Auto Gastric Antrum, were also discussed. All these solutions provide doctors with support by making it easier to obtain appropriate diagnostically correct ultrasound images by automatically performing time-consuming measurements and enabling real-time analysis of the obtained data. Artificial intelligence will most likely be used in the future to create advanced systems facilitating the diagnostic and therapeutic process in intensive care units.

Artificial intelligence has now changed regional anesthesia, facilitating, therefore, the application of the regional block under the USG guidance. Innovative technological solutions make it possible to highlight specific anatomical structures in the USG image in real time, as needed for regional block. This contribution presents such technological solutions as U-Net architecture, BPSegData and Nerveblox and the basis for independent assisting systems in the use of regional blocks, e.g., ScanNav Anatomy PNB or the training system NeedleTrainer. The article describes also the systems integrated with the USG devices, such as Mindray SmartNerve or GE cNerve as well as the robotic system Magellan which substantially increases the patient’s safety, time needed for the regional block and quality of the procedure. All the solutions presented in this article facilitate the performance of regional blocks by less experienced physicians and appear as an excellent educational tool which, at the same time, improves the availability of the more and more popular regional anesthesia. Will, therefore, artificial intelligence replace physicians in regional block procedures? This seems unlikely. It will, however, assist them in a significant manner, contributing to better effectiveness and improved safety of the patient.

Background/Objectives: In this study, serum selenium levels in patients with Crohn’s disease (CD) and ulcerative colitis (UC) were evaluated to identify potential predictive markers of disease activity. Conducted in 100 inflammatory bowel disease (IBD) patients (54 CD, 46 UC) and 100 healthy controls, this research provides novel insights through focusing on the regional selenium status of people with IBD in the Polish population, a demographic with limited existing data. Methods: Selenium concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). Results: Significantly lower levels of selenium were observed in CD (64.79 µg/L ± 12.15 µg/L) and UC (68.61 µg/L ± 11.43 µg/L) patients when compared with the controls (90.52 ± 12.00 µg/L, p < 0.0001). Regression analysis identified leukocyte and erythrocyte counts and bilirubin as significant predictors of selenium levels in UC patients, while no significant predictors were found for CD. Conclusions: The findings suggest that selenium deficiency is linked to IBD and may serve as a non-invasive biomarker for disease severity, particularly in UC. This practical approach offers a potential alternative to invasive procedures such as endoscopy for monitoring disease progression. However, further research is needed to confirm these findings in larger populations and explore the therapeutic role of selenium supplementation in IBD management.

Background/Objectives: The accurate localization of interfascial planes is critical for effective regional anesthesia, yet current techniques relying on ultrasound guidance can be challenging, especially in obese or pediatric patients. Previous cadaveric and clinical studies have suggested that injection pressure varies depending on needle placement relative to fascial and neural structures. This pilot study aimed to evaluate whether the continuous monitoring of injection pressure can reliably differentiate interfascial spaces from surrounding anatomical structures in a porcine tissue model. Methods: A custom-built pressure monitoring system was used to continuously measure saline injection pressure during regional block procedures performed on porcine thighs. Injections were guided by ultrasound and conducted using an infusion pump. Needle positions were classified as intramuscular, resting on fascia, or interfascial. Statistical comparisons of pressure levels, variability, and temporal trends were conducted using Wilcoxon signed-rank tests and regression analysis. Results: Mean intramuscular pressure was significantly higher than the mean interfascial pressure (p < 1 × 10⁻¹³). Interfascial injections demonstrated lower pressure variability (p = 2.1 × 10⁻⁴) and an increasing trend in pressure over time (p = 2.1 × 10⁻⁴), whereas intramuscular injections exhibited a decreasing pressure trend (p = 3.15 × 10⁻³). Conclusions: Continuous pressure monitoring effectively distinguishes interfascial from intramuscular and fascial penetration phases during regional anesthesia. The method demonstrates potential as a real-time, objective tool for enhancing needle guidance and improving the safety and accuracy of interfascial plane blocks. Further cadaveric and clinical studies are warranted to validate these findings.

The performance of advanced air rifles available on the market is comparable to that of small-calibre firearms. The airgun market offers airgun pellets that vary in weight, shape, calibre and material. In view of the ease of airguns tuning, a study of the gunshot damage to the anterior surface of the porcine femoral shaft was carried out with shots fired from a 5.5 mm calibre air rifle. An original human thigh model using a pig femur embedded in ballistic gellatine was used in the study. Gunshot damage was inflicted by firing Haendler&Natterman Baracuda, HollowPoint, Spitzkugel and Excite Apollo 5.5 mm airgun pellets from an Air Arms s410 Hi-Power Xtra FAC 5.5 mm calibre PCP air rifle. Measurements of the velocity and impact energy of the pellets as well as the extent of the bone and periosteal entry damage were taken. Statistical analysis was used to identify differences between pellets with regard to dimensions of gunshot damage to the shafts of the femur. Selected models were subjected to CT imaging.