Strokes are one of the global leading causes of physical or mental impairment and fatality, classified into hemorrhagic and ischemic strokes. Ischemic strokes happen when a thrombus blocks or plugs an artery and interrupts or reduces blood supply to the brain tissue. Deciding on the imaging modality which will be used for stroke detection depends on the expertise and availability of staff and the infrastructure of hospitals. Magnetic resonance imaging provides valuable information, and its sensitivity for smaller infarcts is greater, while computed tomography is more extensively used, since it can promptly exclude acute cerebral hemorrhages and is more favorable speed-wise. The aim of this article was to give information about the neuroimaging modalities used for the diagnosis and monitoring of ischemic strokes. We reviewed the available literature and presented the use of computed tomography, CT angiography, CT perfusion, magnetic resonance imaging, MR angiography and MR perfusion for the detection of ischemic strokes and their monitoring in different phases of stroke development.

This research addresses the respiratory distress syndrome (RDS) in preterm newborns caused by insufficient surfactant synthesis, which can lead to serious complications, including pneumothorax, pulmonary hypertension, and pulmonary hemorrhage, increasing the risk of a fatal outcome. By analyzing chest radiographs and blood gases, we specifically focus on the significant contributions of these parameters to the diagnosis and analysis of the recovery of patients with RDS. The study involved 32 preterm newborns, and the analysis of gas parameters before and after the administration of surfactants and inhalation corticosteroid therapy revealed statistically significant changes in values of parameters such as FiO₂, pH, pCO₂, HCO₃, and BE (Sig. < 0.05), while the pO₂ parameter showed a potential change (Sig. = 0.061). Parallel to this, the research emphasizes the development of a lung segmentation algorithm implemented in the MATLAB programming environment. The key steps of the algorithm include preprocessing, segmentation, and visualization for a more detailed understanding of the recovery dynamics after RDS. These algorithms have achieved promising results, with a global accuracy of 0.93 ± 0.06, precision of 0.81 ± 0.16, and an F-score of 0.82 ± 0.14. These results highlight the potential application of algorithms in the analysis and monitoring of recovery in newborns with RDS, also underscoring the need for further development of software solutions in medicine, particularly in neonatology, to enhance the diagnosis and treatment of preterm newborns with respiratory distress syndrome.

In children, the incidence of Legionnaires’ disease (LD) is unknown, hospital-acquired LD is associated with clinical risk factors and environmental risk, and children with cell-mediated immune deficiency are at high risk of infection. Both newborns were born in the same delivery room; stayed in the same hospital room where they were cared for, bathed, and breastfed; were male; were born on time, with normal birth weight, and with high Apgar score at birth; and survived this severe infection (L. pneumophila, serogroup 2-15) but with different clinical courses. In neonate 1, bleeding in the brain, thrombosis of deep pelvic veins, and necrosis of the lungs, which left behind cystic and cavernous changes in the lungs, were found, while neonate 2 suffered from pneumonia alone. The only difference in risk factors for LD between these two newborns is the number of days of illness until the start of azithromycin treatment (sixth versus the third day of illness). We suggest that a change in the guidelines for diagnosing and treating community-acquired pneumonia and hospital-acquired pneumonia in newborns is needed in terms of mandatory routine testing for Legionella pneumophila. Early initiation of macrolide therapy is crucial for the outcome of LD in the newborn.

Background and Objectives: Aneurysmal subarachnoid hemorrhage (ASAH) is defined as bleeding in the subarachnoid space caused by the rupture of a cerebral aneurysm. About 11% of people who develop ASAH die before receiving medical treatment, and 40% of patients die within four weeks of being admitted to hospital. There are limited data on single-center experiences analyzing intrahospital mortality in ASAH patients treated with an endovascular approach. Given that, we wanted to share our experience and explore the risk factors that influence intrahospital mortality in patients with ruptured intracranial aneurysms treated with endovascular coil embolization. Materials and Methods: Our study was designed as a clinical, observational, retrospective cross-sectional study. It was performed at the Department for Radiology, University Clinical Center Kragujevac in Kragujevac, Serbia. The study inclusion criteria were ≥18 years, admitted within 24 h of symptoms onset, acute SAH diagnosed on CT, aneurysm on DSA, and treated by endovascular coil embolization from January 2014 to December 2018 at our institution. Results: A total of 66 patients were included in the study—48 (72.7%) women and 18 (27.3%) men, and 19.7% of the patients died during hospitalization. After adjustment, the following factors were associated with in-hospital mortality: a delayed ischemic neurological deficit, the presence of blood in the fourth cerebral ventricle, and an elevated urea value after endovascular intervention, increasing the chances of mortality by 16.3, 12, and 12.6 times. Conclusions: Delayed cerebral ischemia and intraventricular hemorrhage on initial head CT scan are strong predictors of intrahospital mortality in ASAH patients. Also, it is important to monitor kidney function and urea levels in ASAH patients, considering that elevated urea values after endovascular aneurysm embolization have been shown to be a significant risk factor for intrahospital mortality.

Background/Objectives: Chronic idiopathic thrombocytopenic purpura (chITP) is an autoimmune disease which develops in 10–30% of patients with newly diagnosed idiopathic thrombocytopenic purpura (ndITP). It is defined as thrombocytopenia which lasts longer than 12 months, with extremely diverse clinical expressions. The aim is to present the most significant clinical and laboratory characteristics of children with chITP. Methods: This is retrospective, observational research, which included children between 2–18 years with chITP who were treated in the Republic of Serbia for 25 years. We analyzed clinical data from personal and family medical histories and different laboratory analyses. Results: The total number of respondents was 152, with female predominance (F:M = 1.27:1) and mild predominance of adolescents. Of the patients, 15% were asymptomatic, but 15% had periodically life-threatening bleeding. Transfusion was not required for 70% of patients. Thirty-five percent of patients had chITP alone, and 45% had high titer levels of autoantibodies. The most frequent comorbidity was Hashimoto thyroiditis (15%). The same percentage (45%) of family members were reported with and without autoimmune diseases. Twenty-five percent of patients were resistant to initial therapy. Helicobacter pylori was detected in 20%, 70% had higher levels of lactate dehydrogenase (LDH), three patients had sufficient serum vitamin D levels, splenomegaly was found in 25%, and accessory spleen in 14% of patients. Around 50% of patients had a platelet count between 20–50 × 10⁹/L, and 40% below 20 × 10⁹/L. Mean platelet volume (MPV) was 10.6 ± 1.4 fL. No dysplastic changes were noted in bone marrow aspirate. Initial first-line therapy was sufficient for 45% of patients, second-line therapy was administered in 25%, splenectomy was performed in 20%, and 10% received all available treatments. Conclusions: The severe clinical form of pediatric chITP is accompanied by a low platelet count, the presence of autoimmune comorbidities, a positive family medical history, resistance to initial therapy, hypovitaminosis D, and rare megakaryocytes in the bone marrow.

This study focuses on developing a model for the precise determination of ultrasound image density and classification using convolutional neural networks (CNNs) for rapid, timely, and accurate identification of hypoxic-ischemic encephalopathy (HIE). Image density is measured by comparing two regions of interest on ultrasound images of the choroid plexus and brain parenchyma using the Delta E CIE76 value. These regions are then combined and serve as input to the CNN model for classification. The classification results of images into three groups (Normal, Moderate, and Intensive) demonstrate high model efficiency, with an overall accuracy of 88.56%, precision of 90% for Normal, 85% for Moderate, and 88% for Intensive. The overall F-measure is 88.40%, indicating a successful combination of accuracy and completeness in classification. This study is significant as it enables rapid and accurate identification of hypoxic-ischemic encephalopathy in newborns, which is crucial for the timely implementation of appropriate therapeutic measures and improving long-term outcomes for these patients. The application of such advanced techniques allows medical personnel to manage treatment more efficiently, reducing the risk of complications and improving the quality of care for newborns with HIE.