Search

Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) that mainly affects developed countries, but the number of cases in developing countries is increasing. We conducted a narrative review on the potential application of ultrasound elastography in the diagnosis and monitoring of UC, as this newly emerging method has promising results in other gut diseases. This review fulfilled the PRISMA Statement criteria with a time cut-off of June 2022. At the end of the review, of the 1334 identified studies, only five fulfilled all the inclusion criteria. Due to the small number of studies in this field, a reliable assessment of the usefulness of ultrasound elastography is difficult. We can only conclude that the transabdominal elastography examination did not significantly differ from the standard gastrointestinal ultrasonography examination and that measurements of the frontal intestinal wall should be made in the longitudinal section. The reports suggest that it is impossible to estimate the clinical scales used in disease assessment solely on the basis of elastographic measurements. Due to the different inclusion criteria, measurement methodologies, and elastographic techniques used in the analysed studies, a reliable comparative evaluation was impossible. Further work is required to assess the validity of expanding gastrointestinal ultrasonography with elastography in the diagnosis and monitoring of UC. [ABSTRACT FROM AUTHOR]

Background: In accordance with the European guidelines on rhinosinusitis and nasal polyps (EPOS 2012), CT is used as the main imaging modality for the assessment intensity of inflammatory lesions. The aim of this study was to measure the differences in the assessment of inflammatory changes in the paranasal sinuses due to different parameters of width (W) and length (L) of the CT window. Material/Methods: A retrospective analysis included 44 CT scans of the paranasal sinuses that were performed in adults. All studies were characterized by the presence of inflammatory changes in at least one of the sinuses. Measurements of the same inflammatory lesions were performed sequentially with different CT windows. The results were statistically analyzed. Results: A statistically significant difference was observed between the average measurements that were performed with the use CT windows dedicated for the sinuses and head. A downward trend in the measured values and a shift towards soft tissue values was observed with decreasing window parameters. Conclusions: A major cause of inaccurate examinations of pathological changes in the paranasal sinuses may be due to selection of unsuitable CT windows. Therefore, in order to avoid missing inflammatory lesions in the paranasal sinuses, it is reasonable to use CT windows dedicated for the sinuses or bones. [ABSTRACT FROM AUTHOR]

In recent years, deep neural networks have enabled countless innovations in the field of image classification. Encouraged by success in this field, researchers worldwide have demonstrated how to use Convolutional Neural Network techniques in medical imaging problems. In this article, the results were obtained through the use of the EfficientNet in the task of classifying 14 different diseases based on chest X-ray images coming from the NIH (National Institutes of Health) ChestX-ray14 dataset. The approach addresses dataset imbalances by introducing a custom split to ensure fair representation. Binary cross entropy loss is utilized to handle the multi-label difficulty. The model architecture comprises an EfficientNet backbone for feature extraction, succeeded by sequential layers including GlobalAveragePooling, Dense, and BatchNormalization. The main contribution of this paper is a proposed solution that outperforms previous state-of-the-art deep learning models average area under the receiver operating characteristic curve—AUC-ROC (score: 84.28%). The usage of the transfer-learning technique and traditional deep learning engineering techniques was shown to enable us to obtain such results on consumer-class GPUs (graphics processing units). [ABSTRACT FROM AUTHOR]

Diagnostic imaging has become an integral part of the healthcare system. In recent years, scientists around the world have been working on artificial intelligence-based tools that help in achieving better and faster diagnoses. Their accuracy is crucial for successful treatment, especially for imaging diagnostics. This study used a deep convolutional neural network to detect four categories of objects on digital chest X-ray images. The data were obtained from the publicly available National Institutes of Health (NIH) Chest X-ray (CXR) Dataset. In total, 112,120 CXRs from 30,805 patients were manually checked for foreign objects: vascular port, shoulder endoprosthesis, necklace, and implantable cardioverter-defibrillator (ICD). Then, they were annotated with the use of a computer program, and the necessary image preprocessing was performed, such as resizing, normalization, and cropping. The object detection model was trained using the You Only Look Once v8 architecture and the Ultralytics framework. The results showed not only that the obtained average precision of foreign object detection on the CXR was 0.815 but also that the model can be useful in detecting foreign objects on the CXR images. Models of this type may be used as a tool for specialists, in particular, with the growing popularity of radiology comes an increasing workload. We are optimistic that it could accelerate and facilitate the work to provide a faster diagnosis. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic, which affected the entire global population, had an impact on our health and quality of life. Many people had complications, were hospitalised or even died due to SARS-CoV-2 infection. The health systems of many countries had to radically change their way of functioning and scientists around the world worked intensively to develop a vaccine for the SARS-CoV-2 virus. Aim: The aim of this work is to assess the quality of life of patients who were hospitalised for COVID-19, using the SF-36 questionnaire. Methods: Between May and August 2022, we conducted a telephone assessment of quality of life in patients who were hospitalised for COVID-19 at the Temporary Hospital in Pyrzowice (Silesia, Poland), between November 2021 and January 2022. Results: Quality of life was significantly lower in women (p = 0.040), those with DM2 (p = 0.013), CKD (p = 0.041) and the vaccinated (p = 0.015). Conclusions: People with chronic kidney disease, diabetes mellitus and women had a lower quality of life after COVID-19 disease. However, people who were vaccinated for SARS-CoV-2 had a lower quality of life than non-vaccinated people did. This is possibly due to the higher mean age, and probably the higher disease burden, in the vaccinated group. [ABSTRACT FROM AUTHOR]

Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all topics that fall under the heading of artificial intelligence (AI) and have gained popularity in recent years. ML involves the application of algorithms to automate decision-making processes using models that have not been manually programmed but have been trained on data. ANNs that are a part of ML aim to simulate the structure and function of the human brain. DL, on the other hand, uses multiple layers of interconnected neurons. This enables the processing and analysis of large and complex databases. In medicine, these techniques are being introduced to improve the speed and efficiency of disease diagnosis and treatment. Each of the AI techniques presented in the paper is supported with an example of a possible medical application. Given the rapid development of technology, the use of AI in medicine shows promising results in the context of patient care. It is particularly important to keep a close eye on this issue and conduct further research in order to fully explore the potential of ML, ANNs, and DL, and bring further applications into clinical use in the future. [ABSTRACT FROM AUTHOR]

Background: Inter-recti distance (IRD) measurement using musculoskeletal USI has been used in physiotherapy research, in particular, to investigate pregnancy-related diastasis recti abdominis (DRA) and to seek its effective treatment methods. Severe and untreated diastasis may result in the formation of umbilical or epigastric hernias. Objective: This study aimed to systematically map physiotherapy-related research articles that included descriptions of IRD measurement procedures using USI to present their similarities and differences, and formulate recommendations on the procedure. Design: A scoping review was conducted according to PRISMA-ScR guidelines, including 49 of 511 publications from three major databases. Publications were selected and screened by two independent reviewers whose decisions were consulted with a third reviewer. The main synthesized data items were: the examinees' body position, breathing phase, measurement sites, and DRA screening methods. The final conclusions and recommendations were the result of a consensus between seven reviewers from four research centers. Results: Studies used 1–5 measurement sites that were differently determined. IRD was measured at the umbilicus (n = 3), at its superior (n = 16) and/or inferior border (n = 9), and at different levels: between 2 and 12 cm above the umbilicus, or a third of the distance and halfway between the umbilicus and xiphoid (n = 37); between 2 and 4.5 cm below the umbilicus or halfway between the umbilicus and pubis (n = 27). Different approaches were used to screen subjects for DRA. Conclusions: The discrepancies between the measurement procedures prevent between-study comparisons. The DRA screening method should be standardized. IRD measurement protocol standardization has been proposed. Critical relevance statement: This scoping review indicates that the inter-recti distance measurement procedures using ultrasound imaging differ between studies, preventing between-study comparisons. Based on the results synthesis, the measurement protocol standardization has been proposed. Key points: The inter-recti distance measurement procedures using USI differ between studies. Proposed standardization concerns body position, breathing phase, measurements number per location. Determination of measurement locations considering individual linea alba length is suggested. Recommended locations: umbilical top, ½ of umbilical top-xiphoid, ¼ of umbilical top-xiphoid/pubis distances. Diastasis recti abdominis diagnostic criteria are needed for proposed measurement locations. [ABSTRACT FROM AUTHOR]

Epilepsy is one of the most frequent serious brain disorders. Approximately 30,000 of the 150,000 children and adolescents who experience unprovoked seizures are diagnosed with epilepsy each year. Magnetic resonance imaging is the method of choice in diagnosing and monitoring patients with this condition. However, one very effective tool using MR images is volBrain software, which automatically generates information about the volume of brain structures. A total of 57 consecutive patients (study group) suffering from epilepsy and 34 healthy patients (control group) who underwent MR examination qualified for the study. Images were then evaluated by volBrain. Results showed atrophy of the brain and particular structures—GM, cerebrum, cerebellum, brainstem, putamen, thalamus, hippocampus and nucleus accumbens volume. Moreover, the statistically significant difference in the volume between the study and the control group was found for brain, lateral ventricle and putamen. A volumetric analysis of the CNS in children with epilepsy confirms a decrease in the volume of brain tissue. A volumetric assessment of brain structures based on MR data has the potential to be a useful diagnostic tool in children with epilepsy and can be implemented in clinical work; however, further studies are necessary to enhance the effectiveness of this software. [ABSTRACT FROM AUTHOR]

Background. Complications of cystic fibrosis-associated liver disease (CFLD) are a leading nonpulmonary cause of death. Noninvasive tests enabling early detection of liver changes, especially in children are sought. The aim of the study was to assess the scale of liver fibrosis with the use of elastography in paediatric patients with diagnosed cystic fibrosis (CF) and its comparison with other tests (APRI and Fibrotest). Methods. We examined 41 children, in the age range 2-21 years, with diagnosed CF. The analysis a included clinical picture, laboratory parameters of liver damage, and cholestasis. Aspartate aminotransferase-to-platelet ratio index (APRI) and Fibrotest were done in all patients. Liver stiffness measurements were acquired using shear-wave elastography (SWE). Results. CFLD was diagnosed in 16/41 patients (39%). Abnormal elastography was observed in 19/41 patients (46.3%), and in 5/41 (12.2%), the changes were advanced (F4). Abnormal elastography was observed in 12/16 (75%) of the patients with CFLD, and in 7/25 (28%), there were no lesions observed in the liver in the course of cystic fibrosis. In all patients with F4, we observed abnormal results of the APRI and Fibrotest. In most patients with small changes in elastography, we found normal results of the APRI and Fibrotest. Conclusion. Elastography seems to be a noninvasive examination useful in everyday clinical work in detecting early liver changes and monitoring of progression in paediatric patients with diagnosed cystic fibrosis, ahead of changes in laboratory tests. The cost-effectiveness of this test, the possibility of its repetition, and its availability are additional benefits. [ABSTRACT FROM AUTHOR]

One modern imaging technique used in the diagnosis of Crohn's disease (CD) is sonoelastrography of the intestine. Guidelines regarding the use of bowel sonoelastography in CD have still not been specified. The aim of our research was to conduct a systematic review of the use of sonoelastography in the diagnosis, assessment, and monitoring of strictures in the course of CD. A systematic review was conducted according to the PRISMA guidelines statement. The following databases were searched in January 2021: MEDINE via PubMed, Embase and Scopus. The search utilised the following MeSH tags: 'Ultrasound Shear Wave', 'Elastography', 'elastogram', 'elastographies' AND 'Crohn disease'. The inclusion criteria were as follows: from 2010 or later, articles with abstracts, articles in English, human-based studies and original articles. Articles were assessed independently by two reviewers. Out of 181 articles, only 15 met the criteria and were included in the review. Due to a small number of studies and significant methodological differences, the feasibility of using sonoelastography for Crohn's disease must be proven through further research and analysis. In the future, standardised assessment criteria and cut-off points should be established for both strain elastography (SE) and shear wave elastography (SWE). [ABSTRACT FROM AUTHOR]