Non-invasive Diagnostic Method Research Articles

Ultrasonography in gynecomastia diagnosis: Clinical experience

Aim. To analyze the applicability of ultrasonography in gynecomastia diagnosis. Materials and methods. The study included 119 males aged 18 to 74 years with complaints of a lump in the projection of the areola, and/or pain/discomfort in the breast gland area. All the patients underwent an ultrasound examination (US) of the breast. In 112 (94.05%) patients, US revealed changes typical of gynecomastia. All patients were divided into three age groups: 18–44 years (n = 99), 45–59 years (n = 15), 60–74 years (n = 5). Results. Out of 112 cases, 97 and 15 were identified as gynecomastia and pseudogynecomastia, respectively. The highest incidence of gynecomastia was observed in the first age group, with peaks at 24–26 and 30–32 years. Gynecomastia was more often defined as bilateral (67%); unilateral gynecomastia was found in 21.6% and 11.4% of cases on the left and right breast, respectively. The average diameter of the glandular disc was not statistically different in the studied groups (p > 0.05, p = 0.5), while the thickness of the glandular layer was statistically significantly different and increased with age (p ≤ 0.05). The symptoms of true gynecomastia included: in 22 cases, pain and/or discomfort in the breast; in 37 cases, an increase in size; and in 38 cases, a combination of symptoms. Subcutaneous mastectomy on both sides was performed in 21 patients. Histologically, the fibrous stage of gynecomastia predominated in 85.7% of cases (n = 18), the intermediate stage accounted for 9.5% of cases (n = 2), and the flowering stage was noted in 4.8% of cases (n = 1). The US diagnostic efficacy was determined as follows: specificity 100%, accuracy 96.3%, and sensitivity 95.45%.Conclusion. Ultrasound examination is an accessible, non-invasive, and safe diagnostic method for patients with suspected breast pathology.

Raman spectroscopy on dried blood plasma allows diagnosis and monitoring of colorectal cancer.

Colorectal cancer (CRC) remains challenging to diagnose, necessitating the identification of a noninvasive biomarker that can differentiate it from other conditions such as inflammatory bowel diseases (IBD) and diverticular disease (DD). Raman spectroscopy (RS) stands out as a promising technique for monitoring blood biochemical profiles, with the potential to identify distinct signatures identifying CRC subjects. We performed RS analysis on dried plasma from 120 subjects: 32 CRC patients, 37 IBD patients, 20 DD patients, and 31 healthy controls. We also conducted longitudinal studies of CRC patient's postsurgery to monitor the spectral changes over time. We identified six spectral features that showed significant differences between CRC and non-CRC patients, corresponding to tryptophan, tyrosine, phenylalanine, lipids, carotenoids, and disulfide bridges. These features enabled the classification of CRC patients with an accuracy of 87.5%. Moreover, longitudinal analysis revealed that the spectral differences normalized over 6 months after surgery, indicating their association with the presence of the disease. Our study demonstrates the potential of RS to identify specific biomolecular signatures related to CRC. These results suggest that RS could be a novel screening and monitoring tool, providing valuable insights for the development of noninvasive and accurate diagnostic methods for CRC.

The Degree of Branching of Serum IgG N-glycans as a Marker of Advanced Endometriosis

Endometriosis is a gynecological disease for which the diagnostics are difficult and often invasive; therefore, non-invasive diagnostic methods using sensitive and specific parameters present in easily available body fluid such as blood serum are needed for the detection of this disease. Our study aimed to answer the question of whether there are any differences between women with advanced endometriosis (AE), patients with gynecological diseases other than endometriosis (NE), and healthy women (control) in terms of the number of antennas of N-glycans from serum IgG. The degree of branching of IgG N-glycans was determined by a modified lectin ELISA with biotinylated lectin Con A (Canavalia ensiformis agglutinin) recognizing α-linked mannose, specifically reacting with biantennary N-glycans. The PHA-L/Con A ratio was calculated from the obtained N-glycan reactivities with Con A and PHA-L (Phaseolus vulgaris leucoagglutinin, specific to tri- and/or tetra-antennary N-linked glycans). The expression of Con A-reactive biantennary N-glycans in serum IgG was significantly lower in the control group than in the NE group (p = 0.045). The values of the PHA-L/Con A ratio were significantly higher in the NE group than in the AE and control groups (p = 0.019 and p = 0.022, respectively). The PHA-L/Con A ratio could be taken into account as a parameter helpful in the non-invasive diagnosis of advanced endometriosis, thus differentiating this disease from other gynecological diseases with an inflammatory background.

Machine-learning-based diabetes classification method using blood flow oscillations and Pearson correlation analysis of feature importance

Abstract Diabetes is a global health issue affecting millions of people and is related to high morbidity and mortality rates. Current diagnostic methods are primarily invasive, involving blood sampling, which can lead to infection and increased patient stress. As a result, there is a growing need for noninvasive diabetes diagnostic methods that are both accurate and fast. High measurement accuracy and fast measurement time are essential for effective noninvasive diabetes diagnosis; these can be achieved using diffuse speckle contrast analysis (DSCA) systems and artificial intelligence algorithms. In this study, we use a machine learning algorithm to analyze rat blood flow signals measured using a DSCA system with simple operation, easy fabrication, and fast measurement for helping diagnose diabetes. The results confirmed that the machine learning algorithm for analyzing blood flow oscillation data shows good potential for diabetes classification. Furthermore, analyzing the blood flow reactivity test revealed that blood flow signals can be quickly measured for diabetes classification. Finally, we evaluated the influence of each blood flow oscillation data on diabetes classification through feature importance and Pearson correlation analysis. The results of this study should provide a basis for the future development of hemodynamic-based disease diagnostic methods.

Synergizing traditional CT imaging with radiomics: a novel model for preoperative diagnosis of gastric neuroendocrine and mixed adenoneuroendocrine carcinoma.

To develop diagnostic models for differentiating gastric neuroendocrine carcinoma (g-NEC) and gastric mixed adeno-neuroendocrine carcinoma (g-MANEC) from gastric adenocarcinoma (g-ADC) based on traditional contrast enhanced CT imaging features and radiomics features. We retrospectively analyzed 90 g-(MA)NEC (g-MANEC and g-NEC) patients matched 1:1 by T-stage with 90 g-ADC patients. Traditional CT features were analyzed using univariable and multivariable logistic regression. Tumor segmentation and radiomics features extraction were performed with Slicer and PyRadiomics. Feature selection was conducted through univariable analysis, correlation analysis, LASSO, and multivariable stepwise logistic. The combined model incorporated clinical and radiomics predictors. Diagnostic performance was assessed with ROC curves and DeLong's test. The models' diagnostic efficacy was further validated in subgroup of g-NEC vs. g-ADC and g-MANEC vs. g-ADC cases. Tumor necrosis and lymph node metastasis were independent predictors for differentiating g-(MA)NEC from g-ADC (P < 0.05). The clinical model's AUC was 0.700 (training) and 0.667(validation). Five radiomics features were retained, with the radiomics model showing AUC of 0.809 (training) and 0.802 (validation). The combined model's AUCs were 0.853 (training) and 0.812 (validation), significantly outperforming the clinical model (P < 0.05). Subgroup analysis revealed that the combined model exhibited acceptable performance in differentiating g-NEC from g-ADC and g-MANEC from g-ADC, with AUCof0.887 and 0.823 in the training cohort and 0.852 and 0.762 in the validation cohort. A combined model based on traditional CT imaging and radiomic features provides a non-invasive and effective preoperative diagnostic method for differentiating g-(MA)NEC from g-ADC.

Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer.

Due to the high mortality rate, more effective non-invasive diagnostic methods are still needed for lung cancer, the most common cause of cancer-related death worldwide. In this study, the integration of Raman and Fourier-transform infrared spectroscopy with advanced data-fusion techniques is investigated to improve the detection of lung cancer from human blood plasma samples. A high statistical significance was found for important protein-related oscillations, which are crucial for differentiating between lung cancer patients and healthy controls. The use of low-level data fusion and feature selection significantly improved model accuracy and emphasizes the importance of structural protein changes in cancer detection. Although other biomolecules such as carbohydrates and nucleic acids also contributed, proteins proved to be the decisive markers found using this technique. This research highlights the power of these combined spectroscopic methods to develop a non-invasive diagnostic tool for discriminating lung cancer from healthy state, with the potential to extend such studies to a variety of other diseases.

Metal Organic Frameworks Based Wearable and Point-of-Care Electrochemical Sensors for Healthcare Monitoring.

The modern healthcare system strives to provide patients with more comfortable and less invasive experiences, focusing on noninvasive and painless diagnostic and treatment methods. A key priority is the early diagnosis of life-threatening diseases, which can significantly improve patient outcomes by enabling treatment at earlier stages. While most patients must undergo diagnostic procedures before beginning treatment, many existing methods are invasive, time-consuming, and inconvenient. To address these challenges, electrochemical-based wearable and point-of-care (PoC) sensing devices have emerged, playing a crucial role in the noninvasive, continuous, periodic, and remote monitoring of key biomarkers. Due to their numerous advantages, several wearable and PoC devices have been developed. In this focused review, we explore the advancements in metal-organic frameworks (MOFs)-based wearable and PoC devices. MOFs are porous crystalline materials that are cost-effective, biocompatible, and can be synthesized sustainably on a large scale, making them promising candidates for sensor development. However, research on MOF-based wearable and PoC sensors remains limited, and no comprehensive review has yet to synthesize the existing knowledge in this area. This review aims to fill that gap by emphasizing the design of materials, fabrication methodologies, sensing mechanisms, device construction, and real-world applicability of these sensors. Additionally, we underscore the importance and potential of MOF-based wearable and PoC sensors for advancing healthcare technologies. In conclusion, this review sheds light on the current state of the art, the challenges faced, and the opportunities ahead in MOF-based wearable and PoC sensing technologies.

Machine learning models for diagnosing Alzheimer's disease using brain cortical complexity.

This study aimed to develop and validate machine learning models (MLMs) to diagnose Alzheimer's disease (AD) using cortical complexity indicated by fractal dimension (FD). A total of 296 participants with normal cognitive (NC) function and 182 with AD from the AD Neuroimaging Initiative database were randomly divided into training and internal validation cohorts. Then, FDs, demographic characteristics, baseline global cognitive function scales [Montreal Cognitive Assessment (MoCA), Functional Activities Questionnaire (FAQ), Global Deterioration Scale (GDS), Neuropsychiatric Inventory (NPI)], phospho-tau (p-tau 181), amyloidβ-42/40, apolipoprotein E (APOE) and polygenic hazard score (PHS) were collected to establish multiple MLMs. Receiver operating characteristic curves were used to evaluate model performance. Participants from our institution (n = 66; 33 with NC and 33 with AD) served as external validation cohorts to validate the MLMs. Decision curve analysis was used to estimate the models' clinical values. The FDs from 30 out of 69 regions showed significant alteration. All MLMs were conducted based on the 30 significantly different FDs. The FD model had good accuracy in predicting AD in three cohorts [area under the receiver operating characteristic (ROC) curve (AUC) = 0.842, 0.808, and 0.803]. There were no statistically significant differences in AUC values between the FD model and the other combined models in the training and internal validation cohorts except MoCA + FD and FAQ + FD models. Among MLMs, the MoCA + FD model showed the best predictive efficiency in three cohorts (AUC = 0.951, 0.931, and 0.955) and had the highest clinical net benefit. The FD model showed favorable diagnostic performance for AD. Among MLMs, the MoCA + FD model can predict AD with the highest efficiency and could be used as a non-invasive diagnostic method.

Role of Magnetic Resonance Spectroscopy and Diffusion-weighted Imaging in the Evaluation of Supratentorial Brain Tumours with Histopathology Correlation at a Tertiary Care Hospital: An Observational Study

Abstract Background: Traditional magnetic resonance imaging (MRI) may face challenges in accurately discerning supratentorial malignancies. However, advanced techniques such as diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) have significantly enhanced diagnostic accuracy. Thus, the study aimed to evaluate the effectiveness of these non-invasive diagnostic methods in patients with suspected intracranial lesions. Materials and Methods: In this prospective observational study at Osmania General and Allied Hospitals, 40 eligible patients were enrolled. After applying the inclusion and exclusion criteria, MRI examinations were conducted at two hospitals utilising GE 1.5T and PHILIPS 1.5T 32-channel machines. Standardised brain sequences, encompassing T1- and T2-weighted scans, DWI, gradient-recalled echo and fluid-attenuated inversion recovery imaging, were systematically performed. In addition, post-contrast administration and contrast-enhanced MRS were employed. Results: In this study, a higher tumour incidence was observed in males (52%) compared to females (48%). The choline/creatine (CHO/Cr) ratio revealed more cases below 1.5 and fewer at the 3.1–3.5 level. Perilesional CHO/Cr ratio had the highest cases (21) at 1.1–2.0 and the lowest (2) at 3.1–4.0. Further analysis revealed significant differences in the mean CHO/Cr ratio amongst primary low-grade (1.8), primary high-grade (3.91) and metastatic tumours (7.23). The mean choline/N-acetyl aspartate (NAA) ratio also differed significantly amongst these tumour types, with choline/NAA and CHO/Cr ratios indicating statistical significance in distinguishing primary low-grade tumours. In addition, mean apparent diffusion coefficient values showed significant differences between primary low-grade tumours (1.1), primary high-grade tumours (0.87) and metastasis (0.855). Conclusion: This study underscores gender-related differences in supratentorial tumour susceptibility and highlights distinct tumour distributions based on grades. These findings emphasise the significance of considering gender, age and histopathological attributes when evaluating supratentorial tumours.

7864 Accurate Machine Learning-Based Diagnosis of At-Risk MASH and MASLD Subtypes Using Categorical Gradient Boosting and Select Clinical, Biochemical, and Metabolomic Measurements: Building Highly Robust Models With Few Variables Through a Multinational, Multi-Center, Biopsy-Proven Cohort

Abstract Disclosure: K. Stefanakis: None. E. Axarloglou: None. C.S. Mantzoros: None. Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by intrahepatic lipid accumulation, may precipitate steatohepatitis (MASH) and liver fibrosis, and is a significant cardiometabolic risk factor. Liver biopsy, though invasive and costly, is the diagnostic gold standard, thus creating an unmet clinical need for accurate and reliable non-invasive diagnostic methods to diagnose MASLD, particularly the combination of MASH and significant fibrosis, classified as “at-risk MASH” and known to markedly increase morbidity and mortality. We aimed to leverage novel machine-learning (ML) algorithms to create lightweight but highly precise models that may accurately diagnose at-risk MASH and related histological outcomes through a top-down approach. This is a study of 443 participants from two Gastroenterology-Hepatology Clinics (Greece, Australia) and one Metabolic Surgery Clinic (Italy), including healthy controls and MASLD patients across the entire spectrum of the disease. All participants underwent liver biopsies, anthropometric, standard biochemical and additional hormonal measurements, and global serum metabolomics using ultra-high-performance liquid chromatography-tandem mass spectrometry, followed by robust batch correction and quality control, eventually identifying 687 known and 152 unknown metabolites. The dataset was randomly divided into a discovery (n=353) and a validation cohort (n=90) ensuring a balanced distribution of at-risk MASH and clinic. Our main ML pipeline implemented Categorical Gradient Boosting Machines using the CatBoost package for R. We pre-specified domain knowledge variables and implemented recursive feature elimination, among additional techniques, to build models through an iterative, algorithm-based process. The models were tested in the validation and entire cohort using k-fold and leave-one-out cross-validation with random resampling, and further assessed on relevant subgroups (MASLD status, obesity, diabetes, clinic, country). The main ML model consists of three routine clinical and biochemical variables, supplemented by two aminoacid metabolites (full model to be shown), and can detect the presence of at-risk MASH with a mean AUROC of 93% and mean accuracy of 92% in the validation cohort, and AUCS&amp;gt;93% with very high sensitivities and specificities per J-statistic in all subgroups. We likewise present ML models for the detection of MASLD, MASH, and fibrosis grades, with AUCs of over 90% in the validation cohort and all subgroups. Our models significantly outperform all applicable biomarker-based indices per DeLong’s tests. Further enhancement with lipidomic and proteomic variables will fully delineate the circulating biochemical snapshot of MASLD and likely lead to even more accurate, similarly structured models. Presentation: 6/1/2024

Endometriosis-Associated Infertility: The Role of Biomarkers of Apoptosis and Proliferation in Early Noninvasive Diagnosis

INTRODUCTION: Endometriosis is a common disease that affects up to 15% of women in the reproductive period and leads to infertility in 25%–50% of cases. The diagnosis of endometriosis is delayed for years due to blurred and diverse clinical presentation, therefore, search for a noninvasive biomarker of endometriosis is an important problem of modern medicine. AIM: To study the significance of changes in the profile of biomarkers: regulator of Wnt/β-catenin signaling pathway (axis inhibition protein 1; AXIN-1), soluble cytokeratin 19 fragment (cytokeratin fragment antigen 21-1; CYFRA-21-1), cancer antigen 125 (carbohydrate antigen 125; CA-125) in blood plasma of patients with endometriosis-associated infertility (before surgery and in the postoperative period). MATERIALS AND METHODS: The study included two groups of female patients. The first group consisted of 20 patients of reproductive age with cystic ovarian endometriosis and infertility. All the patients underwent surgical intervention using a laparoscope and a video system, in all the patients the diagnosis of endometriosis was confirmed histologically. Three times in specified periods (before surgery, on the 10th day of the postoperative period, at 6 months), patients with cystic ovarian endometriosis and infertility were taken biomaterial (blood) with further determination of AXIN-1, CYFRA-21-1, CA-125 in blood plasma. The second group consisted of patients of reproductive age with no gynecological pathology. In the second group, biological material (blood) was taken once with further determination of AXIN-1, CYFRA-21-1, CA-125 in blood plasma. RESULTS: Based on the analysis of the measurement data and comparison of their levels, it was found that the content of the studied AXIN-1, СA-125 biomarkers in patients with cystic ovarian endometriosis and infertility was higher than in patients without gynecological pathology (p 0.05). As for CYFRA-21-1 biomarker, initially lower values were noted compared to the control group (p 0.05), however, in the postoperative period, the content of CYFRA-21-1 increased and reached values close to those of healthy patients. CONCLUSION: Determining the levels of AXIN-1, CYFRA-21-1 apoptosis biomarkers and CA-125 proliferation biomarker in blood of patients with endometriosis-associated infertility gives an insight into the pathophysiological processes in the endometrioid ovarian cysts and may be helpful in development of new noninvasive diagnostic methods and target treatment methods.

A novel method of cardia visualization and comfort level enhancement during magnetic capsule gastroscopy via sugar-glued tether-assisted technique: a randomized pilot study inspired by a Chinese snack-making process (with video).

Magnetic capsule gastroscopy (MCG) is a non-invasive diagnostic method for the digestive tract. However, its efficiency in visualizing the gastric cardia is often compromised due to the capsule's rapid passage. This study introduces a novel sugar-glued tether-assisted technique inspired by a traditional Chinese snack-making process to enhance cardia visualization and patient comfort during MCG. This pilot, open-label, single-center, randomized controlled, non-inferiority study was conducted at Binzhou Medical University Hospital. Seventy-eight patients were enrolled and divided into three groups: conventional MCG, suction cup tether-assisted MCG, and sugar-glued tether-assisted MCG. The primary outcomes included safety, comfort level, and gastric cardia visualization quality. Secondary outcomes assessed technique-associated performance and clinical factors. The sugar-glued tether-assisted MCG demonstrated comparable cardia visualization quality to the suction cup method, with significantly better results than conventional MCG. Comfort levels were significantly higher in the sugar-glued group compared to the suction cup group. The number of swallow attempts was significantly lower in the sugar-glued group, with no adverse events reported. Secondary outcomes showed no significant differences in MCG assembly time and ingestion-to-detachment period between the suction cup and sugar-glued groups. The sugar-glued tether-assisted MCG is a feasible and safe modification that enhances gastric cardia visualization while improving patient comfort. This technique provides a cost-effective alternative to the suction cup method, warranting further investigation in larger, multi-center studies.

Benign breast tumors may arise on different immunological backgrounds.

Benign breast tumors are a nonthreatening condition defined as abnormal cell growth within the breast without the ability to invade nearby tissue. However, benign lesions hold valuable biological information that can lead us toward better understanding of tumor biology. In this study, we have used two pathway analysis algorithms, Pathifier and gene set variation analysis (GSVA), to identify biological differences between normal breast tissue, benign tumors and malignant tumors in our clinical dataset. Our results revealed that one-third of all pathways that were significantly different between benign and malignant tumors were immune-related pathways, and 227 of them were validated by both methods and in the METABRIC dataset. Furthermore, five of these pathways (all including genes involved in cytokine and interferon signaling) were related to overall survival in cancer patients in both datasets. The cellular moieties that contribute to immune differences in malignant and benign tumors were analyzed using the deconvolution tool, CIBERSORT. The results showed that levels of some immune cells were specifically higher in benign than in malignant tumors, and this was especially the case for resting dendritic cells and follicular T-helper cells. Understanding the distinct immune profiles of benign and malignant breast tumors may aid in developing noninvasive diagnostic methods to differentiate between them in the future.

Estimation of Blood Calcium and Potassium Values from ECG Records

Abstract The identification of diseases caused by changes in ion concentration is quite difficult and yet plays a decisive role in the success of clinical care, diagnosis and treatment. The clinically proven approach to diagnosing electrolyte concentration imbalance is blood tests. There is a need to provide a non-invasive diagnostic method that is not of a temporary nature. Bio-signals such as the electrocardiogram (ECG) can be used to meet this demand and become diagnostic tools that facilitate home monitoring of electrolyte concentration on a permanent basis. This study investigates the feasibility and efficiency of methods based on machine learning (ML) and ECG recordings in monitoring critical levels of existing potassium and calcium concentration. Morphological, frequency and frequency-time domain features were extracted to automatically estimate calcium and potassium levels. Furthermore, the potential of estimates based on modeling approaches will be demonstrated to gain insights into relevant clinical findings and improve the performance of monitoring approaches. Using the hold-out validation method, the best results in terms of mean square error (MSE) and R for estimating the calcium value are 0.7157 and 0.57347, using fuzzy inference systems (FIS). Here, R represents the proportion of the variance in the calcium value that is explained by the model.

Salivary cysteine levels as a potential biochemical indicator of oral cancer risk in tobacco consumers.

Aim: Oral cancer is the leading cause of mortality, with a survival rate of less than 5 years, and is predominantly influenced by tobacco mutagens. Invasive diagnostic methods hinder early detection of oral cancer biomarkers. The present study performed salivary biochemical analysis for early oral cancer screening in tobacco consumers.Materials & methods: Three study groups included healthy controls (n=25), tobacco users (n=25) and oral cancer patients (n=25). Salivary total protein, amylase, TNF-α and amino acid levels were evaluated using enzymatic tests, Enzyme linked Immunosorbent Assay (ELISA) and High-Performance Liquid Chromatography (HPLC).Results: Compared with healthy controls, salivary total protein and TNF-αlevels were significantly (p=0.04) higher in oral cancer patients. Salivary amylase levels were significantly lower in tobacco smokers (p=0.02) and higher in oral cancer patients (p=0.01). Interestingly, the amino acid cysteine concentration was significantly higher (p=0.02) in tobacco consumers (62.5±10) than in healthy controls (116.1±28).Conclusion: In high-risk populations, such as tobacco users, salivary biochemical analysis can serve as a promising noninvasive diagnostic method for early oral cancer screening. As a salivary biomarker, the amino acid cysteine exhibits potential as a means of detecting the progression of oral cancer in individuals who consume tobacco.

Early detection of monkeypox: Analysis and optimization of pretrained deep learning models using the Sparrow Search Algorithm

The global spread of monkeypox across over 40 countries is a major health challenge. Its symptoms resemble those of chickenpox and measles, complicating early diagnosis. When PCR tests are unavailable, computational lesion detection offers a promising option. This research presents a non-invasive diagnostic method using the Sparrow Search Algorithm (SpaSA). SpaSA is applied to improve accuracy in medical imaging tasks. Deep learning, especially CNNs, effectively addresses challenges in medical imaging. By combining CNNs with optimization, we analyze large imaging datasets. This study evaluates several pre-trained models on two datasets: “Monkeypox 2022” and “Images of Monkeypox.” The method classifies patients as either “normal” or “pox” (including monkeypox, chickenpox, smallpox, cowpox, and measles). The novelty lies in using SpaSA to optimize pre-trained CNNs' performance. The Xception model achieves 97.66% accuracy without optimization. SpaSA enhances VGG19's performance, reaching 99.87% accuracy. With SpaSA, VGG19 reached 99.87% accuracy in 120 seconds. SpaSA had the fastest time (120s) and lowest failure rate (5%). It outperformed Grid Search, Random Search, Bayesian Optimization, WOA, GA, PSO, and ACO. This shows mathematical optimization's impact on medical imaging. It sets new standards in healthcare diagnostics using SpaSA and CNNs. This research shows the significant role of optimization in improving medical imaging. It sets new standards for healthcare diagnostics using SpaSA and CNNs.

Combining Multiple Spectroscopic Techniques to Reveal the Effects of Staphylococcus aureus Infection on Human Bone Tissues.

Osteomyelitis (OM) and periprosthetic joint infections (PJIs) are major public health concerns in Western countries due to increased life expectancy. Infections usually occur due to bacterial spread through fractures, implants, or blood-borne transmission. The pathogens trigger an inflammatory response that hinders bone tissue regeneration. Treatment requires surgical intervention, which involves the precise removal of infected tissue, wound cleansing, and local and systemic antibiotic administration. Staphylococcus aureus (SA) is one of the most common pathogens causing infection-induced OM and PJIs. It forms antimicrobial-resistant biofilms and is frequently found in healthcare settings. In this proof-of-concept, we present an approach based on multiple spectroscopic techniques aimed at investigating the effects of SA infection on bone tissue, as well as identifying specific markers useful to detect early bacterial colonization on the tissue surface. A cross-section of a human femoral diaphysis, with negative-culture results, was divided into three parts, and the cortical and trabecular regions were separated from each other. Two portions of each bone tissue type were infected with SA for one and seven days, respectively. Multiple techniques were used to investigate the impact of the infection on bone tissue, Brillouin-Raman microspectroscopy and attenuated total reflection Fourier transform infrared spectroscopy were employed to assess and develop a new noninvasive diagnostic method to detect SA by targeting the bone of the host. The results indicate that exposure to SA infection significantly alters the bone structure, especially in the case of the trabecular type, even after just one day. Moreover, Raman spectral markers of the tissue damage were identified, indicating that this technique can detect the effect of the pathogens' presence in bone biopsies and pave the way for potential application during surgery, due to its nondestructive and contactless nature.

Ulcerative colitis and concomitant arterial hypertension (literature review)

ulcerative colitis is a complex disease that results from a complex interaction of genetic predisposition, environmental factors, which leads to dysregulation of the immune system, chronic intestinal inflammation with damage to the mucous membrane. Systemic chronic inflammation can cause the development of arterial hypertension, thereby complicating the course of the primary disease. However, the cause-and-effect relationship between these diseases is not fully understood. Early detection of high blood pressure in patients with ulcerative colitis, a multidisciplinary approach to diagnosis makes it possible to achieve optimal treatment results in a timely manner and prevent the occurrence of intestinal complications. The aim of this study was to provide a comprehensive review of diagnostic procedures such as colonoscopy, inflammatory biomarkers (faecal calprotectin, faecal lactoferrin, serum zonulin), and to study the features of the colon structure in ultrasound diagnostics in patients with ulcerative colitis and concomitant hypertension. The data from PubMed and Ukrainian scientific sources on the comorbidity of these diseases, the possibility of using non-invasive diagnostic methods to assess the condition of the intestine in patients with ulcerative colitis and arterial hypertension were analysed. The literature review includes 50 scientific sources. The main focus is on the pathophysiological relationships of diseases, peculiarities of non-invasive diagnosis of ulcerative colitis during follow-up and early detection of arterial hypertension, which makes it possible to prevent complications in ulcerative colitis. Given the literature review, it can be concluded that the problem of timely diagnosis of hypertension in patients with ulcerative colitis is relevant today. For a rational approach to the management of patients with ulcerative colitis and concomitant hypertension, it is necessary to carry out a set of diagnostic procedures, including outpatient blood pressure measurement, ultrasound examination of the intestinal wall, and the use of non-invasive inflammatory biomarkers.

Radiation dose in cardiac CT for preoperative diagnosis of children with congenital heart disease

BackgroundOne of the most common congenital conditions detected globally, congenital heart diseases, and CT techniques provide a high-quality and thorough presentation of heart anatomy, thoracic vasculature, and extracardiac structures, and hence, it is becoming a more popular non-invasive diagnostic imaging method for congenital heart disease. The drawbacks with CT imaging are the radiation exposure from repeated scans is also rising, especially in young patients. The present study is aimed to evaluate the radiation dose in gated and non-gated cardiac CT for preoperative diagnosis of pediatric patients with congenital heart diseases.ResultsA total of 111 pediatric patients with mean age of 7.47 years were prospectively included in the study. 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The average value of “E” for non-gated technique was observed less than that of gated technique at both 100kVp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$100\\;{\ ext{kV}}_{{\ ext{p}}}$$\\end{document} and 80kVp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$80\\;{\ ext{kV}}_{{\ ext{p}}}$$\\end{document}. The multiple regression analysis shows that “E” is significantly dependent on DLPmGycm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{DLP}}\\left( {{\ ext{mGy}}\\;{\ ext{cm}}} \\right)$$\\end{document} for both gated and non-gated techniques at 95% level of significance p<0.05\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left( {p < 0.05} \\right)$$\\end{document}. The Student’s t-test verifies that the mean value of “E” for both the techniques at 100kVp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$100\\;{\ ext{kV}}_{{\ ext{p}}}$$\\end{document} and 80kVp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$80\\;{\ ext{kV}}_{{\ ext{p}}}$$\\end{document} are significantly different at 95% level of significance p<0.05\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left( {p < 0.05} \\right)$$\\end{document}.ConclusionsThe effective dose received by pediatric patients is much higher when using ECG-gated acquisition with an average value of 4.71mSv\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$4.71\\;{\ ext{mSv}}$$\\end{document} and 3.95mSv\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$3.95\\;{\ ext{mSv}}$$\\end{document} at 100kVp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$100\\;{\ ext{kV}}_{{\ ext{p}}}$$\\end{document}, and at 80kVp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$80\\;{\ ext{kV}}_{{\ ext{p}}}$$\\end{document} respectively. Because low-voltage X-rays are more sensitive to high atomic number iodinated contrast media, the mean “E” for non-gated cardiac CT imaging at 80kVp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$80\\;{\ ext{kV}}_{{\ ext{p}}}$$\\end{document} is 2.26mSv\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2.26\\;{\ ext{mSv}}$$\\end{document}, and results in significant reduction of effective dose.

Biochemical Modulators of Tight Junctions (TJs): Occludin, Claudin-2 and Zonulin as Biomarkers of Intestinal Barrier Leakage in the Diagnosis and Assessment of Inflammatory Bowel Disease Progression.

Considering the increasing worldwide prevalence of inflammatory bowel disease (IBD), the early diagnosis of this disease is extremely important. However, non-invasive diagnostic methods remain limited, while invasive techniques are the most commonly used in daily practice. Therefore, there is a serious need to find new non-invasive biomarkers of IBD. The serum profiles of occludin, claudin-2, and zonulin were assessed in IBD patients using the ELISA method. The levels of the analyzed biomarkers were measured before and after a year of anti-inflammatory treatment, which was a tumor necrosis factor α (TNF-α) inhibitor (adalimumab) in patients with ulcerative colitis (UC) and conventional therapy in patients with Crohn's disease (CD). In IBD patients, the serum level of occludin (p < 0.001) decreased compared to healthy individuals, while the level of claudin-2 (p < 0.001) increased. Additionally, zonulin (p < 0.01) concentration increased in CD patients compared to the control group. The highest diagnostic ability was presented by occludin measurements with the area under the curve (AUC) of 0.959 (95% CI 0.907-1) in UC and 0.948 (95% CI 0.879-1) in CD. Claudin-2 also demonstrated very good ability in diagnosing UC and CD with AUC values of 0.864 (95% CI 0.776-0.952) and 0.896 (95% CI 0.792-0.999), respectively. The ability of zonulin to diagnose CD was estimated as good with an AUC of 0.74 (95% CI 0.598-0.881). Moreover, a significant correlation was identified between C-reactive protein (CRP), claudin-2 (r = -0.37; p < 0.05), and zonulin (r = -0.44; p < 0.05) in UC patients. Treatment with adalimumab improved the level of occludin, claudin-2, and zonulin in UC patients, while anti-inflammatory conventional therapy decreased the concentration of zonulin in CD. Occludin and claudin-2 measurements present significant utility in diagnosing both UC and CD, while zonulin assessments may be useful in CD diagnosis. Additionally, claudin-2 and zonulin measurements may be helpful in evaluating the intensity of the inflammatory process. Anti-TNF-α treatment improved the value of occludin, claudin-2, and zonulin, indicating its beneficial effect on the integrity of tight junctions in UC.