Non-invasive Method For Assessment Research Articles

Study of age-related retinal hemodynamic changes by laser speckle flowgraphy

Background: Diagnostics of hemodynamic changes is important both for clarifying the features of the course of pathological process of many ophthalmic diseases and for optimizing treatment tactics. Laser speckle flowgraphy (LSFG) is a new non-invasive method for quantitative assessment of retinal blood flow. Aim: To study age-related changes of pulse waves both in large blood vessels and microvasculature in the optic nerve head and macula by laser speckle flowgraphy. Materials and methods: Age-related changes in blood flow were studied in 60 healthy volunteers using LSFG-RetFlow. We analyzed MBR — main parameter of pulse wave assessed by the laser speckle flowgraphy and also another 8 pulse wave parameters for large vessels and microvasculature in the areas of optic nerve head and macula. Results: The study revealed statistically significant (p ≤ 0.05) age-related changes in pulse waves for most parameters under study. In the large vessels of the optic disc blood flow dropped after 60 years, while in the microvasculature it decreased progradiently in the groups older than 40 and 60 years. In the macular region, blood flow in large vessels and microvasculature decreased mainly in the group aged over 61. Age-related changes in pulse wave parameters were unidirectional for both large vessels and microvasculature; trends were similar in both areas under investigation. Conclusions: The study demonstrated statistically significant (age-related changes in most laser speckle flowgraphy pulse wave parameters. The MBR, MV (MBR of Vascular area), MT (MBR of Tissue area) indicators are most informative in the ophthalmic hemodinamic screening. The study of another pulse wave parameters seems sufficient for the general MBR.

Evaluation of a New Diabetes Mellitus Index Based on Measurements Using the Scheimpflug Analyzer Corvis ST.

Chronic hyperglycemia causes changes in corneal biomechanics that can be measured with the Scheimpflug Analyzer Corvis ST. The diagnostic reliability of the new diabetes mellitus (DM) index developed based on this should be evaluated. In a prospective cross-sectional study, the index was initially developed using data from 81 patients with DM and 75 healthy subjects based on logistic regression analysis. The reliability of the DM index was subsequently assessed using data from another 61 patients and 37 healthy individuals. In addition, the dependence of the DM index on indicators of disease severity was analyzed. The index initially achieved a sensitivity of 79% and specificity of 80% with a cutoff value of 0.58. The evaluation showed a sensitivity of 67% and specificity of 76% with an optimized cutoff of 0.51 (area under the curve = 0.737, P < 0.001). The DM index correlated weakly with the severity of diabetic retinopathy (r = 0.209, P = 0.014). It was increased in the presence of diabetic maculopathy (P = 0.037) and in type 1 DM compared with patients with type 2 disease (P = 0.039). In this first evaluation, the new DM index achieved sufficiently good sensitivity and specificity and was weakly associated with disease-specific factors. With further improvements, it could complement the diagnostic options in DM with a simple, rapid, and noninvasive assessment method.

Bedside right ventricle quantification using three-dimensional echocardiography in children with congenital heart disease: A comparative study with cardiac magnetic resonance imaging

BackgroundAccurate quantification of right ventricular (RV) volumes and function is crucial for the management of congenital heart diseases. AimsWe aimed to assess the feasibility and accuracy of bedside analysis using new RV quantification software from three-dimensional transthoracic echocardiography in children with or without congenital heart disease, and to compare measurements with cardiac magnetic resonance imaging. MethodsWe included paediatric patients with congenital heart disease (106 patients) responsible for RV volume overload and a control group (30 patients). All patients underwent three-dimensional transthoracic echocardiography using a Vivid E95 ultrasound system. RV end-diastolic and end-systolic volumes and RV ejection fraction were obtained using RV quantification software. Measurements were compared between RV quantification and cardiac magnetic resonance imaging in 27 patients. ResultsBedside RV quantification analysis was feasible in 133 patients (97.8%). Manual contour adjustment was necessary in 126 patients (93%). The mean time of analysis was 62±42s. RV end-diastolic and end-systolic volumes were larger in the congenital heart disease group than the control group: median 85.0 (interquartile range 29.5) mL/m2 vs 55.0 (interquartile range 20.5) mL/m2 for RV end-diastolic volume and 42.5 (interquartile range 15.3) mL/m2 vs 29.0 (interquartile range 11.8) mL/m2 for RV end-systolic volume, respectively. Good agreement for RV end-diastolic and end-systolic volumes and RV ejection fraction was found between RV quantification and magnetic resonance imaging measurements. RV quantification software underestimated RV end-diastolic volume/body surface area by 3mL/m2 and RV ejection fraction by 2.1%, and overestimated RV end-systolic volume/body surface area by 0.2mL/m2. ConclusionsWe found good feasibility and accuracy of bedside RV quantification analysis from three-dimensional transthoracic echocardiography in children with or without congenital heart disease. RV quantification could be a reliable and non-invasive method for RV assessment in daily practice, facilitating appropriate management and follow-up care.

Assessment of multi-modal magnetic resonance imaging for glioma based on a deep learning reconstruction approach with the denoising method.

Deep learning reconstruction (DLR) with denoising has been reported as potentially improving the image quality of magnetic resonance imaging (MRI). Multi-modal MRI is a critical non-invasive method for tumor detection, surgery planning, and prognosis assessment; however, the DLR on multi-modal glioma imaging has not been assessed. To assess multi-modal MRI for glioma based on the DLR method. We assessed multi-modal images of 107 glioma patients (49 preoperative and 58 postoperative). All the images were reconstructed with both DLR and conventional reconstruction methods, encompassing T1-weighted (T1W), contrast-enhanced T1W (CE-T1), T2-weighted (T2W), and T2 fluid-attenuated inversion recovery (T2-FLAIR). The image quality was evaluated using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge sharpness. Visual assessment and diagnostic assessment were performed blindly by neuroradiologists. In contrast with conventionally reconstructed images, (residual) tumor SNR for all modalities and tumor to white/gray matter CNR from DLR images were higher in T1W, T2W, and T2-FLAIR sequences. The visual assessment of DLR images demonstrated the superior visualization of tumor in T2W, edema in T2-FLAIR, enhanced tumor and necrosis part in CE-T1, and fewer artifacts in all modalities. Improved diagnostic efficiency and confidence were observed for preoperative cases with DLR images. DLR of multi-modal MRI reconstruction prototype for glioma has demonstrated significant improvements in image quality. Moreover, it increased diagnostic efficiency and confidence of glioma.

A comparison of handheld versus cart-based ultrasound in the evaluation and diagnosis of carpal tunnel syndrome

BackgroundCarpal tunnel syndrome (CTS) is responsible for over 90 % of median nerve neuropathies. Though a clinical diagnosis, evaluation of nerve conduction via electrodiagnostic studies (EDX) and median nerve cross sectional area (CSA) through sonographic imaging provides supporting evidence and insight into disease severity. The advent of handheld ultrasound devices offers a portable, cost-effective and non-invasive method for median nerve assessment, yet its accuracy compared to traditional cart-based ultrasound has not been assessed in this setting. Methods43 consecutive patients who presented to an outpatient orthopedic clinic within a large academic institution for symptoms consistent with CTS between August 2023 and April 2024 were included. Handheld sonography was performed with the Clarius Convex L20 HD3 8–20 MHz transducer. The GE Venue Go with a 4–20 MHz linear transducer was used for conventional cart-based ultrasound evaluation. A paired t-test was performed to compare the mean cross-sectional area (CSA) measured with the GE machine to the mean CSA measured with the Clarius transducer (p < 0.05). ResultsThe average CSA measurement obtained with the GE was 14.21 ± 4.89 mm2. The average CSA measurement obtained with the Clarius handheld transducer was 13.54 ± 4.50 mm2. The mean difference between the GE and Clarius groups was 0.62 mm2 (95 % CI = −1.47 to 2.71), p = 0.55. ConclusionCSA measurements of the median nerve obtained by a handheld ultrasound transducer are comparable to those measured by a traditional cart-based ultrasound machine for carpal tunnel diagnosis. The adoption of handheld ultrasounds in clinical settings holds the potential for quicker, more precise diagnoses and broader access to imaging.

O84 BLOOD PRESSURE MEASUREMENT VIA IMPEDANCE CARDIOGRAPHY: AN ARTIFICIAL INTELLIGENCE BASED PROOF-OF-CONCEPT

Objective: Accurate blood pressure (BP) measurement is crucial for the diagnosis, risk assessment, treatment decision-making, and monitoring of cardiovascular diseases. Unfortunately, the gold-standard, cuff-based BP measurement suffer from inaccuracies and discomfort. As a result, continuous, cuff-less, and non-invasive BP assessment methods are merging as promising alternatives. This study is the first to comprehensively assess impedance cardiography (ICG) for Machine Learning enabled BP measurement. Methods: We analysed ICG data from 71 young and healthy adults. Nine different Machine Learning algorithms were evaluated for their BP estimation performance. Accuracy measures comprised mean difference, standard deviation, Limits of Agreement, mean absolute error, and root mean squared error. Additionally, the B-Score was calculated to evaluate the “true”, relative performance of the best-performing model. Results: The Multi-Linear Regression model showed the highest performance (mean difference = -0.01, r = 0.82) for systolic BP. The Support Vector Regressor model achieved the best results (mean difference = 0.15, r = 0.51) for diastolic BP. Both models exhibited positive B-Scores, indicative of their predictive capability. All tested models’ estimations correlated with both systolic and diastolic reference BP (r &gt; 0.72 / r &gt; 0.34, p &lt; 0.001). Conclusion: The study highlights the potential of ICG based Machine Learning algorithms for accurately estimating arterial BP. Such algorithms can provide accurate and continuous BP data. This offers the possibility of enhancing patient care, timely diagnostics, and treatment decision-making. Our approach is especially promising for post-surgical and intensive care environments.

Explainable machine-learning-based prediction of QCT/FEA-calculated femoral strength under stance loading configuration using radiomics features.

Finite element analysis can provide precise femoral strength assessment. However, its modeling procedures were complex and time-consuming. This study aimed to develop a model to evaluate femoral strength calculated by quantitative computed tomography-based finite element analysis (QCT/FEA) under stance loading configuration, offering an effective, simple, and explainable method. One hundred participants with hip QCT images were selected from the Hong Kong part of the Osteoporotic fractures in men cohort. Radiomics features were extracted from QCT images. Filter method, Pearson correlation analysis, and least absolute shrinkage and selection operatormethod were employed for feature selection and dimension reduction. The remainingfeatures were utilized as inputs, and femoral strengths were calculated as the ground truth through QCT/FEA. Support vector regressionwas applied to develop a femoral strength prediction model. The influence of various numbers of input features on prediction performance was compared, and the femoral strength prediction model was established. Finally, Shapley additive explanation, accumulated local effects, and partial dependency plotmethods were used to explain the model. The results indicated that the model performed best when six radiomics features were selected. The coefficient of determination (R2), the root mean square error, the normalized root mean square error, and the mean squared erroron the testing set were 0.820, 1016.299 N, 10.645%, and 750.827 N, respectively. Additionally, these features all positively contributed to femoral strength prediction. In conclusion, this study provided a noninvasive, effective, and explainable method of femoral strength assessment, and it may have clinical application potential.

Using Simulation Models to Train Clinicians in the Use of Point-of-Care Ultrasound.

The use of point-of-care ultrasound (POCUS) has shown to be a beneficial non-invasive vascular access assessment method by clinicians, which can provide critical elements of visual and measurable information that proves to be useful in the context of vascular access cannulation, in combination with the practical skill of the clinician performing the cannulation. However, the use of POCUS in this context is to practically train and enable individuals who are novices in using this technique to become proficient in performing this task subsequently on patients in a careful and successful way. The simulation of these vascular conditions may be useful to help healthcare professionals learn, understand, apply, and establish such practical skills for vascular cannulation safely to achieve the desired outcomes. This project intended, through the attendance of a half-day workshop, to establish skills to use POCUS in connection with simulation models and perform specific tasks to enable clinicians to use this method in their clinical practice for vascular access cannulation in patients. A mixed-methods longitudinal study design was used to evaluate the effect of a point-of-care ultrasound workshop for peripheral intravenous cannula insertion, including specific tasks for the participants to be performed on simulation models. A total of 81 individuals participated in 11 half-day workshops through 2021 and 2022. Offering a workshop that uses simulation models in combination with various POCUS devices is useful in establishing this newly learned skill in clinicians, such as measurements of depth, caliper, and direction of a vein with POCUS prior to cannulation providing essential anatomical facts to the operator, which increases the likelihood of first-time success in cannulation.

Amide proton transfer-weighted MRI for assessing rectal adenocarcinoma T-staging and perineural invasion: a prospective study.

To investigate the value of the pre-operative amide proton transfer-weighted (APTw) MRI to assess the prognostic factors in rectal adenocarcinoma (RA). This prospective study ran from January 2022 to September 2023 and consecutively enrolled participants with RA who underwent pre-operative MRI and radical surgery. The APTw signal intensity (SI) values of RA with various tumor (T), node (N) stages, perineural invasion (PNI), and tumor grade were compared by Mann-Whitney U-test or t-test. The receiver operating characteristic curve was used to evaluate the diagnostic performance of the APTw SI values. A total of 51 participants were enrolled (mean age, 58 years ± 10 [standard deviation], 26 men). There were 24 in the T1-T2 stage and 9 with positive PNI. The APTw SI max, 99th, and 95th values were significantly higher in T3-T4 stage tumor than in T1-T2; the median (interquartile range) (M (IQR)) was (4.0% (3.6-4.9%) vs 3.4% (2.9- 4.3%), p = 0.017), (3.7% (3.2-4.1%) vs 3.2% (2.8-3.8%), p = 0.013), and (3.3% (2.8-3.8%) vs 2.9% (2.3-3.5%), p = 0.033), respectively. These indicators also differed significantly between the PNI groups, with the M (IQR) (4.5% (3.6-5.7%) vs 3.7% (3.2-4.2%), p = 0.017), (4.1% (3.4-4.8%) vs 3.3% (3.0-3.9%), p = 0.022), and (3.7% (2.7-4.2%) vs 2.9% (2.6-3.5%), p = 0.045), respectively. Pre-operative APTw MRI has potential value in the assessment of T-staging and PNI determination in RA. Pre-operative amide proton transfer-weighted MRI provides a quantitative method for noninvasive assessment of T-staging and PNI in RA aiding in precision treatment planning. The efficacy of APTw MRI in RA needs further investigation. T3-T4 stage and PNI positive APTw signal intensities were higher than T1-T2 and non-PNI, respectively. APTw MRI provides a quantitative method for assessment of T staging and PNI in RA.

Deep learning for predicting fibrotic progression risk in diabetic individuals with metabolic dysfunction-associated steatotic liver disease initially free of hepatic fibrosis

ObjectiveMetabolic dysfunction-associated steatotic liver disease (MASLD) significantly impacts patients with type 2 diabetes mellitus (T2DM), where current non-invasive assessment methods show limited predictive power for future fibrotic progression. This study aims to develop an enhanced deep learning (DL) model that integrates ultrasound elastography images with clinical data, refining the prediction of fibrotic progression in T2DM patients with MASLD who initially exhibit no signs of hepatic fibrosis. MethodsWe enrolled 946 diabetic MASLD patients without advanced fibrosis, confirmed by initial liver stiffness measurements (LSM) below 6.5 kPa. Patients were divided into a training dataset of 671 and a testing dataset of 275. Hepatic shear wave elastography (SWE) images measured liver stiffness, classifying participants based on progression. A DL integrated model (DI-model) combining SWE images and clinical data was trained and its predictive performance compared with individual Image and Tabular models, as well as a logistic regression model on the testing dataset. ResultsFibrotic progression was observed in 18.1 % of patients over three years. During the training phase, the DI-model outperformed other models, achieving the lowest validation loss of 0.161 and highest accuracy of 0.933 through cross-validation. In the testing phase, it demonstrated robust discrimination with AUCs of 0.884 and 0.903 for the receiver operating characteristic and precision-recall curves, respectively, clearly outperforming other models. Shapley analysis identified BMI, LSM, and glycated hemoglobin as critical predictors. ConclusionThe DI-model significantly enhances the prediction of future fibrotic progression in diabetic MASLD patients, demonstrating the benefit of combining clinical and imaging data for early diagnosis and intervention.

Quantitative US fat fraction for noninvasive assessment of hepatic steatosis in suspected metabolic-associated fatty liver disease

ObjectivesTo evaluate the agreement between quantitative ultrasound system fat fraction (USFF) and proton magnetic resonance spectroscopy (1H-MRS) and the diagnostic value of USFF in assessing metabolic-associated fatty liver disease (MAFLD).MethodsThe participants with or suspected of MAFLD were prospectively recruited and underwent 1H-MRS, USFF, and controlled attenuation parameter (CAP) measurements. The correlation between USFF and 1H-MRS was assessed using Pearson correlation coefficients. The USFF diagnostic performance for different grades of steatosis was evaluated using receiver operating characteristic curve analysis (ROC) and was compared with CAP, visual hepatic steatosis grade (VHSG).ResultsA total of 113 participants (mean age 44.79 years ± 13.56 (SD); 71 males) were enrolled, of whom 98 (86.73%) had hepatic steatosis (1H-MRS ≥ 5.56%). USFF showed a good correlation (Pearson r = 0.76) with 1H-MRS and showed a linear relationship, which was superior to the correlation between CAP and 1H-MRS (Pearson r = 0.61). The USFF provided high diagnostic performance for different grades of hepatic steatosis, with ROC from 0.84 to 0.98, and the diagnostic performance was better than that of the CAP and the VHSG. The cut-off values of the USFF were different for various grades of steatosis, and the cut-off values for S1, S2, and S3 were 12.01%, 19.98%, and 22.22%, respectively.ConclusionsThere was a good correlation between USFF and 1H-MRS. Meanwhile, USFF had good diagnostic performance for hepatic steatosis and was superior to CAP and VHSG. USFF represents a superior method for noninvasive quantitative assessment of MAFLD.Critical relevance statementQuantitative ultrasound system fat fraction (USFF) accurately assesses liver fat content and has a good correlation with magnetic resonance spectroscopy (1H-MRS) for the assessment of metabolic-associated fatty liver disease (MAFLD), as well as for providing an accurate quantitative assessment of hepatic steatosis.Key PointsCurrent diagnostic and monitoring modalities for metabolic-associated fatty liver disease have limitations.USFF correlated well with 1H-MRS and was superior to the CAP.USFF has good diagnostic performance for steatosis, superior to CAP and VHSG.Graphical

Multiple methods of diet assessment reveal differences in Atlantic puffin diet between ages, breeding stages, and years

IntroductionAtlantic puffin (Fratercula arctica, hereafter “puffin”) reproductive success in the Gulf of Maine (GoM) has declined following a recent oceanographic regime shift that has led to rapid warming and increasingly frequent marine heatwaves. Concurrent changes in both the regional forage fish community and puffin chick diets and provisioning rates suggest that inadequate prey resources may be driving this decline. Traditional, noninvasive methods of diet assessment, however, are unable to determine seabird diet at many age classes and breeding stages.MethodsTo determine what prey GoM puffins were feeding on during two years of marine heatwave conditions, we assessed puffin diet using two complementary methods: traditional, observational methods that utilize bill-load photography and emerging methods employing fecal DNA metabarcoding. We then examined the effect of methodology, age, breeding stage, and year on puffin diet composition. ResultsWe identified a strong correlation between the composition of chick diet as estimated through traditional and emerging methods, supporting the interpretation of DNA relative read abundance as a quantitative metric of diet composition. Both methods identified the same dominant prey groups yet metabarcoding identified a greater number of species and offered higher taxonomic resolution. Additionally, metabarcoding revealed adult puffin diet during the incubation period for the first time. Although puffin adults and chicks fed on many of the same prey types, adults consumed a greater variety of taxa and consumed more low quality prey types than they provisioned chicks.DiscussionFor both age classes, diet varied both between and within years, likely reflecting changes in the local forage fish community in response to environmental variability. Puffins exploited unusual abundances of typically-uncommon prey during these two years of marine heatwave conditions, yet low puffin productivity suggests the observed dietary plasticity was not fully able to compensate for apparent prey shortages. Continued refinement of molecular methods and the interpretation of the data they provide will enable better assessments of how seabirds of diverse ages and breeding stages are adapting to changing prey communities.

Shear wave trajectory detection in ultra-fast M-mode images for liver fibrosis assessment: A deep learning-based line detection approach

Stiffness measurement using shear wave propagation velocity has been the most common non-invasive method for liver fibrosis assessment. The velocity is captured through a trace recorded by transient ultrasonographic elastography, with the slope indicating the velocity of the wave. However, due to various factors such as noise and shear wave attenuation, detecting shear wave trajectory on wave propagation maps is a challenging task. In this work, we made the first attempt to use deep learning methods for shear wave trajectory detection on wave propagation maps. Specifically, we adopted five deep learning models in this task and evaluated them by using a well-acknowledged metric based on EA-Angular-Score (EAA) and task-specific metric based on Young s-Score (Ys) in the line-detection field. Furthermore, we proposed an end-to-end framework based on a Transformer and Hough transform, named Transformer-enhanced Hough Transform (TEHT). It took a wave propagation map as input image and directly output the slope of the shear wave trajectory. The framework extracts multi-scale local features from wave propagation maps, employs a deformable attention mechanism for feature fusion, identifies the target line using the Hough transform’s voting mechanism, and calculates the contribution of each scale through channel attention. Wave propagation maps from 68 patients were utilized in this study, with manual annotation performed by a rater who was trained as a radiologist, serving as the reference value. The evaluation revealed that the SLNet model exhibited F-measure of EA and Ys values as 40.33 % and 40.72 %, respectively, while the TEHT model showed F-measure of EA and Ys values as 80.96 % and 98.00 %, respectively. TEHT yielded significantly better performance than other deep learning models. Moreover, TEHT demonstrated strong concordance with the gold standard, yielding R2 values of 0.967 and 0.968 for velocity and liver stiffness, respectively. The present study therefore suggests the application of the TEHT model for assessing liver fibrosis owing to its superiority among the five deep learning models.

Molecular SPECT/CT Profiling of Claudin18.2 Expression In Vivo: Implication for Patients with Gastric Cancer.

Zolbetuximab (IMAB362), a monoclonal antibody targeting Claudin18.2 (CLDN 18.2), demonstrates a significant clinical benefit in patients with advanced gastroesophageal cancers. The noninvasive assessment of CLDN18.2 expression through molecular imaging offers a potential avenue for expedited monitoring and the stratification of patients into risk groups. This study elucidates that CLDN18.2 is expressed at a noteworthy frequency in primary gastric cancers and their metastases. The iodogen method was employed to label IMAB362 with 123I/131I. The results demonstrated the efficient and reproducible synthesis of 123I-IMAB362, with a specific binding affinity to CLDN18.2. Immuno-single-photon emission computed tomography (SPECT) imaging revealed the rapid accumulation of 123I-IMAB362 in gastric cancer xenografts at 12 h, remaining stable for 3 days in patient-derived tumor xenograft models. Additionally, tracer uptake of 123I-IMAB362 in MKN45 cells surpassed that in MKN28 cells at each time point, with tumor uptake correlating significantly with CLDN18.2 expression levels. Positron emission tomography/computed tomography imaging indicated that tumor uptake of 18F-FDG and the functional/viable tumor volume in the 131I-IMAB362 group were significantly lower than those in the 123I-IMAB362 group on day 7. In conclusion, 123I-IMAB362 immuno-SPECT imaging offers an effective method for direct, noninvasive, and whole-body quantitative assessment of tumor CLDN18.2 expression in vivo. This approach holds promise for accelerating the monitoring and stratification of patients with gastric cancer.

Ultrasound contrast-enhanced radiomics model for preoperative prediction of the tumor grade of clear cell renal cell carcinoma: an exploratory study

BackgroundThis study aims to explore machine learning(ML) methods for non-invasive assessment of WHO/ISUP nuclear grading in clear cell renal cell carcinoma(ccRCC) using contrast-enhanced ultrasound(CEUS) radiomics.MethodsThis retrospective study included 122 patients diagnosed as ccRCC after surgical resection. They were divided into a training set (n = 86) and a testing set(n = 36). CEUS radiographic features were extracted from CEUS images, and XGBoost ML models (US, CP, and MP model) with independent features at different phases were established. Multivariate regression analysis was performed on the characteristics of different radiomics phases to determine the indicators used for developing the prediction model of the combined CEUS model and establishing the XGBoost model. The training set was used to train the above four kinds of radiomics models, which were then tested in the testing set. Radiologists evaluated tumor characteristics, established a CEUS reading model, and compared the diagnostic efficacy of CEUS reading model with independent characteristics and combined CEUS model prediction models.ResultsThe combined CEUS radiomics model demonstrated the best performance in the training set, with an area under the curve (AUC) of 0.84, accuracy of 0.779, sensitivity of 0.717, specificity of 0.879, positive predictive value (PPV) of 0.905, and negative predictive value (NPV) of0.659. In the testing set, the AUC was 0.811, with an accuracy of 0.784, sensitivity of 0.783, specificity of 0.786, PPV of 0.857, and NPV of 0.688.ConclusionsThe radiomics model based on CEUS exhibits high accuracy in non-invasive prediction of ccRCC. This model can be utilized for non-invasive detection of WHO/ISUP nuclear grading of ccRCC and can serve as an effective tool to assist clinical decision-making processes.

Non-invasive Scores and Serum Biomarkers for Fatty Liver in the Era of Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD): A Comprehensive Review From NAFLD to MAFLD and MASLD.

The prevalence of non-alcoholic fatty liver disease (NAFLD) is rapidly increasing worldwide, making it the leading cause of liver related morbidity and mortality. Currently, liver biopsy is the gold standard for assessing individuals with steatohepatitis and fibrosis. However, its invasiveness, sampling variability, and impracticality for large-scale screening has driven the search for non-invasive methods for early diagnosis and staging. In this review, we comprehensively summarise the evidence on the diagnostic performance and limitations of existing non-invasive serum biomarkers and scores in the diagnosis and evaluation of steatosis, steatohepatitis, and fibrosis. Several non-invasive serum biomarkers and scores have been developed over the last decade, although none has successfully been able to replace liver biopsy. The introduction of new NAFLD terminology, namely metabolic dysfunction-associated fatty liver disease (MAFLD) and more recently metabolic dysfunction-associated steatotic liver disease (MASLD), has initiated a debate on the interchangeability of these terminologies. Indeed, there is a need for more research on the variability of the performance of non-invasive serum biomarkers and scores across the diagnostic entities of NAFLD, MAFLD and MASLD. There remains a significant need for finding valid and reliable non-invasive methods for early diagnosis and assessment of steatohepatitis and fibrosis to facilitate prompt risk stratification and management to prevent disease progression and complications. Further exploration of the landscape of MASLD under the newly defined disease subtypes is warranted, with the need for more robust evidence to support the use of commonly used serum scores against the new MASLD criteria and validation of previously developed scores.

Diagnostics of acute compartment syndrome : Current gold standard and the state of science of noninvasive assessment methods

Acute compartment syndrome (ACS) is defined by a disorder of the microcirculation due to a persistent pathological pressure increase within amuscle compartment. The ischemia of the tissue leads to an initially reversible functional impairment and finally irreversible damage of the musculature, nerves and other structures. Based on the understanding of the pathophysiology, the current diagnostic concepts and treatment using the so-called dermatofasciotomy of the affected muscle compartments can be derived. In addition to the suspicion of a possible ACS based on the medical history of the patient, the findings of the clinical examination are decisive. This review article gives a summary of all the essential aspects of the diagnostics. In clinically uncertain cases and for monitoring, an objectification of the findings using instrument-based techniques is increasingly required. Nowadays, invasive needle pressure measurement is available; however, due to limited reliability, specificity and sensitivity, these measurements only represent an aid to decision guidance supporting or advising against the indications for dermatofasciotomy. The increasing demands on making a certain diagnosis and justification of a surgical intervention from a legal point of view, substantiate the numerous scientific efforts to develop noninvasive instrument-based diagnostics. These methods are based either on detection of increasing intracompartmental pressure or decreasing perfusion pressure and microcirculation. The various measurement principles are summarized in a lucid form.

The role and place of arthroscopy in the early diagnosis of monoarthrosis (literature review)

Background. Knee osteoarthritis is a progressive incurable disease that in severe cases leads to total joint replacement, which requires significant economic costs and medical and social adaptation, has a number of postoperative complications and adverse outcomes. Therefore, special attention has recently been paid to the prevention and treatment of the early stages of the disease. The purpose of the study was to conduct a systematic analysis of scientific literature on the prospects and possibilities of using arthroscopy in the early diagnosis of monoarthrosis. Material and methods. A literature search was conducted in the PubMed and MEDLINE databases for 2010–2024 using the following medical subject headings and keywords: “deforming osteoarthritis of the knee joint”, “osteoarthritis of the knee joint”, “unilateral deforming osteoarthritis of the knee joint”, “unilateral osteoarthritis of the knee joint”, “gonarthrosis”, “monoarthrosis”, “arthroscopy”, “diagnosis”, “treatment”. If necessary, literature sources beyond the search period were used in some cases. A general search revealed 48 references on the use of arthroscopy as a diagnostic and therapeutic method in the early stages of monoarthrosis. The primary exclusion concerned the literature in which arthroscopy was used for the diagnosis and treatment of late-stage knee osteoarthritis (n = 38). The secondary exclusion included literature sources that contained only background information (summary, figures, references) (n = 12). As a result, only relevant full-text articles in professional journals remained (n = 15). Results. The lack of correlation between clinical symptoms and radiological signs of knee osteoarthritis causes low availability of orthopaedic care: more than 30 % of newly diagnosed patients have a severe stage of the disease, and in some cases the pathology is detected only in connection with the manifestation of complications; the diagnosis of osteoarthritis due to a large percentage of painless development of the disease (40 %) is often established at terminal stages. All of this suggests the need for further research into the various factors that influence the frequency, prevalence, economic and social burden of knee osteoarthritis. Arthroscopy is potentially the gold standard for validating non-invasive assessment methods such as magnetic resonance imaging, as it provides high magnification and direct view of articular cartilage with non-destructive interactive assessment of its structure and functional properties. Arthroscopy allows for a more detailed description of the depth and extent of lesions, as well as the detection of subtle changes such as cartilage softening, fibrillations, and tangential peeling. Clinical symptoms and structural changes in the knee joint elements visualised during arthroscopy in patients with monoarthrosis are covered in a few studies, some of which were published 10 years ago. The results of modern arthroscopic studies can be an important contribution to the development of diagnostic and differential diagnostic criteria for the early stages of monoarthrosis. Conclusions. Based on information and analytical studies of modern scientific literature, it has been found that knee osteoarthritis is accompanied by persistent pain, significant limitation of the lower limb function, and reduced ability to work, which often leads to joint replacement. Diagnosis of osteoarthritis in the early stages is difficult due to the absence of pathognomonic clinical, radiological and laboratory parameters, and in case of monoarthrosis with synovitis, it is complicated by differentiation with specific arthritis of the knee joint. Arthroscopy allows performing the necessary scope of diagnostic and therapeutic measures with verification of the pathological process and determination of gonarthrosis stage.

Body composition analysis using dual-energy x-ray absorptiometry in an Egyptian pediatric sickle cell disease cohort.

Growth failure is commonly encountered in sickle cell disease (SCD). Tissue compartment growth and development are subsequently likely to be altered in such patients. We aimed to analyze body composition in an Egyptian pediatric SCD cohort using dual-energy x-ray absorptiometry (DEXA), one of the most comprehensive and noninvasive assessment methods available. Forty children with SCD ≤18years and 40 healthy youngsters age- and gender-matched were enrolled. Patients' demographic, clinical, and laboratory parameters were obtained from their archived files. All patients and controls were subjected to body composition assessment using a MedixDR-Whole Body DEXA System. In SCD patients; weight and height relative to age Z scores were significantly lower (p<.001), total body lean was significantly higher (p=.006), and total body fat percentage was lower, yet the difference was not statistically significant (p=.09). There were no statistically significant variations in bone mineral density or content, basal metabolic rate, subcutaneous adipose tissue, android/gynoid fat ratio, and visceral adipose tissue. There were no significant gender disparities between SCD patients and controls. Faltering growth in children with SCD should be addressed with a multidisciplinary approach including nutritional support, correction of anemia, and proper medical care. Body composition parameters assessed using DEXA were comparable between cases and controls apart from total body lean. Further clinical studies are needed with multicenter cooperation and a larger sample size to assess the usefulness of DEXA as an assessment tool for body composition in children with SCD.

Impact of obstruction size on ureter dynamics: A computational investigation

Kidney stones, known medically as nephrolithiasis, present a significant health concern globally, particularly in regions such as India and the Middle East. Despite extensive research, the complexity of ureteral obstruction due to kidney stones remains a challenge in urology. This study addresses this gap by analysing the effects of obstruction in a three-dimensional model of the ureter with a constant diameter, simulating various percentages of blockage. Through computational analysis, the pressure and velocity effects on the ureter wall are explored, providing insights into the dynamics of obstructed ureters. Building upon previous research, this study contributes to a deeper understanding of the factors influencing flow patterns and pressure variations within the urinary tract. Additionally, findings from this study may lead to advancements in non-invasive assessment methods for diagnosing and treating ureteral obstruction caused by kidney stones. Furthermore, insights gained from this research could potentially inform clinical decision-making, leading to improved management strategies and better outcomes for patients affected by this debilitating condition. The novelty of this work lies in its comprehensive analysis of the effects of obstruction on the ureteral wall, offering valuable implications for urological practice and patient care.