Non-invasive Diagnostic Method Research Articles

Increased vascular stiffness in children exposed in utero but not children exposed postnatally to emissions from a coal mine fire.

Chronic, low-intensity air pollution exposure has been consistently associated with increased atherosclerosis in adults. However, there was limited research regarding the implications of acute, high-intensity air pollution exposure during childhood. We aimed to determine whether there were any associations between early-life exposure to such an episode and early-life vascular function changes. We conducted a prospective cohort study of children (<9 years old) who lived in the vicinity of the Hazelwood coal mine fire (n = 206). Vascular function was measured using noninvasive diagnostic methods including carotid intima-media thickness and pulse wave velocity (PWV). Exposure estimates were calculated from prognostic models and location diaries during the exposure period completed by each participant's parent. Linear mixed-effects models were used to determine whether there were any associations between exposure and changes in vascular outcomes at the 3- and 7-year follow-ups and over time. At the 7-year follow-up, each 10 μg/m3 increase in daily PM2.5 in utero was associated with increased PWV (β = 0.13 m/s; 95% confidence interval [CI] = 0.02, 0.24; P = 0.02). The association between in utero exposure to daily PM2.5 was not altered by adjustment for covariates, body mass index, and maternal fire stress. Each 1 µg/m3 increase in background PM2.5 was associated with increased PWV (β = 0.68 m/s; 95% CI = 0.10, 1.26; P = 0.025), in children from the in utero exposure group. There was a trend toward smaller PWV (β = -0.17 m/s; 95% CI = -0.366, 0.02) from the 3- to 7-year follow-up clinic suggesting that the deficits observed previously in children exposed postnatally did not persist. There was a moderate improvement in vascular stiffness of children exposed to PM2.5 from a local coal mine fire in infancy. There was a mild increase in vascular stiffness in children exposed to PM2.5 from a local coal mine fire while their mothers were pregnant.

Оценка чувствительности методов диагностики в выявлении гемодинамически значимых односторонних стенозов почечных артерий

Objective. Assessment of renal artery stenosis significance in patients with resistant arterial hypertension using non-invasive diagnostic methods and to compare them with the results of selective angiography and methods of physiological assessment of renal artery stenoses.Materials and methods. Prospectively, 156 patients with drug-resistant arterial hypertension and signs of renal artery stenosis detected by doppler ultrasonography of renal arteries were included in the study. Subsequently, 25 patients were excluded from the study due to multiple variant renal blood supply and bilateral renal artery stenosis. The remaining patients (n=131) underwent selective angiography of renal arteries, and 66 of them additionally underwent CTA of renal arteries with intravenous contrast. If the artery narrowing was 90% or more (n=27) in diameter, the stenosis was considered hemodynamically significant and further stenting of the affected artery was performed, and in case of 60-90% stenosis (n=52) additional assessment of functional significance of the stenosis was performed by measuring translesional pressure gradient, fractional blood flow reserve, instantaneous blood flow reserve (iFR) and Pd/ Pa ratio. Results. Among all patients (n=131), in whom the doppler ultrasonography of renal arteries showed signs of unilateral renal artery stenosis, after angiography combined with additional methods of functional significance assessment, hemodynamically significant renal artery stenosis was confirmed in 41% of cases (n=54). Thus, the sensitivity of doppler ultrasonography of renal arteries in detection of hemodynamically significant stenoses was 74%, prognostic value of positive 78% and negative result 64% (p&lt;0,001). According to CTA (n=66) renal artery stenosis was confirmed in 56 patients. The results of CTA of renal arteries in 88% of cases coincided with the results of selective angiography, and using additional functional methods hemodynamically significant stenosis was confirmed in 32 (48%) patients. The sensitivity of CTA in detection of hemodynamically significant stenoses of renal arteries was 69%, specificity 91%, prognostic value of positive and negative results was 91 and 68% respectively. According to selective angiography, out of 131 patients, 24 patients had no renal artery stenosis, 28 patients had stenosis &lt;60%, 27 patients had renal artery stenosis &gt;90% and 52 patients had stenosis 60-90%. Patients with stenosis &lt;60% were not considered candidates for renal artery stenting.

Utilizing portable electroencephalography to screen for pathology of Alzheimer’s disease: a methodological advancement in diagnosis of neurodegenerative diseases

BackgroundThe current biomarker-supported diagnosis of Alzheimer’s disease (AD) is hindered by invasiveness and cost issues. This study aimed to address these challenges by utilizing portable electroencephalography (EEG). We propose a novel, non-invasive, and cost-effective method for identifying AD, using a sample of patients with biomarker-verified AD, to facilitate early and accessible disease screening.MethodsThis study included 35 patients with biomarker-verified AD, confirmed via cerebrospinal fluid sampling, and 35 age- and sex-balanced healthy volunteers (HVs). All participants underwent portable EEG recordings, focusing on 2-minute resting-state EEG epochs with closed eyes state. EEG recordings were transformed into scalogram images, which were analyzed using “vision Transformer(ViT),” a cutting-edge deep learning model, to differentiate patients from HVs.ResultsThe application of ViT to the scalogram images derived from portable EEG data demonstrated a significant capability to distinguish between patients with biomarker-verified AD and HVs. The method achieved an accuracy of 73%, with an area under the receiver operating characteristic curve of 0.80, indicating robust performance in identifying AD pathology using neurophysiological measures.ConclusionsOur findings highlight the potential of portable EEG combined with advanced deep learning techniques as a transformative tool for screening of biomarker-verified AD. This study not only contributes to the neurophysiological understanding of AD but also opens new avenues for the development of accessible and non-invasive diagnostic methods. The proposed approach paves the way for future clinical applications, offering a promising solution to the limitations of advanced diagnostic practices for dementia.

#2922 The role of urinary extracellular-derived miRNAs dysregulation in IgA nephropathy

Abstract Background and Aims IgA nephropathy (IgAN) is one of the most common forms of glomerulonephritis and causes hematuria and proteinuria by damaging the mesangial and podocyte cells. Urinary extracellular vesicles (uEVs) derived from damaged podocytes may reflect podocyte damage in various glomerular diseases and are considered an early and noninvasive diagnostic method. This study aimed to extract urinary extracellular vesicles (EVs) and investigate the expression dysregulation and diagnostic value of miR-29c, miR-146a, miR-148b, miR-155, miR-200b, and miR-429 in urine samples from patients with IgAN. Method Urine samples were collected from 20 patients with IgAN, 30 patients with membranous nephropathy (MGN), and 16 healthy individuals to extract Urinary EVs by ultracentrifugation. The characterization of EVs was evaluated by the specific protein markers of the EVs, flotillin-1, ALiX, and CD-9, along with histone H1 and podocyte-specific marker podocalyxin via western blotting. SEM and DLS were used to investigate the size and morphology of EVs. The expression levels of the miRNAs were evaluated using Real-time PCR. Results Numerous extracellular vesicles &amp;gt;100 nm in size were present in the urine sample which were considered as EVs based on references. There were higher levels of the specific markers flotillin-1, ALiX, and podococalyxin in the urine samples of IgAN patients than in the control samples (P &amp;lt; 0.001 and P &amp;lt; 0.001, respectively). There was a statistically significant difference among the expression level of miR-29c (P = 0.002 and P = 033) in the group of IgAN patients compared to MGN patients and the group of healthy people, based on Rock curve analysis this urinary marker could discriminate the IgAN patients from MGN group, the area under the curve AUC ≥ 0.73. Conclusion This study showed that the different levels of miRNAs studied in urinary EVs may indicate podocyte damage and have a direct relationship with the pathology of IgAN and MGN. Further studies are needed to confirm these results and determine the diagnostic value of these markers.

#2229 miR-186, a potential noninvasive diagnostic biomarker of Membranous nephropathy in urinary microparticles

Abstract Background and Aims Membranous nephropathy (MN) is one of the most common causes of nephrotic syndrome, and is associated with podocyte damage and proteinuria. Invasive biopsy is the gold-standard diagnostic method for this disease. The use of specific biomarkers, such as microparticles (MPs) originating from damaged podocytes released in a patient's urine, has been proposed as an early, noninvasive, and repetitive diagnostic method. According to the previous studies, MPs derived from podocytes are present in the urine of patients with different glomerulonephritis, such as diabetic nephropathy, lupus nephritis, renal injury in preeclampsia, and renovascular hypertensive disorders. The analysis of urinary microparticle-derived miRNAs from patients with kidney diseases can help detect diagnostic biomarkers. This study aimed to analyze podocyte damage-related miRNAs in MN, miR-30c, miR-135, and miR-18 in the urinary MP of MN patients to identify appropriate candidate biomarkers for MN Method Urine samples from 30 patients with membranous nephropathy and 16 healthy individuals were collected to extract podocyte MPs using ultracentrifugation. Characterization of these particles was determined using the specific protein marker of MPs, TSG-101, and the podocyte-specific marker Nephrin, by western blotting, and SEM was used to check the size and morphology. The expression levels of microRNAs extracted from podocyte MPs, miR-30c, miR-135, and miR-186, were also evaluated by real-time PCR. Results The evaluation of the characteristics of MPs showed that there were many particles with a size of more than 100 nm in the urine sample, and there were higher levels of the specific markers TSG-101 and Nephrin in the urine samples of MGN patients than in the control samples (P &amp;lt; 0.001). The expression level of miR-186 was compared between the three studied groups and based on the results of the expression of this miRNA in the group of membranous nephropathy patients compared to healthy people group, there was a significant increase in expression (P = 0.000) Conclusion This study showed that although the expression levels of miR-186 in podocyte MPs samples extracted from the urine of patients with MN were significantly changed compared to the studied controls, more studies should be performed to determine the diagnostic values.

Emerging Biohybrids of Aptamer-Based Nano-Biosensing Technologies for Effective Early Cancer Detection.

Cancer is a leading global cause of mortality, which underscores the imperative of early detection for improved patient outcomes. Biorecognition molecules, especially aptamers, have emerged as highly effective tools for early and accurate cancer cell identification. Aptamers, with superior versatility in synthesis and modification, offer enhanced binding specificity and stability compared with conventional antibodies. Hence, this article reviews diagnostic strategies employing aptamer-based biohybrid nano-biosensing technologies, focusing on their utility in detecting cancer biomarkers and abnormal cells. Recent developments include the synthesis of nano-aptamers using diverse nanomaterials, such as metallic nanoparticles, metal oxide nanoparticles, carbon-derived substances, and biohybrid nanostructures. The integration of these nanomaterials with aptamers significantly enhances sensitivity and specificity, promising innovative and efficient approaches for cancer diagnosis. This convergence of nanotechnology with aptamer research holds the potential to revolutionize cancer treatment through rapid, accurate, and non-invasive diagnostic methods.

Along-standing conundrum: an unusual case of 2:1 atrioventricular block with conflicting findings.

A2:1 atrioventricular (AV) block can occur anywhere within the conduction system, and noninvasive measurements may not always predict the exact site of the block. Although localization of the block is critical for deciding any treatment, patients should also be carefully questioned about symptoms both at rest and during exertion. Acase of 2:1 AV block that was symptomatic only during exertion, appeared infranodal by noninvasive diagnostic methods, but was found to be intranodal on electrophysiological study is reported.

Alzheimer's disease early screening and staged detection with plasma proteome using machine learning and convolutional neural network.

Alzheimer's disease (AD) stands as the prevalent progressive neurodegenerative disease, precipitating cognitive impairment and even memory loss. Amyloid biomarkers have been extensively used in the diagnosis of AD. However, amyloid proteins offer limited information about the disease process and accurate diagnosis depends on the presence of a substantial accumulation of amyloid deposition which significantly impedes the early screening of AD. In this study, we have combined plasma proteomics with an ensemble learning model (CatBoost) to develop a cost-effective and non-invasive diagnostic method for AD. A longitudinal panel has been identified that can serve as reliable biomarkers across the entire progression of AD. Simultaneously, we have developed a neural network algorithm that utilizes plasma proteins to detect stages of Alzheimer's disease. Based on the developed longitudinal panel, the CatBoost model achieved an area under the operating curve of at least 0.90 in distinguishing mild cognitive impairment from cognitively normal. The neural network model was utilized for the detection of three stages of AD, and the results demonstrated that the neural network model exhibited an accuracy as high as 0.83, surpassing that of the traditional machine learning model.

The role of Peripheral Inflammatory Markers and Coagulation factors in patients with CNS immune disease and glioma.

Gliomas are associated with high rates of disability and mortality, and currently, there is a lack of specific and sensitive biomarkers for diagnosis. The ideal biomarkers should be detected early through non-invasive methods. Our research aims to develop a rapid, convenient non-invasive diagnostic method for gliomas, as well as for grading and differentiation. We retrospectively collected data from patients who underwent surgery for glioma, Trigeminal neuralgia/Hemifacial spasm, schwannoma, and those diagnosed with multiple sclerosis at our institution from January 2018 to December 2020. Inflammatory markers and coagulation factor levels were collected on admission, and NLR, dNLR, PLR, LMR, and PNI were calculated for patients. Analyze the significance of biomarkers in the diagnosis and grading of gliomas, the diagnosis of MS, and the differential diagnosis of them. We evaluated 155 healthy individuals, 64 TN/HS patients, 47 MS patients, 316 schwannoma patients, and 814 with gliomas patients. Compared with healthy controls and MS group, the preoperative levels of NLR, dNLR, D-dimer, Fibrinogen, Antithrobin and Factor VIII of glioma patients were significantly higher in glioma patients and positively correlated with the grade of glioma. Conversely,0020LMR and PNI were significantly lower and negatively correlated with glioma grading. ROC curves confirmed that for the diagnosis of glioma, NLR showed a maximum AUC value of 0.8616 (0.8322-0.8910), followed by D-dimer and Antithrombin, with AUC values of 0.8205 (0.7601-0.8809) and 0.8455 (0.8153-0.8758), respectively. NLR and d-dimer also showed great sensitivity in the diagnosis of MS and differential diagnosis with gliomas. Our study demonstrated that multiple inflammatory markers and coagulation factors could be utilized as biomarkers for the glioma diagnosis, grading, and differential diagnosis of MS. Furthermore, the combination of these markers exhibited high sensitivity and specificity.

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.

Salivary metabolites are promising noninvasive biomarkers of drug-induced liver injury.

Drug-induced liver injury (DILI) is one of the most common adverse events of medication use, and its incidence is increasing. However, early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests. To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools. Saliva samples from 31 DILI patients and 35 healthy controls (HCs) were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry. Subsequent analyses, including partial least squares-discriminant analysis modeling, t tests and weighted metabolite coexpression network analysis (WMCNA), were conducted to identify key differentially expressed metabolites (DEMs) and metabolite sets. Furthermore, we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction. The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves. We found 247 differentially expressed salivary metabolites between the DILI group and the HC group. Using WMCNA, we identified a set of 8 DEMs closely related to liver injury for further prediction testing. Interestingly, the distinct separation of DILI patients and HCs was achieved with five metabolites, namely, 12-hydroxydodecanoic acid, 3-hydroxydecanoic acid, tetradecanedioic acid, hypoxanthine, and inosine (area under the curve: 0.733-1). Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients. Our study may provide a potentially feasible and noninvasive diagnostic method for DILI, but further validation is needed.

Diagnostic performance of volatile organic compounds analysis and electronic noses for detecting colorectal cancer: a systematic review and meta-analysis

IntroductionThe detection of Volatile Organic Compounds (VOCs) could provide a potential diagnostic modality for the early detection and surveillance of colorectal cancers. However, the overall diagnostic accuracy of the proposed tests remains uncertain.ObjectiveThis systematic review is to ascertain the diagnostic accuracy of using VOC analysis techniques and electronic noses (e-noses) as noninvasive diagnostic methods for colorectal cancer within the realm of clinical practice.MethodsA systematic search was undertaken on PubMed, EMBASE, Web of Science, and the Cochrane Library to scrutinize pertinent studies published from their inception to September 1, 2023. Only studies conducted on human subjects were included. Meta-analysis was performed using a bivariate model to obtain summary estimates of sensitivity, specificity, and positive and negative likelihood ratios. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was deployed for quality assessment. The protocol for this systematic review was registered in PROSPERO, and PRISMA guidelines were used for the identification, screening, eligibility, and selection process.ResultsThis review encompassed 32 studies, 22 studies for VOC analysis and 9 studies for e-nose, one for both, with a total of 4688 subjects in the analysis. The pooled sensitivity and specificity of VOC analysis for CRC detection were 0.88 (95% CI, 0.83-0.92) and 0.85 (95% CI, 0.78-0.90), respectively. In the case of e-nose, the pooled sensitivity was 0.87 (95% CI, 0.83-0.90), and the pooled specificity was 0.78 (95% CI, 0.62-0.88). The area under the receiver operating characteristic analysis (ROC) curve for VOC analysis and e-noses were 0.93 (95% CI, 0.90-0.95) and 0.90 (95% CI, 0.87-0.92), respectively.ConclusionThe outcomes of this review substantiate the commendable accuracy of VOC analysis and e-nose technology in detecting CRC. VOC analysis has a higher specificity than e-nose for the diagnosis of CRC and a sensitivity comparable to that of e-nose. However, numerous limitations, including a modest sample size, absence of standardized collection methods, lack of external validation, and a notable risk of bias, were identified. Consequently, there exists an imperative need for expansive, multi-center clinical studies to elucidate the applicability and reproducibility of VOC analysis or e-nose in the noninvasive diagnosis of colorectal cancer.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/#recordDetails, identifier CRD42023398465.

Comparative studies of hair shaft components between healthy and diseased donors.

Globally, the rapid aging of the population is predicted to become even more severe in the second half of the 21st century. Thus, it is expected to establish a growing expectation for innovative, non-invasive health indicators and diagnostic methods to support disease prevention, care, and health promotion efforts. In this study, we aimed to establish a new health index and disease diagnosis method by analyzing the minerals and free amino acid components contained in hair shaft. We first evaluated the range of these components in healthy humans and then conducted a comparative analysis of these components in subjects with diabetes, hypertension, androgenetic alopecia, major depressive disorder, Alzheimer's disease, and stroke. In the statistical analysis, we first used a student's t test to compare the hair components of healthy people and those of patients with various diseases. However, many minerals and free amino acids showed significant differences in all diseases, because the sample size of the healthy group was very large compared to the sample size of the disease group. Therefore, we attempted a comparative analysis based on effect size, which is not affected by differences in sample size. As a result, we were able to narrow down the minerals and free amino acids for all diseases compared to t test analysis. For diabetes, the t test narrowed down the minerals to 15, whereas the effect size measurement narrowed it down to 3 (Cr, Mn, and Hg). For free amino acids, the t test narrowed it down to 15 minerals. By measuring the effect size, we were able to narrow it down to 7 (Gly, His, Lys, Pro, Ser, Thr, and Val). It is also possible to narrow down the minerals and free amino acids in other diseases, and to identify potential health indicators and disease-related components by using effect size.

Past, Present, and Future Diagnostic Methods for the Early Noninvasive Detection of Oral Premalignant Lesions: A State of the Art and Systematic Review.

Objectives: To provide an in-depth analysis of noninvasive methods for the early diagnosis of oral premalignant lesions, focusing on novel biomarkers and optical technologies, and to discuss their potential in improving the prognosis of patients with oral oncological diseases. Methods: This state-of-the-art review examines various noninvasive diagnostic techniques, including the utilization of salivary microRNAs and optical technologies such as Raman spectroscopy, elastic scattering spectroscopy, diffuse reflectance spectroscopy, narrow-band imaging, autofluorescence imaging, toluidine blue staining, and microendoscopy. Results: Several noninvasive techniques have shown varying degrees of effectiveness in detecting oral cancer. Autofluorescence imaging exhibited sensitivities up to 100% but had variable specificity. toluidine blue staining reported sensitivity between 77% and 100% for high-risk lesions or cancer, with specificity around 45% to 67%. Spectroscopy techniques achieved 72% to 100% sensitivities and specificities of 75% to 98%. Microendoscopy presented a sensitivity of 84% to 95% and a specificity of 91% to 95%. Conclusion: The review highlights the strengths and limitations of each noninvasive diagnostic method and their recent advancements. Although promising results have been demonstrated, there is a need for further development of reliable strategies for early detection and intervention in oral oncology.

Proteomic biomarkers for noninvasive left atrial appendage thrombus prediction in patients with atrial fibrillation

IntroductionThe CHA2DS2-VASc score, used to assess the risk of left atrial appendage thrombus (LAAT) formation in patients with atrial fibrillation (AF), has limited predictive value. Moreover, transesophageal echocardiography imaging, the gold standard diagnostic method to identify thrombi, is semi-invasive. Consequently, there is a need for alternative and noninvasive diagnostic methods for LAAT risk assessment. MethodsDeep proteomic analysis was conducted in plasma samples from 8 patients with nonvalvular AF, divided into thrombus and control groups (4 patients in each group) based on the presence or absence of LAAT. Biomarkers associated with LAAT were validated using an enzyme-linked immunosorbent assay in a cohort of 179 patients with available clinical, transthoracic, and transesophageal echocardiography data. Predictive models were developed to assess the improvement in LAAT identification. ResultsThe LAAT group had higher CHA2DS2-VASc scores, larger LA diameter, and lower LAA flow velocities. Deep proteomic analysis identified 30 differentially expressed proteins, including myosin light chain 4, prenylcysteine oxidase 1 (PCYOX1), and decorin as potential diagnostic biomarkers of LAAT. The model showed that PCYOX1 and decorin provided an area under the curve (AUC) of 0.970 for LAAT prediction compared with 0.672 in a model including the CHA2DS2-VASc score and LAA cauliflower morphology. The incremental value of proteomic biomarkers for LAAT in patients with nonvalvular AF was further confirmed with the net reclassification improvement and integrated discrimination improvement indices. ConclusionsProtein levels of PCYOX1 and decorin improve the predictive performance for LAAT in patients with nonvalvular AF.

Association between essential metals, adherence to healthy lifestyle behavior, and ankle-brachial index

BackgroundAnkle-brachial index (ABI) is a noninvasive diagnostic method for peripheral arterial disease (PAD) and a predictor of cardiovascular events. ObjectiveThe present study aimed to evaluate the association between individual or combined essential metals and ABI, as well as assess the collective impact of essential metals when coupled with healthy lifestyle on ABI. MethodsA total of 2865 participants were recruited in Wuhan Tongji Hospital between August 2018 and March 2019. Concentrations of essential metals in urine were measured by inductively coupled plasma mass spectrometer. ResultsThe results of general linear regression models demonstrated that after adjusting for confounding factors, there was a positive association between ABI increase and per unit increase of log 10-transformed, creatinine-corrected urinary Cr (β (95% CI): 0.010 (0.004, 0.016), PFDR = 0.007), Fe (β (95% CI): 0.010 (0.003, 0.017), PFDR = 0.018), and Co (β (95% CI): 0.013 (0.005, 0.021), PFDR = 0.007). The WQS regression revealed a positive relationship between the mixture of essential metals and ABI (β (95% CI): 0.006 (0.003, 0.010), P < 0.001), with Cr and Co contributing most to the relationship (weighted 45.48% and 40.14%, respectively). Compared to individuals with unfavorable lifestyle and the lowest quartile of Cr, Fe and Co, those with favorable lifestyle and the highest quartile of Cr, Fe and Co exhibited the most increase in ABI (β (95% CI): 0.030 (0.017, 0.044) for Cr, β (95% CI): 0.027 (0.013, 0.040) for Fe, and β (95% CI): 0.030 (0.016, 0.044) for Co). ConclusionIn summary, our study indicates that adequate essential metal intake together with healthy lifestyle behaviors perform crucial roles in PAD protection.

Non-Invasive Tools in Perioperative Stroke Risk Assessment for Asymptomatic Carotid Artery Stenosis with a Focus on the Circle of Willis.

This review aims to explore advancements in perioperative ischemic stroke risk estimation for asymptomatic patients with significant carotid artery stenosis, focusing on Circle of Willis (CoW) morphology based on the CTA or MR diagnostic imaging in the current preoperative diagnostic algorithm. Functional transcranial Doppler (fTCD), near-infrared spectroscopy (NIRS), and optical coherence tomography angiography (OCTA) are discussed in the context of evaluating cerebrovascular reserve capacity and collateral vascular systems, particularly the CoW. These non-invasive diagnostic tools provide additional valuable insights into the cerebral perfusion status. They support biomedical modeling as the gold standard for the prediction of the potential impact of carotid artery stenosis on the hemodynamic changes of cerebral perfusion. Intraoperative risk assessment strategies, including selective shunting, are explored with a focus on CoW variations and their implications for perioperative ischemic stroke and cognitive function decline. By synthesizing these insights, this review underscores the potential of non-invasive diagnostic methods to support clinical decision making and improve asymptomatic patient outcomes by reducing the risk of perioperative ischemic neurological events and preventing further cognitive decline.

Deep learning-assisted diagnosis of benign and malignant parotid tumors based on ultrasound: a retrospective study

BackgroundTo develop a deep learning(DL) model utilizing ultrasound images, and evaluate its efficacy in distinguishing between benign and malignant parotid tumors (PTs), as well as its practicality in assisting clinicians with accurate diagnosis.MethodsA total of 2211 ultrasound images of 980 pathologically confirmed PTs (Training set: n = 721; Validation set: n = 82; Internal-test set: n = 89; External-test set: n = 88) from 907 patients were retrospectively included in this study. The optimal model was selected and the diagnostic performance evaluation is conducted by utilizing the area under curve (AUC) of the receiver-operating characteristic(ROC) based on five different DL networks constructed at varying depths. Furthermore, a comparison of different seniority radiologists was made in the presence of the optimal auxiliary diagnosis model. Additionally, the diagnostic confusion matrix of the optimal model was calculated, and an analysis and summary of misjudged cases’ characteristics were conducted.ResultsThe Resnet18 demonstrated superior diagnostic performance, with an AUC value of 0.947, accuracy of 88.5%, sensitivity of 78.2%, and specificity of 92.7% in internal-test set, and with an AUC value of 0.925, accuracy of 89.8%, sensitivity of 83.3%, and specificity of 90.6% in external-test set. The PTs were subjectively assessed twice by six radiologists, both with and without the assisted of the model. With the assisted of the model, both junior and senior radiologists demonstrated enhanced diagnostic performance. In the internal-test set, there was an increase in AUC values by 0.062 and 0.082 for junior radiologists respectively, while senior radiologists experienced an improvement of 0.066 and 0.106 in their respective AUC values.ConclusionsThe DL model based on ultrasound images demonstrates exceptional capability in distinguishing between benign and malignant PTs, thereby assisting radiologists of varying expertise levels to achieve heightened diagnostic performance, and serve as a noninvasive imaging adjunct diagnostic method for clinical purposes.

New progress on diagnosis and treatment for indeterminate-phase chronic hepatitis B virus-infected patients

Authoritative guidelines at home and abroad typically classify chronic hepatitis B virus (HBV) infection into four stages. However, in clinical practice, a considerable number of patients do not meet the guidelines for staging and are called "indeterminate phase" chronic HBV- infected patients. Studies have shown that patients in the indeterminate phase account for about 30%-50% of chronic HBV infection, have significant liver histological changes or even cirrhosis in a large proportion, and are at a higher risk of HCC and death if they do not receive antiviral therapy. Preliminary research shows that patients in the indeterminate phase who receive antiviral treatment have a good virological response and a remarkable reduced HCC risk. To this end, the 2022 publication "Expert Opinions on Expanding Antiviral Treatment for Chronic Hepatitis B" recommends aggressive treatment for patients with an indeterminate phase who have undergone more than a year of follow-up. However, there is still a lack of unified standards to refine the classification, as well as a lack of effective and rapid non-invasive diagnostic methods to identify patients in the indeterminate phase who are at risk for disease progression. This article aims to review the researches on the proportion, clinical characteristics, disease progression, and treatment benefits to further explore how to better manage indeterminate-phase chronic HBV-infected patients.

Challenges and optimization strategies for clinical research and the development of new drugs for liver fibrosis

Liver fibrosis is a key step in the developmental process of various chronic liver diseases, including cirrhosis. Therefore, the focus and difficulty of liver disease research have always been on how to reverse liver fibrosis. However, due to complex mechanisms, difficulties in endpoint evaluation, a lack of non-invasive diagnostic methods, and other factors, the research and development of new drugs are hindered and lengthy. Currently, some new drugs are being researched and developed, which signifies the prospect is optimistic.