Non-invasive Disease Diagnosis Research Articles

Analysis of the longitudinal stability of human plasma miRNAs and implications for disease biomarkers

There is great interest in developing clinical biomarker assays that can aid in non-invasive diagnosis and/or monitoring of human diseases, such as cancer, cardiovascular disease, and neurological diseases. Yet little is known about the longitudinal stability of miRNAs in human plasma. Here we assessed the intraindividual longitudinal stability of miRNAs in plasma from healthy human adults, and the impact of common factors (e.g., hemolysis, age) that may confound miRNA data. We collected blood by venipuncture biweekly over a 3-month period from 22 research participants who had fasted overnight, isolated total RNA, then performed miRNA qPCR. Filtering and normalization of the qPCR data revealed amplification of 134 miRNAs, 74 of which had high test–retest reliability and low percentage level drift, meaning they were stable in an individual over the 3-month time period. We also determined that, of nuisance factors, hemolysis and tobacco use have the greatest impact on miRNA levels and variance. These findings support that many miRNAs show intraindividual longitudinal stability in plasma from healthy human adults, including some reported as candidate biomarkers for Alzheimer’s disease.

Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects.

Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer's and Parkinson's diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research.

Ultrasensitive sensing urinary cystatin C via an interface-engineered graphene extended-gate field-effect transistor for non-invasive diagnosis of chronic kidney disease

Early chronic kidney disease (CKD) has strong concealment and lacks an efficient, non-invasive, and lable-free detection platform. Cystatin C (Cys C) in urine is closely related to the progress of CKD (especially at the early stage), which is an ideal endogenous marker to evaluate the impairment of renal function. Thus, the accurate detection of urinary Cys C (u-Cys C) is great significant for early prevention and treatment and delaying the course of the disease of CKD patients. Herein, we developed an extended-gate field-effect transistor (EG-FET) sensor for ultrasensitive detection of u-Cys C, which consists of a monolithic interface-engineered graphene EG electrode array and a commercially available MOSFET. Laser-induced graphene (LIG) loaded with sputtered Au NPs in the presence of adhesive Cr (Au NPs/Cr/LIG) boosts the electrical performance of the EG electrode. Meanwhile, Au NPs also serve as linkers to immobilize papain that can selectively form protein complexes with Cys C. Supported by the synergistic effect of multilevel interface-engineered graphene, our sensor exhibits a good linear correlation within the u-Cys C concentration range of 5 ag/μL to 50 ng/μL with low detection limit of 0.05 ag/μL. Our work makes accurate, specific and rapid detection of u-Cys C feasible and promising for early screening for CKD.

Machine learning aided non-invasive diagnosis of coronary heart disease based on tongue features fusion.

Coronary heart disease (CHD) is the first cause of death globally. Hypertension is considered to be the most important independent risk factor for CHD. Early and accurate diagnosis of CHD in patients with hypertension can plays a significant role in reducing the risk and harm of hypertension combined with CHD. To propose a non-invasive method for early diagnosis of coronary heart disease according to tongue image features with the help of machine learning techniques. We collected standard tongue images and extract features by Diagnosis Analysis System (TDAS) and ResNet-50. On the basis of these tongue features, a common machine learning method is used to customize the non-invasive CHD diagnosis algorithm based on tongue image. Based on feature fusion, our algorithm has good performance. The results showed that the XGBoost model with fused features had the best performance with accuracy of 0.869, the AUC of 0.957, the AUPR of 0.961, the precision of 0.926, the recall of 0.806, and the F1-score of 0.862. We provide a feasible, convenient, and non-invasive method for the diagnosis and large-scale screening of CHD. Tongue image information is a possible effective marker for the diagnosis of CHD.

Circulating microRNA detection using electrochemical biosensor for rapid diagnosis of liver disease in dogs

We report a new combination of short probe and target overhangs during hybridisation with a flow-based sample cycling setup for sensitive and specific detection of microRNA-122 biomarker. This setup was used towards liver injury diagnostics in dogs.

Optical imaging techniques for non-invasive diagnosis and monitoring of disease

Medical imaging methods such as optical imaging have advanced significantly in their ability to diagnose and monitor various illnesses without any invasive procedures. Optical imaging offers a detailed view of anatomical structures and molecular processes, utilizing the unique properties of light and its interactions with biological tissues. This paper provides a comprehensive overview of optical imaging principles, including techniques like Optical Coherence Tomography (OCT), fluorescence imaging, and diffuse optical imaging. Optical imaging methods provide non-invasive, detailed views of biological tissues, enabling early disease detection and monitoring, thereby significantly advancing diagnostic capabilities and improving patient outcomes. These methods are used in the detection of diseases such as cancer, cardiovascular conditions, and neurological disorders.

Web photoplethysmography: opportunities and prospects

This literature review is devoted to the possibilities of using in clinical practice a new modification of photoplethysmography – its web version. The use of modern innovative techniques in the form of photo/video fixation of the human skin allows for contactless and remote assessment of the main physiological indicators of human health. This approach is of particular importance in conditions of shortage of medical workers, territorial separation of doctors and patients, restrictions in visiting medical institutions in the event of epidemics/pandemics of infectious diseases and it contributes to the development and implementation of telemedicine technologies in the daily work of medical specialists. The article discusses the possibilities of using web photoplethysmography to assess microcirculation (web capillaroscopy), heart rate and other indicators (respiratory rate, pulse rate, saturation, body temperature, etc.). Web photoplethysmography is a sensitive, simple and effective method of registering vital body functions. Its effectiveness as a possible screening method for detecting rhythm disturbances and its prospects in using blood pressure measurement has already been proven. The possibility of using not only video, but also photographic materials, for example, for the detection of cardiovascular diseases, is also described. No less promising is the possibility of using the method in conjunction with thermometry. The importance of studying aspects of web photoplethysmography is seen in the need to activate the processes of import substitution and technological sovereignty, as one of the main paradigms of our country’s development. It is obvious that the development of contactless research methods is one of the priorities in modern healthcare. Given the widespread availability of various devices, it is necessary to further explore the possibilities of using webcams and mobile devices in medical practice. The development and introduction into routine practice of medical devices that allow remote non-invasive early diagnosis of chronic non-communicable diseases is of special interest.

Doctors' original intentionality in adherence to non-invasive diagnoses benefits MAFLD patients

Precisely diagnosing metabolic dysfunction-associated fatty liver disease (MAFLD) and its severity degree can effectively delay disease progression and have important guiding values for treatment. In recent years, research on non-invasive diagnosis of metabolic dysfunction-associated fatty liver disease has made great progress, suggesting that we should not only give full play advantage to professional personnel in the field of liver disease but also actively cooperate with personnel in other fields to explore different high-performance non-invasive diagnostic methods to achieve early detection, diagnosis, and treatment.

RCAR-UNet: Retinal vessel segmentation network algorithm via novel rough attention mechanism

The health status of the retinal blood vessels is a significant reference for rapid and non-invasive diagnosis of various ophthalmological, diabetic, and cardio-cerebrovascular diseases. However, retinal vessels are characterized by ambiguous boundaries, with multiple thicknesses and obscured lesion areas. These phenomena cause deep neural networks to face the characteristic channel uncertainty when segmenting retinal blood vessels. The uncertainty in feature channels will affect the channel attention coefficient, making the deep neural network incapable of paying attention to the detailed features of retinal vessels. This study proposes a retinal vessel segmentation via a rough channel attention mechanism. First, the method integrates deep neural networks to learn complex features and rough sets to handle uncertainty for designing rough neurons. Second, a rough channel attention mechanism module is constructed based on rough neurons, and embedded in U-Net skip connection for the integration of high-level and low-level features. Then, the residual connections are added to transmit low-level features to high-level to enrich network feature extraction and help back-propagate the gradient when training the model. Finally, multiple comparison experiments were carried out on three public fundus retinal image datasets to verify the validity of Rough Channel Attention Residual U-Net (RCAR-UNet) model. The results show that the RCAR-UNet model offers high superiority in accuracy, sensitivity, F1, and Jaccard similarity, especially for the precise segmentation of fragile blood vessels, guaranteeing blood vessels’ continuity.

Liquid Biopsy: An Evolving Paradigm for Non-invasive Disease Diagnosis and Monitoring in Medicine.

Liquid biopsy stands as an innovative instrument in the realm of precision medicine, enabling non-invasive disease diagnosis and the early detection of cancer. Liquid biopsy helps in the extraction of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and cell-free DNA (cfDNA) from blood samples and other body fluids, thereby facilitating disease diagnosis and prediction of high-risk patients.Various techniques such as advanced sequencing methods and biomarker-based cell capture have led to the isolation and study of the different biomarkers such as ctDNA, cfDNA, and CTCs. These biopsies also have immense potential in the early detection and diagnosis of various diseases across all medical specialties, prediction and screening of high-risk cases, and detection of different immune response patterns in response to infectious diseases, and also help in predicting treatment outcomes. Although liquid biopsy has the potential to disrupt the field of medical diagnosis, it is met by various challenges such as limited tumor-derived components, less specificity, and inadequate advancement in methods to isolate biomarkers. Despite all these challenges, liquid biopsies provide the potential to become a minimally invasive method of diagnosisthat would facilitate real-time monitoring of patients, which differentiates them from traditional tissue biopsies. This article aims to provide a complete overview of the current technologies, different biomarkers, and body fluids that can be used in liquid biopsy and its clinical applications and the potential impact that liquid biopsy holds in the field of precision medicine, facilitating early diagnosis and prompt management of various diseases and cancers.

A novel dimensionality reduction algorithm for Cholangiocarcinoma hyperspectral images

Medical hyperspectral imagery (HSI) has become a promising auxiliary diagnostic tool in the field of medical diagnosis and being offered noninvasive disease diagnosis in many cases. However, the huge number of spectral bands may lead to the curse of dimensionality and increase computational complexity. Thus, dimensionality reduction (DR) is an essential step for hyperspectral preprocessing. To maintain the cubic nature of HSI and extract more discriminative and representative information from original data, we proposed a novel DR method termed tensor-based weight-modified multi-manifold discriminant analysis (TWMDA). In this paper, two weight modified intra-class and inter-class adjacency affinity matrices are constructed to make full use of the class information and strengthen the power of capturing discriminant information from high-dimensional data. After that, balancing the effect of within-class adjacency compactness and between-class adjacency separation to obtain better classification performance in tensor space instead of vector space. Experimental results on Cholangiocarcinoma (CCA) microscope hyperspectral data sets prove the efficiency and superiority of the proposed method. Hence, this novel DR approach would be more beneficial for cancer diagnosis based on HSI.

The retina in Alzheimer’s disease: Anatomy and Pathology

AbstractGrowing evidence suggests that Alzheimer’s disease (AD) pathology is not confined to the brain but also appears in the neurosensory retina. Perceived as an extension of the brain, the retina is visible directly and noninvasively at the vascular, cellular and molecular resolution. Aβ accumulation, vascular amyloidosis, hyperphosphorylated (p)tau, microgliosis, astrogliosis, Müller glia changes, abnormal electroretinography patterns, and neuronal degeneration have all been described in the postmortem retina of AD patients, including in early‐stage cases. Although a few studies were unable to consistently repeat these findings, increased proportion of positive studies from subsequent histological, biochemical, and imaging studies validated the original findings. Several studies further provided data suggesting that the brain and retina follow a similar trajectory during AD progression, potentially due to their common embryonic origin and anatomical proximity. A host of retinal vascular abnormalities including reduced blood flow, foveal avascular zone and arteriole‐to‐venule ratio were observed by in vivo fundus imaging, optical coherence tomography (OCT) or OCT‐angiopathy in preclinical, prodromal and clinical AD patients. Further, retinal vascular platelet‐derived growth factor receptor‐β (PDGFRβ) expression and pericyte loss have been associated with retinal vascular amyloidosis and cerebral amyloid angiopathy in mild cognitively impaired (MCI) and AD patients. A recent proteomics profiling study revealed common molecular signatures in the AD retina and brain, with enriched pathways related to inflammation, vascular and photoreceptor vulnerability. Novel imaging techniques, such as curcumin fluorescence, have correlated increases in retinal amyloid burden with brain amyloid PET load and hippocampal atrophy in patients, and together with vascular changes predicted cognitive deficits. This perspective provides an overview on the evidence of AD pathology in the retina and current gaps in knowledge. Future studies exploring retinal pathology in AD and other neurodegenerative diseases may fundamentally contribute to the development of validated retinal biomarkers for improved noninvasive disease diagnosis and monitoring.

Circulating cell-free nucleic acids of plasma in human aging, healthy aging and longevity: current state of knowledge.

Circulating cell-free nucleic acids (ccfNAs) of plasma are a remarkable source of genetic, epigenetic and transcriptomic materials originating from different cells, tissues and organs of an individual. They have been increasingly studied over the past decade as they can carry several important pieces of information about the health status of an individual, which makes them biomarkers of choice for non-invasive diagnosis of numerous diseases and health conditions. However, few studies have investigated variations of plasma ccfNAs in healthy subjects, particularly in relation to aging, healthy aging and longevity, despite the great variability of these biological processes among individuals. Here, we reviewed several studies that focused on the analysis of circulating cell-free DNA (ccfDNA) and microRNAs (ccfmiRNAs) during aging and in the elderly, including some on exceptionally long-lived individuals, i.e., centenarians. After a brief overview of the types, origins and functions of plasma ccfNAs, we described the variations of both ccfDNA and ccfmiRNAs during aging as well as the identification of several potential ccfDNA-based and ccfmiRNA-based biomarkers of aging, healthy aging and/or longevity. We finally highlighted some prospects offered by ccfNAs for the understanding and improvement of healthy aging and longevity.

Extracellular matrix complexity in biomarker studies: a novel assay detecting total serum tenascin-C reveals different distribution to isoform-specific assays.

Serum biomarkers are the gold standard in non-invasive disease diagnosis and have tremendous potential as prognostic and theranostic tools for patient stratification. Circulating levels of extracellular matrix molecules are gaining traction as an easily accessible means to assess tissue pathology. However, matrix molecules are large, multimodular proteins that are subject to a vast array of post-transcriptional and post-translational modifications. These modifications often occur in a tissue- and/or disease-specific manner, generating hundreds of different variants, each with distinct biological roles. Whilst this complexity can offer unique insight into disease processes, it also has the potential to confound biomarker studies. Tenascin-C is a pro-inflammatory matrix protein expressed at low levels in most healthy tissues but elevated in, and associated with the pathogenesis of, a wide range of autoimmune diseases, fibrosis, and cancer. Analysis of circulating tenascin-C has been widely explored as a disease biomarker. Hundreds of different tenascin-C isoforms can be generated by alternative splicing, and this protein is also modified by glycosylation and citrullination. Current enzyme-linked immunosorbent assays (ELISA) are used to measure serum tenascin-C using antibodies, recognising sites within domains that are alternatively spliced. These studies, therefore, report only levels of specific isoforms that contain these domains, and studies on the detection of total tenascin-C are lacking. As such, circulating tenascin-C levels may be underestimated and/or biologically relevant isoforms overlooked. We developed a highly specific and sensitive ELISA measuring total tenascin-C down to 0.78ng/ml, using antibodies that recognise sites in constitutively expressed domains. In cohorts of people with different inflammatory and musculoskeletal diseases, levels of splice-specific tenascin-C variants were lower than and distributed differently from total tenascin-C. Neither total nor splice-specific tenascin-C levels correlated with the presence of autoantibodies to citrullinated tenascin-C in rheumatoid arthritis (RA) patients. Elevated tenascin-C was not restricted to any one disease and levels were heterogeneous amongst patients with the same disease. These data confirm that its upregulation is not disease-specific, instead suggest that different molecular endotypes or disease stages exist in which pathology is associated with, or independent of, tenascin-C. This immunoassay provides a novel tool for the detection of total tenascin-C that is critical for further biomarker studies. Differences between the distribution of tenascin-C variants and total tenascin-C have implications for the interpretation of studies using isoform-targeted assays. These data highlight the importance of assay design for the detection of multimodular matrix molecules and reveal that there is still much to learn about the intriguingly complex biological roles of distinct matrix proteoforms.

An enzyme-propelled target recycling amplification in combination with broad-spectrum quencher aggregated perylene for multiple MicroRNA detection

MicroRNA (miRNA) are regarded as remarkable biomarkers for quick and non-invasive disease diagnosis. In this study, an enzyme-propelled target recycling amplification in combination with DNA/microRNA double strands and perylene diimide (PDI) broad-spectrum quencher was constructed for the determination of multiple miRNAs. The PDI aggregates can be highly efficient in quenching the RNA/DNA and DNA-labeled fluorophores from visible to near-infrared wavelength with quenching efficiencies of over 98 %. The broad-spectrum quenchers can be then employed to establish a multicolor miRNA sensing system by using a label-free approach. In the presence of miRNA, with the help of enzyme, the target recycling was initiated, resulting in the enhancement of fluorescence. The proposed method was highly sensitive to miRNA-21, miRNA-141 and miRNA-155, and the limit of detection obtained was 2.66 fM, 1.33 fM and 1 fM, respectively. Simultaneous and multiplexed detection of various miRNAs in a homogeneous solution was also accomplished. The sensor was used for the determination of miRNA content in human serum samples and the results obtained were satisfactory.

Integrating Reliable Pt-S Bond-Mediated 3D DNA Nanomachine with Magnetic Separation in a Homogeneous Electrochemical Strategy for Exosomal MicroRNA Detection with Low Background and High Sensitivity.

Precise and sensitive analysis of exosomal microRNA (miRNA) is of great importance for noninvasive early disease diagnosis, but it remains a great challenge to detect exosomal miRNA in human blood samples because of their small size, high sequence homology, and low abundance. Herein, we integrated reliable Pt-S bond-mediated three-dimensional (3D) DNA nanomachine and magnetic separation in a homogeneous electrochemical strategy for the detection of exosomal miRNA with low background and high sensitivity. The 3D DNA nanomachine was easily prepared via a facile and rapid freezing method, and it was capable of resisting the influence of biothiols, thus endowing it with high stability. Notably, the as-developed magnetic 3D DNA nanomachine not only enabled the detection system to have a low background but also coupled with liposome nanocarriers to synergistically amplify the current signal. Consequently, by ingeniously combining the low background and multiple signal-amplification strategies in homogeneous electrochemical biosensing, highly sensitive detection of exosomal miRNA was successfully achieved. More significantly, with good anti-interference ability, the as-proposed method could effectively discriminate plasma samples from cancer patients and healthy subjects, thus showing a high potential for application in the nondestructive early clinical diagnosis of disease.

Brain-derived extracellular vesicles: Potential diagnostic biomarkers for central nervous system diseases.

Extracellular vesicles (EVs) are membrane-enclosed nanovesicles secreted by cells into the extracellular space and contain functional biomolecules, e.g. signaling receptors, bioactive lipids, nucleic acids, and proteins, which can serve as biomarkers. Neurons and glial cells secrete EVs, contributing to various physiological and pathological aspects of brain diseases. EVs confer their role in the bidirectional crosstalk between the central nervous system (CNS) and the periphery owing to their distinctive ability to cross the unique blood-brain barrier (BBB). Thus, EVs in the blood, cerebrospinal fluid (CSF), and urine can be intriguing biomarkers, enabling the minimally invasive diagnosis of CNS diseases. Although there has been an enormous interest in evaluating EVs as promising biomarkers, the lack of ultra-sensitive approaches for isolating and detecting brain-derived EVs (BDEVs) has hindered the development of efficient biomarkers. This review presents the recent salient findings of exosomal biomarkers, focusing on brain disorders. We summarize highly sensitive sensors for EV detection and state-of-the-art methods for single EV detection. Finally, the prospect of developing advanced EV analysis approaches for the non-invasive diagnosis of brain diseases is presented.

BIOM-05. FIRST-IN-HUMAN PROSPECTIVE TRIAL OF SONOBIOPSY IN GLIOBLASTOMA PATIENTS USING NEURONAVIGATION-GUIDED FOCUSED ULTRASOUND

Abstract INTRODUCTION Blood-based liquid biopsy for brain cancer offers a noninvasive alternative to invasive surgical biopsies. However, the presence of the blood-brain barrier (BBB) limits the release of brain tumor-derived molecular biomarkers into the bloodstream for sensitive diagnosis. Focused ultrasound (FUS)-enabled blood-based liquid biopsy (sonobiopsy) locally disrupts the BBB and releases tumor-derived biomarkers into blood circulation. Our previous studies have demonstrated that sonobiopsy improved the detection sensitivity of glioblastoma (GBM)-specific cirulating tumor DNA (ctDNA) in animal models of GBM. This study aimed to evaluate the feasibility and safety of sonobiopsy in enriching circulating tumor biomarkers in a first-in-human, prospective clinical trial. METHODS Five GBM patients (G01-05) were enrolled in the initial study. The sonobiopy procedures were performed prior to tumor resection, using a nimble FUS device integrated with a clinical neuronavigation system. The plasma level of glial fibrillary acidic protein (GFAP) was quantified using ultrasensitive single-molecule array (Simoa), while the cell-free DNA (cfDNA) levels were quantified using Bioanalyzer. Patient-specific tumor variants were comprehensively analyzed using a personalized tumor-informed ctDNA assay (Invitae Personalized Cancer Monitoring assay). Additionally, the two most common GBM-specific tumor variants were analyzed using customized ddPCR assays. RESULTS Analysis of plasmas collected before and after FUS sonication showed sonobiopsy enhanced plasma circulating tumor biomarker levels, including a maximum increase of 1.3-fold for GFAP, 1.6-fold for the concentration of mono-nucleosomal cfDNA fragment (120–280 bp), 1.9-fold increase in patient-specific tumor variant levels, and 5.6-fold increase in the TERT mutation level. Histological analysis of surgically resected tumors confirmed the safety of the procedure. Transcriptome analysis of sonicated and nonsonicated tumor tissues found that FUS sonication mainly modulated cell physical structure-related genes. CONCLUSIONS These feasibility and safety data support the continued investigation of sonobiopsy for noninvasive molecular diagnosis of brain diseases.

T1rho and T2rho based myocardial tissue characterisation in small animals at high-field MRI

Abstract Introduction Cardiac tissue characterisation using T2-based MRI promises non-invasive diagnosis or monitoring of inflammatory heart disease, toxic heart damage after chemotherapy and myocardial infarction or post-infarction patients. T2 relaxation is also an indicator for the detection of myocardial oedema or intramyocardial haemorrhage [1]. However, accurate T2 quantification is challenging due to motion, blood flow and field inhomogeneities, especially in high-field MRI [2]. In this work, we present an alternative to T2 imaging that uses spin-locking (SL) to provide a robust measurement of T2ρ relaxation. It is known from relaxation theory that T2ρ has a sensitivity almost identical to T2 [3]. In the small animal study presented here, cardiac T2ρ quantification is tested for the first time using a newly developed pulse sequence and compared with established methods. Methods All measurements were performed on a preclinical 7T MRI. T2 contrast was prepared using a CPMG (Carr-Purcell-Meiboom-Gill) sequence. T2ρ contrast was conventionally generated by a balanced-SL (BSL) preparation [4]. Furthermore, a new approach for T2ρ was developed based on a MLEV sequence (Malcolm-Levitt, [2]). In contrast to [2], all pulse delays were minimised here, producing pure T2ρ contrast (Fig. 1). The new method was first validated in phantom experiments and then tested in three mice with radial image acquisition accelerated for cardio-MRI. Results The results of the phantom study are shown in figure 2. No significant differences were found between BSL and MLEV for T2ρ quantification (mean deviation 0.74%). In vivo, significant artefacts were observed for T2 (Fig. 3), while both T2ρ methods showed improved image quality. For the evaluation of relaxation times in the left ventricle, the mean across all animals was: T2=22.9±2.6ms (R2=0.979), BSL-T2ρ=51.4±5.4ms (R2=0.983) and MLEV-T2ρ=60.0±3.4ms (R2>0.99). Thus, the MLEV-T2ρ method achieves the most robust quantification with a mean R2>0.99 and provides relaxation time maps with diagnostic image quality. Discussion: In the present study, myocardial T2ρ mapping was tested at 7T. While no significant differences between BSL and MLEV appeared in phantom experiments, significant difference was found in vivo. Here, only the MLEV technique could achieve robust quantification. One reason for the improved performance is the continuous refocusing and minimisation of free dephasing of the transverse magnetisation. The results also show that MLEV-T2ρ has improved image quality and more robust quantification compared to CPMG-T2. Conclusion Cardiac T2ρ quantification is a robust alternative to established T2 imaging and can be applied under high-field conditions. A combined measurement of T1ρ and T2ρ relaxation time could be used for native detection of myocardial fibrosis and oedema.Figure 1)Comparison of image qualityFigure 2)Results in a knockout model

Research on electronic stethoscope system and signal processing algorithm

Stethoscopes have an important role in non-invasive diagnosis of cardiovascular and respiratory diseases, digestive diseases, and other kinds of diseases. The emergence of high-end diagnostic devices and new diagnostic methods have caused the status of the stethoscope to decline. However, stethoscope has the advantages of simple operation, mature auscultation theory and low cost, and thus is still widely used in medical diagnosis. This paper first introduces the design and application of electronic stethoscope solutions based on contact sensors and air coupling sensors, and then introduces advanced algorithms for digital signal processing for the diagnosis and treatment of different diseases, including heart sound noise reduction algorithm, heart sound segmentation algorithm and heart sound feature extraction and recognition algorithm. Finally, this paper summarizes the application of the electronic stethoscope system in medical testing, and its future development direction. In summary, the electronic stethoscope system is a reliable medical testing tool, which can convert sound signals into digital signals through complex signal processing algorithms for more accurate detection of human physiological parameters. The research of this paper will be of great value to the research and application of electronic stethoscopes.