Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-de...Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-density matter,understanding planetary science,and laser-driven fusion energy.However,experimental efforts in this regime have been limited by the lack of accessibility of over-critical densities and the poor spatiotemporal resolution of conventional diagnostics.Over the last decade,the advent of femtosecond brilliant hard X-ray free-electron lasers(XFELs)has opened new horizons to overcome these limitations.Here,for the first time,we present full-scale spatiotemporal measurements of solid-density plasma dynamics,including preplasma generation with tens of nanometer scale length driven by the leading edge of a relativistic laser pulse,ultrafast heating and ionization at the main pulse arrival,the laser-driven blast wave,and transient surface return current-induced compression dynamics up to hundreds of picoseconds after interaction.These observations are enabled by utilizing a novel combination of advanced X-ray diagnostics including small-angle X-ray scattering,resonant X-ray emission spectroscopy,and propagation-based X-ray phase-contrast imaging simultaneously at the European XFEL-HED beamline station.展开更多
According to the 2024 global cancer data from GLOBOCAN,liver cancer ranks the 6th most common malignancy and the 3rd leading cause of cancer-related mortality worldwide[1].Among these cases,hepatocellular carcinoma(HC...According to the 2024 global cancer data from GLOBOCAN,liver cancer ranks the 6th most common malignancy and the 3rd leading cause of cancer-related mortality worldwide[1].Among these cases,hepatocellular carcinoma(HCC)accounts for approximately 85%−90%[2,3].Its incidence and mortality rates remain persistently high worldwide.However,China has the highest incidence and mortality rates of the disease in the world[4].And the majority of patients are diagnosed at intermediate or advanced stages.Thus,identifying novel tumor biomarkers for early detection and implementing precision therapy has long been a key focus of research.展开更多
Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two im...Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two imaging methods in different injury grades and different cartilage subregions,and provide evidence-based basis for the accurate diagnosis of clinical cartilage injury.Methods:Clinical and imaging data of 286 patients with knee joint lesions admitted to the Affiliated Hospital of Xiangtan Medicine and Health Vocational College from January 2020 to June 2023 were collected retrospectively.All patients underwent both traditional MRI sequences and T2 Mapping sequences.The knee joint cartilage was divided into 14 subregions.Two senior radiologists independently diagnosed the images of the two imaging technologies using a blind method and recorded the cartilage injury grades.The sensitivity,specificity,accuracy,positive predictive value,negative predictive value,and area under the receiver operating characteristic curve(AUC)of the two technologies for diagnosing cartilage injury were calculated and compared,and the differences in their diagnostic efficacy in different injury grades and different subregions were analyzed.Results:A total of 4004 cartilage subregions from 286 patients were included in the analysis,including 1836 injured subregions and 2168 normal subregions.The overall sensitivity(89.7%),accuracy(91.2%),and AUC(0.946)of T2 Mapping quantitative imaging for diagnosing cartilage injury were significantly higher than those of traditional MRI(76.3%,82.5%,and 0.852 respectively),with statistically significant differences(p<0.001);there was no significant difference in specificity between the two(93.5%vs 90.8%,p=0.062).Subgroup analysis showed that T2 Mapping had the most significant diagnostic advantage in early cartilage injury(Grade 1),with sensitivity(78.5%)33.2%higher than that of traditional MRI(45.3%)(p<0.001).Conclusion:The diagnostic efficacy of T2 Mapping quantitative imaging for knee joint cartilage injury is significantly superior to that of traditional MRI,especially in the detection of early cartilage injury and accurate evaluation of weight-bearing area injury.Data verify its clinical applicability and reliability.It can be used as an important supplementary method to traditional MRI,and is recommended for the early diagnosis,grading evaluation,and clinical follow-up of cartilage injury.展开更多
Background:Alzheimer's disease(AD)represents the most prevalent neurodegenerative disorder,with mitochondrial dysfunction being observed in both AD patients and mouse models.Nonetheless,further investigation is re...Background:Alzheimer's disease(AD)represents the most prevalent neurodegenerative disorder,with mitochondrial dysfunction being observed in both AD patients and mouse models.Nonetheless,further investigation is required to elucidate the pathogenic genes associated with AD and to develop early diagnostic methodologies centered on mitochondrial function.Methods:In this study,the dataset GSE132903 was retrieved from the GEO database,encompassing both non-demented(ND)control and AD samples.Through the combination of differential expression gene analysis,weighted gene co-expression network analysis,and intersection with mitochondrial database gene sets,four hub genes associated with AD were identified.These four hub genes were subsequently validated in APP/PS1 and 5xFAD mouse models using molecular biology techniques.Results:The hub genes identified through bioinformatics analysis include SYNJ2BP,VDAC1,NUBPL,and COX19.Within the GSE132903 dataset,the expression levels of SYNJ2BP,NUBPL,and COX19 were significantly elevated in the AD group compared to the non-demented(ND)group,whereas VDAC1 expression was reduced in the AD group relative to the ND group.Furthermore,in the hippocampus of APP/PS1 and 5xFAD mouse models,the expression patterns of SYNJ2BP and NUBPL were consistent with the bioinformatics analysis results.Conclusion:Hub genes identified here through bioinformatics and molecular biology may help early diagnosis of AD patients and may also help build new AD models to explore its pathogenesis.展开更多
Oxidative stress significantly contributes to secondary damage after spinal cord injury.Despite its importance,research on oxidative stress in spinal cord injury remains limited.Investigating the expression and regula...Oxidative stress significantly contributes to secondary damage after spinal cord injury.Despite its importance,research on oxidative stress in spinal cord injury remains limited.Investigating the expression and regulation of oxidative stress-related genes could enhance the diagnosis and treatment of spinal cord injury.In this study,we analyzed the sequencing data of human blood samples and injured mouse spinal cord tissue that were sourced from GEO databases and identified diagnostic biomarkers associated with the severity of spinal cord injury.We also explored the expression patterns of oxidative stress-related genes,potential regulatory mechanisms,and therapeutic drugs.To validate our findings,we performed immunofluorescence and quantitative polymerase chain reaction to assess gene expression in the injured spinal cord.Our results revealed biomarkers associated with oxidative stress and immune responses across different levels of spinal cord injury in humans.We identified differentially expressed oxidative stress-related genes and key hub genes in injured mouse spinal cord tissue and revealed their temporal expression patterns at both the tissue and single-cell levels.We also clarified the signaling pathways associated with oxidative stress and identified ligand-receptor pairs among various cell types at different time points after injury.Furthermore,we discovered microRNAs,long non-coding RNAs,and transcription factors that regulate these hub genes and revealed their roles in modulating gene expression at various stages after spinal cord injury.We also identified drugs targeting these hub genes.The findings from this study not only aid in identifying diagnostic biomarkers that reflect the severity of spinal cord injury,but also provide insights into the expression dynamics of oxidative stress-related genes.In addition,the study reveals potential regulatory mechanisms and identifies potential drugs to treat patients with spinal cord injury.展开更多
While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput...While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments.These technologies are emerging as transformative tools in molecular diagnostics and medical research.By integrating histopathological morphology with spatial multi-omics profiling(genome,transcriptome,epigenome,and proteome),spatial omics technologies open an avenue for understanding disease progression,therapeutic resistance mechanisms,and precise diagnosis.It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states,which may greatly facilitate tumor molecular subtyping,prognostic assessment,and prediction of the radiotherapy and chemotherapy efficacy.Despite the substantial advancements in spatial omics,the translation of spatial omics into clinical applications remains challenging due to robustness,efficacy,clinical validation,and cost constraints.In this review,we summarize the current progress and prospects of spatial omics technologies,particularly in medical research and diagnostic applications.展开更多
This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma(OSCC),a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis.Saliv...This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma(OSCC),a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis.Saliva has emerged as a noninvasive diagnostic medium capable of reflecting both local tumor activity and systemic physiological changes.Various salivary biomarkers,including microRNAs,cytokines,proteins,metabolites,and exosomes,have been linked to oncogenic signaling pathways involved in tumor progression,immune modulation,and therapeutic resistance.Advances in quantitative polymerase chain reaction,mass spectrometry,and next-generation sequencing have enabled comprehensive biomarker profiling,while point-of-care detection systems and saliva-based omics platforms are accelerating clinical translation.Remaining challenges include variability in salivary composition,lack of standardized collection protocols,and insufficient validation across large patient cohorts.This review highlights the mechanistic relevance,diagnostic potential,and translational challenges of salivary biomarkers in OSCC.展开更多
This study investigates the variability in cancer diagnosis across different tissues and organs, with a focus on the role of diagnostic methods such as Hematoxylin and Eosin (H&E) staining and immunohistochemistry...This study investigates the variability in cancer diagnosis across different tissues and organs, with a focus on the role of diagnostic methods such as Hematoxylin and Eosin (H&E) staining and immunohistochemistry (IHC). The predominance of female breast cancer (30%) aligns with global trends, underscoring the need for robust diagnostic protocols, particularly in developing regions. Other prevalent cancers, including skin, stomach, and cervix uteri, reflect a mix of environmental, genetic, and infectious factors. The underrepresentation of gallbladder and thyroid cancers (<1%) suggests potential underdiagnosis or lower prevalence. Age distribution data indicate peak cancer incidence in individuals aged 31 - 45 years, with gender-specific cancers like breast and cervical cancer predominantly affecting females (63.4%). The analysis also highlights significant diagnostic gaps, as 61.2% of cases did not undergo IHC testing due to resource constraints, leading to potential biases in cancer prevalence and diagnostic accuracy. The study emphasizes the complementary role of IHC in confirming ambiguous H&E findings, with strong alignment observed when both methods were used. However, the absence of IHC in many cases limits the robustness of conclusions, suggesting the need for increased access to IHC testing. The findings advocate for integrating IHC into routine diagnostics, expanding diagnostic capabilities, and improving sample sizes to ensure more reliable and comprehensive cancer data.展开更多
OBJECTIVE:To reach consensus on the diagnostic criteria of syndrome of dampness obstruction in idiopathic membranous nephropathy(IMN)patients by literature research and expert investigation(interviews and a Delphi met...OBJECTIVE:To reach consensus on the diagnostic criteria of syndrome of dampness obstruction in idiopathic membranous nephropathy(IMN)patients by literature research and expert investigation(interviews and a Delphi method).METHODS:Our study was consistent with T/CACM 1336-2020.We searched the monographs and references published in the past 40 years(1983-2022),and established the diagnostic criteria pool of waterdampness syndrome and dampness-turbidity syndrome in Traditional Chinese Medicine(TCM)based on literature by using frequency statistics and correlation analysis.Expert investigation(interview method and two rounds of Delphi method)was used to form the diagnostic criteria of water-dampness syndrome and dampnessturbidity syndrome of idiopathic membranous nephropathy.Clinical diagnostic test research was carried out,and compared with“Diagnostic Criteria for dampness syndrome”(T/CACM 1454-2023)to evaluate the authenticity,reliability and clinical application value of the standard.RESULTS:A total of 122 relevant guides,standards,monographs and documents were included through searching books and Chinese databases.Four experts were interviewed and two rounds of delphi method(75 experts nationwide)were carried out.The experts'opinions are relatively concentrated and the differences are small.Based on the weight of each index,the diagnostic criteria indexes of water-dampness syndrome and dampness-turbidity syndrome were selected.After discussion by the core group members,the diagnostic model of"necessary symptoms and optional symptoms"was established,and the final diagnostic criteria of waterdampness syndrome and dampness-turbidity syndrome were established.One hundred and ninety-one inpatients and outpatients of Guangdong Provincial Hospital of Chinese Medicine from January 2021 to February 2023 were included in Diagnostic test study.There was no statistical difference in gender,age and course of disease(P>0.05).The sensitivity and specificity of the trial standard were 90.34%and 73.33%respectively,while the sensitivity and specificity of T/CACM 1454-2023 were 99.43%and 6.67%,respectively.CONCLUSIONS:The consensus-based diagnostic criteria for IMN can be widely incorporated in TCM.A further clinical study will be conducted to analyze the diagnosis value and cut-off score of our IMN criteria.展开更多
INTRODUCTION For a considerable time,psychiatry has grappled with how best to define its core diagnostic entities.1-3 Traditional psychiatric classification systems,predominantly the Diagnostic and Statistical Manual ...INTRODUCTION For a considerable time,psychiatry has grappled with how best to define its core diagnostic entities.1-3 Traditional psychiatric classification systems,predominantly the Diagnostic and Statistical Manual of Mental Disorders(DSM)and International Classification of Diseases(ICD),have long been the cornerstones of clinical psychiatry.These systems primarily characterise mental disorders through clusters of observable symptoms rather than underlying pathophysiological mechanisms,making few claims about aetiology or causal pathways.展开更多
BACKGROUND Studies investigating diagnostic delays and their effects on patients with alcoholic cirrhosis.AIM To investigate the current status and associated factors influencing diagnostic delays in 401 patients with...BACKGROUND Studies investigating diagnostic delays and their effects on patients with alcoholic cirrhosis.AIM To investigate the current status and associated factors influencing diagnostic delays in 401 patients with alcoholic cirrhosis.METHODS A cross-sectional analysis was conducted at a tertiary hospital in China from June 2020 to December 2023.Data were collected through telephone follow-ups and questionnaires.The Wilcoxon and Kruskal-Wallis H tests were used to compare diagnostic delays across various characteristics.Multivariate linear regression was employed to identify factors associated with diagnostic delays.RESULTS The median diagnostic delay was 5 months,with an interquartile range of 2-11 months.The proportions of patients with alcoholic cirrhosis who initially visited tertiary,secondary,and primary hospitals were 38.9%,37.91%,and 23.19%,respectively.Furthermore,the rates of patients undergoing liver computed tomography(CT)during their first visit at tertiary,secondary,and primary hospitals were 92.95%,13.82%,and 1.08%,respectively(P<0.001).Significant differences were observed in diagnostic delay-related characteristics,including residence,resident type,initial diagnosis,medical insurance,liver CT,and liver ultrasound during the first visit,age,years of education,family size,marital status,annual family income,years of drinking,daily alcohol consumption,and type of alcohol consumed(P<0.01).Furthermore,diagnostic delays were variably associated with daily alcohol consumption and other characteristics(i.e.residence,years of drinking,medical insurance,years of education,annual family income,liver CT and ultrasound during the first visit).Significant predictors of diagnostic delay identified on multivariate linear regression analysis included years of education,daily alcohol consumption,annual family income and blood ammonia levels(P<0.01).Patients with alcoholic cirrhosis experience varying degrees of diagnostic delays,necessitating interventions targeting potential contributing factors.CONCLUSION Our study indicates that patients with alcoholic cirrhosis may experience varying degrees of diagnostic delay.Interventions targeting potential factors contributing to diagnostic delay are necessary.展开更多
Artificial Intelligence(AI)is fundamentally transforming medical diagnostics,driving advancements that enhance accuracy,efficiency,and personalized patient care.This narrative review explores AI integration across var...Artificial Intelligence(AI)is fundamentally transforming medical diagnostics,driving advancements that enhance accuracy,efficiency,and personalized patient care.This narrative review explores AI integration across various diagnostic domains,emphasizing its role in improving clinical decision-making.The evolution of medical diagnostics from traditional observational methods to sophisticated imaging,laboratory tests,and molecular diagnostics lays the foundation for understanding AI’s impact.Modern diagnostics are inherently complex,influenced by multifactorial disease presentations,patient variability,cognitive biases,and systemic factors like data overload and interdisciplinary collaboration.AI-enhanced clinical decision support systems utilize both knowledge-based and non-knowledge-based approaches,employing machine learning and deep learning algorithms to analyze vast datasets,identify patterns,and generate accurate differential diagnoses.AI’s potential in diagnostics is demonstrated through applications in genomics,predictive analytics,and early disease detection,with successful case studies in oncology,radiology,pathology,ophthalmology,dermatology,gastroenterology,and psychiatry.These applications demonstrate AI’s ability to process complex medical data,facilitate early intervention,and extend specialized care to underserved populations.However,integrating AI into diagnostics faces significant limitations,including technical challenges related to data quality and system integration,regulatory hurdles,ethical concerns about transparency and bias,and risks of misinformation and overreliance.Addressing these challenges requires robust regulatory frameworks,ethical guidelines,and continuous advancements in AI technology.The future of AI in diagnostics promises further innovations in multimodal AI,genomic data integration,and expanding access to high-quality diagnostic services globally.Responsible and ethical implementation of AI will be crucial to fully realize its potential,ensuring AI serves as a powerful ally in achieving diagnostic excellence and improving global health care outcomes.This narrative review emphasizes AI’s pivotal role in shaping the future of medical diagnostics,advocating for sustained investment and collaborative efforts to harness its benefits effectively.展开更多
Pancreatic cancer is recognized as one of the leading causes of cancer mortality,representing the second most common source of cancer-related deaths within the gastrointestinal domain.Surgical resection is currently t...Pancreatic cancer is recognized as one of the leading causes of cancer mortality,representing the second most common source of cancer-related deaths within the gastrointestinal domain.Surgical resection is currently the only definitive treatment;however,the subtle emergence of symptoms often leads to a diagnosis at an advanced stage,with merely 10%-15%of patients being eligible for surgical intervention.The primary obstacle to achieving a potential radical resection is the presence of distant metastatic disease or invasion of adjacent major vascular structures.This review aims to highlight the critical role of endoscopic ultrasound in the diagnosis and staging of pancreatic tumors.We systematically searched PubMed,MEDLINE and Web of Science by using‘pancreatic cancer’and‘endoscopic ultrasonography’as keywords.Relevant studies were reviewed and analyzed.Endoscopic ultrasonography(EUS)is efficient in the diagnosis and staging of pancreatic cancer,past studies reported the accuracy of EUS is 63%to 94%for T-staging and 44%to 82%for N-staging but there are still limitations that need to be comprehensively applied with other diagnostic methods to evaluation of distant metastasis for surgical resectability.Our review aims to reveal the value for the staging of pancreatic cancer.展开更多
BACKGROUND Rectal cancer requires accurate preoperative assessment of T stage and differentiation grade for treatment planning.Traditional imaging and serum markers have limitations in diagnostic accuracy.AIM To evalu...BACKGROUND Rectal cancer requires accurate preoperative assessment of T stage and differentiation grade for treatment planning.Traditional imaging and serum markers have limitations in diagnostic accuracy.AIM To evaluate the predictive value of dynamic contrast-enhanced-magnetic resonance imaging(DCE-MRI)parameters and serum biomarkers[carbohydrate antigen(CA)19-9,CA125]for determining T stage and differentiation grade in rectal cancer.METHODS We conducted a retrospective review of clinical data from 126 patients who were pathologically diagnosed with rectal cancer between January 2021 to June 2024.Each patient underwent DCE-MRI scans and serum tests for CA19-9 and CA125.Receiver operating characteristic curves were utilized to assess the diagnostic value of DCE-MRI parameters,including volume transfer constant(Ktrans),rate constant(Kep),and volume fraction of extravascular extracellular space(Ve),as well as serum biomarkers for staging and grading rectal cancer.The DeLong test algorithm was employed to evaluate differences in diagnostic performance among the various indicators.RESULTS There were statistically higher levels of Ktrans,Ve,CA19-9,and CA125 serum concentrations of patients with advanced T stages and on poorly differentiated tumors than that in patients with low stages and moderate to high differentiation(P<0.05).Combined use of Ktrans and Ve for T stage diagnosis showed an area under the curve(AUC)of 0.892[95%confidence interval(CI):0.832-0.952],which increased to 0.923(95%CI:0.865-0.981)when combined with serum biomarkers.For grades differentiation,the combined DCE-MRI parameters had an AUC of 0.883(95%CI:0.821-0.945),which rose to 0.912(95%CI:0.855-0.969)when combined with serum markers.According to the Delong test,the combined diagnostic method performed better than a single diagnostic method(P<0.05).CONCLUSION The combined application of DCE-MRI functional parameters and serum tumor markers can significantly improve the diagnostic accuracy of T staging and differentiation degree of rectal cancer,providing a new approach to improve the preoperative assessment system of rectal cancer.This combined diagnostic model has important clinical application value,but further validation is needed through large-scale multicenter studies.展开更多
Objective:To explore the application value of artificial intelligence-assisted diagnostic systems in the computed tomography(CT)diagnosis of pulmonary nodules.Methods:A total of 80 patients with pulmonary nodules,trea...Objective:To explore the application value of artificial intelligence-assisted diagnostic systems in the computed tomography(CT)diagnosis of pulmonary nodules.Methods:A total of 80 patients with pulmonary nodules,treated from June 2023 to May 2024,were included.All patients underwent pathological examination and CT scans,with pathological results serving as the gold standard.The diagnostic performance of CT alone and CT combined with the artificial intelligence-assisted diagnostic system was analyzed,and differences in CT imaging features and evaluation results of benign and malignant pulmonary nodules were compared.Results:The sensitivity,specificity,and accuracy of CT combined with the artificial intelligence-assisted diagnostic system were significantly higher than those of CT alone(P<0.05).Moreover,the false-positive and false-negative rates were significantly lower for the combined approach compared to CT alone(P<0.05).Conclusion:The artificial intelligence-assisted diagnostic system effectively identifies malignant features in pulmonary nodules,providing valuable clinical reference data and enhancing diagnostic accuracy and efficiency.展开更多
Several promising plasma biomarker proteins,such as amyloid-β(Aβ),tau,neurofilament light chain,and glial fibrillary acidic protein,are widely used for the diagnosis of neurodegenerative diseases.However,little is k...Several promising plasma biomarker proteins,such as amyloid-β(Aβ),tau,neurofilament light chain,and glial fibrillary acidic protein,are widely used for the diagnosis of neurodegenerative diseases.However,little is known about the long-term stability of these biomarker proteins in plasma samples stored at-80°C.We aimed to explore how storage time would affect the diagnostic accuracy of these biomarkers using a large cohort.Plasma samples from 229 cognitively unimpaired individuals,encompassing healthy controls and those experiencing subjective cognitive decline,as well as 99 patients with cognitive impairment,comprising those with mild cognitive impairment and dementia,were acquired from the Sino Longitudinal Study on Cognitive Decline project.These samples were stored at-80°C for up to 6 years before being used in this study.Our results showed that plasma levels of Aβ42,Aβ40,neurofilament light chain,and glial fibrillary acidic protein were not significantly correlated with sample storage time.However,the level of total tau showed a negative correlation with sample storage time.Notably,in individuals without cognitive impairment,plasma levels of total protein and tau phosphorylated protein threonine 181(p-tau181)also showed a negative correlation with sample storage time.This was not observed in individuals with cognitive impairment.Consequently,we speculate that the diagnostic accuracy of plasma p-tau181 and the p-tau181 to total tau ratio may be influenced by sample storage time.Therefore,caution is advised when using these plasma biomarkers for the identification of neurodegenerative diseases,such as Alzheimer's disease.Furthermore,in cohort studies,it is important to consider the impact of storage time on the overall results.展开更多
Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dim...Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dimensional healthcare data,encompassing genomic,transcriptomic,and other omics profiles,as well as radiological imaging and histopathological slides,makes this approach increasingly important because,when examined separately,these data sources only offer a fragmented picture of intricate disease processes.Multimodal deep learning leverages the complementary properties of multiple data modalities to enable more accurate prognostic modeling,more robust disease characterization,and improved treatment decision-making.This review provides a comprehensive overview of the current state of multimodal deep learning approaches in medical diagnosis.We classify and examine important application domains,such as(1)radiology,where automated report generation and lesion detection are facilitated by image-text integration;(2)histopathology,where fusion models improve tumor classification and grading;and(3)multi-omics,where molecular subtypes and latent biomarkers are revealed through cross-modal learning.We provide an overview of representative research,methodological advancements,and clinical consequences for each domain.Additionally,we critically analyzed the fundamental issues preventing wider adoption,including computational complexity(particularly in training scalable,multi-branch networks),data heterogeneity(resulting from modality-specific noise,resolution variations,and inconsistent annotations),and the challenge of maintaining significant cross-modal correlations during fusion.These problems impede interpretability,which is crucial for clinical trust and use,in addition to performance and generalizability.Lastly,we outline important areas for future research,including the development of standardized protocols for harmonizing data,the creation of lightweight and interpretable fusion architectures,the integration of real-time clinical decision support systems,and the promotion of cooperation for federated multimodal learning.Our goal is to provide researchers and clinicians with a concise overview of the field’s present state,enduring constraints,and exciting directions for further research through this review.展开更多
In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has...In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has emerged as a transformative tool in health care,offering rapid,sensitive,and specific identification of microorganisms.This editorial provides a comprehensive overview of LOC technology,highlighting its principles,advantages,applications,challenges,and future directions.Success studies from the field have demonstrated the practical benefits of LOC devices in clinical diagnostics,epidemiology,and food safety.Comparative studies have underscored the superiority of LOC technology over traditional methods,showcasing improvements in speed,accuracy,and portability.The future integration of LOC with biosensors,artificial intelligence,and data analytics promises further innovation and expansion.This call to action emphasizes the importance of continued research,investment,and adoption to realize the full potential of LOC technology in improving healthcare outcomes worldwide.展开更多
Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer...Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer.Methods We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging(MRI).The morphological characteristics of breast lesions were evaluated using DCE,DWI,and T2WI based on BI-RADS lexicon descriptors by trained radiologists.Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions,and the differences between benign and malignant lesions in each group were compared.Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis.Diagnostic efficacies were compared using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results For mass-like lesions,all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE,DWI,and T2WI(P<0.05).The combined method(DCE+DWI+T2WI)had a higher AUC(0.865)than any of the individual modality(DCE:0.786;DWI:0.793;T2WI:0.809)(P<0.05).For non-mass-like lesions,DWI signal intensity was a significant predictor of malignancy(P=0.036),but the model using DWI alone had a low AUC(0.669).Conclusion Morphological assessment using the combination of DCE,DWI,and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.展开更多
Objective:In recent years,the incidence and detection rate of pancreatic cystic lesions(PCLs)have increased significantly.Endoscopic ultrasound(EUS)plays an indispensable role in the diagnosis and differential diagnos...Objective:In recent years,the incidence and detection rate of pancreatic cystic lesions(PCLs)have increased significantly.Endoscopic ultrasound(EUS)plays an indispensable role in the diagnosis and differential diagnosis of PCLs.However,evidence comparing the diagnostic performance of EUS-guided fine-needle aspiration(EUS-FNA)and fine-needle biopsy(FNB)remains limited.This study aims to compare the diagnostic yield,adequacy of tissue acquisition,and safety between EUS-FNA and EUS-FNB in evaluating PCLs to inform clinical practice.Methods:A retrospective review was conducted on patients with PCLs who underwent either EUS-FNA or EUS-FNB between January 2014 and August 2021.The diagnostic yield,tissue acquisition adequacy,and incidence of adverse events were compared between the 2 groups.Results:A total of 90 patients with PCLs were included(52 in the FNA group and 38 in the FNB group).The diagnostic yield was similar between the FNA and FNB groups(94.2%vs 94.7%,P>0.05).The adequacy of tissue acquisition was 71.2%in the FNA group and 81.6%in the FNB group(P>0.05).No statistically significant difference was observed in the incidence of adverse events between the 2 groups(P>0.05).Conclusion:Both EUS-FNA and EUS-FNB demonstrate equally high diagnostic yields and tissue adequacy in PCLs,with excellent safety profiles.Both methods are safe and effective diagnostic tools for evaluating PCLs.展开更多
基金funding from Grant No. HIDSS-0002 DASHH (Data Science in Hamburg-Helmholtz Graduate School for the Structure of Matter)partially supported by the Helmholtz Imaging platform through the project “Smart Phase.”
文摘Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-density matter,understanding planetary science,and laser-driven fusion energy.However,experimental efforts in this regime have been limited by the lack of accessibility of over-critical densities and the poor spatiotemporal resolution of conventional diagnostics.Over the last decade,the advent of femtosecond brilliant hard X-ray free-electron lasers(XFELs)has opened new horizons to overcome these limitations.Here,for the first time,we present full-scale spatiotemporal measurements of solid-density plasma dynamics,including preplasma generation with tens of nanometer scale length driven by the leading edge of a relativistic laser pulse,ultrafast heating and ionization at the main pulse arrival,the laser-driven blast wave,and transient surface return current-induced compression dynamics up to hundreds of picoseconds after interaction.These observations are enabled by utilizing a novel combination of advanced X-ray diagnostics including small-angle X-ray scattering,resonant X-ray emission spectroscopy,and propagation-based X-ray phase-contrast imaging simultaneously at the European XFEL-HED beamline station.
基金supported by a grant from the Central Level Public Welfare Research Institutes Basic Research Expenses of Chinese Academy of Medical Sciences(No.2023-RW320-05)。
文摘According to the 2024 global cancer data from GLOBOCAN,liver cancer ranks the 6th most common malignancy and the 3rd leading cause of cancer-related mortality worldwide[1].Among these cases,hepatocellular carcinoma(HCC)accounts for approximately 85%−90%[2,3].Its incidence and mortality rates remain persistently high worldwide.However,China has the highest incidence and mortality rates of the disease in the world[4].And the majority of patients are diagnosed at intermediate or advanced stages.Thus,identifying novel tumor biomarkers for early detection and implementing precision therapy has long been a key focus of research.
基金Application Research of MRI Physiological Quantitative Imaging Technology in the Diagnosis of Cartilage Injury(Project No.:RCYJ2021-04)。
文摘Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two imaging methods in different injury grades and different cartilage subregions,and provide evidence-based basis for the accurate diagnosis of clinical cartilage injury.Methods:Clinical and imaging data of 286 patients with knee joint lesions admitted to the Affiliated Hospital of Xiangtan Medicine and Health Vocational College from January 2020 to June 2023 were collected retrospectively.All patients underwent both traditional MRI sequences and T2 Mapping sequences.The knee joint cartilage was divided into 14 subregions.Two senior radiologists independently diagnosed the images of the two imaging technologies using a blind method and recorded the cartilage injury grades.The sensitivity,specificity,accuracy,positive predictive value,negative predictive value,and area under the receiver operating characteristic curve(AUC)of the two technologies for diagnosing cartilage injury were calculated and compared,and the differences in their diagnostic efficacy in different injury grades and different subregions were analyzed.Results:A total of 4004 cartilage subregions from 286 patients were included in the analysis,including 1836 injured subregions and 2168 normal subregions.The overall sensitivity(89.7%),accuracy(91.2%),and AUC(0.946)of T2 Mapping quantitative imaging for diagnosing cartilage injury were significantly higher than those of traditional MRI(76.3%,82.5%,and 0.852 respectively),with statistically significant differences(p<0.001);there was no significant difference in specificity between the two(93.5%vs 90.8%,p=0.062).Subgroup analysis showed that T2 Mapping had the most significant diagnostic advantage in early cartilage injury(Grade 1),with sensitivity(78.5%)33.2%higher than that of traditional MRI(45.3%)(p<0.001).Conclusion:The diagnostic efficacy of T2 Mapping quantitative imaging for knee joint cartilage injury is significantly superior to that of traditional MRI,especially in the detection of early cartilage injury and accurate evaluation of weight-bearing area injury.Data verify its clinical applicability and reliability.It can be used as an important supplementary method to traditional MRI,and is recommended for the early diagnosis,grading evaluation,and clinical follow-up of cartilage injury.
基金Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences,Grant/Award Number:2023-PT180-01 and 2023-PT330-01Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences,Grant/Award Number:2021-I2M-1-034National Natural Science Foundation of China,Grant/Award Number:82161138027。
文摘Background:Alzheimer's disease(AD)represents the most prevalent neurodegenerative disorder,with mitochondrial dysfunction being observed in both AD patients and mouse models.Nonetheless,further investigation is required to elucidate the pathogenic genes associated with AD and to develop early diagnostic methodologies centered on mitochondrial function.Methods:In this study,the dataset GSE132903 was retrieved from the GEO database,encompassing both non-demented(ND)control and AD samples.Through the combination of differential expression gene analysis,weighted gene co-expression network analysis,and intersection with mitochondrial database gene sets,four hub genes associated with AD were identified.These four hub genes were subsequently validated in APP/PS1 and 5xFAD mouse models using molecular biology techniques.Results:The hub genes identified through bioinformatics analysis include SYNJ2BP,VDAC1,NUBPL,and COX19.Within the GSE132903 dataset,the expression levels of SYNJ2BP,NUBPL,and COX19 were significantly elevated in the AD group compared to the non-demented(ND)group,whereas VDAC1 expression was reduced in the AD group relative to the ND group.Furthermore,in the hippocampus of APP/PS1 and 5xFAD mouse models,the expression patterns of SYNJ2BP and NUBPL were consistent with the bioinformatics analysis results.Conclusion:Hub genes identified here through bioinformatics and molecular biology may help early diagnosis of AD patients and may also help build new AD models to explore its pathogenesis.
基金supported by Shenzhen Science and Technology Program, No. JCYJ20230807110259002 (to JL)The Seventh Affiliated Hospital of Sun Yat-sen University, No. ZSQYRSFPD0050 (to JL)The Postdoctoral Fellowship Program of CPSF, No. GZC20242074 (to KT)
文摘Oxidative stress significantly contributes to secondary damage after spinal cord injury.Despite its importance,research on oxidative stress in spinal cord injury remains limited.Investigating the expression and regulation of oxidative stress-related genes could enhance the diagnosis and treatment of spinal cord injury.In this study,we analyzed the sequencing data of human blood samples and injured mouse spinal cord tissue that were sourced from GEO databases and identified diagnostic biomarkers associated with the severity of spinal cord injury.We also explored the expression patterns of oxidative stress-related genes,potential regulatory mechanisms,and therapeutic drugs.To validate our findings,we performed immunofluorescence and quantitative polymerase chain reaction to assess gene expression in the injured spinal cord.Our results revealed biomarkers associated with oxidative stress and immune responses across different levels of spinal cord injury in humans.We identified differentially expressed oxidative stress-related genes and key hub genes in injured mouse spinal cord tissue and revealed their temporal expression patterns at both the tissue and single-cell levels.We also clarified the signaling pathways associated with oxidative stress and identified ligand-receptor pairs among various cell types at different time points after injury.Furthermore,we discovered microRNAs,long non-coding RNAs,and transcription factors that regulate these hub genes and revealed their roles in modulating gene expression at various stages after spinal cord injury.We also identified drugs targeting these hub genes.The findings from this study not only aid in identifying diagnostic biomarkers that reflect the severity of spinal cord injury,but also provide insights into the expression dynamics of oxidative stress-related genes.In addition,the study reveals potential regulatory mechanisms and identifies potential drugs to treat patients with spinal cord injury.
基金supported by the National Natural Science Foundation of China(32171022,32221005,and 32401246).
文摘While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments.These technologies are emerging as transformative tools in molecular diagnostics and medical research.By integrating histopathological morphology with spatial multi-omics profiling(genome,transcriptome,epigenome,and proteome),spatial omics technologies open an avenue for understanding disease progression,therapeutic resistance mechanisms,and precise diagnosis.It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states,which may greatly facilitate tumor molecular subtyping,prognostic assessment,and prediction of the radiotherapy and chemotherapy efficacy.Despite the substantial advancements in spatial omics,the translation of spatial omics into clinical applications remains challenging due to robustness,efficacy,clinical validation,and cost constraints.In this review,we summarize the current progress and prospects of spatial omics technologies,particularly in medical research and diagnostic applications.
基金supported by the College of Oral Medicine,Taipei Medical University,Taipei,Taiwan(Grant No.TMUCOM202502)supported by Taipei Medical University Hospital,Taipei,Taiwan(Grant No.114TMUH-NE-05).
文摘This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma(OSCC),a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis.Saliva has emerged as a noninvasive diagnostic medium capable of reflecting both local tumor activity and systemic physiological changes.Various salivary biomarkers,including microRNAs,cytokines,proteins,metabolites,and exosomes,have been linked to oncogenic signaling pathways involved in tumor progression,immune modulation,and therapeutic resistance.Advances in quantitative polymerase chain reaction,mass spectrometry,and next-generation sequencing have enabled comprehensive biomarker profiling,while point-of-care detection systems and saliva-based omics platforms are accelerating clinical translation.Remaining challenges include variability in salivary composition,lack of standardized collection protocols,and insufficient validation across large patient cohorts.This review highlights the mechanistic relevance,diagnostic potential,and translational challenges of salivary biomarkers in OSCC.
文摘This study investigates the variability in cancer diagnosis across different tissues and organs, with a focus on the role of diagnostic methods such as Hematoxylin and Eosin (H&E) staining and immunohistochemistry (IHC). The predominance of female breast cancer (30%) aligns with global trends, underscoring the need for robust diagnostic protocols, particularly in developing regions. Other prevalent cancers, including skin, stomach, and cervix uteri, reflect a mix of environmental, genetic, and infectious factors. The underrepresentation of gallbladder and thyroid cancers (<1%) suggests potential underdiagnosis or lower prevalence. Age distribution data indicate peak cancer incidence in individuals aged 31 - 45 years, with gender-specific cancers like breast and cervical cancer predominantly affecting females (63.4%). The analysis also highlights significant diagnostic gaps, as 61.2% of cases did not undergo IHC testing due to resource constraints, leading to potential biases in cancer prevalence and diagnostic accuracy. The study emphasizes the complementary role of IHC in confirming ambiguous H&E findings, with strong alignment observed when both methods were used. However, the absence of IHC in many cases limits the robustness of conclusions, suggesting the need for increased access to IHC testing. The findings advocate for integrating IHC into routine diagnostics, expanding diagnostic capabilities, and improving sample sizes to ensure more reliable and comprehensive cancer data.
基金the Special Project of State Key Laboratory of Dampness Syndrome of Chinese Medicine:Study on Criteria for Diagnosis of Dampness Syndrome of Idiopathic Membranous Nephropathy,Cohort Study on Pathogenesis and Material Basis of Dampness Syndrome of Idiopathic Membranous Nephropathy,Randomized Controlled Clinical Study of Sanqi Qushi Granule in Treatment of Membranous Nephropathy(No.SZ2021ZZ02,SZ2021ZZ09 and SZ2021ZZ36)the 2020 Guangdong Provincial Science and Technology Innovation Strategy Special Fund:Guangdong-Hong Kong-Macao Joint Lab(No.2020B1212030006)+2 种基金the Natural Science Foundation of Guangdong Province:Study on the Mechanism of Sanqi Qushi Prescription Delaying Podocellular Senescence in Membranous Nephropathy based on Cyclic Guanosine Monophosphate-Adenosine Monophosphate Synthase-Stimulator of Interferon Genes-Nuclear Factor Kappa-B Signaling Pathway(No.2022A1515011628)the Guangzhou Science and Technology Plan Project:to Explore the Mechanism of Treating Membranous Nephropathy from the Perspective of Regulating Amino Acid Metabolism Disorder(No.2023A03J0746)Special Funding for Scientific and Technological Research on Traditional Chinese Medicine,Guangdong Provincial Hospital of Chinese Medicine:a Multimodular Machine Learning Prediction Model based on Pathological Image-transcriptomics and Traditional Chinese Medicine Syndromes was Used to Investigate the Prognostic Correlation of Long non-coding RNA Molecules in Nephropathy and the Intervention Mechanism of Sanqi Qushi Formula,to Investigate the Pathogenesis and Microbiological Mechanism of Dampness Syndrome of Membranous Nephropathy based on the Microecological Changes of Tongue Coating(No.YN2023MB02,YN2023MB10)。
文摘OBJECTIVE:To reach consensus on the diagnostic criteria of syndrome of dampness obstruction in idiopathic membranous nephropathy(IMN)patients by literature research and expert investigation(interviews and a Delphi method).METHODS:Our study was consistent with T/CACM 1336-2020.We searched the monographs and references published in the past 40 years(1983-2022),and established the diagnostic criteria pool of waterdampness syndrome and dampness-turbidity syndrome in Traditional Chinese Medicine(TCM)based on literature by using frequency statistics and correlation analysis.Expert investigation(interview method and two rounds of Delphi method)was used to form the diagnostic criteria of water-dampness syndrome and dampnessturbidity syndrome of idiopathic membranous nephropathy.Clinical diagnostic test research was carried out,and compared with“Diagnostic Criteria for dampness syndrome”(T/CACM 1454-2023)to evaluate the authenticity,reliability and clinical application value of the standard.RESULTS:A total of 122 relevant guides,standards,monographs and documents were included through searching books and Chinese databases.Four experts were interviewed and two rounds of delphi method(75 experts nationwide)were carried out.The experts'opinions are relatively concentrated and the differences are small.Based on the weight of each index,the diagnostic criteria indexes of water-dampness syndrome and dampness-turbidity syndrome were selected.After discussion by the core group members,the diagnostic model of"necessary symptoms and optional symptoms"was established,and the final diagnostic criteria of waterdampness syndrome and dampness-turbidity syndrome were established.One hundred and ninety-one inpatients and outpatients of Guangdong Provincial Hospital of Chinese Medicine from January 2021 to February 2023 were included in Diagnostic test study.There was no statistical difference in gender,age and course of disease(P>0.05).The sensitivity and specificity of the trial standard were 90.34%and 73.33%respectively,while the sensitivity and specificity of T/CACM 1454-2023 were 99.43%and 6.67%,respectively.CONCLUSIONS:The consensus-based diagnostic criteria for IMN can be widely incorporated in TCM.A further clinical study will be conducted to analyze the diagnosis value and cut-off score of our IMN criteria.
文摘INTRODUCTION For a considerable time,psychiatry has grappled with how best to define its core diagnostic entities.1-3 Traditional psychiatric classification systems,predominantly the Diagnostic and Statistical Manual of Mental Disorders(DSM)and International Classification of Diseases(ICD),have long been the cornerstones of clinical psychiatry.These systems primarily characterise mental disorders through clusters of observable symptoms rather than underlying pathophysiological mechanisms,making few claims about aetiology or causal pathways.
基金Supported by National Key Research and Development Program of China,No.2019YFE0190800.
文摘BACKGROUND Studies investigating diagnostic delays and their effects on patients with alcoholic cirrhosis.AIM To investigate the current status and associated factors influencing diagnostic delays in 401 patients with alcoholic cirrhosis.METHODS A cross-sectional analysis was conducted at a tertiary hospital in China from June 2020 to December 2023.Data were collected through telephone follow-ups and questionnaires.The Wilcoxon and Kruskal-Wallis H tests were used to compare diagnostic delays across various characteristics.Multivariate linear regression was employed to identify factors associated with diagnostic delays.RESULTS The median diagnostic delay was 5 months,with an interquartile range of 2-11 months.The proportions of patients with alcoholic cirrhosis who initially visited tertiary,secondary,and primary hospitals were 38.9%,37.91%,and 23.19%,respectively.Furthermore,the rates of patients undergoing liver computed tomography(CT)during their first visit at tertiary,secondary,and primary hospitals were 92.95%,13.82%,and 1.08%,respectively(P<0.001).Significant differences were observed in diagnostic delay-related characteristics,including residence,resident type,initial diagnosis,medical insurance,liver CT,and liver ultrasound during the first visit,age,years of education,family size,marital status,annual family income,years of drinking,daily alcohol consumption,and type of alcohol consumed(P<0.01).Furthermore,diagnostic delays were variably associated with daily alcohol consumption and other characteristics(i.e.residence,years of drinking,medical insurance,years of education,annual family income,liver CT and ultrasound during the first visit).Significant predictors of diagnostic delay identified on multivariate linear regression analysis included years of education,daily alcohol consumption,annual family income and blood ammonia levels(P<0.01).Patients with alcoholic cirrhosis experience varying degrees of diagnostic delays,necessitating interventions targeting potential contributing factors.CONCLUSION Our study indicates that patients with alcoholic cirrhosis may experience varying degrees of diagnostic delay.Interventions targeting potential factors contributing to diagnostic delay are necessary.
文摘Artificial Intelligence(AI)is fundamentally transforming medical diagnostics,driving advancements that enhance accuracy,efficiency,and personalized patient care.This narrative review explores AI integration across various diagnostic domains,emphasizing its role in improving clinical decision-making.The evolution of medical diagnostics from traditional observational methods to sophisticated imaging,laboratory tests,and molecular diagnostics lays the foundation for understanding AI’s impact.Modern diagnostics are inherently complex,influenced by multifactorial disease presentations,patient variability,cognitive biases,and systemic factors like data overload and interdisciplinary collaboration.AI-enhanced clinical decision support systems utilize both knowledge-based and non-knowledge-based approaches,employing machine learning and deep learning algorithms to analyze vast datasets,identify patterns,and generate accurate differential diagnoses.AI’s potential in diagnostics is demonstrated through applications in genomics,predictive analytics,and early disease detection,with successful case studies in oncology,radiology,pathology,ophthalmology,dermatology,gastroenterology,and psychiatry.These applications demonstrate AI’s ability to process complex medical data,facilitate early intervention,and extend specialized care to underserved populations.However,integrating AI into diagnostics faces significant limitations,including technical challenges related to data quality and system integration,regulatory hurdles,ethical concerns about transparency and bias,and risks of misinformation and overreliance.Addressing these challenges requires robust regulatory frameworks,ethical guidelines,and continuous advancements in AI technology.The future of AI in diagnostics promises further innovations in multimodal AI,genomic data integration,and expanding access to high-quality diagnostic services globally.Responsible and ethical implementation of AI will be crucial to fully realize its potential,ensuring AI serves as a powerful ally in achieving diagnostic excellence and improving global health care outcomes.This narrative review emphasizes AI’s pivotal role in shaping the future of medical diagnostics,advocating for sustained investment and collaborative efforts to harness its benefits effectively.
文摘Pancreatic cancer is recognized as one of the leading causes of cancer mortality,representing the second most common source of cancer-related deaths within the gastrointestinal domain.Surgical resection is currently the only definitive treatment;however,the subtle emergence of symptoms often leads to a diagnosis at an advanced stage,with merely 10%-15%of patients being eligible for surgical intervention.The primary obstacle to achieving a potential radical resection is the presence of distant metastatic disease or invasion of adjacent major vascular structures.This review aims to highlight the critical role of endoscopic ultrasound in the diagnosis and staging of pancreatic tumors.We systematically searched PubMed,MEDLINE and Web of Science by using‘pancreatic cancer’and‘endoscopic ultrasonography’as keywords.Relevant studies were reviewed and analyzed.Endoscopic ultrasonography(EUS)is efficient in the diagnosis and staging of pancreatic cancer,past studies reported the accuracy of EUS is 63%to 94%for T-staging and 44%to 82%for N-staging but there are still limitations that need to be comprehensively applied with other diagnostic methods to evaluation of distant metastasis for surgical resectability.Our review aims to reveal the value for the staging of pancreatic cancer.
文摘BACKGROUND Rectal cancer requires accurate preoperative assessment of T stage and differentiation grade for treatment planning.Traditional imaging and serum markers have limitations in diagnostic accuracy.AIM To evaluate the predictive value of dynamic contrast-enhanced-magnetic resonance imaging(DCE-MRI)parameters and serum biomarkers[carbohydrate antigen(CA)19-9,CA125]for determining T stage and differentiation grade in rectal cancer.METHODS We conducted a retrospective review of clinical data from 126 patients who were pathologically diagnosed with rectal cancer between January 2021 to June 2024.Each patient underwent DCE-MRI scans and serum tests for CA19-9 and CA125.Receiver operating characteristic curves were utilized to assess the diagnostic value of DCE-MRI parameters,including volume transfer constant(Ktrans),rate constant(Kep),and volume fraction of extravascular extracellular space(Ve),as well as serum biomarkers for staging and grading rectal cancer.The DeLong test algorithm was employed to evaluate differences in diagnostic performance among the various indicators.RESULTS There were statistically higher levels of Ktrans,Ve,CA19-9,and CA125 serum concentrations of patients with advanced T stages and on poorly differentiated tumors than that in patients with low stages and moderate to high differentiation(P<0.05).Combined use of Ktrans and Ve for T stage diagnosis showed an area under the curve(AUC)of 0.892[95%confidence interval(CI):0.832-0.952],which increased to 0.923(95%CI:0.865-0.981)when combined with serum biomarkers.For grades differentiation,the combined DCE-MRI parameters had an AUC of 0.883(95%CI:0.821-0.945),which rose to 0.912(95%CI:0.855-0.969)when combined with serum markers.According to the Delong test,the combined diagnostic method performed better than a single diagnostic method(P<0.05).CONCLUSION The combined application of DCE-MRI functional parameters and serum tumor markers can significantly improve the diagnostic accuracy of T staging and differentiation degree of rectal cancer,providing a new approach to improve the preoperative assessment system of rectal cancer.This combined diagnostic model has important clinical application value,but further validation is needed through large-scale multicenter studies.
基金supported by Chengdu University of Traditional Chinese Medicine“Xinglin Scholars”Subject Talent Scientific Research Enhancement Plan(No.YYZX2022056).
文摘Objective:To explore the application value of artificial intelligence-assisted diagnostic systems in the computed tomography(CT)diagnosis of pulmonary nodules.Methods:A total of 80 patients with pulmonary nodules,treated from June 2023 to May 2024,were included.All patients underwent pathological examination and CT scans,with pathological results serving as the gold standard.The diagnostic performance of CT alone and CT combined with the artificial intelligence-assisted diagnostic system was analyzed,and differences in CT imaging features and evaluation results of benign and malignant pulmonary nodules were compared.Results:The sensitivity,specificity,and accuracy of CT combined with the artificial intelligence-assisted diagnostic system were significantly higher than those of CT alone(P<0.05).Moreover,the false-positive and false-negative rates were significantly lower for the combined approach compared to CT alone(P<0.05).Conclusion:The artificial intelligence-assisted diagnostic system effectively identifies malignant features in pulmonary nodules,providing valuable clinical reference data and enhancing diagnostic accuracy and efficiency.
基金supported by the National Key Research&Development Program of China,Nos.2021YFC2501205(to YC),2022YFC24069004(to JL)the STI2030-Major Project,Nos.2021ZD0201101(to YC),2022ZD0211800(to YH)+2 种基金the National Natural Science Foundation of China(Major International Joint Research Project),No.82020108013(to YH)the Sino-German Center for Research Promotion,No.M-0759(to YH)a grant from Beijing Municipal Science&Technology Commission(Beijing Brain Initiative),No.Z201100005520018(to JL)。
文摘Several promising plasma biomarker proteins,such as amyloid-β(Aβ),tau,neurofilament light chain,and glial fibrillary acidic protein,are widely used for the diagnosis of neurodegenerative diseases.However,little is known about the long-term stability of these biomarker proteins in plasma samples stored at-80°C.We aimed to explore how storage time would affect the diagnostic accuracy of these biomarkers using a large cohort.Plasma samples from 229 cognitively unimpaired individuals,encompassing healthy controls and those experiencing subjective cognitive decline,as well as 99 patients with cognitive impairment,comprising those with mild cognitive impairment and dementia,were acquired from the Sino Longitudinal Study on Cognitive Decline project.These samples were stored at-80°C for up to 6 years before being used in this study.Our results showed that plasma levels of Aβ42,Aβ40,neurofilament light chain,and glial fibrillary acidic protein were not significantly correlated with sample storage time.However,the level of total tau showed a negative correlation with sample storage time.Notably,in individuals without cognitive impairment,plasma levels of total protein and tau phosphorylated protein threonine 181(p-tau181)also showed a negative correlation with sample storage time.This was not observed in individuals with cognitive impairment.Consequently,we speculate that the diagnostic accuracy of plasma p-tau181 and the p-tau181 to total tau ratio may be influenced by sample storage time.Therefore,caution is advised when using these plasma biomarkers for the identification of neurodegenerative diseases,such as Alzheimer's disease.Furthermore,in cohort studies,it is important to consider the impact of storage time on the overall results.
文摘Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dimensional healthcare data,encompassing genomic,transcriptomic,and other omics profiles,as well as radiological imaging and histopathological slides,makes this approach increasingly important because,when examined separately,these data sources only offer a fragmented picture of intricate disease processes.Multimodal deep learning leverages the complementary properties of multiple data modalities to enable more accurate prognostic modeling,more robust disease characterization,and improved treatment decision-making.This review provides a comprehensive overview of the current state of multimodal deep learning approaches in medical diagnosis.We classify and examine important application domains,such as(1)radiology,where automated report generation and lesion detection are facilitated by image-text integration;(2)histopathology,where fusion models improve tumor classification and grading;and(3)multi-omics,where molecular subtypes and latent biomarkers are revealed through cross-modal learning.We provide an overview of representative research,methodological advancements,and clinical consequences for each domain.Additionally,we critically analyzed the fundamental issues preventing wider adoption,including computational complexity(particularly in training scalable,multi-branch networks),data heterogeneity(resulting from modality-specific noise,resolution variations,and inconsistent annotations),and the challenge of maintaining significant cross-modal correlations during fusion.These problems impede interpretability,which is crucial for clinical trust and use,in addition to performance and generalizability.Lastly,we outline important areas for future research,including the development of standardized protocols for harmonizing data,the creation of lightweight and interpretable fusion architectures,the integration of real-time clinical decision support systems,and the promotion of cooperation for federated multimodal learning.Our goal is to provide researchers and clinicians with a concise overview of the field’s present state,enduring constraints,and exciting directions for further research through this review.
文摘In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has emerged as a transformative tool in health care,offering rapid,sensitive,and specific identification of microorganisms.This editorial provides a comprehensive overview of LOC technology,highlighting its principles,advantages,applications,challenges,and future directions.Success studies from the field have demonstrated the practical benefits of LOC devices in clinical diagnostics,epidemiology,and food safety.Comparative studies have underscored the superiority of LOC technology over traditional methods,showcasing improvements in speed,accuracy,and portability.The future integration of LOC with biosensors,artificial intelligence,and data analytics promises further innovation and expansion.This call to action emphasizes the importance of continued research,investment,and adoption to realize the full potential of LOC technology in improving healthcare outcomes worldwide.
文摘Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer.Methods We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging(MRI).The morphological characteristics of breast lesions were evaluated using DCE,DWI,and T2WI based on BI-RADS lexicon descriptors by trained radiologists.Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions,and the differences between benign and malignant lesions in each group were compared.Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis.Diagnostic efficacies were compared using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results For mass-like lesions,all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE,DWI,and T2WI(P<0.05).The combined method(DCE+DWI+T2WI)had a higher AUC(0.865)than any of the individual modality(DCE:0.786;DWI:0.793;T2WI:0.809)(P<0.05).For non-mass-like lesions,DWI signal intensity was a significant predictor of malignancy(P=0.036),but the model using DWI alone had a low AUC(0.669).Conclusion Morphological assessment using the combination of DCE,DWI,and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.
基金supported by the Special Project for the Construction of Innovative Provinces in Hunan Province,China(2020SK2013)。
文摘Objective:In recent years,the incidence and detection rate of pancreatic cystic lesions(PCLs)have increased significantly.Endoscopic ultrasound(EUS)plays an indispensable role in the diagnosis and differential diagnosis of PCLs.However,evidence comparing the diagnostic performance of EUS-guided fine-needle aspiration(EUS-FNA)and fine-needle biopsy(FNB)remains limited.This study aims to compare the diagnostic yield,adequacy of tissue acquisition,and safety between EUS-FNA and EUS-FNB in evaluating PCLs to inform clinical practice.Methods:A retrospective review was conducted on patients with PCLs who underwent either EUS-FNA or EUS-FNB between January 2014 and August 2021.The diagnostic yield,tissue acquisition adequacy,and incidence of adverse events were compared between the 2 groups.Results:A total of 90 patients with PCLs were included(52 in the FNA group and 38 in the FNB group).The diagnostic yield was similar between the FNA and FNB groups(94.2%vs 94.7%,P>0.05).The adequacy of tissue acquisition was 71.2%in the FNA group and 81.6%in the FNB group(P>0.05).No statistically significant difference was observed in the incidence of adverse events between the 2 groups(P>0.05).Conclusion:Both EUS-FNA and EUS-FNB demonstrate equally high diagnostic yields and tissue adequacy in PCLs,with excellent safety profiles.Both methods are safe and effective diagnostic tools for evaluating PCLs.
