The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-effic...The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.展开更多
Colorectal cancer(CRC)with lung oligometastases,particularly in the presence of extrapulmonary disease,poses considerable therapeutic challenges in clinical practice.We have carefully studied the multicenter study by ...Colorectal cancer(CRC)with lung oligometastases,particularly in the presence of extrapulmonary disease,poses considerable therapeutic challenges in clinical practice.We have carefully studied the multicenter study by Hu et al,which evaluated the survival outcomes of patients with metastatic CRC who received image-guided thermal ablation(IGTA).These findings provide valuable clinical evidence supporting IGTA as a feasible,minimally invasive approach and underscore the prognostic significance of metastatic distribution.However,the study by Hu et al has several limitations,including that not all pulmonary lesions were pathologically confirmed,postoperative follow-up mainly relied on dynamic contrast-enhanced computed tomography,no comparative analysis was performed with other local treatments,and the impact of other imaging features on efficacy and prognosis was not evaluated.Future studies should include complete pathological confirmation,integrate functional imaging and radiomics,and use prospective multicenter collaboration to optimize patient selection standards for IGTA treatment,strengthen its clinical evidence base,and ultimately promote individualized decision-making for patients with metastatic CRC.展开更多
Microscopy imaging is fundamental in analyzing bacterial morphology and dynamics,offering critical insights into bacterial physiology and pathogenicity.Image segmentation techniques enable quantitative analysis of bac...Microscopy imaging is fundamental in analyzing bacterial morphology and dynamics,offering critical insights into bacterial physiology and pathogenicity.Image segmentation techniques enable quantitative analysis of bacterial structures,facilitating precise measurement of morphological variations and population behaviors at single-cell resolution.This paper reviews advancements in bacterial image segmentation,emphasizing the shift from traditional thresholding and watershed methods to deep learning-driven approaches.Convolutional neural networks(CNNs),U-Net architectures,and three-dimensional(3D)frameworks excel at segmenting dense biofilms and resolving antibiotic-induced morphological changes.These methods combine automated feature extraction with physics-informed postprocessing.Despite progress,challenges persist in computational efficiency,cross-species generalizability,and integration with multimodal experimental workflows.Future progress will depend on improving model robustness across species and imaging modalities,integrating multimodal data for phenotype-function mapping,and developing standard pipelines that link computational tools with clinical diagnostics.These innovations will expand microbial phenotyping beyond structural analysis,enabling deeper insights into bacterial physiology and ecological interactions.展开更多
Background:Brain volume measurement serves as a critical approach for assessing brain health status.Considering the close biological connection between the eyes and brain,this study aims to investigate the feasibility...Background:Brain volume measurement serves as a critical approach for assessing brain health status.Considering the close biological connection between the eyes and brain,this study aims to investigate the feasibility of estimating brain volume through retinal fundus imaging integrated with clinical metadata,and to offer a cost-effective approach for assessing brain health.Methods:Based on clinical information,retinal fundus images,and neuroimaging data derived from a multicenter,population-based cohort study,the Kai Luan Study,we proposed a cross-modal correlation representation(CMCR)network to elucidate the intricate co-degenerative relationships between the eyes and brain for 755 subjects.Specifically,individual clinical information,which has been followed up for as long as 12 years,was encoded as a prompt to enhance the accuracy of brain volume estimation.Independent internal validation and external validation were performed to assess the robustness of the proposed model.Root mean square error(RMSE),peak signal-tonoise ratio(PSNR),and structural similarity index measure(SSIM)metrics were employed to quantitatively evaluate the quality of synthetic brain images derived from retinal imaging data.Results:The proposed framework yielded average RMSE,PSNR,and SSIM values of 98.23,35.78 d B,and 0.64,respectively,which significantly outperformed 5 other methods:multi-channel Variational Autoencoder(mcVAE),Pixelto-Pixel(Pixel2pixel),transformer-based U-Net(Trans UNet),multi-scale transformer network(MT-Net),and residual vision transformer(ResViT).The two-(2D)and three-dimensional(3D)visualization results showed that the shape and texture of the synthetic brain images generated by the proposed method most closely resembled those of actual brain images.Thus,the CMCR framework accurately captured the latent structural correlations between the fundus and the brain.The average difference between predicted and actual brain volumes was 61.36 cm~3,with a relative error of 4.54%.When all of the clinical information(including age and sex,daily habits,cardiovascular factors,metabolic factors,and inflammatory factors)was encoded,the difference was decreased to 53.89 cm~3,with a relative error of 3.98%.Based on the synthesized brain magnetic resonance images from retinal fundus images,the volumes of brain tissues could be estimated with high accuracy.Conclusion:This study provides an innovative,accurate,and cost-effective approach to characterize brain health status through readily accessible retinal fundus images.展开更多
BACKGROUND Major depressive disorder(MDD)and obesity(OB)are bidirectionally comorbid conditions with common neurobiological underpinnings.However,the neurocognitive mechanisms of their comorbidity remain poorly unders...BACKGROUND Major depressive disorder(MDD)and obesity(OB)are bidirectionally comorbid conditions with common neurobiological underpinnings.However,the neurocognitive mechanisms of their comorbidity remain poorly understood.AIM To examine regional abnormalities in spontaneous brain activity among patients with MDD-OB comorbidity.METHODS This study adopted a regional homogeneity(ReHo)analysis of resting-state functional magnetic resonance imaging.The study included 149 hospital patients divided into four groups:Patients experiencing their first episode of drug-naive MDD with OB,patients with MDD without OB,and age-and sex-matched healthy individuals with and without OB.Whole-brain ReHo analysis was conducted using SPM12 software and RESTplus toolkits,with group comparisons via ANOVA and post-hoc tests.Correlations between ReHo values and behavioral measures were examined.RESULTS ANOVA revealed significant whole-brain ReHo differences among the four groups in four key regions:The left middle temporal gyrus(MTG.L),right cuneus,left precuneus,and left thalamus.Post-hoc analyses confirmed pairwise differences between all groups across these regions(P<0.05).OB was associated with ReHo alterations in the MTG.L,right cuneus,and left thalamus,whereas abnormalities in the precuneus suggested synergistic pathological mechanisms between MDD and OB.Statistically significant correlations were found between the drive and fun-seeking dimensions of the behavioral activation system,as well as behavioral inhibition and the corresponding ReHo values.CONCLUSION Our findings provide novel evidence for the neuroadaptive mechanisms underlying the MDD-OB comorbidity.Further validation could lead to personalized interventions targeting MTG.L hyperactivity and targeting healthy food cues.展开更多
Magnetic resonance imaging(MRI)is a powerful tool for diagnosing and monitoring brain diseases,but its low sensitivity can hinder early detection.To address this challenge,we utilized chemical exchange saturation tran...Magnetic resonance imaging(MRI)is a powerful tool for diagnosing and monitoring brain diseases,but its low sensitivity can hinder early detection.To address this challenge,we utilized chemical exchange saturation transfer(CEST)MRI,which greatly enhances sensitivity for detecting low-concentration compounds.In this study,we developed a CEST contrast agent based on a recombinant adeno-associated viruses(rAAVs)encoding the protamine-1(PRM1)MRI reporter gene.CEST MRI revealed that PRM1 contrast agent effectively highlighted caudate putamen region after injection of the rAAVs into the mouse brain,clearly distinguishing it from the surrounding tissue,with no observable damage.This method provides a sensitive,metal-free CEST contrast agent for in vivo brain cell detection,demonstrating potential for both diagnostic and therapeutic applications in brain diseases.展开更多
Mesenchymal stromal cell transplantation is an effective and promising approach for treating various systemic and diffuse diseases.However,the biological characteristics of transplanted mesenchymal stromal cells in hu...Mesenchymal stromal cell transplantation is an effective and promising approach for treating various systemic and diffuse diseases.However,the biological characteristics of transplanted mesenchymal stromal cells in humans remain unclear,including cell viability,distribution,migration,and fate.Conventional cell tracing methods cannot be used in the clinic.The use of superparamagnetic iron oxide nanoparticles as contrast agents allows for the observation of transplanted cells using magnetic resonance imaging.In 2016,the National Medical Products Administration of China approved a new superparamagnetic iron oxide nanoparticle,Ruicun,for use as a contrast agent in clinical trials.In the present study,an acute hemi-transection spinal cord injury model was established in beagle dogs.The injury was then treated by transplantation of Ruicun-labeled mesenchymal stromal cells.The results indicated that Ruicunlabeled mesenchymal stromal cells repaired damaged spinal cord fibers and partially restored neurological function in animals with acute spinal cord injury.T2*-weighted imaging revealed low signal areas on both sides of the injured spinal cord.The results of quantitative susceptibility mapping with ultrashort echo time sequences indicated that Ruicun-labeled mesenchymal stromal cells persisted stably within the injured spinal cord for over 4 weeks.These findings suggest that magnetic resonance imaging has the potential to effectively track the migration of Ruicun-labeled mesenchymal stromal cells and assess their ability to repair spinal cord injury.展开更多
Transforming a scattering medium into a lens for imaging very simple binary objects is possible;however,it remains challenging to image complex grayscale objects,let alone measure 3D continuous distribution objects.He...Transforming a scattering medium into a lens for imaging very simple binary objects is possible;however,it remains challenging to image complex grayscale objects,let alone measure 3D continuous distribution objects.Here,we propose and demonstrate the use of a ground glass diffuser as a scattering lens for imaging complex grayscale fringes,and we employ it to achieve microscopic structured light 3D imaging(MSL3DI).The ubiquitous property of the speckle patterns permits the exploitation of the scattering medium as an ultra-thin scattering lens with a variable focal length and a flexible working distance for microscale object measurement.The method provides a light,flexible,and cost-effective imaging device as an alternative to microscope objectives or telecentric lenses in conventional MSL3DI systems.We experimentally demonstrate that employing a scattering lens allows us to achieve relatively good phase information and robust 3D imaging from depth measurements,yielding measurement accuracy only marginally lower than that of a telecentric lens,typically within approximately 10μm.Furthermore,the scattering lens demonstrates robust performance even when the imaging distance exceeds the typical working distance of a telecentric lens.The proposed method facilitates the application of scattering imaging techniques,providing a more flexible solution for MSL3DI.展开更多
Honeycombing Lung(HCL)is a chronic lung condition marked by advanced fibrosis,resulting in enlarged air spaces with thick fibrotic walls,which are visible on Computed Tomography(CT)scans.Differentiating between normal...Honeycombing Lung(HCL)is a chronic lung condition marked by advanced fibrosis,resulting in enlarged air spaces with thick fibrotic walls,which are visible on Computed Tomography(CT)scans.Differentiating between normal lung tissue,honeycombing lungs,and Ground Glass Opacity(GGO)in CT images is often challenging for radiologists and may lead to misinterpretations.Although earlier studies have proposed models to detect and classify HCL,many faced limitations such as high computational demands,lower accuracy,and difficulty distinguishing between HCL and GGO.CT images are highly effective for lung classification due to their high resolution,3D visualization,and sensitivity to tissue density variations.This study introduces Honeycombing Lungs Network(HCL Net),a novel classification algorithm inspired by ResNet50V2 and enhanced to overcome the shortcomings of previous approaches.HCL Net incorporates additional residual blocks,refined preprocessing techniques,and selective parameter tuning to improve classification performance.The dataset,sourced from the University Malaya Medical Centre(UMMC)and verified by expert radiologists,consists of CT images of normal,honeycombing,and GGO lungs.Experimental evaluations across five assessments demonstrated that HCL Net achieved an outstanding classification accuracy of approximately 99.97%.It also recorded strong performance in other metrics,achieving 93%precision,100%sensitivity,89%specificity,and an AUC-ROC score of 97%.Comparative analysis with baseline feature engineering methods confirmed the superior efficacy of HCL Net.The model significantly reduces misclassification,particularly between honeycombing and GGO lungs,enhancing diagnostic precision and reliability in lung image analysis.展开更多
Psychiatric disorders have emerged as significant contributors to the global burden of disease in recent decades.The endocannabinoid system(ECS)influences a range of physiological and pathophysiological processes,incl...Psychiatric disorders have emerged as significant contributors to the global burden of disease in recent decades.The endocannabinoid system(ECS)influences a range of physiological and pathophysiological processes,including nociception,cognition,appetite,memory,and behavior,serving as a crucial mediator in psychiatric disorders.Imaging the ECS provides valuable insights into the pathophysiological mechanisms underlying psychiatric disorders and enhances clinical management strategies.As an advanced noninvasive molecular imaging modality,positron emission tomography(PET)enables the in vivo exploration of biological processes at the cellular and molecular levels.Recent advancements have led to the development of numerous PET tracers that target various components of the ECS,offering opportunities to visualize,characterize,and quantify ECS activity in psychiatric disorders in vivo.In this review,we summarize the existing PET tracers for ECS imaging and discuss their applications in diverse psychiatric conditions,including cannabis use disorder,alcohol use disorder,post-traumatic stress disorder,schizophrenia,and eating disorders.展开更多
As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a no...As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.展开更多
Perianal fistulising Crohn’s disease is a challenging complication that can affect up to 20%of patients with Crohn’s disease and is associated with significant morbidity.Despite advances in medical therapies,particu...Perianal fistulising Crohn’s disease is a challenging complication that can affect up to 20%of patients with Crohn’s disease and is associated with significant morbidity.Despite advances in medical therapies,particularly anti-tumor necrosis factor agents,the majority of patients still require surgical intervention.Accurate diagnosis and monitoring are essential to optimise outcomes and guide multidisciplinary management.Although clinical scoring systems such as the perianal disease activity index are widely used,their subjective application limits their reproducibility and reliability,underscoring the need for more objective methods of evaluating perianal fistulising Crohn’s disease activity.Imaging has thus become central to the objective assessment of perianal fistulising Crohn’s disease,with magnetic resonance imaging(MRI)recognised as the gold standard in view of its ability to provide clear,detailed images of the perianal region in a radiation-free manner.Guidelines also endorse the use of imaging modalities such as endoanal ultrasound and transperineal ultrasound as viable alternatives to MRI for the assessment of perianal fistulising Crohn’s disease in centres with appropriate expertise.This article aims to evaluate and compare the diagnostic accuracy and clinical utility of MRI,endoanal ultrasound,and transperineal ultrasound in the assessment of perianal fistulising Crohn’s disease,highlighting their respective strengths,limitations,and roles in clinical practice.展开更多
Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability.Detailed asse...Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability.Detailed assessment is important to help identify highrisk infants,to help families,and to support appropriate interventions.A wide range of monitoring tools is available to assess changes over time,including urine and blood biomarkers,neurological examination,and electroencephalography.At present,magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic encephalopathy.This review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries,with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction,particularly for infants treated with therapeutic hypothermia.A comprehensive literature search,from 2016 to 2024,identified 20 pertinent articles.This review highlights that while the optimal timing of magnetic resonance imaging scans is not clear,overall,it suggests that magnetic resonance imaging within the first week of life provides strong prognostic accuracy.Many challenges limit the timing consistency,particularly the need for intensive care and clinical monitoring.Conversely,although most reports examined the prognostic value of scans taken between 4 and 10 days after birth,there is evidence from small numbers of cases that,at times,brain injury may continue to evolve for weeks after birth.This suggests that in the future it will be important to explore a wider range of times after hypoxic-ischemic encephalopathy to fully understand the optimal timing for predicting long-term outcomes.展开更多
The rapid development of super-resolution microscopy has made it possible to observe subcellular structures and dynamic behaviors in living cells with nanoscale spatial resolution, greatly advancing progress in life s...The rapid development of super-resolution microscopy has made it possible to observe subcellular structures and dynamic behaviors in living cells with nanoscale spatial resolution, greatly advancing progress in life sciences. As hardware technology continues to evolve, the availability of new fluorescent probes with superior performance is becoming increasingly important. In recent years, fluorescent nanoprobes (FNPs) have emerged as highly promising fluorescent probes for bioimaging due to their high brightness and excellent photostability. This paper focuses on the development and applications of FNPs as probes for live-cell super-resolution imaging. It provides an overview of different super-resolution methods, discusses the performance requirements for FNPs in these methods, and reviews the latest applications of FNPs in the super-resolution imaging of living cells. Finally, it addresses the challenges and future outlook in this field.展开更多
BACKGROUND Colorectal cancer is a malignancy with a high risk of lymph node metastasis and poor prognosis,and thus requires an accurate diagnosis.AIM To assess the diagnostic value of combined magnetic resonance T2-we...BACKGROUND Colorectal cancer is a malignancy with a high risk of lymph node metastasis and poor prognosis,and thus requires an accurate diagnosis.AIM To assess the diagnostic value of combined magnetic resonance T2-weighted imaging(T2WI)and diffusion-weighted imaging(DWI)in colorectal cancer.METHODS We included 120 patients with suspected colorectal cancer who underwent magnetic resonance imaging.Surgical pathology was used as the gold standard for comparison.Combined T2WI and DWI showed higher diagnostic efficacy than either of the two methods used individually.RESULTS The combined method achieved 94.74%sensitivity,95.45%specificity,95.00%accuracy,94.74%positive predictive value,and 95.45%negative predictive value in qualitative diagnosis.It showed 94.44%sensitivity,95.00%specificity,94.74%accuracy,94.44%positive predictive value,and 95.00%negative predictive value in clinical staging.Finally,it showed 94.74%sensitivity,94.59%specificity,94.74%accuracy,94.74%positive predictive value,and 94.59%negative predictive value in diagnosing lymph node metastasis.These results were highly consistent with that of the gold standard.CONCLUSION This study combined T2WI and DWI for accurate diagnosis of colorectal cancer,aiding clinical staging and lymph node metastasis assessment.This approach is promising for clinical application.展开更多
Glioblastoma multiforme(GBM)are the most aggressive and common tumors in the central nervous system.GBM are classified as grade IV according to the World Health Organization.The incidence of GBM slightly differs among...Glioblastoma multiforme(GBM)are the most aggressive and common tumors in the central nervous system.GBM are classified as grade IV according to the World Health Organization.The incidence of GBM slightly differs among countries.The etiology of GBM has not been entirely clarified.No risk factors such as smoking,chemicals or dietary can be identified for GBM.Only the exposure to high radiation dose such as radiotherapy of head and neck cancers have been reported to increase the risk of glioma tumors.In this review,the authors attempted to cover several aspects of GBM.This review was based on a collection of recent publications from different research fields but all related to GBM in order to shed the light on this disease.We highlighted the current insights of GBM in the aspects of epidemiology,pathogenesis,etiology,molecular genetics,imaging technologies,artificial intelligence and treatment.A literature review was conducted for GBM with relevant keywords.Although GBM was known since several decades,its causes are still confounding,and its early detection is often unpredictable.Since the hereditary aspect of GBM is very low,there remains as the common symptoms the interference with normal brain function,memory loss,unusual behavior,headaches and seizures.The progress in GBM treatment is not satisfactory even with the deployment of huge efforts and financial costs in many domains like gene therapy,surgery and chemoradiotherapy.Despite the rapid developments of the standard treatment for GBM,the trend of survival rate did not change among years.展开更多
Although aggregation-induced emission(AIE) units enabled fluorophores as rotor-based probes for advancing biomedical imaging,the quantum-mechanism through which AIEgens enhanced fluorescence via aggregation or rotor e...Although aggregation-induced emission(AIE) units enabled fluorophores as rotor-based probes for advancing biomedical imaging,the quantum-mechanism through which AIEgens enhanced fluorescence via aggregation or rotor effects remains poorly understood.Herein,we elucidate the mechanisms governing the tetraphenylethene(TPE)'s function(rotor-effect or aggregation-effect) in cyanine systems by tuning the methine-chain length from Cy3 to Cy5 to Cy7.Our study shows that modulating the frontier orbital energy difference(ΔE(DA)) between the cyanine and TPE allows TPE to display AIE property in Cy3,act as a rotor in Cy5 uniquely devoid of aggregation activation,or neither in Cy7.In vitro and in vivo results further demonstrate that rotor-specific TPE-Cy5 can serve as a sensitive probe for imaging tumor rigidity.We anticipate that continued advancements in TPE rotor visualization will open new avenues for understanding the biophysical behaviors of tumors.展开更多
Background:Cardiac magnetic resonance imaging(MRI)plays a key role in assessing acute myocardial infarction(AMI)and detecting myocardial edema.Diffusion-weighted imaging(DWI)has recently been applied to cardiac explor...Background:Cardiac magnetic resonance imaging(MRI)plays a key role in assessing acute myocardial infarction(AMI)and detecting myocardial edema.Diffusion-weighted imaging(DWI)has recently been applied to cardiac exploration and is perceived as a promising method for evaluating cardiomyopathies.This study aims to evaluate the role of DWI in the assessment of AMI by analyzing the accuracy of both low b-value diffusion-weighted(DW)spin-echo(SE)echo-planar imaging(EPI)sequence and apparent diffusion coefficient(ADC)mapping in detecting ischemia-induced myocardial edema.Methods:This study included 13 patients with recent reperfused AMI who underwent cardiac MRI.A cardiac protocol was applied,including black blood T2-weighted imaging(BB-T2W),two low b-value DW SE EPI(b=20 s/mm^(2)),one for low b-value DW SE EPI in free-breathing(DWF)and the other for low b-value DW SE EPI in breath-holding(DWH),T2 mapping,and ADC mapping.BB-T2W,DWH,and DWF images were analyzed quantitatively and qualitatively.The T2 and ADC values were measured within the infarct and remote myocardium.Statistical analysis was performed using a nonparametric Wilcoxon test.Results:ADC values in the infarct area were significantly higher than the remote myocardium([2.36±0.34]×10^(-3)mm^(2)/s and[1.20±0.14]×10^(-3)mm^(2)/s,respectively;p=0.001).Besides,low b-value DW SE EPI(DWH and DWF)allowed the detection of ischemia-induced myocardial edema in a way surpassing the BB-T2W sequence with a higher sensitivity to edema(96.7%,96.7%,and 87.9%,respectively).No statistically significant difference was noted between DWH and DWF sequences.Conclusion:DWI may be a promising technique for the exploration of AMI,with the advantage of being feasible for dyspneic patients.展开更多
Tetralogy of Fallot(TOF)is a common cyanotic congenital heart disease.Imaging plays a pivotal role in the diagnosis and surgical planning of TOF.Trans-thoracic echocardiography,cardiac computed tomography,and magnetic...Tetralogy of Fallot(TOF)is a common cyanotic congenital heart disease.Imaging plays a pivotal role in the diagnosis and surgical planning of TOF.Trans-thoracic echocardiography,cardiac computed tomography,and magnetic resonance imaging are the commonly used non-invasive imaging modalities.Precise delineation of cardiac anatomy,pulmonary artery status,and associated anomalies is essential to guide the surgeon.Catheter angiography is used in specific situations for surgical planning and also to perform palliative procedures for cyanotic spells.Advances in imaging and surgical techniques have led to a better life expectancy.This has created a population of repaired TOF patients,in whom imaging plays a crucial role in both follow-up and the evaluation of complications.This article reviews the role of imaging modalities in TOF and repaired TOF,touching upon the basics of each modality,which are necessary for pre-operative diagnosis,surgical planning,and post-operative follow-up.The standard surgical strategies are also discussed,as relevant to post-operative imaging findings.展开更多
Automated prostate cancer detection in magnetic resonance imaging(MRI)scans is of significant importance for cancer patient management.Most existing computer-aided diagnosis systems adopt segmentation methods while ob...Automated prostate cancer detection in magnetic resonance imaging(MRI)scans is of significant importance for cancer patient management.Most existing computer-aided diagnosis systems adopt segmentation methods while object detection approaches recently show promising results.The authors have(1)carefully compared performances of most-developed segmentation and object detection methods in localising prostate imaging reporting and data system(PIRADS)-labelled prostate lesions on MRI scans;(2)proposed an additional customised set of lesion-level localisation sensitivity and precision;(3)proposed efficient ways to ensemble the segmentation and object detection methods for improved performances.The ground-truth(GT)perspective lesion-level sensitivity and prediction-perspective lesion-level precision are reported,to quantify the ratios of true positive voxels being detected by algorithms over the number of voxels in the GT labelled regions and predicted regions.The two networks are trained independently on 549 clinical patients data with PIRADS-V2 as GT labels,and tested on 161 internal and 100 external MRI scans.At the lesion level,nnDetection outperforms nnUNet for detecting both PIRADS≥3 and PIRADS≥4 lesions in majority cases.For example,at the average false positive prediction per patient being 3,nnDetection achieves a greater Intersection-of-Union(IoU)-based sensitivity than nnUNet for detecting PIRADS≥3 lesions,being 80.78%�1.50%versus 60.40%�1.64%(p<0.01).At the voxel level,nnUnet is in general superior or comparable to nnDetection.The proposed ensemble methods achieve improved or comparable lesion-level accuracy,in all tested clinical scenarios.For example,at 3 false positives,the lesion-wise ensemble method achieves 82.24%�1.43%sensitivity versus 80.78%�1.50%(nnDetection)and 60.40%�1.64%(nnUNet)for detecting PIRADS≥3 lesions.Consistent conclusions are also drawn from results on the external data set.展开更多
基金supported by the National Key Research and Development Program of China(2022YFC2402400)the National Natural Science Foundation of China(82027803,62275062)+7 种基金the Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology(2020B121201010)the Shenzhen Science and Technology Innovation Committee under Grant(JCYJ20220818101417039)the Shenzhen Key Laboratory for Molecular lmaging(ZDSY20130401165820357)the Shenzhen Medical Research Fund(D2404002)the Project of Shandong Innovation and Startup Community of High-end Medical Apparatus and Instruments(2023-SGTTXM-002 and 2024-SGTTXM-005)the Shandong Province Technology Innovation Guidance Plan(Central Leading Local Science and Technology Development Fund)(YDZX2023115)the Taishan Scholar Special Funding Project of Shandong Provinceand the Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai(ZL202402).
文摘The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.
文摘Colorectal cancer(CRC)with lung oligometastases,particularly in the presence of extrapulmonary disease,poses considerable therapeutic challenges in clinical practice.We have carefully studied the multicenter study by Hu et al,which evaluated the survival outcomes of patients with metastatic CRC who received image-guided thermal ablation(IGTA).These findings provide valuable clinical evidence supporting IGTA as a feasible,minimally invasive approach and underscore the prognostic significance of metastatic distribution.However,the study by Hu et al has several limitations,including that not all pulmonary lesions were pathologically confirmed,postoperative follow-up mainly relied on dynamic contrast-enhanced computed tomography,no comparative analysis was performed with other local treatments,and the impact of other imaging features on efficacy and prognosis was not evaluated.Future studies should include complete pathological confirmation,integrate functional imaging and radiomics,and use prospective multicenter collaboration to optimize patient selection standards for IGTA treatment,strengthen its clinical evidence base,and ultimately promote individualized decision-making for patients with metastatic CRC.
基金financially supported by the Open Project Program of Wuhan National Laboratory for Optoelectronics(No.2022WNLOKF009)the National Natural Science Foundation of China(No.62475216)+2 种基金the Key Research and Development Program of Shaanxi(No.2024GH-ZDXM-37)the Fujian Provincial Natural Science Foundation of China(No.2024J01060)the Startup Program of XMU,and the Fundamental Research Funds for the Central Universities.
文摘Microscopy imaging is fundamental in analyzing bacterial morphology and dynamics,offering critical insights into bacterial physiology and pathogenicity.Image segmentation techniques enable quantitative analysis of bacterial structures,facilitating precise measurement of morphological variations and population behaviors at single-cell resolution.This paper reviews advancements in bacterial image segmentation,emphasizing the shift from traditional thresholding and watershed methods to deep learning-driven approaches.Convolutional neural networks(CNNs),U-Net architectures,and three-dimensional(3D)frameworks excel at segmenting dense biofilms and resolving antibiotic-induced morphological changes.These methods combine automated feature extraction with physics-informed postprocessing.Despite progress,challenges persist in computational efficiency,cross-species generalizability,and integration with multimodal experimental workflows.Future progress will depend on improving model robustness across species and imaging modalities,integrating multimodal data for phenotype-function mapping,and developing standard pipelines that link computational tools with clinical diagnostics.These innovations will expand microbial phenotyping beyond structural analysis,enabling deeper insights into bacterial physiology and ecological interactions.
基金supported by the National Natural Science Foundation of China(62522119 and 62372358)the Beijing Natural Science Foundation(7242267)+2 种基金the Beijing Scholars Program([2015]160)the Natural Science Basic Research Program of Shaanxi(2023-JC-QN-0719)the Guangdong Basic and Applied Basic Research Foundation(2022A1515110453)。
文摘Background:Brain volume measurement serves as a critical approach for assessing brain health status.Considering the close biological connection between the eyes and brain,this study aims to investigate the feasibility of estimating brain volume through retinal fundus imaging integrated with clinical metadata,and to offer a cost-effective approach for assessing brain health.Methods:Based on clinical information,retinal fundus images,and neuroimaging data derived from a multicenter,population-based cohort study,the Kai Luan Study,we proposed a cross-modal correlation representation(CMCR)network to elucidate the intricate co-degenerative relationships between the eyes and brain for 755 subjects.Specifically,individual clinical information,which has been followed up for as long as 12 years,was encoded as a prompt to enhance the accuracy of brain volume estimation.Independent internal validation and external validation were performed to assess the robustness of the proposed model.Root mean square error(RMSE),peak signal-tonoise ratio(PSNR),and structural similarity index measure(SSIM)metrics were employed to quantitatively evaluate the quality of synthetic brain images derived from retinal imaging data.Results:The proposed framework yielded average RMSE,PSNR,and SSIM values of 98.23,35.78 d B,and 0.64,respectively,which significantly outperformed 5 other methods:multi-channel Variational Autoencoder(mcVAE),Pixelto-Pixel(Pixel2pixel),transformer-based U-Net(Trans UNet),multi-scale transformer network(MT-Net),and residual vision transformer(ResViT).The two-(2D)and three-dimensional(3D)visualization results showed that the shape and texture of the synthetic brain images generated by the proposed method most closely resembled those of actual brain images.Thus,the CMCR framework accurately captured the latent structural correlations between the fundus and the brain.The average difference between predicted and actual brain volumes was 61.36 cm~3,with a relative error of 4.54%.When all of the clinical information(including age and sex,daily habits,cardiovascular factors,metabolic factors,and inflammatory factors)was encoded,the difference was decreased to 53.89 cm~3,with a relative error of 3.98%.Based on the synthesized brain magnetic resonance images from retinal fundus images,the volumes of brain tissues could be estimated with high accuracy.Conclusion:This study provides an innovative,accurate,and cost-effective approach to characterize brain health status through readily accessible retinal fundus images.
基金Supported by Provincial Key Research Project of Henan Province,No.232102310081.
文摘BACKGROUND Major depressive disorder(MDD)and obesity(OB)are bidirectionally comorbid conditions with common neurobiological underpinnings.However,the neurocognitive mechanisms of their comorbidity remain poorly understood.AIM To examine regional abnormalities in spontaneous brain activity among patients with MDD-OB comorbidity.METHODS This study adopted a regional homogeneity(ReHo)analysis of resting-state functional magnetic resonance imaging.The study included 149 hospital patients divided into four groups:Patients experiencing their first episode of drug-naive MDD with OB,patients with MDD without OB,and age-and sex-matched healthy individuals with and without OB.Whole-brain ReHo analysis was conducted using SPM12 software and RESTplus toolkits,with group comparisons via ANOVA and post-hoc tests.Correlations between ReHo values and behavioral measures were examined.RESULTS ANOVA revealed significant whole-brain ReHo differences among the four groups in four key regions:The left middle temporal gyrus(MTG.L),right cuneus,left precuneus,and left thalamus.Post-hoc analyses confirmed pairwise differences between all groups across these regions(P<0.05).OB was associated with ReHo alterations in the MTG.L,right cuneus,and left thalamus,whereas abnormalities in the precuneus suggested synergistic pathological mechanisms between MDD and OB.Statistically significant correlations were found between the drive and fun-seeking dimensions of the behavioral activation system,as well as behavioral inhibition and the corresponding ReHo values.CONCLUSION Our findings provide novel evidence for the neuroadaptive mechanisms underlying the MDD-OB comorbidity.Further validation could lead to personalized interventions targeting MTG.L hyperactivity and targeting healthy food cues.
基金financially supported by the National Natural Science Foundation of China(82127802,22374157)Strategic Priority Research Program,CAS(XDB0540000,XDC0170000)CAS Youth Interdisciplinary Team(JCTD-2022-13).In addition,Xin Zhou acknowledges the support from the Tencent Foundation through the XPLORER PRIZE.
文摘Magnetic resonance imaging(MRI)is a powerful tool for diagnosing and monitoring brain diseases,but its low sensitivity can hinder early detection.To address this challenge,we utilized chemical exchange saturation transfer(CEST)MRI,which greatly enhances sensitivity for detecting low-concentration compounds.In this study,we developed a CEST contrast agent based on a recombinant adeno-associated viruses(rAAVs)encoding the protamine-1(PRM1)MRI reporter gene.CEST MRI revealed that PRM1 contrast agent effectively highlighted caudate putamen region after injection of the rAAVs into the mouse brain,clearly distinguishing it from the surrounding tissue,with no observable damage.This method provides a sensitive,metal-free CEST contrast agent for in vivo brain cell detection,demonstrating potential for both diagnostic and therapeutic applications in brain diseases.
基金supported by the National Key R&D Program of China,Nos.2017YFA0104302(to NG and XM)and 2017YFA0104304(to BW and ZZ)
文摘Mesenchymal stromal cell transplantation is an effective and promising approach for treating various systemic and diffuse diseases.However,the biological characteristics of transplanted mesenchymal stromal cells in humans remain unclear,including cell viability,distribution,migration,and fate.Conventional cell tracing methods cannot be used in the clinic.The use of superparamagnetic iron oxide nanoparticles as contrast agents allows for the observation of transplanted cells using magnetic resonance imaging.In 2016,the National Medical Products Administration of China approved a new superparamagnetic iron oxide nanoparticle,Ruicun,for use as a contrast agent in clinical trials.In the present study,an acute hemi-transection spinal cord injury model was established in beagle dogs.The injury was then treated by transplantation of Ruicun-labeled mesenchymal stromal cells.The results indicated that Ruicunlabeled mesenchymal stromal cells repaired damaged spinal cord fibers and partially restored neurological function in animals with acute spinal cord injury.T2*-weighted imaging revealed low signal areas on both sides of the injured spinal cord.The results of quantitative susceptibility mapping with ultrashort echo time sequences indicated that Ruicun-labeled mesenchymal stromal cells persisted stably within the injured spinal cord for over 4 weeks.These findings suggest that magnetic resonance imaging has the potential to effectively track the migration of Ruicun-labeled mesenchymal stromal cells and assess their ability to repair spinal cord injury.
基金supported by the National Natural Science Foundation of China(Grant Nos.62275188 and 62505216)the Central Guidance on Local Science and Technology Development Fund(Grant No.YDZJSX2024D019)+1 种基金the International Scientific and Technological Cooperative Project in Shanxi Province(Grant No.202104041101009)the Natural Science Foundation of Shanxi Province of China through Research Project(Grant No.20210302123195).
文摘Transforming a scattering medium into a lens for imaging very simple binary objects is possible;however,it remains challenging to image complex grayscale objects,let alone measure 3D continuous distribution objects.Here,we propose and demonstrate the use of a ground glass diffuser as a scattering lens for imaging complex grayscale fringes,and we employ it to achieve microscopic structured light 3D imaging(MSL3DI).The ubiquitous property of the speckle patterns permits the exploitation of the scattering medium as an ultra-thin scattering lens with a variable focal length and a flexible working distance for microscale object measurement.The method provides a light,flexible,and cost-effective imaging device as an alternative to microscope objectives or telecentric lenses in conventional MSL3DI systems.We experimentally demonstrate that employing a scattering lens allows us to achieve relatively good phase information and robust 3D imaging from depth measurements,yielding measurement accuracy only marginally lower than that of a telecentric lens,typically within approximately 10μm.Furthermore,the scattering lens demonstrates robust performance even when the imaging distance exceeds the typical working distance of a telecentric lens.The proposed method facilitates the application of scattering imaging techniques,providing a more flexible solution for MSL3DI.
文摘Honeycombing Lung(HCL)is a chronic lung condition marked by advanced fibrosis,resulting in enlarged air spaces with thick fibrotic walls,which are visible on Computed Tomography(CT)scans.Differentiating between normal lung tissue,honeycombing lungs,and Ground Glass Opacity(GGO)in CT images is often challenging for radiologists and may lead to misinterpretations.Although earlier studies have proposed models to detect and classify HCL,many faced limitations such as high computational demands,lower accuracy,and difficulty distinguishing between HCL and GGO.CT images are highly effective for lung classification due to their high resolution,3D visualization,and sensitivity to tissue density variations.This study introduces Honeycombing Lungs Network(HCL Net),a novel classification algorithm inspired by ResNet50V2 and enhanced to overcome the shortcomings of previous approaches.HCL Net incorporates additional residual blocks,refined preprocessing techniques,and selective parameter tuning to improve classification performance.The dataset,sourced from the University Malaya Medical Centre(UMMC)and verified by expert radiologists,consists of CT images of normal,honeycombing,and GGO lungs.Experimental evaluations across five assessments demonstrated that HCL Net achieved an outstanding classification accuracy of approximately 99.97%.It also recorded strong performance in other metrics,achieving 93%precision,100%sensitivity,89%specificity,and an AUC-ROC score of 97%.Comparative analysis with baseline feature engineering methods confirmed the superior efficacy of HCL Net.The model significantly reduces misclassification,particularly between honeycombing and GGO lungs,enhancing diagnostic precision and reliability in lung image analysis.
基金supported by the National Key Research and Development Program of China(2022YFE0118000,2021YFA1101700)the National Natural Science Foundation of China(82030049,32027802,82394433,82361148130,and 82302262)+2 种基金the Zhejiang Provincial Natural Science Foundation(LMS25H180002)the Postdoctoral Fellowship Program of CPSF(GZC20251313)the Fundamental Research Funds for the Central Universities of China(226-2024-00059).
文摘Psychiatric disorders have emerged as significant contributors to the global burden of disease in recent decades.The endocannabinoid system(ECS)influences a range of physiological and pathophysiological processes,including nociception,cognition,appetite,memory,and behavior,serving as a crucial mediator in psychiatric disorders.Imaging the ECS provides valuable insights into the pathophysiological mechanisms underlying psychiatric disorders and enhances clinical management strategies.As an advanced noninvasive molecular imaging modality,positron emission tomography(PET)enables the in vivo exploration of biological processes at the cellular and molecular levels.Recent advancements have led to the development of numerous PET tracers that target various components of the ECS,offering opportunities to visualize,characterize,and quantify ECS activity in psychiatric disorders in vivo.In this review,we summarize the existing PET tracers for ECS imaging and discuss their applications in diverse psychiatric conditions,including cannabis use disorder,alcohol use disorder,post-traumatic stress disorder,schizophrenia,and eating disorders.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP2/367/46)+1 种基金This research is supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.
文摘Perianal fistulising Crohn’s disease is a challenging complication that can affect up to 20%of patients with Crohn’s disease and is associated with significant morbidity.Despite advances in medical therapies,particularly anti-tumor necrosis factor agents,the majority of patients still require surgical intervention.Accurate diagnosis and monitoring are essential to optimise outcomes and guide multidisciplinary management.Although clinical scoring systems such as the perianal disease activity index are widely used,their subjective application limits their reproducibility and reliability,underscoring the need for more objective methods of evaluating perianal fistulising Crohn’s disease activity.Imaging has thus become central to the objective assessment of perianal fistulising Crohn’s disease,with magnetic resonance imaging(MRI)recognised as the gold standard in view of its ability to provide clear,detailed images of the perianal region in a radiation-free manner.Guidelines also endorse the use of imaging modalities such as endoanal ultrasound and transperineal ultrasound as viable alternatives to MRI for the assessment of perianal fistulising Crohn’s disease in centres with appropriate expertise.This article aims to evaluate and compare the diagnostic accuracy and clinical utility of MRI,endoanal ultrasound,and transperineal ultrasound in the assessment of perianal fistulising Crohn’s disease,highlighting their respective strengths,limitations,and roles in clinical practice.
基金supported by a grant from the Health Research New Zealand(HRC)22/559(to AJG and LB)。
文摘Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability.Detailed assessment is important to help identify highrisk infants,to help families,and to support appropriate interventions.A wide range of monitoring tools is available to assess changes over time,including urine and blood biomarkers,neurological examination,and electroencephalography.At present,magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic encephalopathy.This review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries,with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction,particularly for infants treated with therapeutic hypothermia.A comprehensive literature search,from 2016 to 2024,identified 20 pertinent articles.This review highlights that while the optimal timing of magnetic resonance imaging scans is not clear,overall,it suggests that magnetic resonance imaging within the first week of life provides strong prognostic accuracy.Many challenges limit the timing consistency,particularly the need for intensive care and clinical monitoring.Conversely,although most reports examined the prognostic value of scans taken between 4 and 10 days after birth,there is evidence from small numbers of cases that,at times,brain injury may continue to evolve for weeks after birth.This suggests that in the future it will be important to explore a wider range of times after hypoxic-ischemic encephalopathy to fully understand the optimal timing for predicting long-term outcomes.
基金supported by the following grants:National Natural Science Foundation of China(grant nos.92354305,32271428,and 32201132)National Key R&D Program of China(grant no.2022YFC3401100)+1 种基金Fund for Knowledge Innovation of Wuhan Science and Technology Bureau(grant no.2022020801010558)Director Fund of WNLO.
文摘The rapid development of super-resolution microscopy has made it possible to observe subcellular structures and dynamic behaviors in living cells with nanoscale spatial resolution, greatly advancing progress in life sciences. As hardware technology continues to evolve, the availability of new fluorescent probes with superior performance is becoming increasingly important. In recent years, fluorescent nanoprobes (FNPs) have emerged as highly promising fluorescent probes for bioimaging due to their high brightness and excellent photostability. This paper focuses on the development and applications of FNPs as probes for live-cell super-resolution imaging. It provides an overview of different super-resolution methods, discusses the performance requirements for FNPs in these methods, and reviews the latest applications of FNPs in the super-resolution imaging of living cells. Finally, it addresses the challenges and future outlook in this field.
文摘BACKGROUND Colorectal cancer is a malignancy with a high risk of lymph node metastasis and poor prognosis,and thus requires an accurate diagnosis.AIM To assess the diagnostic value of combined magnetic resonance T2-weighted imaging(T2WI)and diffusion-weighted imaging(DWI)in colorectal cancer.METHODS We included 120 patients with suspected colorectal cancer who underwent magnetic resonance imaging.Surgical pathology was used as the gold standard for comparison.Combined T2WI and DWI showed higher diagnostic efficacy than either of the two methods used individually.RESULTS The combined method achieved 94.74%sensitivity,95.45%specificity,95.00%accuracy,94.74%positive predictive value,and 95.45%negative predictive value in qualitative diagnosis.It showed 94.44%sensitivity,95.00%specificity,94.74%accuracy,94.44%positive predictive value,and 95.00%negative predictive value in clinical staging.Finally,it showed 94.74%sensitivity,94.59%specificity,94.74%accuracy,94.74%positive predictive value,and 94.59%negative predictive value in diagnosing lymph node metastasis.These results were highly consistent with that of the gold standard.CONCLUSION This study combined T2WI and DWI for accurate diagnosis of colorectal cancer,aiding clinical staging and lymph node metastasis assessment.This approach is promising for clinical application.
文摘Glioblastoma multiforme(GBM)are the most aggressive and common tumors in the central nervous system.GBM are classified as grade IV according to the World Health Organization.The incidence of GBM slightly differs among countries.The etiology of GBM has not been entirely clarified.No risk factors such as smoking,chemicals or dietary can be identified for GBM.Only the exposure to high radiation dose such as radiotherapy of head and neck cancers have been reported to increase the risk of glioma tumors.In this review,the authors attempted to cover several aspects of GBM.This review was based on a collection of recent publications from different research fields but all related to GBM in order to shed the light on this disease.We highlighted the current insights of GBM in the aspects of epidemiology,pathogenesis,etiology,molecular genetics,imaging technologies,artificial intelligence and treatment.A literature review was conducted for GBM with relevant keywords.Although GBM was known since several decades,its causes are still confounding,and its early detection is often unpredictable.Since the hereditary aspect of GBM is very low,there remains as the common symptoms the interference with normal brain function,memory loss,unusual behavior,headaches and seizures.The progress in GBM treatment is not satisfactory even with the deployment of huge efforts and financial costs in many domains like gene therapy,surgery and chemoradiotherapy.Despite the rapid developments of the standard treatment for GBM,the trend of survival rate did not change among years.
基金supported by National Natural Science Foundation of China(Nos.32371433 and W2411083)the National Key Research and Development Program of China(No.2022YFB3203800)+4 种基金Guang Dong Basic and Applied Basic Research Foundation(No.2023A1515030207)Key Research and Development Program of Shaanxi(No.2024SF2-GJHX-30)Innovation Capability Support Program of Shaanxi(No.2022TD-52)Dual-chain Integration Special Program of Qin Chuang Yuan Construction(No.23LLRH0070)Xidian University Specially Funded Project for Interdisciplinary Exploration(Nos.TZJH2024035,TZJH2024031)。
文摘Although aggregation-induced emission(AIE) units enabled fluorophores as rotor-based probes for advancing biomedical imaging,the quantum-mechanism through which AIEgens enhanced fluorescence via aggregation or rotor effects remains poorly understood.Herein,we elucidate the mechanisms governing the tetraphenylethene(TPE)'s function(rotor-effect or aggregation-effect) in cyanine systems by tuning the methine-chain length from Cy3 to Cy5 to Cy7.Our study shows that modulating the frontier orbital energy difference(ΔE(DA)) between the cyanine and TPE allows TPE to display AIE property in Cy3,act as a rotor in Cy5 uniquely devoid of aggregation activation,or neither in Cy7.In vitro and in vivo results further demonstrate that rotor-specific TPE-Cy5 can serve as a sensitive probe for imaging tumor rigidity.We anticipate that continued advancements in TPE rotor visualization will open new avenues for understanding the biophysical behaviors of tumors.
文摘Background:Cardiac magnetic resonance imaging(MRI)plays a key role in assessing acute myocardial infarction(AMI)and detecting myocardial edema.Diffusion-weighted imaging(DWI)has recently been applied to cardiac exploration and is perceived as a promising method for evaluating cardiomyopathies.This study aims to evaluate the role of DWI in the assessment of AMI by analyzing the accuracy of both low b-value diffusion-weighted(DW)spin-echo(SE)echo-planar imaging(EPI)sequence and apparent diffusion coefficient(ADC)mapping in detecting ischemia-induced myocardial edema.Methods:This study included 13 patients with recent reperfused AMI who underwent cardiac MRI.A cardiac protocol was applied,including black blood T2-weighted imaging(BB-T2W),two low b-value DW SE EPI(b=20 s/mm^(2)),one for low b-value DW SE EPI in free-breathing(DWF)and the other for low b-value DW SE EPI in breath-holding(DWH),T2 mapping,and ADC mapping.BB-T2W,DWH,and DWF images were analyzed quantitatively and qualitatively.The T2 and ADC values were measured within the infarct and remote myocardium.Statistical analysis was performed using a nonparametric Wilcoxon test.Results:ADC values in the infarct area were significantly higher than the remote myocardium([2.36±0.34]×10^(-3)mm^(2)/s and[1.20±0.14]×10^(-3)mm^(2)/s,respectively;p=0.001).Besides,low b-value DW SE EPI(DWH and DWF)allowed the detection of ischemia-induced myocardial edema in a way surpassing the BB-T2W sequence with a higher sensitivity to edema(96.7%,96.7%,and 87.9%,respectively).No statistically significant difference was noted between DWH and DWF sequences.Conclusion:DWI may be a promising technique for the exploration of AMI,with the advantage of being feasible for dyspneic patients.
文摘Tetralogy of Fallot(TOF)is a common cyanotic congenital heart disease.Imaging plays a pivotal role in the diagnosis and surgical planning of TOF.Trans-thoracic echocardiography,cardiac computed tomography,and magnetic resonance imaging are the commonly used non-invasive imaging modalities.Precise delineation of cardiac anatomy,pulmonary artery status,and associated anomalies is essential to guide the surgeon.Catheter angiography is used in specific situations for surgical planning and also to perform palliative procedures for cyanotic spells.Advances in imaging and surgical techniques have led to a better life expectancy.This has created a population of repaired TOF patients,in whom imaging plays a crucial role in both follow-up and the evaluation of complications.This article reviews the role of imaging modalities in TOF and repaired TOF,touching upon the basics of each modality,which are necessary for pre-operative diagnosis,surgical planning,and post-operative follow-up.The standard surgical strategies are also discussed,as relevant to post-operative imaging findings.
基金National Natural Science Foundation of China,Grant/Award Number:62303275International Alliance for Cancer Early Detection,Grant/Award Numbers:C28070/A30912,C73666/A31378Wellcome/EPSRC Centre for Interventional and Surgical Sciences,Grant/Award Number:203145Z/16/Z。
文摘Automated prostate cancer detection in magnetic resonance imaging(MRI)scans is of significant importance for cancer patient management.Most existing computer-aided diagnosis systems adopt segmentation methods while object detection approaches recently show promising results.The authors have(1)carefully compared performances of most-developed segmentation and object detection methods in localising prostate imaging reporting and data system(PIRADS)-labelled prostate lesions on MRI scans;(2)proposed an additional customised set of lesion-level localisation sensitivity and precision;(3)proposed efficient ways to ensemble the segmentation and object detection methods for improved performances.The ground-truth(GT)perspective lesion-level sensitivity and prediction-perspective lesion-level precision are reported,to quantify the ratios of true positive voxels being detected by algorithms over the number of voxels in the GT labelled regions and predicted regions.The two networks are trained independently on 549 clinical patients data with PIRADS-V2 as GT labels,and tested on 161 internal and 100 external MRI scans.At the lesion level,nnDetection outperforms nnUNet for detecting both PIRADS≥3 and PIRADS≥4 lesions in majority cases.For example,at the average false positive prediction per patient being 3,nnDetection achieves a greater Intersection-of-Union(IoU)-based sensitivity than nnUNet for detecting PIRADS≥3 lesions,being 80.78%�1.50%versus 60.40%�1.64%(p<0.01).At the voxel level,nnUnet is in general superior or comparable to nnDetection.The proposed ensemble methods achieve improved or comparable lesion-level accuracy,in all tested clinical scenarios.For example,at 3 false positives,the lesion-wise ensemble method achieves 82.24%�1.43%sensitivity versus 80.78%�1.50%(nnDetection)and 60.40%�1.64%(nnUNet)for detecting PIRADS≥3 lesions.Consistent conclusions are also drawn from results on the external data set.
