BACKGROUND Nonalcoholic fatty liver disease(NAFLD)is the most common chronic liver disea-se.The accuracy of noninvasive biomarkers for detecting hepatic steatosis is still limited.AIM To assess the diagnostic performa...BACKGROUND Nonalcoholic fatty liver disease(NAFLD)is the most common chronic liver disea-se.The accuracy of noninvasive biomarkers for detecting hepatic steatosis is still limited.AIM To assess the diagnostic performance of noninvasive steatosis biomarkers in diag-nosing NAFLD using magnetic resonance imaging proton density fat fraction(MRI-PDFF)as the gold standard.METHODS A total of 131 suspected NAFLD patients(60%male,median age 36 years)under-going MRI-PDFF were consecutively recruited from a tertiary hospital.Steatosis grades determined by MRI-PDFF were classified as none(<5%),mild(5%-11%),moderate(11%-17%),and severe(≥17%).Six steatosis biomarkers were calculated according to clinical parameters and laboratory tests,including fatty liver index,hepatic steatosis index,ZJU index,Framingham steatosis index,triglycerides and glucose index,and visceral adiposity index.The accuracy of these biomarkers in detecting hepatic steatosis was evaluated using the area under the receiver operating characteristic curves(AUCs).The Youden index was used to determine the optimal cut-off for each biomarker.The linear trend analysis of each biomarker across the steatosis grades was conducted by Mantel-Haenszelχ2 test.Spearman's rank correlation assessed the relationship between steatosis biomarkers and MRI-PDFF.RESULTS Steatosis grades based on MRI-PDFF prevalence were:None 27%,mild 40%,moderate 15%and severe 18%.Six steatosis biomarkers showed a linear trend across the steatosis grades and a significant positive correlation with MRI-PDFF.The six steatosis biomarkers demonstrated AUCs near 0.90(range:0.857-0.912,all P<0.001)for diagnosing NAFLD by MRI-PDFF≥5%.The optimal cut-offs showed sensitivity between 84.4%-91.7%and specificity between 71.4%-85.7%.The diagnostic performance of these biomarkers in detecting moderate-to-severe and severe steatosis was relatively weaker.CONCLUSION These noninvasive steatosis biomarkers accurately diagnosed NAFLD and correlated well with MRI-PDFF for detecting NAFLD,but they did not effectively detect moderate or severe steatosis.展开更多
With the increasing demand for oil exploration and subsurface resource development,density imaging plays an increasingly important role in identifying thin layers.However,conventional density imaging tools are limited...With the increasing demand for oil exploration and subsurface resource development,density imaging plays an increasingly important role in identifying thin layers.However,conventional density imaging tools are limited by poor vertical resolution and therefore suffer from errors in accurately estimating the thickness and relative dip angle of thin layers.This affects the accurate evaluation of thin layer oil and gas reserves.To address this issue,this study evaluates the feasibility of employing novel methods based on advanced tool design.First,an electronically controllable X-ray source is selected to replace the traditional Cs-137 source,aiming to improve the tool's vertical resolution while reducing the radioactive risks commonly associated with chemical sources.Simulation results show that the X-ray tool provides sufficient depth of investigation with better vertical resolution while maintaining the same level of measurement sensitivity.Once the tool design is established,Fisher's optimal segmentation method is improved to enhance the estimation of thin layer thickness and relative dip angle.This is completed by transforming identifying thin layer interface into a mathematical clustering problem.The thin layer interface is fitted using the nonlinear least squares method,which enables the calculation of its parameters.The results demonstrate a 38.5%reduction in RMSE(root mean square error)for thin layer thickness and a 33.7%reduction in RMSE for relative dip angle,demonstrating the superior performance of enhanced X-ray tool in thin layer identification.This study provides a new perspective on the design of density imaging tools and assessment of thin layer,which can help in future thin layer hydrocarbon reserves evaluation and development decisions.展开更多
The objective of the present study was to access to imaging material density close to or identical density imaging of bone and soft tissue, from raw materials of nature to be used in different model applications and t...The objective of the present study was to access to imaging material density close to or identical density imaging of bone and soft tissue, from raw materials of nature to be used in different model applications and to provide comprehensive evaluation of the imaging system and techniques under realistic conditions in radiology departments for educational purposes. The palm tree of abundance in Saudi Arabia was chosen to study the date’s seeds and palm leaves in terms of photographic density. The results achieved were referring to the lack of imaging density of dates seeds and palm leaves compared to bone density. Thus, it was necessary to use two additional materials: Salt and eggshells in order to find the highest density and graphic approach to bone density. The present preliminary study indicated that the permanent and stable model can be achieved by palm leaves, salt & eggshell powder with imaging material density close to the imaging density of the bone and soft tissue for achieving more clinical skills and medical education.展开更多
The purpose of this work was to demonstrate the feasibility of neurite orientation dispersion and density imaging(NODDI)in characterizing the brain tissue microstructural changes of middle cerebral artery occlusion(MC...The purpose of this work was to demonstrate the feasibility of neurite orientation dispersion and density imaging(NODDI)in characterizing the brain tissue microstructural changes of middle cerebral artery occlusion(MCAO)in rats at 3T MRI,and to validate NODDI metrics with histology.A multi-shell diffusion MRI protocol was performed on 11 MCAO rats and 10 control rats at different post-operation time points of 0.5,2,6,12,24 and 72 h.NODDI orientation dispersion index(ODI)and intracellular volume fraction(V_(ic))metrics were compared between MCAO group and control group.The evolution of NODDI metrics was characterized and validated by histology.Infarction was consistent with significantly increased ODI and V_(ic)in comparison to control tissues at all time points(P<0.001).Lesion ODI increased gradually from 0.5 to 72 h,while its V_(ic)showed a more complicated and fluctuated evolution.ODI and V_(ic)were significantly different between hyperacute and acute stroke periods(P<0.001).The NODDI metrics were found to be consistent with the histological findings.In conclusion,NODDI can reflect microstructural changes of brain tissues in MCAO rats at 3T MRI and the metrics are consistent with histology.This study helps to prepare NODDI for the diagnosis and management of ischemic stroke in translational research and clinical practice.展开更多
The prevalence of neurodegenerative diseases is increasing as human longevity increases. The objective biomarkers that enable the staging and early diagnosis of neurodegenerative diseases are eagerly anticipated. It h...The prevalence of neurodegenerative diseases is increasing as human longevity increases. The objective biomarkers that enable the staging and early diagnosis of neurodegenerative diseases are eagerly anticipated. It has recently become possible to determine pathological changes in the brain without autopsy with the advancement of diffusion magnetic resonance imaging techniques. Diffusion magnetic resonance imaging is a robust tool used to evaluate brain microstructural complexity and integrity, axonal order, density, and myelination via the micron-scale displacement of water molecules diffusing in tissues. Diffusion tensor imaging, a type of diffusion magnetic resonance imaging technique is widely utilized in clinical and research settings;however, it has several limitations. To overcome these limitations, cutting-edge diffusion magnetic resonance imaging techniques, such as diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and free water imaging, have been recently proposed and applied to evaluate the pathology of neurodegenerative diseases. This review focused on the main applications, findings, and future directions of advanced diffusion magnetic resonance imaging techniques in patients with Alzheimer's and Parkinson's diseases, the first and second most common neurodegenerative diseases, respectively.展开更多
As the agricultural internet of things(IoT)technology has evolved,smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments.In this paper,we propose the concep...As the agricultural internet of things(IoT)technology has evolved,smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments.In this paper,we propose the concept of a vision-based navigation system for the agricultural IoT and a binocular vision navigation algorithm for smart agricultural robots,which can fuse the edge contour and the height information of rows of crop in images to extract the navigation parameters.First,the speeded-up robust feature(SURF)extracting and matching algorithm is used to obtain featuring point pairs from the green crop row images observed by the binocular parallel vision system.Then the confidence density image is constructed by integrating the enhanced elevation image and the corresponding binarized crop row image,where the edge contour and the height information of crop row are fused to extract the navigation parameters(θ,d)based on the model of a smart agricultural robot.Finally,the five navigation network instruction sets are designed based on the navigation angleθand the lateral distance d,which represent the basic movements for a certain type of smart agricultural robot working in a field.Simulated experimental results in the laboratory show that the algorithm proposed in this study is effective with small turning errors and low standard deviations,and can provide a valuable reference for the further practical application of binocular vision navigation systems in smart agricultural robots in the agricultural IoT system.展开更多
We have developed a new three dimensional (3-D) conductivity imaging approach and have used it to detect human brain conductivity changes corresponding to acute cerebral stroke. The proposed Magnetic Resonance Electri...We have developed a new three dimensional (3-D) conductivity imaging approach and have used it to detect human brain conductivity changes corresponding to acute cerebral stroke. The proposed Magnetic Resonance Electrical Impedance Tomography (MREIT) approach is based on the J-Substitution algorithm and is expanded to imaging 3-D subject conductivity distribution changes. Computer simulation studies have been conducted to evaluate the present MREIT imaging approach. Simulations of both types of cerebral stroke, hemorrhagic stroke and ischemic stroke, were performed on a four-sphere head model. Simulation results showed that the correlation coefficient (CC) and relative error (RE) between target and estimated conductivity distributions were 0.9245±0.0068 and 8.9997%±0.0084%, for hemorrhagic stroke, and 0.6748±0.0197 and 8.8986%±0.0089%, for ischemic stroke, when the SNR (signal-to-noise radio) of added GWN (Gaussian White Noise) was 40. The convergence characteristic was also evaluated according to the changes of CC and RE with different iteration numbers. The CC increases and RE decreases monotonously with the increasing number of iterations. The present simulation results show the feasibility of the proposed 3-D MREIT approach in hemorrhagic and ischemic stroke detection and suggest that the method may become a useful alternative in clinical diagnosis of acute cerebral stroke in humans.展开更多
In the modes of both object motion and camera motion,an enhanced Camshift algorithm,which is based on suppressing similar color features of background and on joint color probability density distribution image,is propo...In the modes of both object motion and camera motion,an enhanced Camshift algorithm,which is based on suppressing similar color features of background and on joint color probability density distribution image,is proposed to real-time track head in dynamic complex environment.The system consists of face detection module,head tracking module and camera control module.When tracking fails,a self-recovery mechanism is introduced.At first the Adaboost face detector based on Haar-like features is implemented to find frontal faces,the false positive is filtered according to the skin color criterion,and the true face is used to initialize the tracking module.In hue saturation value(HSV) colorspace,the hue-saturation(H-S) histogram of face skin and the saturation-value(S-V) histogram of hair are built to produce the joint color probability density distribution image,and this is intended to realize the head tracking with arbitrary pose.During tracking,region of interest(ROI) is introduced,and the color probability density distribution of a specified background area outside the ROI is learned,similar color features in the head are suppressed according to the learning result.The background suppression step is intended to resolve the problem that the tracker maybe fails when the head is distracted by backgrounds having similar colors with the head.A closed loop control model based on speed regulation is applied to drive an active camera to center the head.Once tracking drift or failure is detected,the system stops tracking and returns to the face detection module.Our experimental results show that the presented system is well suitable for tracking head with arbitrary pose in dynamic complex environments,also the active camera can track moving head smoothly and stably.The system is computationally efficient and can run in real-time completely.展开更多
During the last decades,advances in the understanding of genetic,cellular,and microstructural alterations associated to Huntington's disease(HD)have improved the understanding of this progressive and fatal illness...During the last decades,advances in the understanding of genetic,cellular,and microstructural alterations associated to Huntington's disease(HD)have improved the understanding of this progressive and fatal illness.However,events related to early neuropathological events,neuroinflammation,deterioration of neuronal connectivity and compensatory mechanisms still remain vastly unknown.Ultra-high field diffusion MRI(UHFD-MRI)techniques can contribute to a more comprehensive analysis of the early microstructural changes observed in HD.In addition,it is possible to evaluate if early imaging microstructural parameters might be linked to histological biomarkers.Moreover,qualitative studies analyzing histological complexity in brain areas susceptible to neurodegeneration could provide information on inflammatory events,compensatory increase of neuroconnectivity and mechanisms of brain repair and regeneration.The application of ultra-high field diffusion-MRI technology in animal models,particularly the R6/1 mice(a common preclinical mammalian model of HD),provide the opportunity to analyze alterations in a physiologically intact model of the disease.Although some disparities in volumetric changes across different brain structures between preclinical and clinical models has been documented,further application of different diffusion MRI techniques used in combination like diffusion tensor imaging,and neurite orientation dispersion and density imaging have proved effective in characterizing early parameters associated to alteration in water diffusion exchange within intracellular and extracellular compartments in brain white and grey matter.Thus,the combination of diffusion MRI imaging techniques and more complex neuropathological analysis could accelerate the discovery of new imaging biomarkers and the early diagnosis and neuromonitoring of patients affected with HD.展开更多
Diffusion magnetic resonance imaging(dMRI)is a noninvasive method to capture the anisotropic pattern of water displacement in the neuronal tissue.The soma and neurite density imaging(SANDI)model introduced soma size a...Diffusion magnetic resonance imaging(dMRI)is a noninvasive method to capture the anisotropic pattern of water displacement in the neuronal tissue.The soma and neurite density imaging(SANDI)model introduced soma size and density to biophysical model for the first time.In addition to neurite density,it can achieve their joint estimation non-invasively using dMRI.In the traditional method,parameters of the SANDI are estimated in a maximum likelihood frame-work,where the nonlinear model fitting is computationally intensive.Also,the present methods require a large number of diffusion gradients.Efficient and accurate algorithms for tissue microstructure estimation of SANDI is still a challenge currently.Consequently,we introduce deep learning method for tissue microstructure estimation of the SANDI model.The model comprises two functional components.The first component produces the sparse representation of diffusion sig-nals of input patches.The second component computes tissue microstructure from the sparse repre-sentation given by the first component.The deep network can produce not only tissue microstruc-ture estimates but also the uncertainty of the estimates with a reduced number of diffusion gradi-ents.Then,multiple deep networks are trained and their results are fused for the final prediction of tissue microstructure and uncertainty quantification.The deep network was evaluated on the MGH Connectome Diffusion Microstructure Dataset.Results indicate that our approach outperforms the traditional methods in terms of estimation accuracy.展开更多
Dementia is characterized by synaptic and neuronal dysfunction in disease-specific brain regions.Repeated failure of dementia clinical trials with therapeutic drugs targeting abnormal protein aggregates has caused res...Dementia is characterized by synaptic and neuronal dysfunction in disease-specific brain regions.Repeated failure of dementia clinical trials with therapeutic drugs targeting abnormal protein aggregates has caused researchers to shift their focus to synaptic functions and increased the importance of clinically available imaging for synaptic density and the development of synapse-targeted intervention.Synaptic density imaging with positron emission tomography(PET)tracer enables non-invasive detection of synaptic loss and hence investigates the association with other neuropathological events exemplified by disease-specific abnormal protein accumulation.Many studies have reviewed the progress of synaptic density imaging;however,to our knowledge,there is no article yet that summarizes the research progress of multimodal imaging of synaptic density tracers combined with other dementia biomarkers.Moreover,synaptic function intervention for dementia therapy has not yet been summarized.In this review,first we detail the progress of synaptic density imaging including tracer development and preclinical/clinical application,followed by a discussion of multimodal imaging of synaptic density tracers combined with classic dementia biomarkers in the clinical research stage.Finally,we briefly summarize the synapse-targeted drugs for dementia therapy.展开更多
Quantification of hepatic fat and iron content is important for early detection and monitoring of nonalcoholic fatty liver disease(NAFLD) patients. This study evaluated quantification efficiency of hepatic proton dens...Quantification of hepatic fat and iron content is important for early detection and monitoring of nonalcoholic fatty liver disease(NAFLD) patients. This study evaluated quantification efficiency of hepatic proton density fat fraction(PDFF) by MRI using NAFLD rabbits. R2* was also measured to investigate whether it correlates with fat levels in NAFLD. NAFLD rabbit model was successfully established by high fat and cholesterol diet. Rabbits underwent MRI examination for fat and iron analyses,compared with liver histological findings. MR examinations were performed on a 3.0 T MR system using multi-echo 3 D gradient recalled echo(GRE) sequence. MRI-PDFF showed significant differences between different steatosis grades with medians of3.72%(normal), 5.43%(mild), 9.11%(moderate) and 11.17%(severe), whereas this was not observed in R2*. Close correlation between MRI-PDFF and histological steatosis was observed(r=0.78, P=0.000). Hepatic iron deposit was not found in any rabbits. There was no correlation between R2* and either liver MRI-PDFF or histological steatosis. MR measuring MRI-PDFF and R2* simultaneously provides promising quantification of steatosis and iron. Rabbit NAFLD model confirmed accuracy of MRI-PDFF for liver fat quantification. R2* measurement and relationship between fat and iron of NAFLD liver need further experimental investigation.展开更多
Background Detection rate of retropharyngeal lymph node metastasis in patients with nasopharyngeal carcinoma （NPC） needs to be improved. The purpose of this study was to compare three magnetic resonance （MR） seque...Background Detection rate of retropharyngeal lymph node metastasis in patients with nasopharyngeal carcinoma （NPC） needs to be improved. The purpose of this study was to compare three magnetic resonance （MR） sequences for detecting lymph nodes in patients with NPC. Methods Between July 2007 and March 2008, MR staging of pre-treated tumor was conducted on 120 patients with pathologically confirmed NPC. The outcome of three different sequences for MR NPC staging were compared： coronal short T1 inversion recovery （STIR）, axial proton density fat-suppressed （PDWI fs）, and coronal contrast enhanced fast spin echo T1 weighted fat-suppressed （CE FSE TlWl fs）. Nodal classification method （1999） was applied to count the number of retropharyngeal and cervical lymph nodes discovered by each MR sequence. Paired t tests were used for statistical analysis. Results A total of 2575 lymph nodes were found using coronal STIR sequence; 1816 lymph nodes for coronal CE FSE TIWI fs sequence and 2638 lymph nodes for axial PDWl fs sequence. Significant differences existed in the number of lymph nodes detected by axial PDWI fs and coronal CE FSE T1WI fs sequence （paired t test, P 〈0.05）, with the former sequence getting higher numbers. Statistical differences also existed between coronal STIR and coronal CE FSE TlWl fs sequence （paired ttest, P 〈0.05）, with the former sequence getting higher numbers. No significant difference was found between coronal STIR sequence and axial PDWI fs sequence （paired ttest, P 〉0.05）. Conclusions For the detection of retropharyngeal and cervical lymph nodes, coronal STIR sequence and axial PDWI fs sequence have similar performance and both sequences showed better detection than CE FSE TIWI fs sequence. Furthermore, by combining coronal STIR sequence and axial PDWI fs sequence, we can improve the detection of lymph nodes in NPC N-staging before treatment, especially for lymph nodes located in the thoracic entrance.展开更多
Genetic susceptibility to metabolic associated fatty liver disease(MAFLD)is complex and poorly characterized.Accurate characterization of the genetic background of hepatic fat content would provide insights into disea...Genetic susceptibility to metabolic associated fatty liver disease(MAFLD)is complex and poorly characterized.Accurate characterization of the genetic background of hepatic fat content would provide insights into disease etiology and causality of risk factors.We performed genome-wide association study(GWAS)on two noninvasive definitions of hepatic fat content:magnetic resonance imaging proton density fat fraction(MRI-PDFF)in 16,050 participants and fatty liver index(FLI)in 388,701 participants from the United Kingdom(UK)Biobank(UKBB).Heritability,genetic overlap,and similarity between hepatic fat content phenotypes were analyzed,and replicated in 10,398 participants from the University Medical Center Groningen(UMCG)Genetics Lifelines Initiative(UGLI).Meta-analysis of GWASs of MRI-PDFF in UKBB revealed five statistically significant loci,including two novel genomic loci harboring CREB3L1(rs72910057-T,P=5.40E−09)and GCM1(rs1491489378-T,P=3.16E−09),respectively,as well as three previously reported loci:PNPLA3,TM6SF2,and APOE.GWAS of FLI in UKBB identified 196 genome-wide significant loci,of which 49 were replicated in UGLI,with top signals in ZPR1(P=3.35E−13)and FTO(P=2.11E−09).Statistically significant genetic correlation(rg)between MRI-PDFF(UKBB)and FLI(UGLI)GWAS results was found(rg=0.5276,P=1.45E−03).Novel MRI-PDFF genetic signals(CREB3L1 and GCM1)were replicated in the FLI GWAS.We identified two novel genes for MRI-PDFF and 49 replicable loci for FLI.Despite a difference in hepatic fat content assessment between MRI-PDFF and FLI,a substantial similar genetic architecture was found.FLI is identified as an easy and reliable approach to study hepatic fat content at the population level.展开更多
基金Supported by the Leap-forward Development Program for Beijing Biopharmaceutical Industry(G20),No.Z171100001717008the Fundamental Research Funds for the Central Universities and Research projects on biomedical transformation of China-Japan Friendship Hospital,No.PYBZ1815.
文摘BACKGROUND Nonalcoholic fatty liver disease(NAFLD)is the most common chronic liver disea-se.The accuracy of noninvasive biomarkers for detecting hepatic steatosis is still limited.AIM To assess the diagnostic performance of noninvasive steatosis biomarkers in diag-nosing NAFLD using magnetic resonance imaging proton density fat fraction(MRI-PDFF)as the gold standard.METHODS A total of 131 suspected NAFLD patients(60%male,median age 36 years)under-going MRI-PDFF were consecutively recruited from a tertiary hospital.Steatosis grades determined by MRI-PDFF were classified as none(<5%),mild(5%-11%),moderate(11%-17%),and severe(≥17%).Six steatosis biomarkers were calculated according to clinical parameters and laboratory tests,including fatty liver index,hepatic steatosis index,ZJU index,Framingham steatosis index,triglycerides and glucose index,and visceral adiposity index.The accuracy of these biomarkers in detecting hepatic steatosis was evaluated using the area under the receiver operating characteristic curves(AUCs).The Youden index was used to determine the optimal cut-off for each biomarker.The linear trend analysis of each biomarker across the steatosis grades was conducted by Mantel-Haenszelχ2 test.Spearman's rank correlation assessed the relationship between steatosis biomarkers and MRI-PDFF.RESULTS Steatosis grades based on MRI-PDFF prevalence were:None 27%,mild 40%,moderate 15%and severe 18%.Six steatosis biomarkers showed a linear trend across the steatosis grades and a significant positive correlation with MRI-PDFF.The six steatosis biomarkers demonstrated AUCs near 0.90(range:0.857-0.912,all P<0.001)for diagnosing NAFLD by MRI-PDFF≥5%.The optimal cut-offs showed sensitivity between 84.4%-91.7%and specificity between 71.4%-85.7%.The diagnostic performance of these biomarkers in detecting moderate-to-severe and severe steatosis was relatively weaker.CONCLUSION These noninvasive steatosis biomarkers accurately diagnosed NAFLD and correlated well with MRI-PDFF for detecting NAFLD,but they did not effectively detect moderate or severe steatosis.
基金the support of theNational Natural Science Foundation of China(U23B20151 and52171253)。
文摘With the increasing demand for oil exploration and subsurface resource development,density imaging plays an increasingly important role in identifying thin layers.However,conventional density imaging tools are limited by poor vertical resolution and therefore suffer from errors in accurately estimating the thickness and relative dip angle of thin layers.This affects the accurate evaluation of thin layer oil and gas reserves.To address this issue,this study evaluates the feasibility of employing novel methods based on advanced tool design.First,an electronically controllable X-ray source is selected to replace the traditional Cs-137 source,aiming to improve the tool's vertical resolution while reducing the radioactive risks commonly associated with chemical sources.Simulation results show that the X-ray tool provides sufficient depth of investigation with better vertical resolution while maintaining the same level of measurement sensitivity.Once the tool design is established,Fisher's optimal segmentation method is improved to enhance the estimation of thin layer thickness and relative dip angle.This is completed by transforming identifying thin layer interface into a mathematical clustering problem.The thin layer interface is fitted using the nonlinear least squares method,which enables the calculation of its parameters.The results demonstrate a 38.5%reduction in RMSE(root mean square error)for thin layer thickness and a 33.7%reduction in RMSE for relative dip angle,demonstrating the superior performance of enhanced X-ray tool in thin layer identification.This study provides a new perspective on the design of density imaging tools and assessment of thin layer,which can help in future thin layer hydrocarbon reserves evaluation and development decisions.
文摘The objective of the present study was to access to imaging material density close to or identical density imaging of bone and soft tissue, from raw materials of nature to be used in different model applications and to provide comprehensive evaluation of the imaging system and techniques under realistic conditions in radiology departments for educational purposes. The palm tree of abundance in Saudi Arabia was chosen to study the date’s seeds and palm leaves in terms of photographic density. The results achieved were referring to the lack of imaging density of dates seeds and palm leaves compared to bone density. Thus, it was necessary to use two additional materials: Salt and eggshells in order to find the highest density and graphic approach to bone density. The present preliminary study indicated that the permanent and stable model can be achieved by palm leaves, salt & eggshell powder with imaging material density close to the imaging density of the bone and soft tissue for achieving more clinical skills and medical education.
基金National Natural Science Foundation of China(No.81570462,No.81730049,and No.81801666).
文摘The purpose of this work was to demonstrate the feasibility of neurite orientation dispersion and density imaging(NODDI)in characterizing the brain tissue microstructural changes of middle cerebral artery occlusion(MCAO)in rats at 3T MRI,and to validate NODDI metrics with histology.A multi-shell diffusion MRI protocol was performed on 11 MCAO rats and 10 control rats at different post-operation time points of 0.5,2,6,12,24 and 72 h.NODDI orientation dispersion index(ODI)and intracellular volume fraction(V_(ic))metrics were compared between MCAO group and control group.The evolution of NODDI metrics was characterized and validated by histology.Infarction was consistent with significantly increased ODI and V_(ic)in comparison to control tissues at all time points(P<0.001).Lesion ODI increased gradually from 0.5 to 72 h,while its V_(ic)showed a more complicated and fluctuated evolution.ODI and V_(ic)were significantly different between hyperacute and acute stroke periods(P<0.001).The NODDI metrics were found to be consistent with the histological findings.In conclusion,NODDI can reflect microstructural changes of brain tissues in MCAO rats at 3T MRI and the metrics are consistent with histology.This study helps to prepare NODDI for the diagnosis and management of ischemic stroke in translational research and clinical practice.
基金supported by research grants from the program for Brain/MINDS Beyond program from the Japan Agency for Medical Research and Development(AMED)under Grant Number JP18dm0307024(to KK)MEXT-Supported Program for the Private University Research Branding Project+1 种基金ImPACT Program of Council for Science,Technology and Innovation(Cabinet Office,Government of Japan)JSPS KAKENHI Grant Number JP16K10327(to KK)
文摘The prevalence of neurodegenerative diseases is increasing as human longevity increases. The objective biomarkers that enable the staging and early diagnosis of neurodegenerative diseases are eagerly anticipated. It has recently become possible to determine pathological changes in the brain without autopsy with the advancement of diffusion magnetic resonance imaging techniques. Diffusion magnetic resonance imaging is a robust tool used to evaluate brain microstructural complexity and integrity, axonal order, density, and myelination via the micron-scale displacement of water molecules diffusing in tissues. Diffusion tensor imaging, a type of diffusion magnetic resonance imaging technique is widely utilized in clinical and research settings;however, it has several limitations. To overcome these limitations, cutting-edge diffusion magnetic resonance imaging techniques, such as diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and free water imaging, have been recently proposed and applied to evaluate the pathology of neurodegenerative diseases. This review focused on the main applications, findings, and future directions of advanced diffusion magnetic resonance imaging techniques in patients with Alzheimer's and Parkinson's diseases, the first and second most common neurodegenerative diseases, respectively.
基金the National Natural Science Foundationof China(No.31760345).
文摘As the agricultural internet of things(IoT)technology has evolved,smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments.In this paper,we propose the concept of a vision-based navigation system for the agricultural IoT and a binocular vision navigation algorithm for smart agricultural robots,which can fuse the edge contour and the height information of rows of crop in images to extract the navigation parameters.First,the speeded-up robust feature(SURF)extracting and matching algorithm is used to obtain featuring point pairs from the green crop row images observed by the binocular parallel vision system.Then the confidence density image is constructed by integrating the enhanced elevation image and the corresponding binarized crop row image,where the edge contour and the height information of crop row are fused to extract the navigation parameters(θ,d)based on the model of a smart agricultural robot.Finally,the five navigation network instruction sets are designed based on the navigation angleθand the lateral distance d,which represent the basic movements for a certain type of smart agricultural robot working in a field.Simulated experimental results in the laboratory show that the algorithm proposed in this study is effective with small turning errors and low standard deviations,and can provide a valuable reference for the further practical application of binocular vision navigation systems in smart agricultural robots in the agricultural IoT system.
基金Project supported partly by the National Science Foundation (No.BES-0411898) and the National Institues of Health (No. R01EB00178) USA
文摘We have developed a new three dimensional (3-D) conductivity imaging approach and have used it to detect human brain conductivity changes corresponding to acute cerebral stroke. The proposed Magnetic Resonance Electrical Impedance Tomography (MREIT) approach is based on the J-Substitution algorithm and is expanded to imaging 3-D subject conductivity distribution changes. Computer simulation studies have been conducted to evaluate the present MREIT imaging approach. Simulations of both types of cerebral stroke, hemorrhagic stroke and ischemic stroke, were performed on a four-sphere head model. Simulation results showed that the correlation coefficient (CC) and relative error (RE) between target and estimated conductivity distributions were 0.9245±0.0068 and 8.9997%±0.0084%, for hemorrhagic stroke, and 0.6748±0.0197 and 8.8986%±0.0089%, for ischemic stroke, when the SNR (signal-to-noise radio) of added GWN (Gaussian White Noise) was 40. The convergence characteristic was also evaluated according to the changes of CC and RE with different iteration numbers. The CC increases and RE decreases monotonously with the increasing number of iterations. The present simulation results show the feasibility of the proposed 3-D MREIT approach in hemorrhagic and ischemic stroke detection and suggest that the method may become a useful alternative in clinical diagnosis of acute cerebral stroke in humans.
文摘In the modes of both object motion and camera motion,an enhanced Camshift algorithm,which is based on suppressing similar color features of background and on joint color probability density distribution image,is proposed to real-time track head in dynamic complex environment.The system consists of face detection module,head tracking module and camera control module.When tracking fails,a self-recovery mechanism is introduced.At first the Adaboost face detector based on Haar-like features is implemented to find frontal faces,the false positive is filtered according to the skin color criterion,and the true face is used to initialize the tracking module.In hue saturation value(HSV) colorspace,the hue-saturation(H-S) histogram of face skin and the saturation-value(S-V) histogram of hair are built to produce the joint color probability density distribution image,and this is intended to realize the head tracking with arbitrary pose.During tracking,region of interest(ROI) is introduced,and the color probability density distribution of a specified background area outside the ROI is learned,similar color features in the head are suppressed according to the learning result.The background suppression step is intended to resolve the problem that the tracker maybe fails when the head is distracted by backgrounds having similar colors with the head.A closed loop control model based on speed regulation is applied to drive an active camera to center the head.Once tracking drift or failure is detected,the system stops tracking and returns to the face detection module.Our experimental results show that the presented system is well suitable for tracking head with arbitrary pose in dynamic complex environments,also the active camera can track moving head smoothly and stably.The system is computationally efficient and can run in real-time completely.
基金supported in part by the High Magnetic Field Laboratory(NHMFL)and Advanced Magnetic Resonance Imaging and Spectroscopy(AMRIS)under Magnetic Laboratory Visiting Scientist Program Award,No.VSP#327(to RG)。
文摘During the last decades,advances in the understanding of genetic,cellular,and microstructural alterations associated to Huntington's disease(HD)have improved the understanding of this progressive and fatal illness.However,events related to early neuropathological events,neuroinflammation,deterioration of neuronal connectivity and compensatory mechanisms still remain vastly unknown.Ultra-high field diffusion MRI(UHFD-MRI)techniques can contribute to a more comprehensive analysis of the early microstructural changes observed in HD.In addition,it is possible to evaluate if early imaging microstructural parameters might be linked to histological biomarkers.Moreover,qualitative studies analyzing histological complexity in brain areas susceptible to neurodegeneration could provide information on inflammatory events,compensatory increase of neuroconnectivity and mechanisms of brain repair and regeneration.The application of ultra-high field diffusion-MRI technology in animal models,particularly the R6/1 mice(a common preclinical mammalian model of HD),provide the opportunity to analyze alterations in a physiologically intact model of the disease.Although some disparities in volumetric changes across different brain structures between preclinical and clinical models has been documented,further application of different diffusion MRI techniques used in combination like diffusion tensor imaging,and neurite orientation dispersion and density imaging have proved effective in characterizing early parameters associated to alteration in water diffusion exchange within intracellular and extracellular compartments in brain white and grey matter.Thus,the combination of diffusion MRI imaging techniques and more complex neuropathological analysis could accelerate the discovery of new imaging biomarkers and the early diagnosis and neuromonitoring of patients affected with HD.
文摘Diffusion magnetic resonance imaging(dMRI)is a noninvasive method to capture the anisotropic pattern of water displacement in the neuronal tissue.The soma and neurite density imaging(SANDI)model introduced soma size and density to biophysical model for the first time.In addition to neurite density,it can achieve their joint estimation non-invasively using dMRI.In the traditional method,parameters of the SANDI are estimated in a maximum likelihood frame-work,where the nonlinear model fitting is computationally intensive.Also,the present methods require a large number of diffusion gradients.Efficient and accurate algorithms for tissue microstructure estimation of SANDI is still a challenge currently.Consequently,we introduce deep learning method for tissue microstructure estimation of the SANDI model.The model comprises two functional components.The first component produces the sparse representation of diffusion sig-nals of input patches.The second component computes tissue microstructure from the sparse repre-sentation given by the first component.The deep network can produce not only tissue microstruc-ture estimates but also the uncertainty of the estimates with a reduced number of diffusion gradi-ents.Then,multiple deep networks are trained and their results are fused for the final prediction of tissue microstructure and uncertainty quantification.The deep network was evaluated on the MGH Connectome Diffusion Microstructure Dataset.Results indicate that our approach outperforms the traditional methods in terms of estimation accuracy.
基金funding support from the National Natural Science Foundation of China(81971016)Shanghai Science and Technology program(21010502300)Construction project of Shanghai Key Laboratory of Molecular Imaging(18DZ2260400).
文摘Dementia is characterized by synaptic and neuronal dysfunction in disease-specific brain regions.Repeated failure of dementia clinical trials with therapeutic drugs targeting abnormal protein aggregates has caused researchers to shift their focus to synaptic functions and increased the importance of clinically available imaging for synaptic density and the development of synapse-targeted intervention.Synaptic density imaging with positron emission tomography(PET)tracer enables non-invasive detection of synaptic loss and hence investigates the association with other neuropathological events exemplified by disease-specific abnormal protein accumulation.Many studies have reviewed the progress of synaptic density imaging;however,to our knowledge,there is no article yet that summarizes the research progress of multimodal imaging of synaptic density tracers combined with other dementia biomarkers.Moreover,synaptic function intervention for dementia therapy has not yet been summarized.In this review,first we detail the progress of synaptic density imaging including tracer development and preclinical/clinical application,followed by a discussion of multimodal imaging of synaptic density tracers combined with classic dementia biomarkers in the clinical research stage.Finally,we briefly summarize the synapse-targeted drugs for dementia therapy.
文摘Quantification of hepatic fat and iron content is important for early detection and monitoring of nonalcoholic fatty liver disease(NAFLD) patients. This study evaluated quantification efficiency of hepatic proton density fat fraction(PDFF) by MRI using NAFLD rabbits. R2* was also measured to investigate whether it correlates with fat levels in NAFLD. NAFLD rabbit model was successfully established by high fat and cholesterol diet. Rabbits underwent MRI examination for fat and iron analyses,compared with liver histological findings. MR examinations were performed on a 3.0 T MR system using multi-echo 3 D gradient recalled echo(GRE) sequence. MRI-PDFF showed significant differences between different steatosis grades with medians of3.72%(normal), 5.43%(mild), 9.11%(moderate) and 11.17%(severe), whereas this was not observed in R2*. Close correlation between MRI-PDFF and histological steatosis was observed(r=0.78, P=0.000). Hepatic iron deposit was not found in any rabbits. There was no correlation between R2* and either liver MRI-PDFF or histological steatosis. MR measuring MRI-PDFF and R2* simultaneously provides promising quantification of steatosis and iron. Rabbit NAFLD model confirmed accuracy of MRI-PDFF for liver fat quantification. R2* measurement and relationship between fat and iron of NAFLD liver need further experimental investigation.
基金This study was supported by a grant from the Natural Science Foundation of Fujian Province （No. 2004Y008）.
文摘Background Detection rate of retropharyngeal lymph node metastasis in patients with nasopharyngeal carcinoma （NPC） needs to be improved. The purpose of this study was to compare three magnetic resonance （MR） sequences for detecting lymph nodes in patients with NPC. Methods Between July 2007 and March 2008, MR staging of pre-treated tumor was conducted on 120 patients with pathologically confirmed NPC. The outcome of three different sequences for MR NPC staging were compared： coronal short T1 inversion recovery （STIR）, axial proton density fat-suppressed （PDWI fs）, and coronal contrast enhanced fast spin echo T1 weighted fat-suppressed （CE FSE TlWl fs）. Nodal classification method （1999） was applied to count the number of retropharyngeal and cervical lymph nodes discovered by each MR sequence. Paired t tests were used for statistical analysis. Results A total of 2575 lymph nodes were found using coronal STIR sequence; 1816 lymph nodes for coronal CE FSE TIWI fs sequence and 2638 lymph nodes for axial PDWl fs sequence. Significant differences existed in the number of lymph nodes detected by axial PDWI fs and coronal CE FSE T1WI fs sequence （paired t test, P 〈0.05）, with the former sequence getting higher numbers. Statistical differences also existed between coronal STIR and coronal CE FSE TlWl fs sequence （paired ttest, P 〈0.05）, with the former sequence getting higher numbers. No significant difference was found between coronal STIR sequence and axial PDWI fs sequence （paired ttest, P 〉0.05）. Conclusions For the detection of retropharyngeal and cervical lymph nodes, coronal STIR sequence and axial PDWI fs sequence have similar performance and both sequences showed better detection than CE FSE TIWI fs sequence. Furthermore, by combining coronal STIR sequence and axial PDWI fs sequence, we can improve the detection of lymph nodes in NPC N-staging before treatment, especially for lymph nodes located in the thoracic entrance.
基金supported by the Netherlands Organization for Scientific Research NWO(Grant No.175.010.2007.006)the Economic Structure Enhancing Fund of the Dutch government+20 种基金the Ministry of Economic Affairsthe Ministry of Education,Culture,and Sciencethe Ministry for Health,Welfare,and Sportsthe Northern Netherlands Alliancethe Province of Groningen,University Medical Center Groningenthe University of Groningen,Dutch Kidney Foundation,and Dutch Diabetes Research Foundationsupported by the Dutch Heart Foundation IN-CONTROL(Grant No.CVON2018-27)the ERC Consolidator Grant(Grant No.101001678)the NWO VICI(Grant No.VI.C.202.022)the Netherlands Organ-on-Chip Initiative,an NWO Gravitation project(Grant No.024.003.001)funded by the Ministry of Education,CultureScience of the government of The Netherlandssupported by the Chinese Scholarship Council.Dasha V.Zhernakova was supported by the NWO VENI(Grant No.194.006)supported by the Seerave Foundation.Rinse K.Weersma and Ranko Gacesa were supported by the TIMID project(Grant No.LSHM18057-SGF)financed by the PPP Allowance made available by Top Sector Life Sciences&Health to Samenwerkende Gezondheidsfondsen(SGF)to stimulate public–private partnerships and co-financing by health foundations that are part of the SGFsupported by the NWO VENI(Grant No.09150161810030)the Health∼Holland Public Private Partnership from the Dutch Ministry of Economic Affairs(Grant No.#PPP-2019-024)supported by the UK Medical Research Council and Wellcome Trustthe UK Department of Healththe Scottish and Welsh Governmentsthe North West Development Agencythe British Heart Foundationthe Diabetes UK.
文摘Genetic susceptibility to metabolic associated fatty liver disease(MAFLD)is complex and poorly characterized.Accurate characterization of the genetic background of hepatic fat content would provide insights into disease etiology and causality of risk factors.We performed genome-wide association study(GWAS)on two noninvasive definitions of hepatic fat content:magnetic resonance imaging proton density fat fraction(MRI-PDFF)in 16,050 participants and fatty liver index(FLI)in 388,701 participants from the United Kingdom(UK)Biobank(UKBB).Heritability,genetic overlap,and similarity between hepatic fat content phenotypes were analyzed,and replicated in 10,398 participants from the University Medical Center Groningen(UMCG)Genetics Lifelines Initiative(UGLI).Meta-analysis of GWASs of MRI-PDFF in UKBB revealed five statistically significant loci,including two novel genomic loci harboring CREB3L1(rs72910057-T,P=5.40E−09)and GCM1(rs1491489378-T,P=3.16E−09),respectively,as well as three previously reported loci:PNPLA3,TM6SF2,and APOE.GWAS of FLI in UKBB identified 196 genome-wide significant loci,of which 49 were replicated in UGLI,with top signals in ZPR1(P=3.35E−13)and FTO(P=2.11E−09).Statistically significant genetic correlation(rg)between MRI-PDFF(UKBB)and FLI(UGLI)GWAS results was found(rg=0.5276,P=1.45E−03).Novel MRI-PDFF genetic signals(CREB3L1 and GCM1)were replicated in the FLI GWAS.We identified two novel genes for MRI-PDFF and 49 replicable loci for FLI.Despite a difference in hepatic fat content assessment between MRI-PDFF and FLI,a substantial similar genetic architecture was found.FLI is identified as an easy and reliable approach to study hepatic fat content at the population level.
