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Purpose To explore the application value of combining 18F-FDG PET images with interpretable deep learning radiomics(IDLR)models in the differential diagnosis of primary Parkinson's disease(IPD)and atypical Parkinson's syndrome.Materials and Methods This cross-sectional study was conducted using the Parkinson's Disease PET Imaging Benchmark Database from Huashan Hospital,Fudan University from March 2015 to February 2023.A total of 330 Parkinson's disease patients underwent 18F-FDG PET imaging,both 18F-FDG PET imaging and clinical scale information were collected for all subjects.The study included two cohorts,a training group(n=270)and a testing group(n=60),with a total of 211 cases in the IPD group,59 cases in the progressive supranuclear palsy(PSP)group,and a group of 60 patients with multiple system atrophy(MSA).The clinical information between different groups were compared.An IDLR model was developed to extract feature indicators.Under the supervision of radiomics features,IDLR features were selected from the features collected by neural network extractors,and a binary support vector machine model was constructed for the selected features in images of in testing group.The constructed IDLR model,traditional radiomics model and standard uptake ratio model were separately used to calculate the performance metrics and area under curve values of deep learning models for pairwise classification between IPD/PSP/MSA groups.The study conducted independent classification and testing in two cohorts using 100 10-fold cross-validation tests.Brain-related regions of interest were displayed through feature mapping,using gradient weighted class activation maps to highlight and visualize the most relevant information in the brain.The output heatmaps of different disease groups were examined and compared with clinical diagnostic locations.Results The IDLR model showed promising results for differentiating between Parkinson's syndrome patients.It achieved the best classification performance and had the highest area under the curve values compared to other comparative models such as the standard uptake ratio model(Z=1.22-3.23,all P<0.05),and radiomics model(Z=1.31-2.96,all P<0.05).The area under the curve values for the IDLR model in differentiating MSA and IPD were 0.935 7,for MSA and PSP were 0.975 4,for IPD and PSP were 0.982 5 in the test set.The IDLR model also showed consistency between its filtered feature maps and the visualization of gradient-weighted class activation mapping slice thermal maps in the radiomics regions of interest.Conclusion The IDLR model has the potential for differential diagnosis between IPD and atypical Parkinson's syndrome in 18F-FDG PET images.
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Fluorescence diffuse optical tomography (FDOT) is a new molecular imaging technology, which uses near-infrared light to excite the fluorophore in tissues. According to the measurements detected on the surface of imaged object, the fluorescent quantum yield as well as lifetime of the fluorescence can be reconstructed. However, the reconstruction of FDOT remains a challenging problem because the conventional forward solvers are time consuming. Thus, a forward model solver that would enable the fast imaging is necessary. This paper describes a new forward solver to simulate the propagation of photons in tissues based on the lattice Boltzmann method (LBM). This is accomplished by propagation photons in tissues guided by the LBM. To evaluate the performance of the proposed LBM, based on the numerical simulation, we compared the light distribution generated by the LBM with the diffusion equation implemented by COMSOL in four different cases. The experimental results indicate that compared to diffusion equation, the LBM can reduce the computation time for the forward solver of FDOT while preserving the similar accuracy.
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Tomografía Óptica , Difusión , Colorantes Fluorescentes , Imagen Molecular , FotonesRESUMEN
Blood Pressure (BP) measurement can assist doctors to assess patients' cardiovascular status and diagnose heart diseases. Pulse Wave Transit Time (PWTT) model is one frequently used BP estimation method to monitor BP continuously in clinics. However, individual variations may influence the measurement accuracy of PWTT model. Focusing on above promble, this paper proposes a novel BP estimation method combining a classical PWTT model and a neural network model. The novel method is composed of five steps: signal pre-processing, feature extraction, initial PWTT model selection, model correction by neural network model, and final PWTT model identification. A validation experiment based on 10 patients from Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) database showed that the BP estimation results by our method had a minimum mean of error readout value 5 mmHg with a standard deviation of error readout value ±8mmHg. As a result, both the diastolic blood pressure and systolic blood pressure estimation by our method can meet clinical requirements.
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Determinación de la Presión Sanguínea , Presión Sanguínea , Humanos , Redes Neurales de la Computación , Análisis de la Onda del Pulso , Procesamiento de Señales Asistido por ComputadorRESUMEN
Cone-beam X-ray luminescence optical tomography (CB-XLOT) plays an important role in in vivo small animal imaging study, which can non-invasively image the three-dimensional (3-D) distribution of x-ray-excitable nanophosphors deeply embedded in imaged object. However, CB-XLOT suffers from a low spatial resolution due to the ill-posed nature of optical reconstruction. To alleviate the ill-posedness of reconstruction and improve the imaging performance of XLOT, in this paper, we propose an iterative weighted L1 minimization method which is achieved by incorporating YALL1 (Your algorithm for L1 norm problems). The physical phantom experiment was conducted to evaluate the performance of the proposed method, where a custom-made cone-beam XLOT system was used as the imaging platform. The experimental results indicate that by applying the proposed iterative weighted strategy to YALL1 method, the reconstruction performance of XLOT can be improved when compared with the conventional YALL1 method.
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Tomografía Computarizada de Haz Cónico , Algoritmos , Procesamiento de Imagen Asistido por Computador , Luminiscencia , Fantasmas de Imagen , Tomografía Óptica , Tomografía Computarizada por Rayos X , Rayos XRESUMEN
Biomedical Engineering (BME) bachelor education aims to train qualified engineers who devote themselves to addressing biological and medical problems by integrating the technological, medical and biological knowledge. Design thinking and teamwork with other disciplines are necessary for biomedical engineers. In the current biomedical engineering education system of Shanghai University (SHU), however, such design thinking and teamwork through a practical project is lacking. This paper describes a creative "joint assignment" project in Shanghai University, China, which has provided BME bachelor students a two-year practical experience to work with students from multidisciplinary departments including sociology, mechanics, computer sciences, business and art, etc. To test the feasibility of this project, a twenty-month pilot project has been carried out from May 2015 to December 2016. The results showed that this pilot project obviously enhanced competitive power of BME students in Shanghai University, both in the capabilities of design thinking and teamwork.
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Ingeniería Biomédica , China , Curriculum , Proyectos Piloto , UniversidadesRESUMEN
The "joint assignment" is a creative bachelor education project for Biomedical Engineering (BME) in Shanghai University (SHU), China. The objective of this project is to improve students' capabilities in design thinking and teamwork through practices in the process of the design and development of complex medical product. As the first step, a pilot project "design and development of intelligent nursing bed" was set up in May 2015. This paper describes details of how project organization and management, various teaching methods and scientific evaluation approaches were achieved in this pilot project. For example, a method containing one main line and four branches is taken to manage the project and "prototyping model" was used as the main research approach. As a result a multi-win situation was achieved. The results showed, firstly, 62 bachelor students including 16 BME students were well trained. They improved themselves in use of practical tools, communication skills and scientific writing; Secondly, commercial companies received a nice product design on intelligent nursing bed, and have been working on industrializing it; Thirdly, the university and associated schools obtained an excellent practical education experience to supplement traditional class education; Fourthly and most importantly, requirements from end-users will be met. The results also showed that the "joint assignment" task could become a significant component in BME bachelor education.
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Lechos , Proyectos Piloto , Estudiantes , Estudiantes de Enfermería , Pensamiento , EscrituraRESUMEN
Objective:To explore the potential application of combining 18F-FDG PET imaging and radiomics in the diagnosis of Parkinson′s disease (PD) and atypical parkinsonian syndromes (APS). Methods:A total of 154 subjects of two cohorts (training set and validation set) were enrolled from Huashan Hospital, Fudan University from March 2015 to August 2020 in this cross-sectional study, including 40 normal controls (NC; 23 males and 17 females, age: (60.2±10.5) years), 40 PD patients (20 males and 20 females, age: (64.7±6.3) years), 40 progressive supranuclear palsy (PSP) patients (20 males and 20 females, age: (64.1±5.9) years), and 34 multiple system atrophy (MSA) patients (19 males and 15 females, age: (65.0±9.2) years). 18F-FDG PET images and clinical scale were selected, and one-way analysis of variance was used to compare differences of clinical scale among groups. Radiomic features extraction and feature selection were carried out. Two and three classification models were constructed based on logistic regression, and the ROC curves of clinical model, radiomics model and combined model were calculated. Independent classification tests were conducted 100 times with 5-fold cross validation in two cohorts. Results:There were significant differences in the scores of unified PD Rating Scale (UPDRS) and Hoehn-Yahr rating scale (H&Y) among different groups in cohort 1 and cohort 2 respectively ( F values: 4.83-17.95, all P<0.05). A total of 2 444 imaging features were extracted from each subject, and after features selection, 15 features for classification were obtained. In the two classification experiment, the AUCs of the three models in binary classification of PD/MSA/PSP/NC group were 0.56-0.68, 0.74-0.93 and 0.72-0.93, respectively. The classification effects of the radiomics model were significantly better than those of the clinical model ( z values: 1.71-2.85, all P<0.05). In the three classification experiment, the sensitivity of the radiomics model reached 80%, 80% and 77% for PD, MSA and PSP, respectively. Conclusion:18F-FDG imaging combined with radiomics has potential in the diagnosis of PD and APS.
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Objective:To reveal the abnormal topology of brain network in Alzheimer′s disease (AD), and evaluate the laterality of tau protein deposition in brains of AD patients based on 18F-APN-1607 PET brain imaging combined with graph theory. Methods:From November 2018 to January 2020, 23 clinically diagnosed AD patients (9 males, 14 females; age (61.3±10.7) years) and 13 normal controls (NC) (9 males, 4 females; age (61.6±4.5) years) who underwent 18F-APN-1607 PET imaging in Huashan Hospital, Fudan University were analyzed in this cross-sectional study. The brain network analysis method based on graph theory was used to construct the tau network of the NC group and the AD group, the network attributes (clustering coefficient, shortest path length, local efficiency, and small-worldness) were calculated, and the asymmetry index (AI) of each group to evaluate the laterality of tau protein deposition was obtained. Permutation test (1 000 times) was used to analyze the differences in brain network parameters between the NC group and the AD group. Results:The tau network of the AD group had obvious topological disorder, and the connections in the olfactory cortex and temporal lobe were weakened, while in the posterior cingulate gyrus, anterior wedge, and parietal occipital lobe, the connections were enhanced. Compared with NC group, clustering coefficient ( t values: 2.28-2.69), local efficiency ( t values: 2.34-3.06) and small-worldness ( t values: 2.26-3.32) were significantly decreased in AD group (all P<0.05) with the sparsity of 20%-50%, while the shortest path length was significantly increased ( t values: 2.13-2.85; all P<0.05). There was significant tau laterality in the posterior cingulate gyrus, superior parietal gyrus, paracentral lobule, superior temporal gyrus and middle temporal gyrus (AI: 10.5%(8.1%, 13.9%), 14.1%(7.6%, 20.3%), -12.4%(-15.7%, -7.8%), -10.8%(-15.3%, -2.1%) , -12.1%(-17.9%, -6.6%), respectively). Conclusion:The tau network analysis based on 18F-APN-1607 may be used to reveal abnormal topological changes of AD patients, and the tau deposition in the posterior cingulate gyrus, superior parietal gyrus, paracentral lobule, superior temporal gyrus and middle temporal gyrus has obvious laterality in AD patients.
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Objective:Exploring tau related disease pattern (tauRDP) in the brain of Alzheimer′s disease (AD) patients based on 18F-APN-1607 PET scan. Methods:18F-APN-1607 PET images were collected from 17 AD patients (6 males and 11 females, age: (61.7±12.3) years, Mini-Mental State Examination (MMSE) score: 17.6±7.9) and 10 normal controls (NC; 6 males and 4 females, age: (61.2±4.7) years) from Huashan Hospital of Fudan University. The scaled subprofile model (SSM) based on principal component analysis (PCA) technique was used to construct the tauRDP. Then the expression value of tauRDP in each sample was calculated. The differences on tauRDP expression values between AD patients and NC were compared by independent-sample t test. Pearson correlation analysis was used to analyze the correlation between tauRDP expression values and MMSE values in AD patients. Results:The tauRDP area mainly included: precentral gyrus, dorsolateral superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus of opercular part, inferior frontal gyrus of triangular part, supplementary motor area, medial superior frontal gyrus, left median cingulate and paracingulate gyri, right cuneus, superior occipital gyrus, middle occipital gyrus, postcentral gyrus, superior parietal gyrus inferior parietal, but supramarginal and angular gyri, supramarginal gyrus, angular gyrus, precuneus and middle temporal gyrus. There were significant differences ( t=4.395, P<0.001) between AD group (12.6±8.0) and NC group (0.0±1.0) in tauRDP expression values. The tauRDP expression values were correlated with MMSE values in AD group significantly ( r=-0.566, P=0.018). Conclusions:TauRDP established basing on SSM/PCA method can be used to quantitatively express the abnormal spatial distributions of tau deposition. Expression value of tauRDP has the potential to initially assess the severity of AD.
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Objective To explore the topological abnormality of brain metabolic network in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and compare it with the topology of brain metabolic network in patients with Parkinson's disease (PD).Methods The 18F-fluorodeoxyglucose (FDG) PET brain images of 19 patients with iRBD diagnosed with polysomnography (PSG) (iRBD group;15 males,4 females,average age:64.9 years),19 patients with PD (PD group;12 males,7 females,average age:62.2 years) and 19 gender and age-matched healthy controls (HC group;15 males,4 females,average age:63.1 years) in Huashan Hospital from September 2014 to June 2015 were retrospectively analyzed.According to the complex brain network method based on graph theory,the brain metabolic networks of each group was constructed and the network parameters (clustering coefficient,characteristic path length,local efficiency,global efficiency and small-world property,etc) were evaluated quantitatively.The 500 times non-parametric permutation test was used to determine the differences in network parameters between groups.Results The brain metabolic networks of iRBD group and PD group both had abnormal topological structure,which showed that the characteristic path length (for example,when sparsity =34%,HC vs iRBD vs PD groups:1.517 vs 1.552 vs 1.561) and local efficiency (for example,when sparsity=30%,HC vs iRBD vs PD groups:0.802 vs 0.824 vs 0.831) were significantly increased (both P<0.05),the global efficiency (for example,when sparsity =36%,HC vs iRBD vs PD groups:0.672 vs 0.658 vs 0.656) was significantly decreased (P<0.05).The topology was more aggravated in PD group compared with that in iRBD group.Conclusion The graph-based complex brain network analysis can reveal the abnormal topological structure of the brain metabolic network in which iRBD progresses to PD.
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Objective@#To explore the topological abnormality of brain metabolic network in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and compare it with the topology of brain metabolic network in patients with Parkinson′s disease (PD).@*Methods@#The 18F-fluorodeoxyglucose (FDG) PET brain images of 19 patients with iRBD diagnosed with polysomnography (PSG) (iRBD group; 15 males, 4 females, average age: 64.9 years), 19 patients with PD (PD group; 12 males, 7 females, average age: 62.2 years) and 19 gender and age-matched healthy controls (HC group; 15 males, 4 females, average age: 63.1 years) in Huashan Hospital from September 2014 to June 2015 were retrospectively analyzed. According to the complex brain network method based on graph theory, the brain metabolic networks of each group was constructed and the network parameters (clustering coefficient, characteristic path length, local efficiency, global efficiency and small-world property, etc) were evaluated quantitatively. The 500 times non-parametric permutation test was used to determine the differences in network parameters between groups.@*Results@#The brain metabolic networks of iRBD group and PD group both had abnormal topological structure, which showed that the characteristic path length (for example, when sparsity=34%, HC vs iRBD vs PD groups: 1.517 vs 1.552 vs 1.561) and local efficiency (for example, when sparsity=30%, HC vs iRBD vs PD groups: 0.802 vs 0.824 vs 0.831) were significantly increased (both P<0.05), the global efficiency (for example, when sparsity=36%, HC vs iRBD vs PD groups: 0.672 vs 0.658 vs 0.656) was significantly decreased (P<0.05). The topology was more aggravated in PD group compared with that in iRBD group.@*Conclusion@#The graph-based complex brain network analysis can reveal the abnormal topological structure of the brain metabolic network in which iRBD progresses to PD.
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In aging society the development of non-invasive continuously blood pressure monitors which are suitable for homes, communities and nursing homes has a wide range of applications. This paper proposes a non-invasive continuously blood pressure monitoring based on wearable device which uses MSP430F5529 as the central processor. The design is divided into signal acquisition module, central control module, display module, power supply module and host computer module. The experimental results showed that DBP (375/390, 96.15%) and SBP estimation values (377/390, 96.67%) are in 95% confidence interval, which means our design passes Bland-Altman test with high accuracy and stability.
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Presión Sanguínea , Determinación de la Presión Sanguínea , Monitores de Presión Sanguínea , Suministros de Energía Eléctrica , Dispositivos Electrónicos VestiblesRESUMEN
With the advent of social aging, the development of intelligent multifunctional nursing beds that are suitable for hospitals, nursing homes, homes and the like has a wide range of applications, this paper presents an intelligent nursing bed design based on Internet of Things technology. The design uses STM32F103 as the central processor. The design is divided into nursing bed module based on tri-fold structure, central control module based on data processing, weight scale module based on weight detection, power supply module based on system power supply and host computer module based on user operation. The design uses a closed control mode, greatly improving the bed control accuracy. Experimental tests showed that under the action of the intelligent control bed control system, the error rate of bed position information driven bedboard can be less than 2%, which has high accuracy and stability.
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Lechos , Diseño de Equipo , Hospitales , Internet , Monitoreo Fisiológico , Casas de Salud , TecnologíaAsunto(s)
Ingeniería Biomédica/organización & administración , Biotecnología/organización & administración , Educación Profesional/organización & administración , Pobreza/prevención & control , Sociedades/organización & administración , Universidades/organización & administración , China , Humanos , EstudiantesRESUMEN
China has a largest population in the world (1.3Billion) and 0.9 Billion is rural population. Most of rural people earn less than US$3/day, and they are called 'Base of the economic pyramid (BoP)'. Compared with high level market, BoP is a new market, which means a low individual profit, but a large population. This paper discusses the healthcare issues in rural China (BoP) and study their healthcare needs through field study and case studies. This research is carried out within the framework of 'Design for Sustainability at Base-of-the-Pyramid (BoP)' programme of the School of Industrial Design Engineering at Delft University of Technology. And the aim of this research is to provide a low cost advanced healthcare product design, which will meet poor's needs and create a business case for commercial partners.
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Atención a la Salud/economía , Atención a la Salud/organización & administración , Población Rural , China , Factores SocioeconómicosRESUMEN
China has a largest population in the world (1.3Billion) and 0.9 Billion is rural population. Most of rural people earn less than US$3/day, and they are called 'Base of the economic pyramid (BoP)'. A new research project has been initiated on 'The Healthcare Design for China Rural BoP' to the PhD of first author. This paper is about one part of this research: user context research. Two main processes will be introduced in this step: Qualitative research and quantitative research. Some healthcare needs in China rural like 'Cancer early detection' has been found as the insights of this research.