Identifying Demyelinating and Ischemia brain diseases through magnetic resonance images processing

Cardiovascular health interacts with cognitive and psychological health in complex ways. Yet, little is known about the phenotypic and genetic links of heart-brain systems. Using cardiac and brain magnetic resonance imaging (CMR and brain MRI) data from over 40,000 UK Biobank subjects, we developed detailed analyses of the structural and functional connections between the heart and the brain. CMR measures of the cardiovascular system were strongly correlated with brain basic morphometry, structural connectivity, and functional connectivity after controlling for body size and body mass index. The effects of cardiovascular risk factors on the brain were partially mediated by cardiac structures and functions. Using 82 CMR traits, genome-wide association study identified 80 CMR-associated genomic loci (P < 6.09 * 10^{-10}), which were colocalized with a wide spectrum of heart and brain diseases. Genetic correlations were observed between CMR traits and brain-related complex traits and disorders, including schizophrenia, bipolar disorder, anorexia nervosa, stroke, cognitive function, and neuroticism. Our results reveal a strong heart-brain connection and the shared genetic influences at play, advancing a multi-organ perspective on human health and clinical outcomes.

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Using deep learning to predict brain age from brain magnetic resonance images and cognitive tests reveals that anatomical and functional brain aging are phenotypically and genetically distinct

10.1101/2021.06.22.21259280 ◽

2021 ◽

Author(s):

Alan Le Goallec ◽

Samuel Diai ◽

Sasha Collin ◽

Theo Vincent ◽

Chirag J Patel

Keyword(s):

Magnetic Resonance ◽

Genetic Factors ◽

Brain Aging ◽

Magnetic Resonance Images ◽

Brain Diseases ◽

World Population ◽

Cognitive Tests ◽

Functional Brain ◽

Age Related ◽

Brain Age

With the world population aging, the prevalence of age-related brain diseases such as Alzheimer's, Parkinson's, Lou Gehrig's, and cerebrovascular diseases. In the following, we built brain age predictors by leveraging 46,000 brain magnetic resonance images [MRIs] and cognitive tests from UK Biobank participants. We predicted age with a R-Squared [R2] of 76.4+/-1.0% and a root mean squared error of 3.58+/-0.05 years. We defined accelerated brain aging as the difference between brain age (predicted age) and age. Accelerated brain aging is partially heritable (h_g2=35.9+/-2.6%), and is associated with 219 single nucleotide polymorphisms [SNPs] in 25 genes (e.g CRHR1, involved in the hypothalamic-pituitary-adrenal pathway). Similarly, it is associated with biomarkers (e.g blood pressure), clinical phenotypes (e.g general health), diseases (e.g diabetes), environmental (e.g smoking) and socioeconomic variables (e.g income and education). We performed the same analysis, this time distinguishing between anatomical (MRI-based) and functional (cognitive tests-based) brain aging. We found the two accelerated aging phenotypes to be phenotypically .112+/-.006 correlated and genetically uncorrelated, with distinct SNPs and non-genetic factors associated with each. In conclusion, anatomical and functional brain aging are two distinct, complex phenotypes, which also differ in their genetic and non-genetic factors. Our brain predictors could be used to monitor the effects of emerging rejuvenating therapies on the brain.

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PBTNet: A New Computer-Aided Diagnosis System for Detecting Primary Brain Tumors

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.765654 ◽

2021 ◽

Vol 9 ◽

Author(s):

Si-Yuan Lu ◽

Suresh Chandra Satapathy ◽

Shui-Hua Wang ◽

Yu-Dong Zhang

Keyword(s):

Magnetic Resonance ◽

Brain Tumors ◽

Computer Aided Diagnosis ◽

Magnetic Resonance Images ◽

Brain Diseases ◽

Functional Link ◽

Diagnosis System ◽

Primary Brain Tumors ◽

Computer Aided ◽

Aided Diagnosis

Brain tumors are among the leading human killers. There are over 120 different types of brain tumors, but they mainly fall into two groups: primary brain tumors and metastatic brain tumors. Primary brain tumors develop from normal brain cells. Early and accurate detection of primary brain tumors is vital for the treatment of this disease. Magnetic resonance imaging is the most common method to diagnose brain diseases, but the manual interpretation of the images suffers from high inter-observer variance. In this paper, we presented a new computer-aided diagnosis system named PBTNet for detecting primary brain tumors in magnetic resonance images. A pre-trained ResNet-18 was selected as the backbone model in our PBTNet, but it was fine-tuned only for feature extraction. Then, three randomized neural networks, Schmidt neural network, random vector functional-link, and extreme learning machine served as the classifiers in the PBTNet, which were trained with the features and their labels. The final predictions of the PBTNet were generated by the ensemble of the outputs from the three classifiers. 5-fold cross-validation was employed to evaluate the classification performance of the PBTNet, and experimental results demonstrated that the proposed PBTNet was an effective tool for the diagnosis of primary brain tumors.

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Demyelinating and ischemic brain diseases: detection algorithm through regular magnetic resonance images

Applications of Digital Image Processing XL ◽

10.1117/12.2274579 ◽

2017 ◽

Cited By ~ 1

Author(s):

Darwin P. Castillo Malla ◽

René Samaniego ◽

María José Rodríguez-Álvarez ◽

Yuliana Jiménez ◽

Oscar Vivanco ◽

...

Keyword(s):

Magnetic Resonance ◽

Detection Algorithm ◽

Magnetic Resonance Images ◽

Brain Diseases ◽

Ischemic Brain

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Morphometric Evaluation of Fourth Ventricle by Using Magnetic Resonance Imaging

RAS Medical Science ◽

10.51520/2766-5240-7 ◽

2021 ◽

Vol 1 (2) ◽

Author(s):

Osama Othman Mohammed Ambarak ◽

Abtehag A. Taib ◽

Mohammad A. Abdalla ◽

Alsanussi Elsherif ◽

Azza S H Greiw

Keyword(s):

Magnetic Resonance ◽

Fourth Ventricle ◽

Neurological Diseases ◽

Data Entry ◽

Magnetic Resonance Images ◽

Brain Diseases ◽

Gender And Age ◽

The Brain ◽

4Th Ventricle

Background: The fourth ventricle is one of the components of the ventricular system in the brain, along with the lateral and third ventricles. The ventricular size is considered as a potential indicator in determination of many brain diseases. There are dimensional differences between males and females which appeared larger in males. Aim: The aim of this study was to determine the radiological dimensions of fourth ventricle and to assess their relationship with gender and age. Subjects and methods: Brain Magnetic Resonance Images (MRI) of 100 patients (44 males and 56 females) were examined. The dimensions of the fourth ventricle were estimated. Additionally, the variation with sex and age were also described. After collection and checking of data, Statistical Package for Social Sciences (SPSS) was used for data entry and analysis. Results: The AP length of 4th ventricle of all patients ranged from 6.5-13.9 mm with mean (± SD) 10.67 ± 1.66 mm. In females, it ranged from 6.5-13.9 mm with mean (± SD) 10.48 ± 1.76 mm while in males; it ranged from 7-13.9 mm with mean (± SD) 10.92 ± 1.51 mm. The mean of 4th ventricle AP length of males were comparatively higher than females. Similarly, the 4th ventricle width of all patients ranged from 8.7-16.1 mm with mean (± SD) 12.06 ± 1.41 mm. In females, it ranged from 8.7-14.6 mm with mean (± SD) 11.85 ± 1.32 mm while in males; it ranged from 9.1-16.1 mm with mean (± SD) 12.32 ± 1.48 mm. The study showed that width of fourth ventricle was more than the AP length and both were greater in males than in females. AP length and width showed negative correlation with age. Conclusion: The normal reference values of ventricles obtained from MRI are necessary to form the baseline data for interpreting pathological changes, planning surgery, and determining presence and progress of some neurological diseases. Furthermore, the dimension of fourth ventricle should be taken into consideration during radiological reports and during clinical examination.

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An emerging technology: Nuclear magnetic resonance microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010010706x ◽

1988 ◽

Vol 46 ◽

pp. 1000-1001

Author(s):

M.J. Hennessy ◽

E. Kwok

Keyword(s):

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Relaxation Times ◽

Basic Research ◽

Local Environment ◽

Magnetic Resonance Images ◽

Nmr Microscopy ◽

Mri Scans ◽

Temperature Relaxation ◽

Nuclear Magnetic

Much progress in nuclear magnetic resonance microscope has been made in the last few years as a result of improved instrumentation and techniques being made available through basic research in magnetic resonance imaging (MRI) technologies for medicine. Nuclear magnetic resonance (NMR) was first observed in the hydrogen nucleus in water by Bloch, Purcell and Pound over 40 years ago. Today, in medicine, virtually all commercial MRI scans are made of water bound in tissue. This is also true for NMR microscopy, which has focussed mainly on biological applications. The reason water is the favored molecule for NMR is because water is,the most abundant molecule in biology. It is also the most NMR sensitive having the largest nuclear magnetic moment and having reasonable room temperature relaxation times (from 10 ms to 3 sec). The contrast seen in magnetic resonance images is due mostly to distribution of water relaxation times in sample which are extremely sensitive to the local environment.

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Functional information from magnetic resonance imaging

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100136799 ◽

1995 ◽

Vol 53 ◽

pp. 84-85

Author(s):

Alan P. Koretsky ◽

Afonso Costa e Silva ◽

Yi-Jen Lin

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

High Resolution ◽

Cancer Biology ◽

Imaging Modality ◽

Magnetic Resonance Images ◽

Great Success ◽

Functional Information ◽

Resonance Imaging ◽

High Resolution Mri

Magnetic resonance imaging (MRI) has become established as an important imaging modality for the clinical management of disease. This is primarily due to the great tissue contrast inherent in magnetic resonance images of normal and diseased organs. Due to the wide availability of high field magnets and the ability to generate large and rapidly switched magnetic field gradients there is growing interest in applying high resolution MRI to obtain microscopic information. This symposium on MRI microscopy highlights new developments that are leading to increased resolution. The application of high resolution MRI to significant problems in developmental biology and cancer biology will illustrate the potential of these techniques.In combination with a growing interest in obtaining high resolution MRI there is also a growing interest in obtaining functional information from MRI. The great success of MRI in clinical applications is due to the inherent contrast obtained from different tissues leading to anatomical information.

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