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https://www.readbyqxmd.com/read/28748504/whole-brain-analyses-of-age-related-microstructural-changes-quantified-using-different-diffusional-magnetic-resonance-imaging-methods
#1
Miho Ota, Noriko Sato, Norihide Maikusa, Daichi Sone, Hiroshi Matsuda, Hiroshi Kunugi
PURPOSE: The new diffusional magnetic resonance imaging (dMRI) techniques, diffusional kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) have been developed to clarify the microstructural changes. To our knowledge, however, there is little information on the similarities and differences of these metrics evaluated by the image-by-image paired t test. MATERIALS AND METHODS: Twenty-three healthy subjects underwent dMRI. We estimated the relationships of these metrics evaluated by the image-by-image paired t-test and compared aging effects on each metric...
July 26, 2017: Japanese Journal of Radiology
https://www.readbyqxmd.com/read/28732674/3d-mb-muse-a-robust-3d-multi-slab-multi-band-and-multi-shot-reconstruction-approach-for-ultrahigh-resolution-diffusion-mri
#2
Iain P Bruce, Hing-Chiu Chang, Christopher Petty, Nan-Kuei Chen, Allen W Song
Recent advances in achieving ultrahigh spatial resolution (e.g. sub-millimeter) diffusion MRI (dMRI) data have proven highly beneficial in characterizing tissue microstructures in organs such as the brain. However, the routine acquisition of in-vivo dMRI data at such high spatial resolutions has been largely prohibited by factors that include prolonged acquisition times, motion induced artifacts, and low SNR. To overcome these limitations, we present here a framework for acquiring and reconstructing 3D multi-slab, multi-band and interleaved multi-shot EPI data, termed 3D-MB-MUSE...
July 18, 2017: NeuroImage
https://www.readbyqxmd.com/read/28721357/whole-mouse-brain-imaging-using-optical-coherence-tomography-reconstruction-normalization-segmentation-and-comparison-with-diffusion-mri
#3
Joël Lefebvre, Alexandre Castonguay, Philippe Pouliot, Maxime Descoteaux, Frédéric Lesage
An automated massive histology setup combined with an optical coherence tomography (OCT) microscope was used to image a total of [Formula: see text] whole mouse brains. Each acquisition generated a dataset of thousands of OCT volumetric tiles at a sampling resolution of [Formula: see text]. This paper describes techniques for reconstruction and segmentation of the sliced brains. In addition to the measured OCT optical reflectivity, a single scattering photon model was used to compute the attenuation coefficients within each tissue slice...
October 2017: Neurophotonics
https://www.readbyqxmd.com/read/28713174/fusing-multiple-neuroimaging-modalities-to-assess-group-differences-in-perception-action-coupling
#4
Jordan Muraskin, Jason Sherwin, Gregory Lieberman, Javier O Garcia, Timothy Verstynen, Jean M Vettel, Paul Sajda
In the last few decades, non-invasive neuroimaging has revealed macro-scale brain dynamics that underlie perception, cognition and action. Advances in non-invasive neuroimaging target two capabilities; 1) increased spatial and temporal resolution of measured neural activity, and 2) innovative methodologies to extract brain-behavior relationships from evolving neuroimaging technology. We target the second. Our novel methodology integrated three neuroimaging methodologies and elucidated expertise-dependent differences in functional (fused EEG-fMRI) and structural (dMRI) brain networks for a perception-action coupling task...
January 2017: Proceedings of the IEEE
https://www.readbyqxmd.com/read/28708547/multimodal-fusion-with-reference-searching-for-joint-neuromarkers-of-working-memory-deficits-in-schizophrenia
#5
Shile Qi, Vince D Calhoun, Theo G M van Erp, Juan Bustillo, Eswar Damaraju, Jessica A Turner, Yuhui Du, Jian Yang, Jiayu Chen, Qingbao Yu, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon A Mueller, Aysenil Belger, Sarah McEwen, Steven G Potkin, Adrian Preda, Tianzi Jiang, Jing Sui
By exploiting cross-information among multiple imaging data, multimodal fusion has often been used to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. There is increasing interest to uncover the neurocognitive mapping of specific clinical measurements on enriched brain imaging data; hence, a supervised, goal-directed model that employs prior information as a reference to guide multimodal data fusion is much needed and becomes a natural option...
July 11, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28702836/sequential-language-learning-and-language-immersion-in-bilingualism-diffusion-mri-connectometry-reveals-microstructural-evidence
#6
Farzaneh Rahmani, Soheila Sobhani, Mohammad Hadi Aarabi
Study of bilingual brain has provided evidence for probable advantageous outcomes of early second language learning and brain structural correlates to these outcomes. DMRI connectometry is a novel approach that tracts fibers based on correlation of the adjacent voxels with a variable of interest or group differences. Using the data deposited by Pliatsikas et al., we investigated through diffusion MRI connectometry and correlation analysis, the structural differences in white matter tracts of 20 healthy sequential bilingual adults who used English as a second language on a daily basis, compared to 25 age matched in fiber differentiation analyses...
July 12, 2017: Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale
https://www.readbyqxmd.com/read/28692970/a-kernel-based-low-rank-klr-model-for-low-dimensional-manifold-recovery-in-highly-accelerated-dynamic-mri
#7
Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu, Dong Liang, Leslie Ying
While many low rank and sparsity based approaches have been developed for accelerated dynamic magnetic resonance imaging (dMRI), they all use low rankness or sparsity in input space, overlooking the intrinsic nonlinear correlation in most dMRI data. In this paper, we propose a kernel-based framework to allow nonlinear manifold models in reconstruction from sub- Nyquist data. Within this framework, many existing algorithms can be extended to kernel framework with nonlinear models. In particular, we have developed a novel algorithm with a kernel-based low-rank (KLR) model generalizing the conventional low rank formulation...
July 5, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28692678/bilateral-effects-of-unilateral-cerebellar-lesions-as-detected-by-voxel-based-morphometry-and-diffusion-imaging
#8
Giusy Olivito, Michael Dayan, Valentina Battistoni, Silvia Clausi, Mara Cercignani, Marco Molinari, Maria Leggio, Marco Bozzali
Over the last decades, the importance of cerebellar processing for cortical functions has been acknowledged and consensus was reached on the strict functional and structural cortico-cerebellar interrelations. From an anatomical point of view strictly contralateral interconnections link the cerebellum to the cerebral cortex mainly through the middle and superior cerebellar peduncle. Diffusion MRI (dMRI) based tractography has already been applied to address cortico-cerebellar-cortical loops in healthy subjects and to detect diffusivity alteration patterns in patients with neurodegenerative pathologies of the cerebellum...
2017: PloS One
https://www.readbyqxmd.com/read/28684331/fiberprint-a-subject-fingerprint-based-on-sparse-code-pooling-for-white-matter-fiber-analysis
#9
Kuldeep Kumar, Christian Desrosiers, Kaleem Siddiqi, Olivier Colliot, Matthew Toews
White matter characterization studies use the information provided by diffusion magnetic resonance imaging (dMRI) to draw cross-population inferences. However, the structure, function, and white matter geometry vary across individuals. Here, we propose a subject fingerprint, called Fiberprint, to quantify the individual uniqueness in white matter geometry using fiber trajectories. We learn a sparse coding representation for fiber trajectories by mapping them to a common space defined by a dictionary. A subject fingerprint is then generated by applying a pooling function for each bundle, thus providing a vector of bundle-wise features describing a particular subject's white matter geometry...
July 3, 2017: NeuroImage
https://www.readbyqxmd.com/read/28672181/corpus-callosum-macro-and-microstructure-in-late-life-depression
#10
Louise Emsell, Christopher Adamson, François-Laurent De Winter, Thibo Billiet, Daan Christiaens, Filip Bouckaert, Katarzyna Adamczuk, Rik Vandenberghe, Marc L Seal, Pascal Sienaert, Stefan Sunaert, Mathieu Vandenbulcke
BACKGROUND: Differences in corpus callosum (CC) morphology and microstructure have been implicated in late-life depression and may distinguish between late and early-onset forms of the illness. However, a multimodal approach using complementary imaging techniques is required to disentangle microstructural alterations from macrostructural partial volume effects. METHODS: 107 older adults were assessed: 55 currently-depressed patients without dementia and 52 controls without cognitive impairment...
November 2017: Journal of Affective Disorders
https://www.readbyqxmd.com/read/28669918/estimation-of-white-matter-fiber-parameters-from-compressed-multiresolution-diffusion-mri-using-sparse-bayesian-learning
#11
Pramod Kumar Pisharady, Stamatios N Sotiropoulos, Julio M Duarte-Carvajalino, Guillermo Sapiro, Christophe Lenglet
We present a sparse Bayesian unmixing algorithm BusineX: Bayesian Unmixing for Sparse Inference-based Estimation of Fiber Crossings (X), for estimation of white matter fiber parameters from compressed (under-sampled) diffusion MRI (dMRI) data. BusineX combines compressive sensing with linear unmixing and introduces sparsity to the previously proposed multiresolution data fusion algorithm RubiX, resulting in a method for improved reconstruction, especially from data with lower number of diffusion gradients. We formulate the estimation of fiber parameters as a sparse signal recovery problem and propose a linear unmixing framework with sparse Bayesian learning for the recovery of sparse signals, the fiber orientations and volume fractions...
June 29, 2017: NeuroImage
https://www.readbyqxmd.com/read/28664183/the-virtual-mouse-brain-a-computational-neuroinformatics-platform-to-study-whole-mouse-brain-dynamics
#12
Francesca Melozzi, Marmaduke M Woodman, Viktor K Jirsa, Christophe Bernard
Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease...
May 2017: ENeuro
https://www.readbyqxmd.com/read/28644799/hybrid-cs-dmri-periodic-time-variant-subsampling-and-omnidirectional-total-variation-based-reconstruction
#13
Yipeng Liu, Shan Wu, Xiaolin Huang, Bing Chen, Ce Zhu
Compressive sensing (CS) has been used to accelerate dynamic magnetic resonance imaging (DMRI). Currently, the online CS-DMRI is faster, whereas the offline CS-DMRI provides higher accuracy for image reconstruction. To achieve good image reconstruction performance in terms of both speed and accuracy, we propose a hybrid CS-DMRI method using periodic timevariant subsampling for different frames. In each period, there is one reference frame that is sampled at a higher subsampling ratio. The two nearby reference frames with good reconstruction quality can be used to provide rough predictions of the other frames between them...
June 20, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28609579/diffusion-mri-and-the-detection-of-alterations-following-traumatic-brain-injury
#14
REVIEW
Elizabeth B Hutchinson, Susan C Schwerin, Alexandru V Avram, Sharon L Juliano, Carlo Pierpaoli
This article provides a review of brain tissue alterations that may be detectable using diffusion magnetic resonance imaging MRI (dMRI) approaches and an overview and perspective on the modern dMRI toolkits for characterizing alterations that follow traumatic brain injury (TBI). Noninvasive imaging is a cornerstone of clinical treatment of TBI and has become increasingly used for preclinical and basic research studies. In particular, quantitative MRI methods have the potential to distinguish and evaluate the complex collection of neurobiological responses to TBI arising from pathology, neuroprotection, and recovery...
June 13, 2017: Journal of Neuroscience Research
https://www.readbyqxmd.com/read/28580294/gender-differences-in-the-structural-connectome-of-the-teenage-brain-revealed-by-generalized-q-sampling-mri
#15
Yeu-Sheng Tyan, Jan-Ray Liao, Chao-Yu Shen, Yu-Chieh Lin, Jun-Cheng Weng
The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28558269/white-matter-pathways-mediate-parental-effects-on-children-s-reading-precursors
#16
Maaike Vandermosten, Lieselore Cuynen, Jolijn Vanderauwera, Jan Wouters, Pol Ghesquière
Previous studies have shown that the link between parental and offspring's reading is mediated by the cognitive system of the offspring, yet information about the mediating role of the neurobiological system is missing. This family study includes cognitive and diffusion MRI (dMRI) data collected in 71 pre-readers as well as parental reading and environmental data. Using sequential path analyses, which take into account the interrelationships between the different components, we observed mediating effects of the neurobiological system...
May 27, 2017: Brain and Language
https://www.readbyqxmd.com/read/28532604/validation-of-dwi-pre-processing-procedures-for-reliable-differentiation-between-human-brain-gliomas
#17
Sebastian Vellmer, Aram S Tonoyan, Dieter Suter, Igor N Pronin, Ivan I Maximov
Diffusion magnetic resonance imaging (dMRI) is a powerful tool in clinical applications, in particular, in oncology screening. dMRI demonstrated its benefit and efficiency in the localisation and detection of different types of human brain tumours. Clinical dMRI data suffer from multiple artefacts such as motion and eddy-current distortions, contamination by noise, outliers etc. In order to increase the image quality of the derived diffusion scalar metrics and the accuracy of the subsequent data analysis, various pre-processing approaches are actively developed and used...
May 19, 2017: Zeitschrift Für Medizinische Physik
https://www.readbyqxmd.com/read/28511065/quantifying-the-brain-s-sheet-structure-with-normalized-convolution
#18
Chantal M W Tax, Carl-Fredrik Westin, Tom Dela Haije, Andrea Fuster, Max A Viergever, Evan Calabrese, Luc Florack, Alexander Leemans
The hypothesis that brain pathways form 2D sheet-like structures layered in 3D as "pages of a book" has been a topic of debate in the recent literature. This hypothesis was mainly supported by a qualitative evaluation of "path neighborhoods" reconstructed with diffusion MRI (dMRI) tractography. Notwithstanding the potentially important implications of the sheet structure hypothesis for our understanding of brain structure and development, it is still considered controversial by many for lack of quantitative analysis...
July 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28506703/abnormal-asymmetry-of-white-matter-tracts-between-ventral-posterior-cingulate-cortex-and-middle-temporal-gyrus-in-recent-onset-schizophrenia
#19
Sung Woo Joo, Myong-Wuk Chon, Yogesh Rathi, Martha E Shenton, Marek Kubicki, Jungsun Lee
INTRODUCTION: Previous studies have reported abnormalities in the ventral posterior cingulate cortex (vPCC) and middle temporal gyrus (MTG) in schizophrenia patients. However, it remains unclear whether the white matter tracts connecting these structures are impaired in schizophrenia. Our study investigated the integrity of these white matter tracts (vPCC-MTG tract) and their asymmetry (left versus right side) in patients with recent onset schizophrenia. METHOD: Forty-seven patients and 24 age-and sex-matched healthy controls were enrolled in this study...
May 12, 2017: Schizophrenia Research
https://www.readbyqxmd.com/read/28457975/robust-and-fast-nonlinear-optimization-of-diffusion-mri-microstructure-models
#20
R L Harms, F J Fritz, A Tobisch, R Goebel, A Roebroeck
Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initialization strategy to estimate its parameter maps. Since data fit, accuracy and precision is hard to verify, this creates additional challenges to comparability and generalization of results from diffusion microstructure models...
July 15, 2017: NeuroImage
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