Functional Connectivity: Integrating Behavioral, Diffusion Tensor Imaging, and Functional Magnetic Resonance Imaging Data Sets

2005 ◽  
Vol 17 (4) ◽  
pp. 687-693 ◽  
Author(s):  
Abigail A. Baird ◽  
Mary K. Colvin ◽  
John D. VanHorn ◽  
Souheil Inati ◽  
Michael S. Gazzaniga
Keyword(s):  
Diffusion Tensor Imaging ◽  
Individual Differences ◽  
Magnetic Resonance ◽  
Corpus Callosum ◽  
Information Transfer ◽  
Structural Integrity ◽  
Diffusion Tensor ◽  
Bold Response ◽  
Imaging Data ◽  
Imaging Results

In the present study, we combined 2 types of magnetic resonance technology to explore individual differences on a task that required the recognition of objects presented from unusual viewpoints. This task was chosen based on previous work that has established the necessity of information transfer from the right parietal cortex to the left inferior cortex for its successful completion. We used reaction times (RTs) to localize regions of cortical activity in the superior parietal and inferior frontal regions (blood oxygen level-dependent [BOLD] response) that were more active with longer response times. These regions were then sampled, and their signal change used to predict individual differences in structural integrity of white matter in the corpus callosum (using diffusion tensor imaging). Results show that shorter RTs (and associated increases in BOLD response) are associated with increased organization in the splenium of the corpus callosum, whereas longer RTs are associated with increased organization in the genu.

scholarly journals Machine Learning for the Classification of Alzheimer’s Disease and Its Prodromal Stage Using Brain Diffusion Tensor Imaging Data: A Systematic Review

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1071
Author(s):  
Lucia Billeci ◽  
Asia Badolato ◽  
Lorenzo Bachi ◽  
Alessandro Tonacci
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Classification Problem ◽  
Computer Algorithms ◽  
Imaging Data

Alzheimer’s disease is notoriously the most common cause of dementia in the elderly, affecting an increasing number of people. Although widespread, its causes and progression modalities are complex and still not fully understood. Through neuroimaging techniques, such as diffusion Magnetic Resonance (MR), more sophisticated and specific studies of the disease can be performed, offering a valuable tool for both its diagnosis and early detection. However, processing large quantities of medical images is not an easy task, and researchers have turned their attention towards machine learning, a set of computer algorithms that automatically adapt their output towards the intended goal. In this paper, a systematic review of recent machine learning applications on diffusion tensor imaging studies of Alzheimer’s disease is presented, highlighting the fundamental aspects of each work and reporting their performance score. A few examined studies also include mild cognitive impairment in the classification problem, while others combine diffusion data with other sources, like structural magnetic resonance imaging (MRI) (multimodal analysis). The findings of the retrieved works suggest a promising role for machine learning in evaluating effective classification features, like fractional anisotropy, and in possibly performing on different image modalities with higher accuracy.

scholarly journals Microstructural changes in thickened corpus callosum in children: contribution of magnetic resonance diffusion tensor imaging

2014 ◽  
Vol 45 (6) ◽  
pp. 896-901 ◽  
Author(s):  
Laura Merlini ◽  
Mehrak Anooshiravani ◽  
Aikaterini Kanavaki ◽  
Sylviane Hanquinet
Keyword(s):  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Corpus Callosum ◽  
Diffusion Tensor ◽  
Microstructural Changes

Evaluation of the Corpus Callosum of Patient with Alzheimer's Disease by Using Magnetic Resonance Diffusion Tensor Imaging

2010 ◽  
Vol 57 (5) ◽  
pp. 1257-1262 ◽  
Author(s):  
Bo-Young Choe ◽  
Youl-Hun Seoung ◽  
Hak-Moon Kim ◽  
Sung-Bong Cho ◽  
Seong-Woo Hong ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Corpus Callosum ◽  
Diffusion Tensor

MAGNETIC RESONANCE AND DIFFUSION TENSOR IMAGING STUDY OF THE CORPUS CALLOSUM IN ADOLESCENT AND ADULT SCHIZOPHRENIA

2008 ◽  
Vol 102 (1-3) ◽  
pp. 78
Author(s):  
Emily Canfield ◽  
Monte Buchsbaum ◽  
Mehmet Haznedar ◽  
Eugene Wang ◽  
Randall Newmark ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Corpus Callosum ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
And Diffusion ◽  
Diffusion Tensor Imaging Study

Increase in glutamate as a sensitive indicator of extracellular matrix integrity in peritumoral edema: a 3.0-tesla proton magnetic resonance spectroscopy study

2007 ◽  
Vol 106 (4) ◽  
pp. 609-613 ◽  
Author(s):  
Teruo Kimura ◽  
Masaki Ohkubo ◽  
Hironaka Igarashi ◽  
Ingrid L. Kwee ◽  
Tsutomu Nakada
Keyword(s):  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Mr Spectroscopy ◽  
Proton Magnetic Resonance ◽  
Structural Integrity ◽  
Diffusion Tensor ◽  
Resonance Spectroscopy ◽  
Peritumoral Edema ◽  
3.0 Tesla ◽  
Glial Tumors

Object The authors of previous studies based on diffusion tensor imaging have indicated that there are two types of peritumoral edema—namely, edema with preserved structural integrity of the glial matrix and edema with compromised glial matrix. The authors of this study hypothesized that functionality of the glutamate (Glu)–glutamine shuttle, a vital neuron–glia interaction, may be differentially affected by peritumoral edema. They tested this hypothesis using proton magnetic resonance (MR) spectroscopy on a 3.0-tesla system that is capable of quantifying Glu without need of editing. Methods Twenty-three patients, each with a single brain tumor mass and peritumoral edema (nine high-grade gliomas, eight metastatic brain tumors, and six meningiomas), and nine healthy individuals participated in this study. Single-voxel proton MR imaging targeting the region of peritumoral edema was performed using a 3.0-tesla system. Glutamate levels in the peritumoral edema of nonglial tumors was significantly elevated (p < 0.01) compared with edema associated with glial tumors or normal white matter. The finding confirmed that peritumoral edema in nonglial tumors is distinct from that of glial tumors, as previously indicated in diffusion tensor imaging studies. The authors hypothesized that the former condition represents a compensatory increase in activities of the Glu–glutamine shuttle brought about by simple expansion of the extracellular space due to edema. Conclusions The assessment of Glu concentrations in peritumoral edema using 3.0-tesla proton MR spectroscopy may be developed into an objective index of the structural integrity of the glial matrix.

scholarly journals Corpus callosum morphology in first-episode and chronic schizophrenia: combined magnetic resonance and diffusion tensor imaging study of Chinese Singaporean patients

2014 ◽  
Vol 204 (1) ◽  
pp. 55-60 ◽  
Author(s):  
Simon L. Collinson ◽  
Swu Chyi Gan ◽  
Puay San Woon ◽  
Carissa Kuswanto ◽  
Min Yi Sum ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Corpus Callosum ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
Chronic Schizophrenia ◽  
First Episode ◽  
First Episode Schizophrenia ◽  
And Diffusion ◽  
Area And Volume

BackgroundAbnormalities in the corpus callosum have been reported in patients with schizophrenia for over 30 years but the influence of inter-individual differences and illness characteristics remains to be fully elucidated.AimsTo examine the influence of individual and illness characteristics on the corpus callosum in Chinese Singaporean patients with schizophrenia.MethodUsing magnetic resonance and diffusion tensor imaging, mean corpus callosum area, volume and fractional anisotropy were investigated in 120 Chinese Singaporean patients (52 with chronic and 68 with first-episode schizophrenia) and compared with data from 75 matched healthy controls.ResultsBoth area and volume were significantly reduced in patients relative to controls but no significant differences in corpus callosum existed between genders in either patients or controls. Differences in area and volume of the corpus callosum were greatest in patients whose condition was chronic relative to patients with a first episode and controls. Anterior callosum in patients, regardless of chronicity, was no different to that of controls.ConclusionsMorphological abnormalities in the corpus callosum may increase with illness progression.

Sign in / Sign up

Export Citation Format

Share Document