scholarly journals Longitudinal change in magnetic susceptibility of new enhanced multiple sclerosis (MS) lesions measured on serial quantitative susceptibility mapping (QSM)

2016 ◽  
Vol 44 (2) ◽  
pp. 426-432 ◽  
Author(s):  
Yan Zhang ◽  
Susan A. Gauthier ◽  
Ajay Gupta ◽  
Joseph Comunale ◽  
Gloria Chia-Yi Chiang ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Magnetic Susceptibility ◽  
Susceptibility Mapping ◽  
Longitudinal Change ◽  
Quantitative Susceptibility Mapping

IC-P-145: EX-VIVO QUANTITATIVE SUSCEPTIBILITY MAPPING (QSM) IN A COMMUNITY COHORT REVEALS LINK BETWEEN MAGNETIC SUSCEPTIBILITY AND ALZHEIMER'S PATHOLOGY

2014 ◽  
Vol 10 ◽  
pp. P83-P84
Author(s):  
Arnold Moya Evia ◽  
Konstantinos Arfanakis ◽  
David Bennett ◽  
Julie Schneider ◽  
Aikaterini Kotrotsou ◽  
...  
Keyword(s):  
Magnetic Susceptibility ◽  
Ex Vivo ◽  
Susceptibility Mapping ◽  
Quantitative Susceptibility Mapping ◽  
Alzheimer’S Pathology

scholarly journals Quantitative susceptibility mapping (QSM) of white matter multiple sclerosis lesions: Interpreting positive susceptibility and the presence of iron

2014 ◽  
Vol 74 (2) ◽  
pp. 564-570 ◽  
Author(s):  
Cynthia Wisnieff ◽  
Sriram Ramanan ◽  
John Olesik ◽  
Susan Gauthier ◽  
Yi Wang ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Susceptibility Mapping ◽  
Quantitative Susceptibility Mapping

Effect of respiratory hyperoxic challenge on magnetic susceptibility in human brain assessed by quantitative susceptibility mapping (QSM)

2015 ◽  
Vol 28 (12) ◽  
pp. 1688-1696 ◽  
Author(s):  
Pinar Senay Özbay ◽  
Cristina Rossi ◽  
Roman Kocian ◽  
Manuel Redle ◽  
Andreas Boss ◽  
...  
Keyword(s):  
Magnetic Susceptibility ◽  
Human Brain ◽  
Susceptibility Mapping ◽  
Quantitative Susceptibility Mapping

scholarly journals DeepQSM - Using Deep Learning to Solve the Dipole Inversion for MRI Susceptibility Mapping

2018 ◽  
Author(s):  
Kasper Gade Bøtker Rasmussen ◽  
Mads Kristensen ◽  
Rasmus Guldhammer Blendal ◽  
Lasse Riis Østergaard ◽  
Maciej Plocharski ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Magnetic Susceptibility ◽  
Iron Homeostasis ◽  
Nerve Fibers ◽  
Susceptibility Mapping ◽  
Source Inversion ◽  
Tissue Properties ◽  
Ill Posed ◽  
Phase Data

Quantitative susceptibility mapping (QSM) aims to extract the magnetic susceptibility of tissue from magnetic resonance imaging (MRI) phase measurements. The mapping of magnetic susceptibility in vivo has gained broad interest in several fields of science and medicine because it yields relevant information on biological tissue properties, predominantly myelin, iron and calcium. Thereby, QSM can also reveal pathological changes of these key components in devastating diseases such as Parkinson’s disease, Multiple Sclerosis, or hepatic iron overload. As QSM requires the solution of an ill-posed field-to-source-inversion, current techniques utilize manual optimization of regularization parameters to balance between smoothing, artifacts and quantification accuracy. We trained a fully convolutional deep neural network - DeepQSM - to invert the magnetic dipole kernel convolution. This network is capable of solving the ill-posed field-to-source inversion on real-world in vivo MRI phase data without the need for manual parameter tuning, which proves that this network has generalized the underlying mathematical principle of the dipole inversion. We demonstrate that DeepQSM’s susceptibility maps enable identification of deep brain substructures that are not visible in MRI phase data and provide information on their respective magnetic tissue properties. We illustrate DeepQSM’s clinical relevance in a patient with multiple sclerosis showing its sensitivity to white matter lesions. In summary, DeepQSM can be used to determine the composition of myelin sheets of nerve fibers in the brain, and to assess quantitative information on iron homeostasis and its dysregulation, and will subsequently contribute to a better understanding of these biological processes in health and disease.

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