Patents on Quantitative Susceptibility Mapping (QSM) of Tissue Magnetism

2019 ◽  
Vol 13 (2) ◽  
pp. 90-113
Author(s):  
Feng Lin ◽  
Martin R. Prince ◽  
Pascal Spincemaille ◽  
Yi Wang
Keyword(s):  
Neurological Diseases ◽  
Background Field ◽  
Bayesian Framework ◽  
Susceptibility Mapping ◽  
Quantitative Susceptibility Mapping ◽  
Liver Iron ◽  
Seamless Integration ◽  
Tissue Ischemia ◽  
Susceptibility Maps ◽  
Wide Range

<P>Background: Quantitative susceptibility mapping (QSM) depicts biodistributions of tissue magnetic susceptibility sources, including endogenous iron and calcifications, as well as exogenous paramagnetic contrast agents and probes. When comparing QSM with simple susceptibility weighted MRI, QSM eliminates blooming artifacts and shows reproducible tissue susceptibility maps independent of field strength and scanner manufacturer over a broad range of image acquisition parameters. For patient care, QSM promises to inform diagnosis, guide surgery, gauge medication, and monitor drug delivery. The Bayesian framework using MRI phase data and structural prior knowledge has made QSM sufficiently robust and accurate for routine clinical practice.Objective:To address the lack of a summary of US patents that is valuable for QSM product development and dissemination into the MRI community.Method:We searched the USPTO Full-Text and Image Database for patents relevant to QSM technology innovation. We analyzed the claims of each patent to characterize the main invented method and we investigated data on clinical utility. </P><P> Results: We identified 17 QSM patents; 13 were implemented clinically, covering various aspects of QSM technology, including the Bayesian framework, background field removal, numerical optimization solver, zero filling, and zero-TE phase.Conclusion:Our patent search identified patents that enable QSM technology for imaging the brain and other tissues. QSM can be applied to study a wide range of diseases including neurological diseases, liver iron disorders, tissue ischemia, and osteoporosis. MRI manufacturers can develop QSM products for more seamless integration into existing MRI scanners to improve medical care.</P>

scholarly journals Abdominal single-step quantitative susceptibility mapping with spherical mean value filter and structure prior-based regularization

2020 ◽  
Author(s):  
Anton Abyzov ◽  
Bernard E. Van Beers ◽  
Philippe Garteiser
Keyword(s):  
Subcutaneous Fat ◽  
Background Field ◽  
Mean Value ◽  
Single Step ◽  
Susceptibility Mapping ◽  
Small Animals ◽  
Quantitative Susceptibility Mapping ◽  
Split Bregman ◽  
Spherical Mean ◽  
Susceptibility Maps

Abdominal quantitative susceptibility mapping (QSM), especially in small animals, is challenging because of respiratory motion and blood flow that, in addition to noise, deteriorate the quality of the input data. Efficient artefact suppression in QSM reconstruction is crucial in these conditions. Single-step QSM algorithms combine background field removal and magnetic field-to-susceptibility inverse problem regularization in a single optimization equation. Here, we propose a single-step QSM algorithm that uses spherical mean value kernels of different radii for background field removal and structure prior (consistency with magnitude image) with L1 norm for regularization. The optimization problem is solved using the split-Bregman method on the graphic processor unit. The method was compared with previously reported singlestep methods: a method using discrete Laplacian instead of spherical mean value kernels, a method using total variational penalty instead of structure prior, and a method using L2 norm for structure prior. With the proposed method relative to the previous ones, a numerical susceptibility phantom was reconstructed more precisely. In living mice, susceptibility maps with more homogeneous liver, higher contrast between liver and blood vessels, and well-preserved structural details were obtained. In patients, susceptibility maps with more homogeneous subcutaneous fat and higher contrast between subcutaneous fat and liver were obtained. These results show the potential of the proposed single-step method for abdominal QSM in small animals and humans.

scholarly journals SHARQnet - Sophisticated Harmonic Artifact Reduction in Quantitative Susceptibility Mapping using a Deep Convolutional Neural Network

2019 ◽  
Author(s):  
Steffen Bollmann ◽  
Matilde Holm Kristensen ◽  
Morten Skaarup Larsen ◽  
Mathias Vassard Olsen ◽  
Mads Jozwiak Pedersen ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Background Field ◽  
Susceptibility Mapping ◽  
Deep Convolutional Neural Network ◽  
Quantitative Susceptibility Mapping ◽  
Iterative Optimization ◽  
Wide Range ◽  
Ill Posed ◽  
Background Fields

AbstractQuantitative susceptibility mapping (QSM) reveals pathological changes in widespread diseases such as Parkinson’s disease, Multiple Sclerosis, or hepatic iron overload. QSM requires multiple processing steps after the acquisition of magnetic resonance imaging (MRI) phase measurements such as unwrapping, background field removal and the solution of an ill-posed field-to-source-inversion. Current techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and lead to suboptimal or over-regularized solutions requiring a careful choice of parameters that make a clinical application of QSM challenging. We have previously demonstrated that a deep convolutional neural network can invert the magnetic dipole kernel with a very efficient feed forward multiplication not requiring iterative optimization or the choice of regularization parameters. In this work, we extended this approach to remove background fields in QSM. The prototype method, called SHARQnet, was trained on simulated background fields and tested on 3T and 7T brain datasets. We show that SHARQnet outperforms current background field removal procedures and generalizes to a wide range of input data without requiring any parameter adjustments. In summary, we demonstrate that the solution of ill-posed problems in QSM can be achieved by learning the underlying physics causing the artifacts and removing them in an efficient and reliable manner and thereby will help to bring QSM towards clinical applications.

scholarly journals MRI-based quantitative susceptibility mapping (QSM) and R2* mapping of liver iron overload: Comparison with SQUID-based biomagnetic liver susceptometry

2016 ◽  
Vol 78 (1) ◽  
pp. 264-270 ◽  
Author(s):  
Samir D. Sharma ◽  
Roland Fischer ◽  
Bjoern P. Schoennagel ◽  
Peter Nielsen ◽  
Hendrik Kooijman ◽  
...  
Keyword(s):  
Iron Overload ◽  
Susceptibility Mapping ◽  
Quantitative Susceptibility Mapping ◽  
Liver Iron ◽  
Liver Iron Overload

Abstract TP348: Quantitative Serial Neuroimaging of Iron in the Intracerebral Hemorrhage Pig Model

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Muhammad E Haque ◽  
Refaat E Gabr ◽  
Xiurong Zhao ◽  
Khader M Hasan ◽  
Ponnada A Narayana ◽  
...  
Keyword(s):  
Intracerebral Hemorrhage ◽  
Autologous Blood ◽  
Iron Concentration ◽  
Susceptibility Mapping ◽  
Pig Model ◽  
Large Animal ◽  
Quantitative Susceptibility Mapping ◽  
Secondary Damage ◽  
Susceptibility Maps ◽  
The Brain

Objective: To serially quantify changes of iron concentration within hematomas in the intracerebral hemorrhage (ICH) pig model using non-invasive R2* and quantitative susceptibility mapping (QSM) MRI methods. Introduction: Hemolysis-related release of hemoglobin/heme/free iron after ICH causes cytotoxic injury. An accurate post hemorrhage assessment of iron would be valuable to develop strategies to prevent secondary damage. The T2* relaxation rate (R2* =1/T2*) on MRI depends on the regional oxy- versus deoxyhemoglobin. Post-ICH excess of deoxyhemoglobin has been applied as a quantitative marker to estimate iron in the brain. However, quantitative susceptibility mapping (QSM) is a new MRI technique that can quantify iron concentration within the hematoma by measuring induced magnetic susceptibility. Using R2* mapping and QSM in a large animal ICH model, we measured spatiotemporal changes in iron concentration in the brain. Methods: Lobar ICH was induced by infusion of 2.5 ml autologous blood in 8 Yorkshire pigs with average age/wt of 4-6wk/12.5±2.5kg. MRI was obtained at days 1 and 7. A 3D anatomical and multi-echo gradient echo images were obtained on a clinical 3.0 T Philips Ingenia MRI system. Parametric R2* and susceptibility maps were generated. Regions of interest were placed within hematoma and contralesional CSF. Results: R2* measurements in the hematoma at day 1 and day 7 were 41.3 ± 7.3 and 37.7 ± 7.7 s -1 , respectively, whereas the corresponding susceptibility measurements were 0.75± 0.3 and 0.70 ± 0.5 ppm. The CSF R2* were 5.53 ± 2.1 and 6.85 ± 2.4 s -1 , whereas susceptibility showed 0.06 ± 0.16 and 0.02 ± 0.03 ppm at the two time points. Both R2* and QSM showed no significant change in iron concentration within the hematoma ROI with p-value of 0.18 and 0.72 over a week. Absence of hyperintense regions remote from the hematoma in susceptibility maps suggested lack of diffuse iron deposition. Good correlation was observed between R2* and QSM (correlation coefficient 0.83 and 0.78 within hematoma, and -0.66 and -0.07 within CSF, at day 1 and 7, respectively). Conclusion: R2* and especially QSM, with their ability to provide quantitative iron content, are valuable tools to test new ICH treatments particularly targeting iron in this large animal model.

scholarly journals The Effect of Oblique Image Acquisition on the Accuracy of Quantitative Susceptibility Mapping and a Robust Tilt Correction Method

2021 ◽  
Author(s):  
Oliver C. Kiersnowski ◽  
Anita Karsa ◽  
Stephen J. Wastling ◽  
John S. Thornton ◽  
Karin Shmueli
Keyword(s):  
Mean Squared Error ◽  
Image Acquisition ◽  
Similarity Index ◽  
Background Field ◽  
Phase Unwrapping ◽  
Susceptibility Mapping ◽  
Main Magnetic Field ◽  
Quantitative Susceptibility Mapping ◽  
Tilt Correction

Purpose: Quantitative susceptibility mapping (QSM) is increasingly used for clinical research where oblique image acquisition is commonplace but its effects on QSM accuracy are not well understood. Theory and Methods: The QSM processing pipeline involves defining the unit magnetic dipole kernel, which requires knowledge of the direction of the main magnetic field B0 with respect to the acquired image volume axes. The direction of B0 is dependent upon the axis and angle of rotation in oblique acquisition. Using both a numerical brain phantom and in-vivo acquisitions, we analysed the effects of oblique acquisition on magnetic susceptibility maps. We compared three tilt correction schemes at each step in the QSM pipeline: phase unwrapping, background field removal and susceptibility calculation, using the root-mean-squared error and QSM-tuned structural similarity index (XSIM). Results: Rotation of wrapped phase images gave severe artefacts. Background field removal with projection onto dipole fields gave the most accurate susceptibilities when the field map was first rotated into alignment with B0. LBV and VSHARP background field removal methods gave accurate results without tilt correction. For susceptibility calculation, thresholded k-space division, iterative Tikhonov regularisation and weighted linear total variation regularisation all performed most accurately when local field maps were rotated into alignment with B0 before susceptibility calculation. Conclusion: For accurate QSM, oblique acquisition must be taken into account. Rotation of images into alignment with B0 should be carried out after phase unwrapping and before background field removal. We provide open-source tilt-correction code to incorporate easily into existing pipelines: https://github.com/o-snow/QSM_TiltCorrection.git.

scholarly journals Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging

2019 ◽  
Vol 92 (1101) ◽  
pp. 20181016 ◽  
Author(s):  
Pascal P. R. Ruetten ◽  
Jonathan H. Gillard ◽  
Martin J. Graves
Keyword(s):  
Magnetic Field ◽  
Magnetic Susceptibility ◽  
External Magnetic Field ◽  
Clinical Applications ◽  
Susceptibility Mapping ◽  
Susceptibility Weighted Imaging ◽  
Post Processing ◽  
Quantitative Susceptibility Mapping ◽  
Wide Range

Quantitative Susceptibility Mapping (QSM) and Susceptibility Weighted Imaging (SWI) are MRI techniques that measure and display differences in the magnetization that is induced in tissues, i.e. their magnetic susceptibility, when placed in the strong external magnetic field of an MRI system. SWI produces images in which the contrast is heavily weighted by the intrinsic tissue magnetic susceptibility. It has been applied in a wide range of clinical applications. QSM is a further advancement of this technique that requires sophisticated post-processing in order to provide quantitative maps of tissue susceptibility. This review explains the steps involved in both SWI and QSM as well as describing some of their uses in both clinical and research applications.

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