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Wang Y, Zhu Y, Luo L, He J. Q-space imaging based on Gaussian radial basis function with Laplace regularization. Magn Reson Med 2024; 92:128-144. [PMID: 38361281 DOI: 10.1002/mrm.30049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/21/2024] [Accepted: 01/24/2024] [Indexed: 02/17/2024]
Abstract
PURPOSE To introduce the diffusion signal characteristics presented by spherical harmonics (SH) basis into the q-space imaging method based on Gaussian radial basis function (GRBF) to robustly reconstruct ensemble average diffusion propagator (EAP) in diffusion MRI (dMRI). METHODS We introduced the Laplacian regularization of the signal into the dMRI imaging method based on GRBF, and derived the relevant indicators of microstructure imaging and the orientation distribution function (ODF) providing fiber bundle direction information based on EAP. In addition, this method is combined with a multi-compartment model to calculate the diameter of fiber bundle axons. The evaluation of the results included qualitative comparisons and quantitative assessments of the signal fitting. RESULTS The results show that the proposed method achieves the more significant accuracy improvement in reconstructing signal. Meanwhile, ODFs estimated by the proposed method show the sharper profiles and less spurious peaks, even under the sparse and noisy conditions. In the 36 sets of axon diameter estimation experiments, 34 and 30 sets of results showed that the proposed method reduced the mean and SD of axon diameter estimates, respectively. Moreover, compared with the current state-of-the-art method, the mean and SD of axon diameter estimated by the proposed method are mostly lower, with 32 and 29 of 36 groups. CONCLUSION The proposed method outperforms the GRBF regarding signal fitting and the estimation of the EAP and ODF with multi-shell sparse samples. Moreover, it shows the potential to recover important features of microstructures with less uncertainty by using proposed method together with multi-compartment models.
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Affiliation(s)
- Yuanjun Wang
- Institute of Medical Imaging Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Yuemin Zhu
- Institute of Medical Imaging Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Lingli Luo
- Institute of Medical Imaging Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Jianglin He
- Institute of Medical Imaging Engineering, University of Shanghai for Science and Technology, Shanghai, China
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2
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Wu D, Kang L, Li H, Ba R, Cao Z, Liu Q, Tan Y, Zhang Q, Li B, Yuan J. Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging. Neuroimage 2024; 290:120553. [PMID: 38403092 DOI: 10.1016/j.neuroimage.2024.120553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 02/27/2024] Open
Abstract
Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.
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Affiliation(s)
- Dan Wu
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Innovation Center for Smart Medical Technologies & Devices, Binjiang Institute of Zhejiang University, Hangzhou, China.
| | - Liyi Kang
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Innovation Center for Smart Medical Technologies & Devices, Binjiang Institute of Zhejiang University, Hangzhou, China
| | - Haotian Li
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Ruicheng Ba
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Zuozhen Cao
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Qian Liu
- United Imaging Healthcare Co., Ltd, Shanghai, China
| | - Yingchao Tan
- United Imaging Healthcare Co., Ltd, Shanghai, China
| | - Qinwei Zhang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Bo Li
- United Imaging Healthcare Co., Ltd, Shanghai, China
| | - Jianmin Yuan
- United Imaging Healthcare Co., Ltd, Shanghai, China
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3
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Fokkinga E, Hernandez-Tamames JA, Ianus A, Nilsson M, Tax CMW, Perez-Lopez R, Grussu F. Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology. J Magn Reson Imaging 2023. [PMID: 38032021 DOI: 10.1002/jmri.29144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 12/01/2023] Open
Abstract
Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncological applications of body imaging, where new biomarkers are urgently needed. The objective of this article is to review the state-of-the-art of DW-MRI in body imaging (ie, not including the nervous system) in oncology, and to analyze its value as compared to reference colocalized histology measurements, given that demonstrating the histological validity of any new DW-MRI method is essential. In this article, we review the current landscape of DW-MRI techniques that extend standard apparent diffusion coefficient (ADC), describing their acquisition protocols, signal models, fitting settings, microstructural parameters, and relationship with histology. Preclinical, clinical, and in/ex vivo studies were included. The most used techniques were intravoxel incoherent motion (IVIM; 36.3% of used techniques), diffusion kurtosis imaging (DKI; 16.7%), vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT; 13.3%), and imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED; 11.7%). Another notable category of techniques relates to innovative b-tensor diffusion encoding or joint diffusion-relaxometry. The reviewed approaches provide histologically meaningful indices of cancer microstructure (eg, vascularization/cellularity) which, while not necessarily accurate numerically, may still provide useful sensitivity to microscopic pathological processes. Future work of the community should focus on improving the inter-/intra-scanner robustness, and on assessing histological validity in broader contexts. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ella Fokkinga
- Biomedical Engineering, Track Medical Physics, Delft University of Technology, Delft, The Netherlands
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Andrada Ianus
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Markus Nilsson
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund, Sweden
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Raquel Perez-Lopez
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Francesco Grussu
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
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4
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Chakwizira A, Westin C, Brabec J, Lasič S, Knutsson L, Szczepankiewicz F, Nilsson M. Diffusion MRI with pulsed and free gradient waveforms: Effects of restricted diffusion and exchange. NMR IN BIOMEDICINE 2023; 36:e4827. [PMID: 36075110 PMCID: PMC10078514 DOI: 10.1002/nbm.4827] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 08/27/2022] [Accepted: 09/06/2022] [Indexed: 05/06/2023]
Abstract
Monitoring time dependence with diffusion MRI yields observables sensitive to compartment sizes (restricted diffusion) and membrane permeability (water exchange). However, restricted diffusion and exchange have opposite effects on the diffusion-weighted signal, which can lead to errors in parameter estimates. In this work, we propose a signal representation that incorporates the effects of both restricted diffusion and exchange up to second order in b-value and is compatible with gradient waveforms of arbitrary shape. The representation features mappings from a gradient waveform to two scalars that separately control the sensitivity to restriction and exchange. We demonstrate that these scalars span a two-dimensional space that can be used to choose waveforms that selectively probe restricted diffusion or exchange, eliminating the correlation between the two phenomena. We found that waveforms with specific but unconventional shapes provide an advantage over conventional pulsed and oscillating gradient acquisitions. We also show that parametrization of waveforms into a two-dimensional space can be used to understand protocols from other approaches that probe restricted diffusion and exchange. For example, we found that the variation of mixing time in filter-exchange imaging corresponds to variation of our exchange-weighting scalar at a fixed value of the restriction-weighting scalar. The proposed signal representation was evaluated using Monte Carlo simulations in identical parallel cylinders with hexagonal and random packing as well as parallel cylinders with gamma-distributed radii. Results showed that the approach is sensitive to sizes in the interval 4-12 μm and exchange rates in the simulated range of 0 to 20 s - 1 , but also that there is a sensitivity to the extracellular geometry. The presented theory constitutes a simple and intuitive description of how restricted diffusion and exchange influence the signal as well as a guide to protocol design capable of separating the two effects.
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Affiliation(s)
- Arthur Chakwizira
- Department of Medical Radiation Physics, LundLund UniversityLundSweden
| | - Carl‐Fredrik Westin
- Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Jan Brabec
- Department of Medical Radiation Physics, LundLund UniversityLundSweden
| | - Samo Lasič
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and ResearchCopenhagen University Hospital ‐ Amager and HvidovreCopenhagenDenmark
- Random Walk Imaging ABLundSweden
| | - Linda Knutsson
- Department of Medical Radiation Physics, LundLund UniversityLundSweden
- Russell H. Morgan Department of Radiology and Radiological ScienceJohns Hopkins University School of MedicineBaltimoreMarylandUSA
- F. M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
| | | | - Markus Nilsson
- Department of Clinical Sciences Lund, RadiologyLund UniversityLundSweden
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5
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Effect of Matrix Size Reduction on Textural Information in Clinical Magnetic Resonance Imaging. J Clin Med 2022; 11:jcm11092526. [PMID: 35566657 PMCID: PMC9103884 DOI: 10.3390/jcm11092526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/12/2022] [Accepted: 04/26/2022] [Indexed: 12/10/2022] Open
Abstract
The selection of the matrix size is an important element of the magnetic resonance imaging (MRI) process, and has a significant impact on the acquired image quality. Signal to noise ratio, often used to assess MR image quality, has its limitations. Thus, for this purpose we propose a novel approach: the use of texture analysis as an index of the image quality that is sensitive for the change of matrix size. Image texture in biomedical images represents tissue and organ structures visualized via medical imaging modalities such as MRI. The correlation between texture parameters determined for the same tissues visualized in images acquired with different matrix sizes is analyzed to aid in the assessment of the selection of the optimal matrix size. T2-weighted coronal images of shoulders were acquired using five different matrix sizes while maintaining the same field of view; three regions of interest (bone, fat, and muscle) were considered. Lin’s correlation coefficients were calculated for all possible pairs of the 310-element texture feature vectors evaluated for each matrix. The obtained results are discussed considering the image noise and blurring effect visible in images acquired with smaller matrices. Taking these phenomena into account, recommendations for the selection of the matrix size used for the MRI imaging were proposed.
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6
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Vis G, Nilsson M, Westin CF, Szczepankiewicz F. Accuracy and precision in super-resolution MRI: Enabling spherical tensor diffusion encoding at ultra-high b-values and high resolution. Neuroimage 2021; 245:118673. [PMID: 34688898 PMCID: PMC9272945 DOI: 10.1016/j.neuroimage.2021.118673] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 10/13/2021] [Accepted: 10/20/2021] [Indexed: 12/31/2022] Open
Abstract
Diffusion MRI (dMRI) can probe the tissue microstructure but suffers from low signal-to-noise ratio (SNR) whenever high resolution is combined with high diffusion encoding strengths. Low SNR leads to poor precision as well as poor accuracy of the diffusion-weighted signal; the latter is caused by the rectified noise floor and can be observed as a positive bias in magnitude signal. Super-resolution techniques may facilitate a beneficial tradeoff between bias and resolution by allowing acquisition at low spatial resolution and high SNR, whereafter high spatial resolution is recovered by image reconstruction. In this work, we describe a super-resolution reconstruction framework for dMRI and investigate its performance with respect to signal accuracy and precision. Using phantom experiments and numerical simulations, we show that the super-resolution approach improves accuracy by facilitating a more beneficial trade-off between spatial resolution and diffusion encoding strength before the noise floor affects the signal. By contrast, precision is shown to have a less straightforward dependency on acquisition, reconstruction, and intrinsic tissue parameters. Indeed, we find a gain in precision from super-resolution reconstruction is substantial only when some spatial resolution is sacrificed. Finally, we deployed super-resolution reconstruction in a healthy brain for the challenging combination of spherical b-tensor encoding at ultra-high b-values and high spatial resolution—a configuration that produces a unique contrast that emphasizes tissue in which diffusion is restricted in all directions. This demonstration showcased that super-resolution reconstruction enables a vastly superior image contrast compared to conventional imaging, facilitating investigations that would otherwise have prohibitively low SNR, resolution or require non-conventional MRI hardware.
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Affiliation(s)
- Geraline Vis
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden.
| | - Markus Nilsson
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden.
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
| | - Filip Szczepankiewicz
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
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7
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Mohanty V, McKinnon ET, Helpern JA, Jensen JH. Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain. Magn Reson Imaging 2018; 48:80-88. [PMID: 29306048 DOI: 10.1016/j.mri.2017.12.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Accepted: 12/29/2017] [Indexed: 12/31/2022]
Abstract
PURPOSE To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging. THEORY AND METHODS For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm2. For the QS estimates, b-values ranging from 0 up to 10,000s/mm2 were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula. The kurtosis was then calculated directly from the second and fourth order moments of the dPDF. These two approximations were studied for in vivo human data obtained on a 3T MRI scanner using three orthogonal diffusion encoding directions. RESULTS The whole brain mean values for the CE and QS kurtosis estimates differed by 16% or less in each of the considered diffusion encoding directions, and the Pearson correlation coefficients all exceeded 0.85. Nonetheless, there were large discrepancies in many voxels, particularly those with either very high or very low kurtoses relative to the mean values. CONCLUSION Estimates of the diffusional kurtosis in brain obtained using CE and QS approximations are strongly correlated, suggesting that they encode similar information. However, for the choice of b-values employed here, there may be substantial differences, depending on the properties of the diffusion microenvironment in each voxel.
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Affiliation(s)
- Vaibhav Mohanty
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Emilie T McKinnon
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Joseph A Helpern
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA.
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8
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Chuhutin A, Hansen B, Jespersen SN. Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3777. [PMID: 28841758 PMCID: PMC5715207 DOI: 10.1002/nbm.3777] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Revised: 06/14/2017] [Accepted: 07/03/2017] [Indexed: 05/22/2023]
Abstract
Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging that accounts for leading non-Gaussian diffusion effects. In DKI studies, a wide range of different gradient strengths (b-values) is used, which is known to affect the estimated diffusivity and kurtosis parameters. Hence there is a need to assess the accuracy and precision of the estimated parameters as a function of b-value. This work examines the error in the estimation of mean of the kurtosis tensor (MKT) with respect to the ground truth, using simulations based on a biophysical model for both gray (GM) and white (WM) matter. Model parameters are derived from densely sampled experimental data acquired in ex vivo rat brain and in vivo human brain. Additionally, the variability of MKT is studied using the experimental data. Prevalent fitting protocols are implemented and investigated. The results show strong dependence on the maximum b-value of both net relative error and standard deviation of error for all of the employed fitting protocols. The choice of b-values with minimum MKT estimation error and standard deviation of error was found to depend on the protocol type and the tissue. Protocols that utilize two terms of the cumulant expansion (DKI) were found to achieve minimum error in GM at b-values less than 1 ms/μm2 , whereas maximal b-values of about 2.5 ms/μm2 were found to be optimal in WM. Protocols including additional higher order terms of the cumulant expansion were found to provide higher accuracy for the more commonly used b-value regime in GM, but were associated with higher error in WM. Averaged over multiple voxels, a net average error of around 15% for both WM and GM was observed for the optimal b-value choice. These results suggest caution when using DKI generated metrics for microstructural modeling and when comparing results obtained using different fitting techniques and b-values.
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Affiliation(s)
- Andrey Chuhutin
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Brian Hansen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Sune Nørhøj Jespersen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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9
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Nilsson M, Lasič S, Drobnjak I, Topgaard D, Westin C. Resolution limit of cylinder diameter estimation by diffusion MRI: The impact of gradient waveform and orientation dispersion. NMR IN BIOMEDICINE 2017; 30:e3711. [PMID: 28318071 PMCID: PMC5485041 DOI: 10.1002/nbm.3711] [Citation(s) in RCA: 97] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Revised: 01/16/2017] [Accepted: 01/20/2017] [Indexed: 05/20/2023]
Abstract
Diffusion MRI has been proposed as a non-invasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong gradients, which is a challenge for the transition of the technique from preclinical to clinical MRI scanners, since these have weaker gradients. In this work, we develop a framework to estimate the lower bound for accurate diameter estimation, which we refer to as the resolution limit. We analyse only the contribution from the intra-axonal space and assume that axons can be represented by impermeable cylinders. To address the growing interest in using techniques for diffusion encoding that go beyond the conventional single diffusion encoding (SDE) sequence, we present a generalised analysis capable of predicting the resolution limit regardless of the gradient waveform. Using this framework, waveforms were optimised to minimise the resolution limit. The results show that, for parallel cylinders, the SDE experiment is optimal in terms of yielding the lowest possible resolution limit. In the presence of orientation dispersion, diffusion encoding sequences with square-wave oscillating gradients were optimal. The resolution limit for standard clinical MRI scanners (maximum gradient strength 60-80 mT/m) was found to be between 4 and 8 μm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300 mT/m, the limit was reduced to between 2 and 5 μm.
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Affiliation(s)
- Markus Nilsson
- Clinical Sciences Lund, Department of RadiologyLund UniversityLundSweden
| | | | | | - Daniel Topgaard
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
| | - Carl‐Fredrik Westin
- Department of Biomedical EngineeringLinköping UniversityLinköpingSweden
- Brigham and Women's HospitalHarvard Medical SchoolBostonMAUSA
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10
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Li H, Jiang X, Xie J, Gore JC, Xu J. Impact of transcytolemmal water exchange on estimates of tissue microstructural properties derived from diffusion MRI. Magn Reson Med 2017; 77:2239-2249. [PMID: 27342260 PMCID: PMC5183568 DOI: 10.1002/mrm.26309] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Revised: 05/23/2016] [Accepted: 05/24/2016] [Indexed: 12/19/2022]
Abstract
PURPOSE To investigate the influence of transcytolemmal water exchange on estimates of tissue microstructural parameters derived from diffusion MRI using conventional PGSE and IMPULSED methods. METHODS Computer simulations were performed to incorporate a broad range of intracellular water life times τin (50-∞ ms), cell diameters d (5-15 μm), and intrinsic diffusion coefficient Din (0.6-2 μm2 /ms) for different values of signal-to-noise ratio (SNR) (10 to 50). For experiments, murine erythroleukemia (MEL) cancer cells were cultured and treated with saponin to selectively change cell membrane permeability. All fitted microstructural parameters from simulations and experiments in vitro were compared with ground-truth values. RESULTS Simulations showed that, for both PGSE and IMPULSED methods, cell diameter d can be reliably fit with sufficient SNR (≥ 50), whereas intracellular volume fraction fin is intrinsically underestimated due to transcytolemmal water exchange. Din can be reliably fit only with sufficient SNR and using the IMPULSED method with short diffusion times. These results were confirmed with those obtained in the cell culture experiments in vitro. CONCLUSION For the sequences and models considered in this study, transcytolemmal water exchange has minor effects on the fittings of d and Din with physiologically relevant membrane permeabilities if the SNR is sufficient (> 50), but fin is intrinsically underestimated. Magn Reson Med 77:2239-2249, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Hua Li
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - Xiaoyu Jiang
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - Jingping Xie
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - John C. Gore
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN 37232, USA
| | - Junzhong Xu
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN 37232, USA
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11
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Tian Q, Rokem A, Folkerth RD, Nummenmaa A, Fan Q, Edlow BL, McNab JA. Q-space truncation and sampling in diffusion spectrum imaging. Magn Reson Med 2016; 76:1750-1763. [PMID: 26762670 PMCID: PMC4942411 DOI: 10.1002/mrm.26071] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2015] [Revised: 10/30/2015] [Accepted: 11/05/2015] [Indexed: 11/11/2022]
Abstract
PURPOSE To characterize the q-space truncation and sampling on the spin-displacement probability density function (PDF) in diffusion spectrum imaging (DSI). METHODS DSI data were acquired using the MGH-USC connectome scanner (Gmax = 300 mT/m) with bmax = 30,000 s/mm2 , 17 × 17 × 17, 15 × 15 × 15 and 11 × 11 × 11 grids in ex vivo human brains and bmax = 10,000 s/mm2 , 11 × 11 × 11 grid in vivo. An additional in vivo scan using bmax =7,000 s/mm2 , 11 × 11 × 11 grid was performed with a derated gradient strength of 40 mT/m. PDFs and orientation distribution functions (ODFs) were reconstructed with different q-space filtering and PDF integration lengths, and from down-sampled data by factors of two and three. RESULTS Both ex vivo and in vivo data showed Gibbs ringing in PDFs, which becomes the main source of artifact in the subsequently reconstructed ODFs. For down-sampled data, PDFs interfere with the first replicas or their ringing, leading to obscured orientations in ODFs. CONCLUSION The minimum required q-space sampling density corresponds to a field-of-view approximately equal to twice the mean displacement distance (MDD) of the tissue. The 11 × 11 × 11 grid is suitable for both ex vivo and in vivo DSI experiments. To minimize the effects of Gibbs ringing, ODFs should be reconstructed from unfiltered q-space data with the integration length over the PDF constrained to around the MDD. Magn Reson Med 76:1750-1763, 2016. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Qiyuan Tian
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Ariel Rokem
- Department of Psychology, Stanford University, Stanford, California, USA
| | - Rebecca D. Folkerth
- Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Brian L. Edlow
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jennifer A. McNab
- Department of Radiology, Stanford University, Stanford, California, USA
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12
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Szczepankiewicz F, van Westen D, Englund E, Westin CF, Ståhlberg F, Lätt J, Sundgren PC, Nilsson M. The link between diffusion MRI and tumor heterogeneity: Mapping cell eccentricity and density by diffusional variance decomposition (DIVIDE). Neuroimage 2016; 142:522-532. [PMID: 27450666 DOI: 10.1016/j.neuroimage.2016.07.038] [Citation(s) in RCA: 120] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Revised: 06/24/2016] [Accepted: 07/16/2016] [Indexed: 01/18/2023] Open
Abstract
The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms of the variance of apparent diffusivities within a voxel. However, the link between the diffusional variance and the tissue heterogeneity is not well-established. To investigate this link we test the hypothesis that diffusional variance, caused by microscopic anisotropy and isotropic heterogeneity, is associated with variable cell eccentricity and cell density in brain tumors. We performed dMRI using a novel encoding scheme for diffusional variance decomposition (DIVIDE) in 7 meningiomas and 8 gliomas prior to surgery. The diffusional variance was quantified from dMRI in terms of the total mean kurtosis (MKT), and DIVIDE was used to decompose MKT into components caused by microscopic anisotropy (MKA) and isotropic heterogeneity (MKI). Diffusion anisotropy was evaluated in terms of the fractional anisotropy (FA) and microscopic fractional anisotropy (μFA). Quantitative microscopy was performed on the excised tumor tissue, where structural anisotropy and cell density were quantified by structure tensor analysis and cell nuclei segmentation, respectively. In order to validate the DIVIDE parameters they were correlated to the corresponding parameters derived from microscopy. We found an excellent agreement between the DIVIDE parameters and corresponding microscopy parameters; MKA correlated with cell eccentricity (r=0.95, p<10-7) and MKI with the cell density variance (r=0.83, p<10-3). The diffusion anisotropy correlated with structure tensor anisotropy on the voxel-scale (FA, r=0.80, p<10-3) and microscopic scale (μFA, r=0.93, p<10-6). A multiple regression analysis showed that the conventional MKT parameter reflects both variable cell eccentricity and cell density, and therefore lacks specificity in terms of microstructure characteristics. However, specificity was obtained by decomposing the two contributions; MKA was associated only to cell eccentricity, and MKI only to cell density variance. The variance in meningiomas was caused primarily by microscopic anisotropy (mean±s.d.) MKA=1.11±0.33 vs MKI=0.44±0.20 (p<10-3), whereas in the gliomas, it was mostly caused by isotropic heterogeneity MKI=0.57±0.30 vs MKA=0.26±0.11 (p<0.05). In conclusion, DIVIDE allows non-invasive mapping of parameters that reflect variable cell eccentricity and density. These results constitute convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI. Decomposing effects of microscopic anisotropy and isotropic heterogeneity facilitates an improved interpretation of tumor heterogeneity as well as diffusion anisotropy on both the microscopic and macroscopic scale.
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Affiliation(s)
- Filip Szczepankiewicz
- Lund University, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden.
| | - Danielle van Westen
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden; Skåne University Hospital, Department of Imaging and Function, Lund, Sweden
| | - Elisabet Englund
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund, Sweden
| | - Carl-Fredrik Westin
- Harvard Medical School, Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA
| | - Freddy Ståhlberg
- Lund University, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden; Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden
| | - Jimmy Lätt
- Skåne University Hospital, Department of Imaging and Function, Lund, Sweden
| | - Pia C Sundgren
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden
| | - Markus Nilsson
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden; Lund University, Lund University Bioimaging Center, Lund, Sweden
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13
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Westin CF, Knutsson H, Pasternak O, Szczepankiewicz F, Özarslan E, van Westen D, Mattisson C, Bogren M, O'Donnell LJ, Kubicki M, Topgaard D, Nilsson M. Q-space trajectory imaging for multidimensional diffusion MRI of the human brain. Neuroimage 2016; 135:345-62. [PMID: 26923372 PMCID: PMC4916005 DOI: 10.1016/j.neuroimage.2016.02.039] [Citation(s) in RCA: 196] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 12/29/2015] [Accepted: 02/12/2016] [Indexed: 12/28/2022] Open
Abstract
This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.
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Affiliation(s)
- Carl-Fredrik Westin
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
| | - Hans Knutsson
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Evren Özarslan
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Physics, Bogazici University, Istanbul, Turkey
| | | | | | - Mats Bogren
- Clinical Sciences, Psychiatry, Lund University, Lund, Sweden
| | | | - Marek Kubicki
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Topgaard
- Division of Physical Chemistry, Department of Chemistry, Lund University, Lund, Sweden
| | - Markus Nilsson
- Lund University Bioimaging Center, Lund University, Lund, Sweden
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14
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Teh I, Burton RAB, McClymont D, Capel RA, Aston D, Kohl P, Schneider JE. Mapping cardiac microstructure of rabbit heart in different mechanical states by high resolution diffusion tensor imaging: A proof-of-principle study. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2016; 121:85-96. [PMID: 27320383 PMCID: PMC4959513 DOI: 10.1016/j.pbiomolbio.2016.06.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Accepted: 06/13/2016] [Indexed: 01/27/2023]
Abstract
Myocardial microstructure and its macroscopic materialisation are fundamental to the function of the heart. Despite this importance, characterisation of cellular features at the organ level remains challenging, and a unifying description of the structure of the heart is still outstanding. Here, we optimised diffusion tensor imaging data to acquire high quality data in ex vivo rabbit hearts in slack and contractured states, approximating diastolic and systolic conditions. The data were analysed with a suite of methods that focused on different aspects of the myocardium. In the slack heart, we observed a similar transmural gradient in helix angle of the primary eigenvector of up to 23.6°/mm in the left ventricle and 24.2°/mm in the right ventricle. In the contractured heart, the same transmural gradient remained largely linear, but was offset by up to +49.9° in the left ventricle. In the right ventricle, there was an increase in the transmural gradient to 31.2°/mm and an offset of up to +39.0°. The application of tractography based on each eigenvector enabled visualisation of streamlines that depict cardiomyocyte and sheetlet organisation over large distances. We observed multiple V- and N-shaped sheetlet arrangements throughout the myocardium, and insertion of sheetlets at the intersection of the left and right ventricle. This study integrates several complementary techniques to visualise and quantify the heart's microstructure, projecting parameter representations across different length scales. This represents a step towards a more comprehensive characterisation of myocardial microstructure at the whole organ level.
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Affiliation(s)
- Irvin Teh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Rebecca A B Burton
- Department of Pharmacology, University of Oxford, Oxford, United Kingdom
| | - Darryl McClymont
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Rebecca A Capel
- Department of Pharmacology, University of Oxford, Oxford, United Kingdom
| | - Daniel Aston
- Department of Pharmacology, University of Oxford, Oxford, United Kingdom
| | - Peter Kohl
- National Heart and Lung Institute, Imperial College London, London, United Kingdom; Institute for Experimental Cardiovascular Medicine, University Heart Centre Freiburg - Bad Krozingen, Medical School of the University of Freiburg, Germany
| | - Jürgen E Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
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15
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Fick RHJ, Wassermann D, Caruyer E, Deriche R. MAPL: Tissue microstructure estimation using Laplacian-regularized MAP-MRI and its application to HCP data. Neuroimage 2016; 134:365-385. [PMID: 27043358 DOI: 10.1016/j.neuroimage.2016.03.046] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 02/02/2016] [Accepted: 03/18/2016] [Indexed: 10/22/2022] Open
Abstract
The recovery of microstructure-related features of the brain's white matter is a current challenge in diffusion MRI. To robustly estimate these important features from multi-shell diffusion MRI data, we propose to analytically regularize the coefficient estimation of the Mean Apparent Propagator (MAP)-MRI method using the norm of the Laplacian of the reconstructed signal. We first compare our approach, which we call MAPL, with competing, state-of-the-art functional basis approaches. We show that it outperforms the original MAP-MRI implementation and the recently proposed modified Spherical Polar Fourier (mSPF) basis with respect to signal fitting and reconstruction of the Ensemble Average Propagator (EAP) and Orientation Distribution Function (ODF) in noisy, sparsely sampled data of a physical phantom with reference gold standard data. Then, to reduce the variance of parameter estimation using multi-compartment tissue models, we propose to use MAPL's signal fitting and extrapolation as a preprocessing step. We study the effect of MAPL on the estimation of axon diameter using a simplified Axcaliber model and axonal dispersion using the Neurite Orientation Dispersion and Density Imaging (NODDI) model. We show the positive effect of using it as a preprocessing step in estimating and reducing the variances of these parameters in the Corpus Callosum of six different subjects of the MGH Human Connectome Project. Finally, we correlate the estimated axon diameter, dispersion and restricted volume fractions with Fractional Anisotropy (FA) and clearly show that changes in FA significantly correlate with changes in all estimated parameters. Overall, we illustrate the potential of using a well-regularized functional basis together with multi-compartment approaches to recover important microstructure tissue parameters with much less variability, thus contributing to the challenge of better understanding microstructure-related features of the brain's white matter.
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Affiliation(s)
- Rutger H J Fick
- Athena Project-Team, Inria Sophia Antipolis, Méditerranée, France.
| | | | | | - Rachid Deriche
- Athena Project-Team, Inria Sophia Antipolis, Méditerranée, France
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16
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Abstract
Objects making up complex porous systems in Nature usually span a range of sizes. These size distributions play fundamental roles in defining the physicochemical, biophysical and physiological properties of a wide variety of systems - ranging from advanced catalytic materials to Central Nervous System diseases. Accurate and noninvasive measurements of size distributions in opaque, three-dimensional objects, have thus remained long-standing and important challenges. Herein we describe how a recently introduced diffusion-based magnetic resonance methodology, Non-Uniform-Oscillating-Gradient-Spin-Echo (NOGSE), can determine such distributions noninvasively. The method relies on its ability to probe confining lengths with a (length)6 parametric sensitivity, in a constant-time, constant-number-of-gradients fashion; combined, these attributes provide sufficient sensitivity for characterizing the underlying distributions in μm-scaled cellular systems. Theoretical derivations and simulations are presented to verify NOGSE's ability to faithfully reconstruct size distributions through suitable modeling of their distribution parameters. Experiments in yeast cell suspensions - where the ground truth can be determined from ancillary microscopy - corroborate these trends experimentally. Finally, by appending to the NOGSE protocol an imaging acquisition, novel MRI maps of cellular size distributions were collected from a mouse brain. The ensuing micro-architectural contrasts successfully delineated distinctive hallmark anatomical sub-structures, in both white matter and gray matter tissues, in a non-invasive manner. Such findings highlight NOGSE's potential for characterizing aberrations in cellular size distributions upon disease, or during normal processes such as development.
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Affiliation(s)
- Noam Shemesh
- Department of Chemical Physics, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Gonzalo A. Álvarez
- Department of Chemical Physics, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Lucio Frydman
- Department of Chemical Physics, Weizmann Institute of Science, Rehovot, 76100, Israel
- * E-mail:
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17
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Xu J, Li H, Harkins KD, Jiang X, Xie J, Kang H, Does MD, Gore JC. Mapping mean axon diameter and axonal volume fraction by MRI using temporal diffusion spectroscopy. Neuroimage 2014; 103:10-19. [PMID: 25225002 PMCID: PMC4312203 DOI: 10.1016/j.neuroimage.2014.09.006] [Citation(s) in RCA: 93] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Revised: 09/02/2014] [Accepted: 09/04/2014] [Indexed: 02/01/2023] Open
Abstract
Mapping mean axon diameter and intra-axonal volume fraction may have significant clinical potential because nerve conduction velocity is directly dependent on axon diameter, and several neurodegenerative diseases affect axons of specific sizes and alter axon counts. Diffusion-weighted MRI methods based on the pulsed gradient spin echo (PGSE) sequence have been reported to be able to assess axon diameter and volume fraction non-invasively. However, due to the relatively long diffusion times used, e.g. >20ms, the sensitivity to small axons (diameter<2μm) is low, and the derived mean axon diameter has been reported to be overestimated. In the current study, oscillating gradient spin echo (OGSE) diffusion sequences with variable frequency gradients were used to assess rat spinal white matter tracts with relatively short effective diffusion times (1-5ms). In contrast to previous PGSE-based methods, the extra-axonal diffusion cannot be modeled as hindered (Gaussian) diffusion when short diffusion times are used. Appropriate frequency-dependent rates are therefore incorporated into our analysis and validated by histology-based computer simulation of water diffusion. OGSE data were analyzed to derive mean axon diameters and intra-axonal volume fractions of rat spinal white matter tracts (mean axon diameter of ~1.27-5.54μm). The estimated values were in good agreement with histology, including the small axon diameters (<2.5μm). This study establishes a framework for the quantification of nerve morphology using the OGSE method with high sensitivity to small axons.
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Affiliation(s)
- Junzhong Xu
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA.
| | - Hua Li
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
| | - Kevin D Harkins
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
| | - Xiaoyu Jiang
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - Jingping Xie
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37203, USA
| | - Mark D Does
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| | - John C Gore
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
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18
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Shemesh N, Álvarez GA, Frydman L. Measuring small compartment dimensions by probing diffusion dynamics via Non-uniform Oscillating-Gradient Spin-Echo (NOGSE) NMR. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2013; 237:49-62. [PMID: 24140623 DOI: 10.1016/j.jmr.2013.09.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2013] [Revised: 09/13/2013] [Accepted: 09/14/2013] [Indexed: 05/22/2023]
Abstract
Noninvasive measurements of microstructure in materials, cells, and in biological tissues, constitute a unique capability of gradient-assisted NMR. Diffusion-diffraction MR approaches pioneered by Callaghan demonstrated this ability; Oscillating-Gradient Spin-Echo (OGSE) methodologies tackle the demanding gradient amplitudes required for observing diffraction patterns by utilizing constant-frequency oscillating gradient pairs that probe the diffusion spectrum, D(ω). Here we present a new class of diffusion MR experiments, termed Non-uniform Oscillating-Gradient Spin-Echo (NOGSE), which dynamically probe multiple frequencies of the diffusion spectral density at once, thus affording direct microstructural information on the compartment's dimension. The NOGSE methodology applies N constant-amplitude gradient oscillations; N-1 of these oscillations are spaced by a characteristic time x, followed by a single gradient oscillation characterized by a time y, such that the diffusion dynamics is probed while keeping (N-1)x+y≡TNOGSE constant. These constant-time, fixed-gradient-amplitude, multi-frequency attributes render NOGSE particularly useful for probing small compartment dimensions with relatively weak gradients - alleviating difficulties associated with probing D(ω) frequency-by-frequency or with varying relaxation weightings, as in other diffusion-monitoring experiments. Analytical descriptions of the NOGSE signal are given, and the sequence's ability to extract small compartment sizes with a sensitivity towards length to the sixth power, is demonstrated using a microstructural phantom. Excellent agreement between theory and experiments was evidenced even upon applying weak gradient amplitudes. An MR imaging version of NOGSE was also implemented in ex vivo pig spinal cords and mouse brains, affording maps based on compartment sizes. The effects of size distributions on NOGSE are also briefly analyzed.
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Affiliation(s)
- Noam Shemesh
- Department of Chemical Physics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Gonzalo A Álvarez
- Department of Chemical Physics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Lucio Frydman
- Department of Chemical Physics, Weizmann Institute of Science, Rehovot 76100, Israel.
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19
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The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2013; 26:345-70. [PMID: 23443883 PMCID: PMC3728433 DOI: 10.1007/s10334-013-0371-x] [Citation(s) in RCA: 100] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2012] [Revised: 01/28/2013] [Accepted: 02/01/2013] [Indexed: 12/27/2022]
Abstract
Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.
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20
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Laun FB, Kuder TA, Wetscherek A, Stieltjes B, Semmler W. NMR-based diffusion pore imaging. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2012; 86:021906. [PMID: 23005784 DOI: 10.1103/physreve.86.021906] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2012] [Revised: 05/23/2012] [Indexed: 06/01/2023]
Abstract
Nuclear magnetic resonance (NMR) diffusion experiments offer a unique opportunity to study boundaries restricting the diffusion process. In a recent Letter [Phys. Rev. Lett. 107, 048102 (2011)], we introduced the idea and concept that such diffusion experiments can be interpreted as NMR imaging experiments. Consequently, images of closed pores, in which the spins diffuse, can be acquired. In the work presented here, an in-depth description of the diffusion pore imaging technique is provided. Image artifacts due to gradient profiles of finite duration, field inhomogeneities, and surface relaxation are considered. Gradients of finite duration lead to image blurring and edge enhancement artifacts. Field inhomogeneities have benign effects on diffusion pore images, and surface relaxation can lead to a shrinkage and shift of the pore image. The relation between boundary structure and the imaginary part of the diffusion weighted signal is analyzed, and it is shown that information on pore coherence can be obtained without the need to measure the phase of the diffusion weighted signal. Moreover, it is shown that quite arbitrary gradient profiles can be used for diffusion pore imaging. The matrices required for numerical calculations are stated and provided as supplemental material.
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Affiliation(s)
- Frederik Bernd Laun
- Medical Physics in Radiology, German Cancer Research Center, DKFZ, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
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21
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Nilsson M, Lätt J, Ståhlberg F, van Westen D, Hagslätt H. The importance of axonal undulation in diffusion MR measurements: a Monte Carlo simulation study. NMR IN BIOMEDICINE 2012; 25:795-805. [PMID: 22020832 DOI: 10.1002/nbm.1795] [Citation(s) in RCA: 116] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2010] [Revised: 08/31/2011] [Accepted: 09/02/2011] [Indexed: 05/12/2023]
Abstract
Many axons follow wave-like undulating courses. This is a general feature of extracranial nerve segments, but is also found in some intracranial nervous tissue. The importance of axonal undulation has previously been considered, for example, in the context of biomechanics, where it has been shown that posture affects undulation properties. However, the importance of axonal undulation in the context of diffusion MR measurements has not been investigated. Using an analytical model and Monte Carlo simulations of water diffusion, this study compared undulating and straight axons in terms of diffusion propagators, diffusion-weighted signal intensities and parameters derived from diffusion tensor imaging, such as the mean diffusivity (MD), the eigenvalues and the fractional anisotropy (FA). All parameters were strongly affected by the presence of undulation. The diffusivity perpendicular to the undulating axons increased with the undulation amplitude, thus resembling that of straight axons with larger diameters. Consequently, models assuming straight axons for the estimation of the axon diameter from diffusion MR measurements might overestimate the diameter if undulation is present. FA decreased from approximately 0.7 to 0.5 when axonal undulation was introduced into the simulation model structure. Our results indicate that axonal undulation may play a role in diffusion measurements when investigating, for example, the optic and sciatic nerves and the spinal cord. The simulations also demonstrate that the stretching or compression of neuronal tissue comprising undulating axons alters the observed water diffusivity, suggesting that posture may be of importance for the outcome of diffusion MRI measurements.
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Affiliation(s)
- Markus Nilsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden.
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22
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Fieremans E, Pires A, Jensen JH. A simple isotropic phantom for diffusional kurtosis imaging. Magn Reson Med 2011; 68:537-42. [PMID: 22161496 DOI: 10.1002/mrm.23263] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2011] [Revised: 09/08/2011] [Accepted: 09/30/2011] [Indexed: 01/03/2023]
Abstract
Dairy cream is shown to be a simple, inexpensive, isotropic phantom useful for testing diffusional kurtosis imaging data acquisition and postprocessing. The MR-visible protons of cream exhibit slow and fast diffusion components, attributed to the fat and water protons, respectively, which give rise to a diffusion coefficient of 1.1 μm(2)/ms and a diffusional kurtosis of 1.2. These parameter values are similar to those observed in vivo for human brain. Heating the cream is found to increase the T(2)-relaxation time of the fat protons, which facilitates the evaluation of typical diffusional kurtosis imaging protocols used in clinical settings. The diffusion coefficient and diffusional kurtosis can both be measured directly and predicted based on the corresponding diffusion parameters of the individual water and fat components, which are independently measurable due to chemical shift misregistration, thus providing an important consistency check. This phantom is proposed as a convenient calibration standard for multicenter diffusional kurtosis imaging studies.
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Affiliation(s)
- Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York 10016, United States of America.
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23
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Drobnjak I, Alexander DC. Optimising time-varying gradient orientation for microstructure sensitivity in diffusion-weighted MR. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2011; 212:344-354. [PMID: 21889378 DOI: 10.1016/j.jmr.2011.07.017] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2011] [Revised: 07/16/2011] [Accepted: 07/21/2011] [Indexed: 05/31/2023]
Abstract
Here we investigate whether varying the diffusion-gradient orientation during a general waveform single pulsed-field gradient sequence improves sensitivity to the size of coherently oriented pores over having a fixed orientation. The experiment optimises the shape and the orientation of the gradient waveform in each of a set of measurements to minimise the expected variance of estimates of the parameters of a simple model. A key application motivating the work is measuring the size of axons in white matter. Thus, we use a two compartment white matter model with impermeable, single-radius cylinders, and search for waveforms that maximise the sensitivity to axon radius, intra-cellular volume fraction and diffusion constants. Output of the optimisation suggests the only benefit of allowing the gradient orientation to vary in the plane perpendicular to the cylinders is that we can gain perpendicular gradient strength by maximising two orthogonal gradients simultaneously. This suggests that varying orientation in itself does not increase the sensitivity to model parameters. On the other hand, the variation in a plane containing the parallel direction increases the sensitivity significantly because parallel sensitivity improves the diffusion constant estimates. However, we also find that similar improvement in the estimates can be achieved without optimising the orientation, but by having one measurement in the parallel and the rest in the perpendicular direction. The optimisation searches a very large space where it cannot hope to find the global minimum so we cannot make a categorical conclusion. However, given the consistency of the results in multiple reruns and variations of the experiments reported here, we can suggest that for probing coherently oriented systems, pulse sequences with variable orientation, such as double-wave vector sequences, do not offer more advantage than fixed orientation sequences with optimised shape. The advantage of varying orientation is however likely to emerge for more complex systems with dispersed pore orientation.
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Affiliation(s)
- Ivana Drobnjak
- Center for Medical Image Computing, Department of Computer Science, University College London (UCL), Gower Street, London WC1E 6BT, UK.
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Alexander DC, Hubbard PL, Hall MG, Moore EA, Ptito M, Parker GJM, Dyrby TB. Orientationally invariant indices of axon diameter and density from diffusion MRI. Neuroimage 2010; 52:1374-89. [PMID: 20580932 DOI: 10.1016/j.neuroimage.2010.05.043] [Citation(s) in RCA: 499] [Impact Index Per Article: 35.6] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2009] [Revised: 05/14/2010] [Accepted: 05/16/2010] [Indexed: 11/30/2022] Open
Affiliation(s)
- Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
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Nilsson M, Alerstam E, Wirestam R, Ståhlberg F, Brockstedt S, Lätt J. Evaluating the accuracy and precision of a two-compartment Kärger model using Monte Carlo simulations. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2010; 206:59-67. [PMID: 20594881 DOI: 10.1016/j.jmr.2010.06.002] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2010] [Revised: 05/27/2010] [Accepted: 06/02/2010] [Indexed: 05/29/2023]
Abstract
Specific parameters of the neuronal tissue microstructure, such as axonal diameters, membrane permeability and intracellular water fractions are assessable using diffusion MRI. These parameters are commonly estimated using analytical models, which may introduce bias in the estimated parameters due to the approximations made when deriving the models. As an alternative to using analytical models, a database of signal curves generated by fast Monte Carlo simulations can be employed. Simulated diffusion MRI measurements were generated and evaluated using the two-compartment Kärger model as well as the simulation model based on a database containing signal curves from approximately 60000 simulations performed with different combinations of microstructural parameters. A protocol based on a pulsed gradient spin echo sequence with diffusion times of 30 and 60 ms and with gradient amplitudes obtainable with a clinical MRI scanner was employed for the investigations. When using the analytical model, a major negative bias (up to approximately 25%) in the estimated intracellular volume fraction was observed for short exchange times, while almost no bias was seen for the simulation model. In general, the simulation model improved the accuracy of the estimated parameters as compared to the analytical model, except for the exchange time parameter.
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Affiliation(s)
- M Nilsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden.
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Drobnjak I, Siow B, Alexander DC. Optimizing gradient waveforms for microstructure sensitivity in diffusion-weighted MR. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2010; 206:41-51. [PMID: 20580294 DOI: 10.1016/j.jmr.2010.05.017] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2010] [Revised: 05/24/2010] [Accepted: 05/25/2010] [Indexed: 05/22/2023]
Abstract
Variations in gradient waveforms can provide different levels of sensitivity to microstructure parameters in diffusion-weighted MR. We present a method that identifies gradient waveforms with maximal sensitivity to parameters of a model relating microstructural features to diffusion MR signals. The method optimizes the shape of the gradient waveform, constrained by hardware limits and fixed orientation, to minimize the expected variance of parameter estimates. The waveform is defined discretely and each point optimized independently. The method is illustrated with a biomedical application in which we maximize the sensitivity to microstructural features of white matter such as axon radius, intra-cellular volume fraction and diffusion constants. Simulation experiments find that optimization of the shape of the gradient waveform improves sensitivity to model parameters for both human and animal MR systems. In particular, the optimized waveforms make axon radii smaller than 5 microm more distinguishable than standard pulsed gradient spin-echo (PGSE). The identified class of optimized gradient waveforms have dominant square-wave components with frequency that increases as the radius size decreases.
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Affiliation(s)
- Ivana Drobnjak
- Center for Medical Image Computing, Department of Computer Science, University College London (UCL), Gower Street, London WC1E 6BT, UK.
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Farrell JAD, Zhang J, Jones MV, Deboy CA, Hoffman PN, Landman BA, Smith SA, Reich DS, Calabresi PA, van Zijl PCM. q-space and conventional diffusion imaging of axon and myelin damage in the rat spinal cord after axotomy. Magn Reson Med 2010; 63:1323-35. [PMID: 20432303 DOI: 10.1002/mrm.22389] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Parallel and perpendicular diffusion properties of water in the rat spinal cord were investigated 3 and 30 days after dorsal root axotomy, a specific insult resulting in early axonal degeneration followed by later myelin damage in the dorsal column white matter. Results from q-space analysis (i.e., the diffusion probability density function) obtained with strong diffusion weighting were compared to conventional anisotropy and diffusivity measurements at low b-values, as well as to histology for axon and myelin damage. q-Space contrasts included the height (return to zero displacement probability), full width at half maximum, root mean square displacement, and kurtosis excess of the probability density function, which quantifies the deviation from gaussian diffusion. Following axotomy, a significant increase in perpendicular diffusion (with decreased kurtosis excess) and decrease in parallel diffusion (with increased kurtosis excess) were found in lesions relative to uninjured white matter. Notably, a significant change in abnormal parallel diffusion was detected from 3 to 30 days with full width at half maximum, but not with conventional diffusivity. Also, directional full width at half maximum and root mean square displacement measurements exhibited different sensitivities to white matter damage. When compared to histology, the increase in perpendicular diffusion was not specific to demyelination, whereas combined reduced parallel diffusion and increased perpendicular diffusion was associated with axon damage.
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Affiliation(s)
- Jonathan A D Farrell
- Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
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Jensen JH, Helpern JA. MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR IN BIOMEDICINE 2010; 23:698-710. [PMID: 20632416 PMCID: PMC2997680 DOI: 10.1002/nbm.1518] [Citation(s) in RCA: 873] [Impact Index Per Article: 62.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Quantification of non-Gaussianity for water diffusion in brain by means of diffusional kurtosis imaging (DKI) is reviewed. Diffusional non-Gaussianity is a consequence of tissue structure that creates diffusion barriers and compartments. The degree of non-Gaussianity is conveniently quantified by the diffusional kurtosis and derivative metrics, such as the mean, axial, and radial kurtoses. DKI is a diffusion-weighted MRI technique that allows the diffusional kurtosis to be estimated with clinical scanners using standard diffusion-weighted pulse sequences and relatively modest acquisition times. DKI is an extension of the widely used diffusion tensor imaging method, but requires the use of at least 3 b-values and 15 diffusion directions. This review discusses the underlying theory of DKI as well as practical considerations related to data acquisition and post-processing. It is argued that the diffusional kurtosis is sensitive to diffusional heterogeneity and suggested that DKI may be useful for investigating ischemic stroke and neuropathologies, such as Alzheimer's disease and schizophrenia.
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Affiliation(s)
- Jens H Jensen
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York 10016-3295, USA.
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The effect of finite diffusion gradient pulse duration on fibre orientation estimation in diffusion MRI. Neuroimage 2010; 51:743-51. [DOI: 10.1016/j.neuroimage.2010.02.041] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2009] [Revised: 01/19/2010] [Accepted: 02/13/2010] [Indexed: 11/19/2022] Open
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Lätt J, Nilsson M, van Westen D, Wirestam R, Ståhlberg F, Brockstedt S. Diffusion-weighted MRI measurements on stroke patients reveal water-exchange mechanisms in sub-acute ischaemic lesions. NMR IN BIOMEDICINE 2009; 22:619-628. [PMID: 19306340 DOI: 10.1002/nbm.1376] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
The aim of this study was to investigate the diffusion time dependence of signal-versus-b curves obtained from diffusion-weighted magnetic resonance imaging (DW-MRI) of sub-acute ischaemic lesions in stroke patients. In this case series study, 16 patients with sub-acute ischaemic stroke were examined with DW-MRI using two different diffusion times (60 and 260 ms). Nine of these patients showed sufficiently large lesions without artefacts to merit further analysis. The signal-versus-b curves from the lesions were plotted and analysed using a two-compartment model including compartmental exchange. To validate the model and to aid the interpretation of the estimated model parameters, Monte Carlo simulations were performed. In eight cases, the plotted signal-versus-b curves, obtained from the lesions, showed a signal-curve split-up when data for the two diffusion times were compared, revealing effects of compartmental water exchange. For one of the patients, parametric maps were generated based on the extracted model parameters. These novel observations suggest that water exchange between different water pools is measurable and thus potentially useful for clinical assessment. The information can improve the understanding of the relationship between the DW-MRI signal intensity and the microstructural properties of the lesions.
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Affiliation(s)
- J Lätt
- Department of Medical Radiation Physics, Lund University, Lund, Sweden.
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Nilsson M, Lätt J, Nordh E, Wirestam R, Ståhlberg F, Brockstedt S. On the effects of a varied diffusion time in vivo: is the diffusion in white matter restricted? Magn Reson Imaging 2009; 27:176-87. [DOI: 10.1016/j.mri.2008.06.003] [Citation(s) in RCA: 80] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2008] [Revised: 06/04/2008] [Accepted: 06/12/2008] [Indexed: 11/29/2022]
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Alexander DC. A general framework for experiment design in diffusion MRI and its application in measuring direct tissue-microstructure features. Magn Reson Med 2008; 60:439-48. [PMID: 18666109 DOI: 10.1002/mrm.21646] [Citation(s) in RCA: 223] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This article introduces a new and general framework for optimizing the experiment design for diffusion MRI of samples with unknown orientation. An illustration then uses the framework to study the feasibility of measuring direct features of brain-tissue microstructure in vivo. The study investigates the accuracy and precision with which we can estimate potentially important new biomarkers such as axon density and radius in white matter. Simulation experiments use a simple model of white matter based on CHARMED (composite hindered and restricted model of diffusion). The optimization finds acquisition protocols achievable on modern human and animal systems that consist of 120 measurements with fixed maximum gradient strengths. Axon radii in brain tissue are typically in the range 0.25-10 microm. Simulations suggest that estimates of radii in the range 5-10 microm have highest precision and that a maximum gradient strength of 0.07 T m(-1) is sufficient to distinguish radii of 5, 10, and 20 microm. Smaller radii are more difficult to distinguish from one another but are identifiable as small. A maximum gradient strength of 0.2 T m(-1) distinguishes radii of 1 and 2 microm. The simulations also suggest that axon densities and diffusivity parameters in the normal range for white matter are recoverable. The experiment-design optimization has applications well beyond the current work to optimize the protocol for fitting any model of the diffusion process.
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Affiliation(s)
- Daniel C Alexander
- Department of Computer Science, University College London, London, United Kingdom.
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Ronen I, Kim DS. Compartment-specific q-space analysis of diffusion-weighted data from isolated rhesus optic and sciatic nerves. Magn Reson Imaging 2008; 27:531-40. [PMID: 18929454 DOI: 10.1016/j.mri.2008.08.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2008] [Revised: 08/14/2008] [Accepted: 08/29/2008] [Indexed: 12/01/2022]
Abstract
We investigated compartment-specific water diffusion properties in two widely structurally different isolated bovine nerves. Sciatic and optic nerves were immersed in saline containing Gd-DTPA(2+). Consequently, T(1) became non-monoexponential and fit well to a biexponential function. q-Space diffusion data were collected for each component. In the sciatic nerve, the slow-decaying component (T(1s)) was considerably more restricted and directional than the fast-decaying component (T(1f)). In the optic nerve, fractional anisotropy of both components was comparable and similar to that of the total H(2)O signal. The root mean square of the displacement distribution functions of T(1s) correlated well with the widely different axonal diameters of both nerves. Possibly, the source of T(1s) is the intra-axonal compartment and that of T(1f) is associated with the inter-axonal space. The compartment specificity of the method shown makes it useful for the investigation of the contribution of each nerve compartment to diffusion tensor imaging measurements and other diffusion-based methods.
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Affiliation(s)
- Itamar Ronen
- Center for Biomedical Imaging, Boston University School of Medicine, 715 Albany Street, Boston, MA 02118, USA.
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Lätt J, Nilsson M, Rydhög A, Wirestam R, Ståhlberg F, Brockstedt S. Effects of restricted diffusion in a biological phantom: a q-space diffusion MRI study of asparagus stems at a 3T clinical scanner. ACTA ACUST UNITED AC 2007; 20:213-22. [DOI: 10.1007/s10334-007-0085-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2007] [Revised: 08/15/2007] [Accepted: 09/25/2007] [Indexed: 01/12/2023]
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