Resolution limit of cylinder diameter estimation by diffusion MRI: The impact of gradient waveform and orientation dispersion

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. I...

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Published inNMR in biomedicine Vol. 30; no. 7
Main Authors Nilsson, Markus, Lasič, Samo, Drobnjak, Ivana, Topgaard, Daniel, Westin, Carl‐Fredrik
Format Journal Article
LanguageEnglish
Published England Wiley Subscription Services, Inc 01.07.2017
John Wiley and Sons Inc
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Online AccessGet full text
ISSN0952-3480
1099-1492
1099-1492
DOI10.1002/nbm.3711

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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. Accurate quantification of the axon diameter demands strong gradients and can thus be challenging for clinical MRI scanners. We define the resolution limit as the lower bound for accurate diameter estimation and predict its value for diffusion encoding techniques that go beyond the conventional single diffusion encoding sequence. In standard clinical MRI scanners (maximum gradient strength 60‐80 mT/m), the resolution limit was found to be between 4 and 8 μm, depending on noise levels and the level of orientation dispersion.
AbstractList 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 60-80mT/m) was found to be between 4 and 8μm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300mT/m, the limit was reduced to between 2 and 5μm.
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.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.
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, wave-forms were optimised to minimise the resolution limit. There sults 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 60-80mT/m) was found to be between 4 and 8 mu m, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300mT/m, the limit was reduced to between 2 and 5 mu m.
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.
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 60-80mT/m) was found to be between 4 and 8µm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300mT/m, the limit was reduced to between 2 and 5µm.
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. Accurate quantification of the axon diameter demands strong gradients and can thus be challenging for clinical MRI scanners. We define the resolution limit as the lower bound for accurate diameter estimation and predict its value for diffusion encoding techniques that go beyond the conventional single diffusion encoding sequence. In standard clinical MRI scanners (maximum gradient strength 60‐80 mT/m), the resolution limit was found to be between 4 and 8 μm, depending on noise levels and the level of orientation dispersion.
Author Nilsson, Markus
Topgaard, Daniel
Drobnjak, Ivana
Lasič, Samo
Westin, Carl‐Fredrik
AuthorAffiliation 5 Department of Biomedical Engineering Linköping University Linköping Sweden
4 Division of Physical Chemistry, Department of Chemistry Lund University Lund Sweden
3 University College London London UK
6 Brigham and Women's Hospital Harvard Medical School Boston MA USA
1 Clinical Sciences Lund, Department of Radiology Lund University Lund Sweden
2 CR Development AB Lund Sweden
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– name: 5 Department of Biomedical Engineering Linköping University Linköping Sweden
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Copyright Copyright © 2017 The Authors. Published by John Wiley & Sons Ltd.
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CorporateAuthor Multidimensional microstructure imaging
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Issue 7
Keywords resolution limit
microstructure
single diffusion encoding
oscillating diffusion encoding
q-trajectory encoding
diffusion imaging
Axon diameter
double diffusion encoding
Language English
License Attribution-NonCommercial
http://creativecommons.org/licenses/by-nc/4.0
Copyright © 2017 The Authors. NMR in Biomedicine Published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
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Snippet Diffusion MRI has been proposed as a non‐invasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong...
Diffusion MRI has been proposed as a non-invasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong...
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SourceType Open Access Repository
Aggregation Database
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Enrichment Source
Publisher
SubjectTerms Algorithms
Anisotropy
Axon diameter
Axons
Axons - ultrastructure
Biological products
Clinical Medicine
Computer Simulation
Cylinders
Diffusion
diffusion imaging
Diffusion Tensor Imaging - methods
double diffusion encoding
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Klinisk medicin
Lower bounds
Magnetic Fields
Magnetic resonance imaging
Mapping
Medical and Health Sciences
Medicin och hälsovetenskap
microstructure
Models, Anatomic
Models, Neurological
Noise levels
Orientation
oscillating diffusion encoding
q‐trajectory encoding
Radiation Dosage
Radiologi och bildbehandling
Radiology and Medical Imaging
Reproducibility of Results
resolution limit
Scanners
Sensitivity and Specificity
Signal-To-Noise Ratio
single diffusion encoding
Waveforms
White Matter - cytology
White Matter - diagnostic imaging
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Title Resolution limit of cylinder diameter estimation by diffusion MRI: The impact of gradient waveform and orientation dispersion
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fnbm.3711
https://www.ncbi.nlm.nih.gov/pubmed/28318071
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https://www.proquest.com/docview/1879191108
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