Tensor‐valued diffusion MRI in under 3 minutes: an initial survey of microscopic anisotropy and tissue heterogeneity in intracranial tumors

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Abstract

Purpose

To evaluate the feasibility of a 3‐minutes protocol for assessment of the microscopic anisotropy and tissue heterogeneity based on tensor‐valued diffusion MRI in a wide range of intracranial tumors.

Methods

B‐tensor encoding was performed in 42 patients with intracranial tumors (gliomas, meningiomas, adenomas, and metastases). Microscopic anisotropy and tissue heterogeneity were evaluated by estimating the anisotropic kurtosis (MK _A) and isotropic kurtosis (MK _I), respectively. An extensive imaging protocol was compared with a 3‐minutes protocol.

Results

The fast imaging protocol yielded parameters with characteristics in terms of bias and precision similar to the full protocol. Glioblastomas had lower microscopic anisotropy than meningiomas (MK _A = 0.29 ± 0.06 vs. 0.45 ± 0.08, P = 0.003). Metastases had higher tissue heterogeneity (MK _I = 0.57 ± 0.07) than both the glioblastomas (0.44 ± 0.06, P < 0.001) and meningiomas (0.46 ± 0.06, P = 0.03).

Conclusion

Evaluation of the microscopic anisotropy and tissue heterogeneity in intracranial tumor patients is feasible in clinically relevant times frames.

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Most cited references 57

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Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-Dependent Field Gradient

E. O. Stejskal, J. E. Tanner (1965)

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Determination of the appropriate b value and number of gradient directions for high-angular-resolution diffusion-weighted imaging.

Fernando Calamante, Alan Connelly, Jacques-Donald Tournier (2013)

High-angular-resolution diffusion-weighted imaging (HARDI) is one of the most common MRI acquisition schemes for use with higher order models of diffusion. However, the optimal b value and number of diffusion-weighted (DW) directions for HARDI are still undetermined, primarily as a result of the large number of available reconstruction methods and corresponding parameters, making it impossible to identify a single criterion by which to assess performance. In this study, we estimate the minimum number of DW directions and optimal b values required for HARDI by focusing on the angular frequency content of the DW signal itself. The spherical harmonic (SH) series provides the spherical analogue of the Fourier series, and can hence be used to examine the angular frequency content of the DW signal. Using high-quality data acquired along 500 directions over a range of b values, we estimate that SH terms above l = 8 are negligible in practice for b values up to 5000 s/mm(2), implying that a minimum of 45 DW directions is sufficient to fully characterise the DW signal. l > 0 SH terms were found to increase as a function of b value, levelling off at b = 3000 s/mm(2), suggesting that this value already provides the highest achievable angular resolution. In practice, it is recommended to acquire more than the minimum of 45 DW directions to avoid issues with imperfections in the uniformity of the DW gradient directions and to meet signal-to-noise requirements of the intended reconstruction method. Copyright © 2013 John Wiley & Sons, Ltd.

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Q-space trajectory imaging for multidimensional diffusion MRI of the human brain.

Carl-Fredrik Westin, Hans Knutsson, Ofer Pasternak … (2016)

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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Author and article information

Contributors

Markus Nilsson:

ORCID: https://orcid.org/0000-0002-3140-8223

markus.nilsson@med.lu.se , https://twitter.com/@m_nilsson

Journal

Journal ID (nlm-ta): Magn Reson Med

Journal ID (iso-abbrev): Magn Reson Med

Journal ID (doi): 10.1002/(ISSN)1522-2594

Journal ID (publisher-id): MRM

Title: Magnetic Resonance in Medicine

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Print): 0740-3194

ISSN (Electronic): 1522-2594

Publication date (Electronic): 13 September 2019

Publication date (Print): February 2020

Volume: 83

Issue: 2 ( doiID: 10.1002/mrm.v83.2 )

Pages: 608-620

Affiliations

[ ¹ ] Department of Clinical Sciences Lund, Radiology Lund University Lund Sweden

[ ² ] Brigham and Women's Hospital Harvard Medical School Boston Massachusetts

[ ³ ] Department of Clinical Sciences Lund, Medical Radiation Physics Lund University Lund Sweden

[ ⁴ ] Lund University Bioimaging Center (LBIC) Lund University Lund Sweden

Author notes

[*] [* ] Correspondence

Markus Nilsson, Clinical Sciences Lund, Radiology, Lund University, Sweden.

Email: markus.nilsson@ 123456med.lu.se

Twitter: https://twitter.com/@m_nilsson

Author information

Markus Nilsson https://orcid.org/0000-0002-3140-8223

Filip Szczepankiewicz https://orcid.org/0000-0002-5251-587X

Article

Publisher ID: MRM27959

DOI: 10.1002/mrm.27959

PMC ID: 6900060

PubMed ID: 31517401

SO-VID: 6b50271e-5d9d-4160-a2e6-a11d92369a1e

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

History

Date received : 22 February 2019

Date revision received : 05 July 2019

Date accepted : 30 July 2019

Page count

Figures: 6, Tables: 0, Pages: 13, Words: 16706

Funding

Funded by: Swedish Research Council , open-funder-registry 10.13039/501100004359;

Award ID: 2016‐03443

Award ID: 2016‐02199‐3

Funded by: Swedish Cancer Society , open-funder-registry 10.13039/501100002794;

Award ID: CAN 2016/365

Funded by: Crafoord Foundation , open-funder-registry 10.13039/501100003173;

Award ID: 20160990

Funded by: Random Walk Imaging AB

Award ID: MN15

Custom metadata

source-schema-version-number 2.0

cover-date February 2020

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.2 mode:remove_FC converted:05.12.2019

ScienceOpen disciplines: Radiology & Imaging

Keywords: diffusion mri,microscopic anisotropy,tumor heterogeneity

Data availability:

ScienceOpen disciplines: Radiology & Imaging

Keywords: diffusion mri, microscopic anisotropy, tumor heterogeneity

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Tensor‐valued diffusion MRI in under 3 minutes: an initial survey of microscopic anisotropy and tissue heterogeneity in intracranial tumors

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Most cited references 57

Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-Dependent Field Gradient

Determination of the appropriate b value and number of gradient directions for high-angular-resolution diffusion-weighted imaging.

Q-space trajectory imaging for multidimensional diffusion MRI of the human brain.

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