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Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology

Fokkinga, Ella ; Hernandez-Tamames, Juan A. ; Ianus, Andrada ; Nilsson, Markus LU ; Tax, Chantal M.W. ; Perez-Lopez, Raquel and Grussu, Francesco (2023) In Journal of Magnetic Resonance Imaging
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... (More)

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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type
Contribution to journal
publication status
epub
subject
keywords
body, cancer, diffusion-weighted magnetic resonance imaging, histology, microstructure
in
Journal of Magnetic Resonance Imaging
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:38032021
  • scopus:85178189454
ISSN
1053-1807
DOI
10.1002/jmri.29144
language
English
LU publication?
yes
additional info
Funding Information: FG receives the support of a fellowship from “la Caixa” Foundation (ID 100010434). The fellowship code is LCF/BQ/PR22/11920010. RP‐L is supported by “laCaixa” Foundation, a CRIS Foundation Talent Award (TALENT 1905), the FERO Foundation, the Instituto de Salud Carlos III‐Investigacion en Salud (PI18/01395 and PI21/01019), the Prostate Cancer Foundation (18YOUN19), and the Asociación Española Contra el Cáncer (AECC) (PRYCO211023SERR). AI is supported by “la Caixa” Foundation (ID 100010434) and European Union's Horizon 2020 Research and Innovation Program (Marie Skłodowska‐Curie grant No. 847648), fellowship code LCF/BQ/PI20/11760029. CMWT was supported by a Veni grant (17331) from the Dutch Research Council (NWO) and a Sir Henry Wellcome Fellowship (215944/Z/19/Z). MN is supported by the Swedish Research Council (2020‐04549), the Cancer Foundation (2022/2414), and ALF. This research was funded in whole, or in part, by the Wellcome Trust (Grant number 215944/Z/19/Z). For the purpose of open access, the author has applied a CC BY public copyright license to any author accepted manuscript version arising from this submission. Publisher Copyright: © 2023 International Society for Magnetic Resonance in Medicine.
id
f24886d0-2bdc-4cab-875d-2e31e5ad99d0
date added to LUP
2024-01-10 10:49:28
date last changed
2024-04-25 06:48:05
@article{f24886d0-2bdc-4cab-875d-2e31e5ad99d0,
  abstract     = {{<p>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.</p>}},
  author       = {{Fokkinga, Ella and Hernandez-Tamames, Juan A. and Ianus, Andrada and Nilsson, Markus and Tax, Chantal M.W. and Perez-Lopez, Raquel and Grussu, Francesco}},
  issn         = {{1053-1807}},
  keywords     = {{body; cancer; diffusion-weighted magnetic resonance imaging; histology; microstructure}},
  language     = {{eng}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Journal of Magnetic Resonance Imaging}},
  title        = {{Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology}},
  url          = {{http://dx.doi.org/10.1002/jmri.29144}},
  doi          = {{10.1002/jmri.29144}},
  year         = {{2023}},
}