4.5 Article

Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T imaging, and histology

期刊

MAGNETIC RESONANCE IN MEDICINE
卷 88, 期 1, 页码 365-379

出版社

WILEY
DOI: 10.1002/mrm.29174

关键词

diffusion MRI; hepatocyte; histology; liver; microstructure; Monte Carlo simulations

资金

  1. postdoctoral fellowships programme Beatriu de Pinos by the Secretary of Universities and Research (Government of Catalonia) [2020 BP 00117]
  2. Beatriu de Pino's post-doctoral grant [2019 BP 00182]
  3. CRIS Foundation Talent Award [TALENT19-05]
  4. Spanish Ministry for Science, Innovation and Universities [RTI2018-095209-B-C21, FIS--G64384969]
  5. Prostate Cancer Foundation
  6. Fero Foundation
  7. Fundacio la Caixa [100010434]
  8. European Union [847648, LCF/BQ/PI20/1176003]
  9. Fundacio La Caixa
  10. Instituto de Salud Carlos III--Investigacion en Salud [PI18/01395]

向作者/读者索取更多资源

This study investigates the relationship between diffusion-weighted MRI signals and hepatocyte microstructure, and finds that important information about liver cell size and diffusivity can be obtained from minimal diffusion encodings under specific conditions.
Purpose Relationships between diffusion-weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange? Methods Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity L/D0, and clinical protocols (single diffusion encoding; maximum b-value: {1000, 1500, 2000} s/mm(2); 5 unique gradient duration/separation pairs; SNR = {infinity, 100, 80, 40, 20}), accounting for heterogeneity in (D0,L) and perfusion contamination. Diffusion (D) and kurtosis (K) coefficients were calculated, and relationships between (D0,L) and (D,K) were visualized. Functions mapping (D,K) to (D0,L) were computed to predict unseen (D0,L) values, tested for their ability to classify discrete cell-size contrasts, and deployed on 9.4T ex vivo MRI-histology data of fixed mouse livers Results Relationships between (D,K) and (D0,L) are complex and depend on the diffusion encoding. Functions mapping (D,K) to (D0,L) captures salient characteristics of D0(D,K) and L(D,K) dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three-class cell-size classification task (for SNR = 20, bmax = 1500 s/mm(2), delta = 20 ms, and Delta = 75 ms). MRI detects cell-size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes. Conclusion Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible.

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