Coregistered histology sections with diffusion tensor imaging data at 200 µm resolution in meningioma tumors DOI Creative Commons
Jan Brabec, Elisabet Englund, Johan Bengzon

et al.

Data in Brief, Journal Year: 2023, Volume and Issue: 48, P. 109261 - 109261

Published: May 23, 2023

A significant problem in diffusion MRI (dMRI) is the lack of understanding regarding which microstructural features account for variability tensor imaging (DTI) parameters observed meningioma tumors. common assumption that mean diffusivity (MD) and fractional anisotropy (FA) from DTI are inversely proportional to cell density tissue anisotropy, respectively. Although these associations have been established across a wide range tumors, they challenged interpreting within-tumor variations where several additional suggested as contributing MD FA. To facilitate investigation biological underpinnings parameters, we performed ex-vivo at 200 µm isotropic resolution on sixteen excised tumor samples. The samples exhibit variety because dataset includes meningiomas six different types two grades. Diffusion-weighted signal (DWI) maps, DWI maps averaged over all directions given b-value, intensities without encoding (S0) well parameters: MD, FA, in-plane FA (FAIP), axial (AD) radial (RD), were coregistered Hematoxylin & Eosin- (H&E) Elastica van Gieson-stained (EVG) histological sections by non-linear landmark-based approach. Here, provide histology describe pipeline processing raw data coregistration. raw, processed, hosted Analytic Imaging Diagnostics Arena (AIDA) hub registry, software tools provided via GitHub. We hope can be used research education concerning link between microstructure obtained DTI.

Language: Английский

Advanced Diffusion‐Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology DOI
Ella P. Fokkinga,

Juan A. Hernández‐Tamames,

Andrada Ianuş

et al.

Journal of Magnetic Resonance Imaging, Journal Year: 2023, Volume and Issue: 60(4), P. 1278 - 1304

Published: Nov. 30, 2023

Diffusion‐weighted magnetic resonance imaging (DW‐MRI) aims to disentangle multiple biological signal sources in each voxel, enabling the computation of innovative maps tissue microstructure. DW‐MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity histology are gaining momentum other contexts, for example, oncological applications body imaging, where new biomarkers urgently needed. The objective this article is review state‐of‐the‐art (ie, not including nervous system) oncology, and analyze its value as compared reference colocalized measurements, given that demonstrating histological validity any method essential. In article, we current landscape techniques extend standard apparent diffusion coefficient (ADC), describing their acquisition protocols, models, fitting settings, microstructural parameters, relationship histology. Preclinical, clinical, in/ex vivo studies were included. most used intravoxel incoherent motion (IVIM; 36.3% techniques), kurtosis (DKI; 16.7%), vascular, extracellular, restricted cytometry tumors (VERDICT; 13.3%), parameters using limited spectrally edited (IMPULSED; 11.7%). Another notable category relates b ‐tensor encoding or joint diffusion‐relaxometry. reviewed approaches provide histologically meaningful indices cancer microstructure (eg, vascularization/cellularity) which, while necessarily accurate numerically, may still useful sensitivity microscopic pathological processes. Future work community should focus on improving inter‐/intra‐scanner robustness, assessing broader contexts. Level Evidence NA Technical Efficacy Stage 2

Language: Английский

Citations

13
Diffusion MRI with double diffusion encoding and variable mixing times disentangles water exchange from transient kurtosis DOI Creative Commons
Arthur Chakwizira, Filip Szczepankiewicz, Markus Nilsson

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 13, 2025

Abstract Double diffusion encoding (DDE) makes MRI sensitive to a wide range of microstructural features, and the acquired data can be analysed using different approaches. Correlation tensor imaging (CTI) uses DDE resolve three components diffusional kurtosis: isotropic, anisotropic, microscopic kurtosis. The kurtosis is estimated from contrast between single (SDE) parallel signals at same b-value. Another approach multi-Gaussian exchange (MGE), which employs measure exchange. Sensitivity obtained by contrasting SDE CTI MGE exploit signal quantify exchange, this study investigates interplay these two quantities. We perform Monte Carlo simulations in geometries with varying levels behaviour parameters MGE. conclude that rate intercompartmental transient individual compartments are distinct sources In an attempt disentangle sources, we propose heuristic representation referred as tMGE (MGE incorporating kurtosis) accounts for both effects exploiting signatures mixing time: causes slow dependence on time while arguably has much faster dependence. find applying multiple times orthogonal may enable estimation well

Language: Английский

Citations

0
Layer‐Dependent Effect of Aβ‐Pathology on Cortical Microstructure With Ex Vivo Human Brain Diffusion MRI at 7 Tesla DOI Creative Commons
Zhiyong Zhao, Zuozhen Cao, Qinfeng Zhu

et al.

Human Brain Mapping, Journal Year: 2025, Volume and Issue: 46(7)

Published: May 1, 2025

ABSTRACT The laminar‐specific distributions of Aβ and Tau deposition in the neocortex Alzheimer's disease (AD) have been established. However, direct evidence about effect AD pathology on cortical microstructure is lacking human studies. We performed high‐resolution T2‐weighted diffusion‐weighted MRI (dMRI) 15 ex vivo whole‐hemisphere specimens, including eight cases with low neuropathologic change, three primary age‐related tauopathy (PART), four healthy controls (HCs). Using diffusion tensor model, we evaluated patterns six layers gray matter cortex MRI‐histology correlation analysis across layers. Aβ‐positive exhibited higher diffusivity than Aβ‐negative (PART HC) selected regions, particularly inferior frontal cortex. Both Aβ/Tau depositions dMRI‐based microstructural markers demonstrated distinct layer‐dependent region‐specific patterns. A significant positive was observed between increased burden but not burden. Furthermore, mean layer V significantly Amyloid stage. Our findings demonstrate a brain, which may be used to serve as marker change.

Language: Английский

Citations

0
Layer-dependent effect of Aβ-pathology on cortical microstructure with ex-vivo human brain diffusion MRI at 7 Tesla DOI Creative Commons
Zhiyong Zhao, Zuozhen Cao, Qinfeng Zhu

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 8, 2023

Abstract Background The laminar-specific distributions of Aβ and Tau deposition in the neocortex Alzheimer’s disease (AD) have been established. However, direct evidence about effect AD pathology on cortical microstructure is lacking human studies. Methods We performed high-resolution T2-weighted diffusion-weighted MRI (dMRI) fifteen ex-vivo whole-hemisphere specimens, including eight cases with an pathology, three primary age-related tauopathy (PART) four healthy controls (HCs). Using diffusion tensor model, we evaluated patterns six layers grey matter cortex MRI-histology correlation analysis across layers. Results Aβ-positive exhibited higher diffusivity than Aβ-negative (PART HC) selected regions, particularly inferior frontal cortex. Both Aβ/Tau depositions dMRI-based microstructural markers demonstrated distinct layer-dependent region-specific patterns. A significant positive was observed between increased burden layers, but not burden. Furthermore, mean layer-V significantly Amyloid stage. Conclusion Our findings demonstrate a Aβ-pathology brain, which may be used to serve as early pathology.

Language: Английский

Citations

1
The interplay between exchange and microscopic kurtosis as measured by diffusion MRI with double diffusion encoding: Theory and simulations DOI Creative Commons
Arthur Chakwizira, Filip Szczepankiewicz, Markus Nilsson

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 29, 2024

Abstract Double diffusion encoding (DDE) makes MRI sensitive to a wide range of microstructural features, and the acquired data can be analysed using different approaches. Correlation tensor imaging (CTI) uses DDE resolve three components diffusional kurtosis: isotropic, anisotropic, microscopic. The microscopic kurtosis is estimated from contrast between single (SDE) parallel signals at same b-value. Another approach multi-Gaussian exchange (MGE), which employs measure exchange. Sensitivity obtained by contrasting SDE CTI MGE exploit signal quantify exchange, this study investigates interplay these two quantities. We perform Monte-Carlo simulations in geometries with varying levels behaviour parameters MGE. conclude that rate. In an attempt separate we propose heuristic representation referred as µMGE (MGE incorporating kurtosis) accounts for both effects, exploiting distinct signatures mixing time: causes dependence on time while does not. find applying multiple times orthogonal allows estimation well all sources kurtosis.

Language: Английский

Citations

0
Coregistered histology sections with diffusion tensor imaging data at 200 µm resolution in meningioma tumors DOI Creative Commons
Jan Brabec, Elisabet Englund, Johan Bengzon

et al.

Data in Brief, Journal Year: 2023, Volume and Issue: 48, P. 109261 - 109261

Published: May 23, 2023

A significant problem in diffusion MRI (dMRI) is the lack of understanding regarding which microstructural features account for variability tensor imaging (DTI) parameters observed meningioma tumors. common assumption that mean diffusivity (MD) and fractional anisotropy (FA) from DTI are inversely proportional to cell density tissue anisotropy, respectively. Although these associations have been established across a wide range tumors, they challenged interpreting within-tumor variations where several additional suggested as contributing MD FA. To facilitate investigation biological underpinnings parameters, we performed ex-vivo at 200 µm isotropic resolution on sixteen excised tumor samples. The samples exhibit variety because dataset includes meningiomas six different types two grades. Diffusion-weighted signal (DWI) maps, DWI maps averaged over all directions given b-value, intensities without encoding (S0) well parameters: MD, FA, in-plane FA (FAIP), axial (AD) radial (RD), were coregistered Hematoxylin & Eosin- (H&E) Elastica van Gieson-stained (EVG) histological sections by non-linear landmark-based approach. Here, provide histology describe pipeline processing raw data coregistration. raw, processed, hosted Analytic Imaging Diagnostics Arena (AIDA) hub registry, software tools provided via GitHub. We hope can be used research education concerning link between microstructure obtained DTI.

Language: Английский

Citations

0