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Layer‐Dependent Effect of Aβ‐Pathology on Cortical Microstructure With Ex Vivo Human Brain Diffusion MRI at 7 Tesla

Zhao, Zhiyong, Cao, Zuozhen, Zhu, Qinfeng, Xu, Haoan, Li, Sihui, Zhu, Liangying, Xu, Guojun, Zhu, Keqing, Zhang, Jing, Wu, Dan·2025·Human Brain Mapping
DOI 10.1002/hbm.70222PMC PMC12046383
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Abstract

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

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FIGURE 1 The pipeline of data processing. (1) and (2) represent segmentation of GM/WM and cortical layers in T2‐weighted image, respectively; (3) represents the calculation of diffusion measures; (4) shows averaged values of each dMRI metric in each layer; (5–8) represent the color deconvolution, Moment thresholding, laminar segmentation and averaged values of histological measures at each layer, respectively; (9) shows the correlations between dMRI and histology. AD, axial diffusivity; FA, fractional anisotropy; MD, mean diffusivity; RD, radial diffusivity.
FIGURE 1 The pipeline of data processing. (1) and (2) represent segmentation of GM/WM and cortical layers in T2‐weighted image, respectively; (3) represents the calculation of diffusion measures; (4) shows averaged values of each dMRI metric in each layer; (5–8) represent the color deconvolution, Moment thresholding, laminar segmentation and averaged values of histological measures at each layer, respectively; (9) shows the correlations between dMRI and histology. AD, axial diffusivity; FA, fractional anisotropy; MD, mean diffusivity; RD, radial diffusivity.CC BY · PubMed Central
FIGURE 2 The display of GM‐WM and cortical layer segmentations in three slices of one case across sagittal, coronal, and axial views, respectively. The six cortical layers of GM cortex are shown, excluding the innermost and outermost laminae from eight equidistant laminae.
FIGURE 2 The display of GM‐WM and cortical layer segmentations in three slices of one case across sagittal, coronal, and axial views, respectively. The six cortical layers of GM cortex are shown, excluding the innermost and outermost laminae from eight equidistant laminae.CC BY · PubMed Central
FIGURE 3 (A) Microstructural maps of the neocortex of the entire hemisphere and averaged values in each cortical layer and (B) layer‐dependent changes of dMRI measurements in different parcels (with different color lines) of one HC sample. From the pial to WM surface, FA and diffusivity show a gradual increase and decrease, respectively. Note that similar patterns were also observed in the other three HC samples, which are shown in the Supporting Information. The mFA, mMD, mAD, and mRD represent FA, MD, AD (axial diffusivity), and RD values in each parcel divided by the mean value of the entire cortex to minimize the individual differences.
FIGURE 3 (A) Microstructural maps of the neocortex of the entire hemisphere and averaged values in each cortical layer and (B) layer‐dependent changes of dMRI measurements in different parcels (with different color lines) of one HC sample. From the pial to WM surface, FA and diffusivity show a gradual increase and decrease, respectively. Note that similar patterns were also observed in the other three HC samples, which are shown in the Supporting Information. The mFA, mMD, mAD, and mRD represent FA, MD, AD (axial diffusivity), and RD values in each parcel divided by the mean value of the entire cortex to minimize the individual differences.CC BY · PubMed Central
FIGURE 4 (A) Comparisons of layer‐dependent and region‐specific MD values among three groups in several ROIs and (B) a positive correlation between MD in layer IV of the opercular areas of the inferior frontal cortex and Amyloid stage. In the B panel, each dot represents a PART or AD subject, and the mMD label of the y‐axis represents the MD value in each parcel divided by the mean value of the entire cortex. IFJa, a subdivision of the inferior frontal sulcus; PH, parahippocampal areas; FOP3/4, frontal opercular area 3/4.
FIGURE 4 (A) Comparisons of layer‐dependent and region‐specific MD values among three groups in several ROIs and (B) a positive correlation between MD in layer IV of the opercular areas of the inferior frontal cortex and Amyloid stage. In the B panel, each dot represents a PART or AD subject, and the mMD label of the y‐axis represents the MD value in each parcel divided by the mean value of the entire cortex. IFJa, a subdivision of the inferior frontal sulcus; PH, parahippocampal areas; FOP3/4, frontal opercular area 3/4.CC BY · PubMed Central
FIGURE 5 The relationship between dMRI measurements and Aβ/Tau density across six cortical layers in two Aβ‐positive (ad1/3) and one PART (PART3) samples. (A) Shows manual matching of MR sections with histological images; regions within red circles in the MRI are most similar to histological images. (B, C) display changes in dMRI indices and Aβ/Tau density with cortical layers from the pial surface to WM, respectively. (D) Shows correlations between ΔMD (difference between the MD in a layer in the patient and corresponding MD in that layer in the matched HC; paired cases: ad1‐HC3, ad3‐HC2 and PART3‐HC2) and Aβ/Tau density across six cortical layers. Here we hypothesized that the dMRI changes in patients, compared to normal controls, reflect microstructural impairments attributable to pathological protein burdens.
FIGURE 5 The relationship between dMRI measurements and Aβ/Tau density across six cortical layers in two Aβ‐positive (ad1/3) and one PART (PART3) samples. (A) Shows manual matching of MR sections with histological images; regions within red circles in the MRI are most similar to histological images. (B, C) display changes in dMRI indices and Aβ/Tau density with cortical layers from the pial surface to WM, respectively. (D) Shows correlations between ΔMD (difference between the MD in a layer in the patient and corresponding MD in that layer in the matched HC; paired cases: ad1‐HC3, ad3‐HC2 and PART3‐HC2) and Aβ/Tau density across six cortical layers. Here we hypothesized that the dMRI changes in patients, compared to normal controls, reflect microstructural impairments attributable to pathological protein burdens.CC BY · PubMed Central

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Metadata

Authors
Zhao, Z., Cao, Z., Zhu, Q., Xu, H., Li, S., Zhu, L., Xu, G., Zhu, K., Zhang, J., & Wu, D.
Affiliations
  • Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China
  • Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering College of Biomedical Engineering & Instrument Science, Zhejiang University Hangzhou China
  • National Human Brain Bank for Health and Disease Zhejiang University Hangzhou China
ORCID
Venue
Human Brain Mapping
Publisher
Wiley
Published
2025-05
Volume
46
Issue
7
ISSN
  • 1065-9471
  • 1097-0193
DOI
10.1002/hbm.70222
PMC
PMC12046383
Cited by
8
References
16
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor, 1 d)
Funders
  • National Natural Science Foundation of China (81971184, 81971606, 82122032)
  • Science and Technology Department of Zhejiang Province (202006140, 2022C03057)

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CoChat. (2026). Citation check: Layer‐Dependent Effect of Aβ‐Pathology on Cortical Microstructure With Ex Vivo Human Brain Diffusion MRI at 7 Tesla. https://app.cochat.ai/papers/10.1002/hbm.70222
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Zhao, Z., Cao, Z., Zhu, Q., Xu, H., Li, S., Zhu, L., Xu, G., Zhu, K., Zhang, J., & Wu, D. (2025). Layer‐Dependent Effect of Aβ‐Pathology on Cortical Microstructure With Ex Vivo Human Brain Diffusion MRI at 7 Tesla. Human Brain Mapping. https://doi.org/10.1002/hbm.70222