Investigation and validation for cortical laminar structures of myelin and iron using χ-separation
Poster No:
2139
Submission Type:
Abstract Submission
Authors:
Byeongpil Moon1, Hyeong-Geol Shin2, Jiye Kim3, Sooyeon Ji4, Chungseok Oh5, Jongho Lee4
Institutions:
1Seoul National University, Seoul, Korea, Republic of, 2Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 3Seoul National University, Gwanak-gu, Korea, Republic of, 4Seoul National University, Seoul, Seoul, 5Department of Electrical Computer Engineering, Seoul National University, Seoul, Korea, Republic of
First Author:
Co-Author(s):
Hyeong-Geol Shin
Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
Baltimore, MD
Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
Baltimore, MD
Chungseok Oh
Department of Electrical Computer Engineering, Seoul National University
Seoul, Korea, Republic of
Department of Electrical Computer Engineering, Seoul National University
Seoul, Korea, Republic of
Introduction:
χ-separation(chi-separation) is an advanced quantitative susceptibility mapping method that separate paramagnetic and diamagnetic susceptibility9. Previous studies have confirmed the relationship between iron and paramagnetic susceptibility, and myelin and diamagnetic susceptibility3,4,5,9 respectively, but quantitative layer-wise comparison with ex-vivo histology is yet to be done.
Primary visual cortex (V1) can be distinguished by the presence of Gennari line2,3. The Gennari line exhibits line-shaped distribution where both iron and myelin are more prominent than the surrounding cortex layers. Therefore, these distinctive structures can serve as valuable reference to evaluate the relationship between χ-separation maps and iron and myelin accumulations.
Therefore, this study aims to quantitatively assess how precisely χ-separation can distinguish susceptibility sources by comparing layer-wise profiles in iron-, myelin- stained images and ex-vivo χ-separation maps in the V1 region.
Primary visual cortex (V1) can be distinguished by the presence of Gennari line2,3. The Gennari line exhibits line-shaped distribution where both iron and myelin are more prominent than the surrounding cortex layers. Therefore, these distinctive structures can serve as valuable reference to evaluate the relationship between χ-separation maps and iron and myelin accumulations.
Therefore, this study aims to quantitatively assess how precisely χ-separation can distinguish susceptibility sources by comparing layer-wise profiles in iron-, myelin- stained images and ex-vivo χ-separation maps in the V1 region.
Methods:
An ex-vivo human brain specimen, containing the V1, was scanned9 at 7T MRI (Siemens Terra, Erlangen, Germany). 3D multi-echo gradient-echo and 3D multi-echo spin-echo data were from χ-separation paper data9. χ-separation is conducted using local field1,10, R2*6, and R27 maps which are processed from acquired data. After the MRI scan, specimen was utilized for LFB myelin staining and LA_ICP_MS iron staining9. LFB myelin staining image represents optical density, which have low intensity in myelinated areas, is transformed into absorbance map using the Beer-Bouguer-Lambert law.
V1 ROI is manually segmented using AutoCAD (version 2024, Autodesk Inc.) considering microstructural and macroscopic features2 in χ-separation and staining maps.
Cortex boundaries were defined as follows: Interface between CSF and cortex was defined as outer contour with 0% depth. Border between deepest cortex and the white matter2 was defined as inner contour with 100% depth.
Depth trajectory is defined as a line perpendicular to cortical layers, heading to the white matter. Evenly spaced trajectories are manually drawn along the cortex8. Within the ROIs, there exist 54 depth trajectories.
Additionally, cortical depth-wise points were sampled over each depth trajectory with 5% depth increments. Using depth-wise samples, laminar profile was acquired by averaging intensity at each depth.
Cortical laminar profiles were z-score normalized for quantitative comparison of intermodal differences. Laminar profiles between χpara and iron staining; and χdia and myelin staining were visually assessed and similarity was measured using the mean Euclidean Distance2.
V1 ROI is manually segmented using AutoCAD (version 2024, Autodesk Inc.) considering microstructural and macroscopic features2 in χ-separation and staining maps.
Cortex boundaries were defined as follows: Interface between CSF and cortex was defined as outer contour with 0% depth. Border between deepest cortex and the white matter2 was defined as inner contour with 100% depth.
Depth trajectory is defined as a line perpendicular to cortical layers, heading to the white matter. Evenly spaced trajectories are manually drawn along the cortex8. Within the ROIs, there exist 54 depth trajectories.
Additionally, cortical depth-wise points were sampled over each depth trajectory with 5% depth increments. Using depth-wise samples, laminar profile was acquired by averaging intensity at each depth.
Cortical laminar profiles were z-score normalized for quantitative comparison of intermodal differences. Laminar profiles between χpara and iron staining; and χdia and myelin staining were visually assessed and similarity was measured using the mean Euclidean Distance2.
·Figure 1. Segmentation in χ-separation maps and stained maps.
Results:
Fig. 1 depicts segmented depth-wise points in χ-separation and staining map. Segmented depth-wise points agree well each other. V1 ROI, cortex boundary and depth trajectory are highlighted for detailed explanation.
In Fig. 2, z-score normalized laminar profiles are plotted. χpara and iron staining; χdia and myelin staining display remarkable similarity between two profiles including Gennari line peak at 65% depth. Difference of χparaand iron staining is demonstrated with mean Euclidean distance of 0.357±0.043, while χdia and myelin staining demonstrated higher mean Euclidean distance of 0.909±0.143.
In Fig. 2, z-score normalized laminar profiles are plotted. χpara and iron staining; χdia and myelin staining display remarkable similarity between two profiles including Gennari line peak at 65% depth. Difference of χparaand iron staining is demonstrated with mean Euclidean distance of 0.357±0.043, while χdia and myelin staining demonstrated higher mean Euclidean distance of 0.909±0.143.
·Figure 2. Comparison of laminar profiles of χ-separation maps and histology maps.
Conclusions:
In this study, we investigated the laminar profiles of visual cortex within χ-separation maps and histological maps. The results show that the profiles of iron histology and χpara; myelin histology and χdia coincide throughout the cortex, including a peak at the Gennari line, respectively. Although we performed manual segmentation to maximize alignment of segmented cortical boundaries, the boundaries were less distinct in the iron staining map, potentially resulting in some inconsistencies.
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Cyto- and Myeloarchitecture 1
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Keywords:
Cortex
Cortical Columns
Cortical Layers
MRI
Myelin
Other - quantitative susceptibility mapping
1|2Indicates the priority used for review
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