# Magnetic Susceptibility Source Separation Solely from Gradient Echo Data: Histological Validation

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. MR Signal Modeling for ${R}_{2}^{*}QSM$

#### 2.2. Postmortem Tissue Imaging

^{3}, first TE = 5.9 ms, ΔTE = 5.9 ms, #TE = 8, TR = 52.2 ms, flip angle = 12 degrees, receiver bandwidth (rBW) = 244 Hz/pixel, acquisition time 69 min. For lesion identification, T2 FSE (voxel size = 0.5 × 0.5 × 2 mm

^{3}, TE = 60.3 ms, TR = 6332 ms, flip angle = 111°, rBW = 195 Hz/pixel, number of excitations (NEX) = 12, acquisition time 36 min) was acquired.

#### 2.3. Data Processing

#### 2.4. Immunohistochemistry

#### 2.5. Histology Optical Density Estimation

^{2}) were manually drawn within the lesion and adjacent normal appearing white matter by a reader with 5 years of experience (KG). NAWM ROIs were sampled 0.57 ± 0.24 mm from the outer rim edge in iron− lesions and 1.24 ± 0.52 mm from the outer rim edge in iron+ lesions. For each lesion, we placed 1 ROI in the NAWM, 1 ROI in the rim (lesion perimeter for rim-negative lesions), and 1 ROI in the center. Lesions were defined histologically by the absence of MBP staining in the center. Histology ROIs were captured in Panoramic Viewer (version 1.15.4). Each image was processed in FIJI [16] where color deconvolution was applied to generate three images: hematoxylin, DAB, and residual (grayscale range [0…255]). Mean grey values from the DAB channel were averaged and used to calculate optical density (OD) using the following equation [17]: $\mathit{O}\mathit{D}={\mathbf{log}}_{10}\left(\frac{\mathit{255}}{\mathit{M}\mathit{e}\mathit{a}\mathit{n}\mathit{G}\mathit{r}\mathit{e}\mathit{y}\mathit{V}\mathit{a}\mathit{l}\mathit{u}\mathit{e}}\right)$.

#### 2.6. Statistical Analysis

## 3. Results

#### 3.1. Tissue Composition

**,**and magnitude images and histological stains of MS lesions are shown in Figure 1 and Figure 2. Typical reconstruction ${\mathit{\chi}}^{+/-}$ reconstruction time was 15 min.

#### 3.2. Lesion ROIs

## 4. Discussion

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

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**Figure 1.**Results of the ${\mathit{R}}_{\mathbf{2}}^{*}$-based separation of magnetic sources in a chronic active lesion. Paramagnetic lesion rim readily identifiable in QSM and ${\chi}^{+}$ (yellow dashed line) appears to be in good morphological agreement with the iron distribution revealed by Perls’ staining. Similarly, strong demyelination of the lesion core estimated with the proposed method is well reflected by the MBP staining. NAWM is shown with white dashed line.

**Figure 2.**Example of the ${\mathit{R}}_{\mathbf{2}}^{*}$-based separation of magnetic sources in a chronic silent lesion. The lesion appears to be weakly paramagnetic in the susceptibility map, with the Perls’ and MBP staining suggesting almost complete loss of myelin and partial loss of iron within the lesion ROI. These findings were similarly reflected in the estimated ${\chi}^{+}$ and ${\chi}^{-}$ maps.

**Figure 3.**Correlation analysis between the average lesion/NAWM ROI source susceptibility and corresponding optical density of the histological stains.

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**MDPI and ACS Style**

Dimov, A.V.; Gillen, K.M.; Nguyen, T.D.; Kang, J.; Sharma, R.; Pitt, D.; Gauthier, S.A.; Wang, Y.
Magnetic Susceptibility Source Separation Solely from Gradient Echo Data: Histological Validation. *Tomography* **2022**, *8*, 1544-1551.
https://doi.org/10.3390/tomography8030127

**AMA Style**

Dimov AV, Gillen KM, Nguyen TD, Kang J, Sharma R, Pitt D, Gauthier SA, Wang Y.
Magnetic Susceptibility Source Separation Solely from Gradient Echo Data: Histological Validation. *Tomography*. 2022; 8(3):1544-1551.
https://doi.org/10.3390/tomography8030127

**Chicago/Turabian Style**

Dimov, Alexey V., Kelly M. Gillen, Thanh D. Nguyen, Jerry Kang, Ria Sharma, David Pitt, Susan A. Gauthier, and Yi Wang.
2022. "Magnetic Susceptibility Source Separation Solely from Gradient Echo Data: Histological Validation" *Tomography* 8, no. 3: 1544-1551.
https://doi.org/10.3390/tomography8030127