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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.08711 |
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| _version_ | 1866918492354117632 |
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| author | Khodakarami, Zahra Emrani, Sheina Khandelwal, Pulkit Athalye, Chinmayee Denning, Amanda Trotman, Winifred Levorse, Lisa M Teunissen-Bermeo, Eric Radhakrishnan, Hamsanandini Ohm, Daniel Olm, Christophe Capp, Noah Ittyerah, Ranjit Prabhakaran, Karthik Detre, John A. Das, Sandhitsu R. Wolk, David A. McMillan, Corey T Mizsei, Gabor Tisdall, M. Dylan Irwin, David J Robinson, John L. Lee, Edward B Yushkevich, Paul A. |
| author_facet | Khodakarami, Zahra Emrani, Sheina Khandelwal, Pulkit Athalye, Chinmayee Denning, Amanda Trotman, Winifred Levorse, Lisa M Teunissen-Bermeo, Eric Radhakrishnan, Hamsanandini Ohm, Daniel Olm, Christophe Capp, Noah Ittyerah, Ranjit Prabhakaran, Karthik Detre, John A. Das, Sandhitsu R. Wolk, David A. McMillan, Corey T Mizsei, Gabor Tisdall, M. Dylan Irwin, David J Robinson, John L. Lee, Edward B Yushkevich, Paul A. |
| contents | White matter hyperintensities (WMH) are bright regions on T2-weighted magnetic resonance imaging (MRI) scans and are associated with cerebrovascular pathology and neurodegeneration, including myelin loss. While Luxol Fast Blue histopathology provides visualization of myelin integrity, quantitative analysis requires measuring Optical Density as a proxy for myelin concentration. However, differences in laboratory protocols and tissue processing introduce staining variability that acts as systematic noise, obscuring the biological signal and preventing consistent comparison across histology runs. To address this, we developed an automated pipeline that identifies reference (non-pathologic) regions in whole-slide images to compute normalized Optical Density heatmaps. We validated this approach through two complementary evaluations: (1) comparison against expert ratings of myelin loss severity, and (2) cross-modal spatial comparison with co-registered 7T ex vivo MRI for voxel-wise evaluation within white matter regions. The pipeline's reference selection showed strong concordance with expert-identified reference regions, and normalized Optical Density demonstrated a substantially stronger correlation with MRI signal intensity than raw measurements. This correlation persisted within WMH, confirming that the pipeline captures continuous myelin pathology rather than merely the presence or absence of myelin loss contrast. By mitigating staining artifacts, this pipeline provides a robust, validated framework for quantitative cross-modal comparison, establishing a critical methodological foundation for future translation to in vivo myelin mapping and biomarker discovery. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_08711 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Automated Optical Density Normalization for Myelin Quantification: Cross-Modal Validation with 7T Ex Vivo MRI Khodakarami, Zahra Emrani, Sheina Khandelwal, Pulkit Athalye, Chinmayee Denning, Amanda Trotman, Winifred Levorse, Lisa M Teunissen-Bermeo, Eric Radhakrishnan, Hamsanandini Ohm, Daniel Olm, Christophe Capp, Noah Ittyerah, Ranjit Prabhakaran, Karthik Detre, John A. Das, Sandhitsu R. Wolk, David A. McMillan, Corey T Mizsei, Gabor Tisdall, M. Dylan Irwin, David J Robinson, John L. Lee, Edward B Yushkevich, Paul A. Medical Physics Neurons and Cognition Quantitative Methods I.4.9; I.2.10; J.3 White matter hyperintensities (WMH) are bright regions on T2-weighted magnetic resonance imaging (MRI) scans and are associated with cerebrovascular pathology and neurodegeneration, including myelin loss. While Luxol Fast Blue histopathology provides visualization of myelin integrity, quantitative analysis requires measuring Optical Density as a proxy for myelin concentration. However, differences in laboratory protocols and tissue processing introduce staining variability that acts as systematic noise, obscuring the biological signal and preventing consistent comparison across histology runs. To address this, we developed an automated pipeline that identifies reference (non-pathologic) regions in whole-slide images to compute normalized Optical Density heatmaps. We validated this approach through two complementary evaluations: (1) comparison against expert ratings of myelin loss severity, and (2) cross-modal spatial comparison with co-registered 7T ex vivo MRI for voxel-wise evaluation within white matter regions. The pipeline's reference selection showed strong concordance with expert-identified reference regions, and normalized Optical Density demonstrated a substantially stronger correlation with MRI signal intensity than raw measurements. This correlation persisted within WMH, confirming that the pipeline captures continuous myelin pathology rather than merely the presence or absence of myelin loss contrast. By mitigating staining artifacts, this pipeline provides a robust, validated framework for quantitative cross-modal comparison, establishing a critical methodological foundation for future translation to in vivo myelin mapping and biomarker discovery. |
| title | Automated Optical Density Normalization for Myelin Quantification: Cross-Modal Validation with 7T Ex Vivo MRI |
| topic | Medical Physics Neurons and Cognition Quantitative Methods I.4.9; I.2.10; J.3 |
| url | https://arxiv.org/abs/2605.08711 |