A framework for optimal whole-sample histological quantification of neurite orientation dispersion in the human spinal cord
Open accessAbstract
BACKGROUND: The complexity of fibre distributions in tissues is an important microstructural feature, now measurable in vivo by magnetic resonance imaging (MRI) through orientation dispersion (OD) indices. OD metrics have gained popularity for the characterisation of neurite morphology, but they still lack systematic validation. This paper demonstrates a framework for whole-sample histological quantification of OD in spinal cord specimens, potentially useful for validating MRI-derived OD estimates. NEW METHOD: Our methodological framework is based on (i) sagittal sectioning; (ii) Palmgren's silver staining; (iii) structure tensor (ST) analysis; (iv) directional statistics. Novel elements are the data-driven optimisation of the spatial scale of ST analysis, and a new multivariate, weighted directional statistical approach for anisotropy-informed quantification of OD. RESULTS: Palmgren's silver staining of sagittal spinal cord sections provides robust visualisation of neuronal elements, enabling OD quantification. The choice of spatial scale of ST analysis influences OD values, and weighted directional statistics provide OD maps with high contrast-to-noise. Segmentation of neurites prior to OD quantification is recommended. COMPARISON WITH EXISTING METHODS: Our framework can potentially provide OD even in demyelinating diseases, where myelin-based histology is not suitable. As compared to conventional univariate approaches, our multivariate weighted directional statistics improve the contrast-to-noise of OD maps and more accurately describe the distribution of ST metrics. CONCLUSIONS: Our framework enables practical whole-specimen characterisation of OD in the spinal cord. We recommend tuning the scale of ST analysis for optimal OD quantification, as well as neurite segmentation and weighted directional statistics, of which examples are provided herein.
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Areas of nonspecific staining were excluded with a combination of manual and automatic segmentation to calculate CV.
“excluded areas of nonspecific staining with a combination of manual and automatic segmentation to calculate CV, given their potential to bias this metric.33”
From Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? (2017) · cites this paper as [33]
Section 2.2.3 says the authors manually masked areas with large vessels and concentrations of neuronal cell bodies. Sections 2.3 and 4.7 describe automated neurite segmentation used to assess CV while excluding non-neurite pixels, but section 4.7 presents automatic removal of nonspecifically stained areas as a future improvement—not something the study did. (LLM, conf=0.88)
Experimental — accuracy not yet measuredNeurite orientation dispersion is a marker of microstructural pathology, as it detects trends of reduced geometrical complexity of neurite architecture within multiple sclerosis lesions.
“Through the combination of state‐of‐the‐art histology33 and post mortem NODDI26, 27 MRI, we show for the first time that neurite orientation dispersion is a marker of microstructural pathology, as it detects trends of reduced geometrical complexity of neurite architecture within multiple sclerosis lesions.”
From Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? (2017) · cites this paper as [33]
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Cites
NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain
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Self-citationAxonal loss in multiple sclerosis: a pathological survey of the corticospinal and sensory tracts
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Self-citationHistological validation of high-resolution DTI in human post mortem tissue
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Neurite orientation dispersion and density imaging of the healthy cervical spinal cord in vivo
Grussu, F., Schneider, T., Zhang, H., Alexander, D. C., & Wheeler–Kingshott, C. A. M. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.045 · Cited by 118 · see citing works
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Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?
Grussu, F., Schneider, T., Tur, C., Yates, R. L., Tachrount, M., Ianuş, A., Yiannakas, M. C., Newcombe, J., Zhang, H., Alexander, D. C., et al. (2017) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.445 · Cited by 291 · see citing works
“We verified that histological section thickness did not vary between lesional and nonlesional tissue (data not shown) and excluded areas of nonspecific staining with a combination of manual and automatic segmentation to calculate CV, given their potential to bias this metric.(33)”
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- Authors
- Grussu, F., Schneider, T., Yates, R. L., Zhang, H., Wheeler-Kingshott, C. A. M. G., DeLuca, G. C., & Alexander, D. C.
- Affiliations
- National Hospital for Neurology and Neurosurgery (GB)
- University of Oxford (GB)
- University College London (GB)
- Corresponding author
- Grussu, Francesco
- ORCID
- Venue
- Journal of Neuroscience Methods
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 273
- Pages
- 20-32
- ISSN
- 0165-0270 (ISSN-L)
- OpenAlex
- W2478162388
- Cited by
- 26
- References
- 4
- Citations by year
- 2024: 2 · 2023: 3 · 2022: 3 · 2021: 2 · 2019: 5 · 2018: 6 · 2017: 4 · 2016: 1
- FWCI
- 4.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience Methods (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Institute for Health and Care Research (D 03/10/RAG0449)
- University College London Hospitals NHS Foundation Trust
- Horizon 2020 Framework Programme (634541)
- Medical Research Council (MR/M009106/1, MR/L022656/1)
- Engineering and Physical Sciences Research Council (EP/L022680/1, EP/M020533/1, EP/N018702/1, EP/G007748/1, 634541, EP/M00855X/1, G007748, EP/I027084/1, EP/M029778/1, H2020-EU.3.1, I027084, 1023513, M020533)
- UCLH Biomedical Research Centre
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- neurite orientation dispersion, spinal cord, histological quantification, structure tensor analysis, demyelinating disease, MRI validation, anisotropy
- MeSH terms
- Aged, Female, Humans, Image Processing, Computer-Assisted, Male, Spinal Cord, Neurites, Silver Staining, Anisotropy, Diffusion Tensor Imaging, Optical Imaging
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