Insights and improvements in correspondence between axonal volume fraction measured with diffusion‐weighted MRI and electron microscopy
Year: 2023
Type: article
Abstract: Biophysical diffusion‐weighted imaging (DWI) models are increasingly used in neuroscience to estimate the axonal water fraction ( ), which in turn is key for noninvasive estimation of the axonal volume fraction ( ). These models require thorough validation by comparison with a reference method, for example, electron microscopy (EM). While EM studies often neglect the unmyelinated axons and solely report the fraction of myelinated axons, in DWI both myelinated and unmyelinated axons contribute to the DWI signal. However, DWI models often include simplifications, for example, the neglect of differences in the compartmental relaxation times or fixed diffusivities, which in turn might affect the estimation of . We investigate whether linear calibration parameters (scaling and offset) can improve the comparability between EM‐ and DWI‐based metrics of . To this end, we (a) used six DWI models based on the so‐called standard model of white matter (WM), including two models with fixed compartmental diffusivities (e.g., neurite orientation dispersion and density imaging, NODDI) and four models that fitted the compartmental diffusivities (e.g., white matter tract integrity, WMTI), and (b) used a multimodal data set including ex vivo diffusion DWI and EM data in mice with a broad dynamic range of fibre volume metrics. We demonstrated that the offset is associated with the volume fraction of unmyelinated axons and the scaling factor is associated with different compartmental and can substantially enhance the comparability between EM‐ and DWI‐based metrics of . We found that DWI models that fitted compartmental diffusivities provided the most accurate estimates of the EM‐based . Finally, we introduced a more efficient hybrid calibration approach, where only the offset is estimated but the scaling is fixed to a theoretically predicted value. Using this approach, a similar one‐to‐one correspondence to EM was achieved for WMTI. The method presented can pave the way for use of validated DWI‐based models in clinical research and neuroscience.
Source: NMR in Biomedicine
DOI: 10.1002/nbm.5070
Institutions: University Medical Center Hamburg-Eppendorf, Max Planck Institute for Human Development, Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, Vanderbilt University, Vanderbilt University Medical Center, Max Planck Institute for Human Cognitive and Brain Sciences
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $5,150
Awards: G1278211685, G1679778923, G2424121955, Wellcome Centre for Human Neuroimaging, G3005325708, G3337114174, NEURON-Verbund hMRTofScI: Entschlüsselung der pathophysiologischen Prozesse induziert durch eine Querschnittlähmung: Anwendung von MRT basierter in vivo und ex vivo Histologie, G5135212881, MRI Toolbox for Rodent Brain Microstructure Imaging, Understanding the mechanisms of atrophy associated with spinal cord injury: the application of MRI-based in vivo histology and ex vivo histology, G5581198352, NEURON-Verbund hMRIofSCI: Entschlüsselung der pathophysiologischen Prozesse induziert durch eine Querschnittlähmung: Anwendung von MRT basierter in vivo und ex vivo Histologie, G6004913796, G604397192, G6512545055, G6536710286, G7976181444, G8532526476, G8546314794, G8610749481, G939948813
OpenAlex ID: W4389791075