Mesoscopic characterization of human white-matter: a computational in-vivo MRI framework

Projektinformationen

MWMI

ID Finanzhilfevereinbarung: 658589

DOI

10.3030/658589

Projekt abgeschlossen

EK-Unterschriftsdatum 5 April 2015

Startdatum 1 Dezember 2015

Enddatum 30 November 2017

Finanziert unter

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Gesamtkosten

€ 171 460,80

EU-Beitrag

€ 171 460,80

Koordiniert durch

UNIVERSITAETSKLINIKUM HAMBURG-EPPENDORF
Germany

Periodic Reporting for period 1 - MWMI (Mesoscopic characterization of human white-matter: a computational in-vivo MRI framework)

Berichtszeitraum: 2015-12-01 bis 2017-11-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The main goal of this Marie-Curie project was to improve our understanding of the human central nervous system (CNS) by extending our knowledge of the white-matter micro-scale composition, which is integral to brain function. Information flow in the brain is conveyed from the periphery via white matter pathways in the spinal cord to the cortex. However, it is currently not known to which degree the micro-scale composition of these pathways (e.g. myelin-sheath thickness or axonal diameter) determines the performance of functional networks associated with the cortex.

The goal of this proposal was to develop a novel computational in-vivo MRI method, which we call Mesoscopic White-Matter magnetic resonance Imaging (MWMI). MWMI will allow the assessment of 4 specific micro-scale metrics at high spatial resolution: myelin, water concentration, axonal density and the ratio between inner and outer fiber diameters (g-ratio) - a surrogate measure for the conductance speed in a fiber. Conventional quantitative MRI (qMRI), such as Diffusion Tensor Imaging (DTI), can detect microstructural changes but do not provide any information on the origin of these changes. In contrast, MWMI is capable of detecting microstructural changes and in addition provides insight into the underlying processes leading to these changes (e.g. whether pain leads to axonal reorganization or (de)myelination).

To main objectives of this project can be summarized as follows:

(i) To develop biophysical models that link the MR signal to the microscopic tissue composition.
(ii) To achieve high spatial resolution and integration of different MRI techniques.
(iv) To apply these MWMI methods to the pain circuit, which is a fundamental and well-described circuit of the human CNS.
(v) To disseminate the MWMI method to the community by providing an imaging protocol and an open-source toolbox to the community.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

The main work performed during this Marie-Curie stipend can be divided into five sub-projects:
1. We developed biophysical models that relate different quantitative MRI techniques to the underlying tissue composition.
2. We developed image processing methods that greatly enhance the quality of quantitative MRI maps thereby facilitating the integration of different qMRI techniques, suffering from different imaging artifacts.
3. We estimated high-resolution maps of biophysical markers (e.g. myelin or fiber densities) from quantitative MRI maps by combining an efficient imaging protocol with the developed, novel and efficient biophysical models (1.) and new processing methods (2.).
4. We showed the feasibility of using the MWMI method in a neuroscience study, where we acquired behavioral and quantitative MRI data with the aim of revealing that nociceptive long-term habituation affects microstructure.
5. We developed open-source toolboxes for: (a) processing and estimating quantitative parameter maps, (b) adaptive denoising of quantitative MRI maps, and (c) processing DTI maps in the spinal cord.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The impact of the project from the scientific perspective can be summarized as follows:

• The biophysical NODDI-DTI method increases the understanding of how physical DTI metrics, which are routinely used in clinical and neuroscience research, are related to biophysical properties such as the density of axons in white matter (see Figure).
• Our newly developed method for artifact correction in spinal cord DTI reduces the artifact-induced variability across subjects and thus improves the statistical power for detecting group differences. In principle, this method can be extended to other model-based qMRI techniques, such as the MPM model.

These main achievements of these Marie-Curie project are the main pillars of MWMI and built the foundation for neuroscience studies using multi-modal qMRI.

In terms of communication and results dissemination, these happened across different channels:

• The project website (https://goo.gl/zsVcgP) is part of our institutes' website, which includes news, articles and code releases.
• Tweets posts by the author (@siawooshm) and journals (e.g. @FrontNeurosci).
• Presentations at 5 international conferences, including two oral presentations: one at the SFN 2016, San Diego and at the ISMRM 2017 in Hawaii.
• Invited speaker on computational MRI, biophysical models, and MRI-based in vivo histology. 39th Annual Meeting of the Japan Neuroscience Society 2016, Yokohama, Japan.
• At the ESMRMB lecture on “Quantitative MRI for Characterising Brain Tissue Microstructure” in Leipzig, 2016, the author has given a presentation about biophysical models using diffusion MRI.
• The methods developed in this Marie-Curie project are (or will become) part of two open-source toolboxes: (a) the method for estimating a myelin biomarker (which can be calculated from the proton density maps) is part of the hMRI toolbox and available here: b the methods for artifact correction in spinal cord DTI will become available under www.diffusiontools.com after the paper has been published.

slide6.jpg