CITATION.bib

@article{kor_role_2019,
  title    = {The role of iron and myelin in orientation dependent {R2}* of white matter},
  volume   = {32},
  issn     = {1099-1492},
  url      = {https://onlinelibrary.wiley.com/doi/abs/10.1002/nbm.4092},
  doi      = {10.1002/nbm.4092},
  abstract = {Brain myelin and iron content are important parameters in neurodegenerative diseases such as multiple sclerosis (MS). Both myelin and iron content influence the brain's R2* relaxation rate. However, their quantification based on R2* maps requires a realistic tissue model that can be fitted to the measured data. In structures with low myelin content, such as deep gray matter, R2* shows a linear increase with increasing iron content. In white matter, R2* is not only affected by iron and myelin but also by the orientation of the myelinated axons with respect to the external magnetic field. Here, we propose a numerical model which incorporates iron and myelin, as well as fibre orientation, to simulate R2* decay in white matter. Applying our model to fibre orientation-dependent in vivo R2* data, we are able to determine a unique solution of myelin and iron content in global white matter. We determine an averaged myelin volume fraction of 16.02 {\textpm} 2.07\% in non-lesional white matter of patients with MS, 17.32 {\textpm} 2.20\% in matched healthy controls, and 18.19 {\textpm} 2.98\% in healthy siblings of patients with MS. Averaged iron content was 35.6 {\textpm} 8.9 mg/kg tissue in patients, 43.1 {\textpm} 8.3 mg/kg in controls, and 47.8 {\textpm} 8.2 mg/kg in siblings. All differences in iron content between groups were significant, while the difference in myelin content between MS patients and the siblings of MS patients was significant. In conclusion, we demonstrate that a model that combines myelin-induced orientation-dependent and iron-induced orientation-independent components is able to fit in vivo R2* data.},
  language = {en},
  number   = {7},
  urldate  = {2024-02-28},
  journal  = {NMR in Biomedicine},
  author   = {Kor, Daniel and Birkl, Christoph and Ropele, Stefan and Doucette, Jonathan and Xu, Tianyou and Wiggermann, Vanessa and Hern{\'a}ndez-Torres, Enedino and Hametner, Simon and Rauscher, Alexander},
  year     = {2019},
  note     = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/nbm.4092},
  keywords = {MRI, R2*, myelin, brain iron, multiple sclerosis, neurodegenerative disease, susceptibility-weighted imaging, white matter fibre orientation},
  pages    = {e4092},
  file     = {Full Text PDF:/home/jdoucette/Zotero/storage/B9HX9KCF/Kor et al. - 2019 - The role of iron and myelin in orientation depende.pdf:application/pdf;Snapshot:/home/jdoucette/Zotero/storage/PVG6CACY/nbm.html:text/html}
}

@article{wharton_fiber_2012,
  title    = {Fiber orientation-dependent white matter contrast in gradient echo {MRI}},
  volume   = {109},
  issn     = {0027-8424},
  url      = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3494918/},
  doi      = {10.1073/pnas.1211075109},
  abstract = {Recent studies have shown that there is a direct link between the orientation of the nerve fibers in white matter (WM) and the contrast observed in magnitude and phase images acquired using gradient echo MRI. Understanding the origin of this link is of great interest because it could offer access to a new diagnostic tool for investigating tissue microstructure. Since it has been suggested that myelin is the dominant source of this contrast, creating an accurate model for characterizing the effect of the myelin sheath on the evolution of the NMR signal is an essential step toward fully understanding WM contrast. In this study, we show by comparison of the results of simulations and experiments carried out on human subjects at 7T, that the magnitude and phase of signals acquired from WM in vivo can be accurately characterized by (i) modeling the myelin sheath as a hollow cylinder composed of material having an anisotropic magnetic susceptibility that is described by a tensor with a radially oriented principal axis, and (ii) adopting a two-pool model in which the water in the sheath has a reduced T2 relaxation time and spin density relative to its surroundings, and also undergoes exchange. The accuracy and intrinsic simplicity of the hollow cylinder model provides a versatile framework for future exploitation of the effect of WM microstructure on gradient echo contrast in clinical MRI.},
  number   = {45},
  urldate  = {2017-11-24},
  journal  = {Proc Natl Acad Sci U S A},
  author   = {Wharton, Samuel and Bowtell, Richard},
  month    = nov,
  year     = {2012},
  pmid     = {23091011},
  pmcid    = {PMC3494918},
  pages    = {18559--18564},
  file     = {PubMed Central Full Text PDF:/home/jdoucette/Zotero/storage/K7UHKC6V/Wharton and Bowtell - 2012 - Fiber orientation-dependent white matter contrast .pdf:application/pdf}
}

@article{xu_effect_2018,
  title     = {The effect of realistic geometries on the susceptibility-weighted {MR} signal in white matter},
  volume    = {79},
  copyright = {{\textcopyright} 2017 The Authors Magnetic Resonance in Medicine published by John Wiley \& Sons Ltd on behalf of International Society for Magnetic Resonance in Medicine},
  issn      = {1522-2594},
  url       = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.26689},
  doi       = {10.1002/mrm.26689},
  abstract  = {Purpose To investigate the effect of realistic microstructural geometry on the susceptibility-weighted MR signal in white matter (WM), with application to demyelination. Methods Previous work has modeled susceptibility-weighted signals under the assumption that axons are cylindrical. In this study, we explored the implications of this assumption by considering the effect of more realistic geometries. A three-compartment WM model incorporating relevant properties based on the literature was used to predict the MR signal. Myelinated axons were modeled with several cross-sectional geometries of increasing realism: nested circles, warped/elliptical circles, and measured axonal geometries from electron micrographs. Signal simulations from the different microstructural geometries were compared with measured signals from a cuprizone mouse model with varying degrees of demyelination. Results Simulation results suggest that axonal geometry affects the MR signal. Predictions with realistic models were significantly different compared with circular models under the same microstructural tissue properties, for simulations with and without diffusion. Conclusion The geometry of axons affects the MR signal significantly. Literature estimates of myelin susceptibility, which are based on fitting biophysical models to the MR signal, are likely to be biased by the assumed geometry, as will any derived microstructural properties. Magn Reson Med 79:489{\textendash}500, 2018. {\textcopyright} 2017 International Society for Magnetic Resonance in Medicine.},
  language  = {en},
  number    = {1},
  urldate   = {2019-09-17},
  journal   = {Magnetic Resonance in Medicine},
  author    = {Xu, Tianyou and Foxley, Sean and Kleinnijenhuis, Michiel and Chen, Way Cherng and Miller, Karla L.},
  year      = {2018},
  keywords  = {R2*, GRE phase signal, magnetic susceptibility modeling, white matter microstructure, myelin},
  pages     = {489--500},
  file      = {Full Text PDF:/home/jdoucette/Zotero/storage/U9RXXI46/Xu et al. - 2017 - The effect of realistic geometries on the suscepti.pdf:application/pdf;Snapshot:/home/jdoucette/Zotero/storage/VXFR49RH/abstract.html:text/html;Snapshot:/home/jdoucette/Zotero/storage/BKHHC9XS/mrm.html:text/html;Submitted Version:/home/jdoucette/Zotero/storage/6XTN92NH/Xu et al. - 2018 - The effect of realistic geometries on the suscepti.pdf:application/pdf}
}

@article{harrison_ferritins_1996,
  title      = {The ferritins: molecular properties, iron storage function and cellular regulation},
  volume     = {1275},
  issn       = {0005-2728},
  shorttitle = {The ferritins},
  url        = {https://www.sciencedirect.com/science/article/pii/0005272896000229},
  doi        = {10.1016/0005-2728(96)00022-9},
  abstract   = {The iron storage protein, ferritin, plays a key role in iron metabolism. Its ability to sequester the element gives ferritin the dual functions of iron detoxification and iron reserve. The importance of these functions is emphasised by ferritin's ubiquitous distribution among living species. Ferritin's three-dimensional structure is highly conserved. All ferritins have 24 protein subunits arranged in 432 symmetry to give a hollow shell with an 80 {\r A} diameter cavity capable of storing up to 4500 Fe(III) atoms as an inorganic complex. Subunits are folded as 4-helix bundles each having a fifth short helix at roughly 60{\textdegree} to the bundle axis. Structural features of ferritins from humans, horse, bullfrog and bacteria are described: all have essentially the same architecture in spite of large variations in primary structure (amino acid sequence identities can be as low as 14\%) and the presence in some bacterial ferritins of haem groups. Ferritin molecules isolated from vertebrates are composed of two types of subunit (H and L), whereas those from plants and bacteria contain only H-type chains, where {\textquoteleft}H-type{\textquoteright} is associated with the presence of centres catalysing the oxidation of two Fe(II) atoms. The similarity between the dinuclear iron centres of ferritin H-chains and those of ribonucleotide reductase and other proteins suggests a possible wider evolutionary linkage. A great deal of research effort is now concentrated on two aspects of fenitin: its functional mechanisms and its regulation. These form the major part of the review. Steps in iron storage within ferritin molecules consist of Fe(II) oxidation, FE(III) migration and the nucleation and growth of the iron core mineral. H-chains are important for Fe(II) oxidation and L-chains assist in core formation. Iron mobilisation, relevant to ferritin's role as iron reserve, is also discussed. Translational regulation of mammalian ferritin synthesis in response to iron and the apparent links between iron and citrate metabolism through a single molecule with dual function are described. The molecule, when binding a [4Fe-4S] cluster, is a functioning (cytoplasmic) aconitase. When cellular iron is low, loss of the [4Fe-4S] cluster allows the molecule to bind to the 5'-untranslated region (5'-UTR) of the ferritin m-RNA and thus to repress translation. In this form it is known as the iron regulatory protein (IRP) and the stem-loop RNA structure to which it binds is the iron regulatory element (IRE). IREs are found in the 3'-UTR of the transferrin receptor and in the 5'-UTR of erythroid aminolaevulinic acid synthase, enabling tight co-ordination between cellular iron uptake and the synthesis of ferritin and haem. Degradation of ferritin could potentially lead to an increase in toxicity due to uncontrolled release of iron. Degradation within membrane-encapsulated {\textquoteleft}secondary lysosomes{\textquoteright} may avoid this problem and this seems to be the origin of another form of storage iron known as haemosiderin. However, in certain pathological states, massive deposits of {\textquoteleft}haemosiderin{\textquoteright} are found which do not arise directly from ferritin breakdown. Understanding the numerous inter-relationships between the various intracellular iron complexes presents a major challenge.},
  number     = {3},
  urldate    = {2024-03-08},
  journal    = {Biochimica et Biophysica Acta (BBA) - Bioenergetics},
  author     = {Harrison, Pauline M. and Arosio, Paolo},
  month      = jul,
  year       = {1996},
  keywords   = {Dinuclear iron, Ferritin, Ferroxidase activity, Haemosiderin, Iron regulatory element (IRE), Iron regulatory protein (IRP), Iron storage},
  pages      = {161--203},
  file       = {Harrison and Arosio - 1996 - The ferritins molecular properties, iron storage .pdf:/home/jdoucette/Zotero/storage/V8FYFWLP/Harrison and Arosio - 1996 - The ferritins molecular properties, iron storage .pdf:application/pdf;ScienceDirect Snapshot:/home/jdoucette/Zotero/storage/DE369F4M/0005272896000229.html:text/html}
}

@article{schenck_magnetic_2003,
  title    = {Magnetic resonance imaging of brain iron},
  volume   = {207},
  issn     = {0022-510X, 1878-5883},
  url      = {https://www.jns-journal.com/article/S0022-510X(02)00431-8/abstract},
  doi      = {10.1016/S0022-510X(02)00431-8},
  language = {English},
  number   = {1},
  urldate  = {2024-03-08},
  journal  = {Journal of the Neurological Sciences},
  author   = {Schenck, John F.},
  month    = mar,
  year     = {2003},
  pmid     = {12614939},
  note     = {Publisher: Elsevier},
  pages    = {99--102},
  file     = {Schenck - 2003 - Magnetic resonance imaging of brain iron.pdf:/home/jdoucette/Zotero/storage/HK3P4DWN/Schenck - 2003 - Magnetic resonance imaging of brain iron.pdf:application/pdf}
}