Affiliation:
1. Mallinckrodt Institute of Radiology Washington University in St. Louis St. Louis Missouri USA
2. Hope Center for Neurological Disorders St. Louis Missouri USA
3. Knight Alzheimer Disease Research Center St. Louis Missouri USA
4. Department of Biomedical Engineering Washington University in St. Louis St. Louis Missouri USA
Abstract
AbstractPurposeDespite significant impact on the study of human brain, MRI lacks a theory of signal formation that integrates quantum interactions involving proton dipoles (a primary MRI signal source) with brain intricate cellular environment. The purpose of the present study is developing such a theory.MethodsWe introduce the Transient Hydrogen Bond (THB) model, where THB‐mediated quantum dipole interactions between water and protons of hydrophilic heads of amphipathic biomolecules forming cells, cellular membranes and myelin sheath serve as a major source of MR signal relaxation.ResultsThe THB theory predicts the existence of a hydrogen‐bond‐driven structural order of dipole–dipole connections within THBs as a primary factor for the anisotropy observed in MRI signal relaxation. We have also demonstrated that the conventional Lorentzian spectral density function decreases too fast at high frequencies to adequately capture the field dependence of brain MRI signal relaxation. To bridge this gap, we introduced a stretched spectral density function that surpasses the limitations of Lorentzian dispersion. In human brain, our findings reveal that at any time point only about 4% to 7% of water protons are engaged in quantum encounters within THBs. These ultra‐short (2 to 3 ns), but frequent quantum spin exchanges lead to gradual recovery of magnetization toward thermodynamic equilibrium, that is, relaxation of MRI signal.ConclusionBy incorporating quantum proton interactions involved in brain imaging, the THB approach introduces new insights on the complex relationship between brain tissue cellular structure and MRI measurements, thus offering a promising new tool for better understanding of brain microstructure in health and disease.
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2 articles.
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