New approach to phase correction in multi-echo T2 relaxometry

Connexin 50 Influences the Physiological Optics of the In Vivo Mouse Lens

Purpose

The purpose of this study was to utilize multi-parametric magnetic resonance imaging (MRI) to investigate in vivo age-related changes in the physiology and optics of mouse lenses where Connexin 50 has been deleted (Cx50KO) or replaced by Connexin 46 (Cx50KI46).

Methods

The lenses of transgenic Cx50KO and Cx50KI46 mice were imaged between 3 weeks and 6 months of age using a 7T MRI. Measurements of lens geometry, the T2 (water-bound protein ratios), the refractive index (n), and T1 (free water content) values were calculated by processing the acquired images. The lens power was calculated from an optical model that combined the geometry and the n. All transgenic mice were compared with control mice at the same age.

Results

Cx50KO and Cx50KI46 mice developed smaller lenses compared with control mice. The lens thickness, volume, and surface radii of curvatures all increased with age but were limited to the size of the lenses. Cx50KO lenses exhibited higher lens power than Cx50KI46 lenses at all ages, and this was correlated with significantly lower water content in these lenses, which was probably modulated by the gap junction coupling. The refractive power tended to a steady state with age, similar to the control mice.

Conclusions

The modification of Cx50 gap junctions significantly impacted lens growth and physiological optics as the mouse aged. The lenses showed delayed development growth, and altered optics governed by different lens physiology. This research provides new insights into how gap junctions regulate the development of the lens's physiological optics.

Age-Dependent Changes in the Water Content and Optical Power of the In Vivo Mouse Lens Revealed by Multi-Parametric MRI and Optical Modeling

Purpose

The purpose of this study was to utilize in vivo magnetic resonance imaging (MRI) and optical modeling to investigate how changes in water transport, lens curvature, and gradient refractive index (GRIN) alter the power of the mouse lens as a function of age.

Methods

Lenses of male C57BL/6 wild-type mice aged between 3 weeks and 12 months (N = 4 mice per age group) were imaged using a 7T MRI scanner. Measurements of lens shape and the distribution of T2 (water-bound protein ratios) and T1 (free water content) values were extracted from MRI images. T2 values were converted into the refractive index (n) using an age-corrected calibration equation to calculate the GRIN at different ages. GRIN maps and shape parameters were inputted into an optical model to determine ageing effects on lens power and spherical aberration.

Results

The mouse lens showed two growth phases. From 3 weeks to 3 months, T2 decreased, GRIN increased, and T1 decreased. This was accompanied by increased lens thickness, volume, and surface radii of curvatures. The refractive power of the lens also increased significantly, and a negative spherical aberration was developed and maintained. Between 6 and 12 months of age, all physiological, geometrical, and optical parameters remained constant, although the lens continued to grow.

Conclusions

In the first 3 months, the mouse lens power increased as a result of changes in shape and in the GRIN, the latter driven by the decreased water content of the lens nucleus. Further research into the mechanisms regulating this decrease in mouse lens water could improve our understanding of how lens power changes during emmetropization in the developing human lens.

A method for T1 and T2 relaxation times validation and harmonization as a support to MRI mapping

We present a proof-of-concept study focusing on a method for the intra- and inter-center validation and harmonization of data obtained from MRI T₁ and T₂ maps. The method is based on a set of MnCl₂ samples that provide in-scan ground-truth reference values regardless of the details of the MRI protocol. The relaxation times of MnCl₂ aqueous solutions were first measured by means of an NMR laboratory relaxometer, as a function of concentration and temperature. The obtained T₁ and T₂ values, once renormalized at the scanner temperature, were used as reference values for the MRI mapping measurements of the MnCl₂ relaxation times. By using different clinical MRI scanners and sequences, we found a good agreement for standard and turbo sequences (limits of agreement: 5% for IR, SE, IR-TSE; 10% for TSE), while an under-estimation and an over-estimation were found respectively for MOLLI and T₂-prep TrueFISP, as already reported in the literature. The linearity of the relaxation rates with the concentration predicted by the Solomon-Bloembergen-Morgan theory was observed for every dataset at all temperatures, except for T₂-prep TrueFISP maps results. Some preliminary results of an in vivo experiment are also presented.

A diffusion model-free framework with echo time dependence for free-water elimination and brain tissue microstructure characterization

PURPOSE

The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill-posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free-water component.

THEORY AND METHODS

Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization.

RESULTS

Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free-water contamination and to estimate tissue parameters.

CONCLUSION

Formulation of the diffusion-relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free-water elimination.

A multicomponent T2 relaxometry algorithm for myelin water imaging of the brain

PURPOSE

Models based on a sum of damped exponentials occur in many applications, particularly in multicomponent T2 relaxometry. The problem of estimating the relaxation parameters and the corresponding amplitudes is known to be difficult, especially as the number of components increases. In this article, the commonly used non-negative least squares spectrum approach is compared to a recently published estimation algorithm abbreviated as Exponential Analysis via System Identification using Steiglitz-McBride.

METHODS

The two algorithms are evaluated via simulation, and their performance is compared to a statistical benchmark on precision given by the Cramér-Rao bound. By applying the algorithms to an in vivo brain multi-echo spin-echo dataset, containing 32 images, estimates of the myelin water fraction are computed.

RESULTS

Exponential Analysis via System Identification using Steiglitz-McBride is shown to have superior performance when applied to simulated T2 relaxation data. For the in vivo brain, Exponential Analysis via System Identification using Steiglitz-McBride gives an myelin water fraction map with a more concentrated distribution of myelin water and less noise, compared to non-negative least squares.

CONCLUSION

The Exponential Analysis via System Identification using Steiglitz-McBride algorithm provides an efficient and user-parameter-free alternative to non-negative least squares for estimating the parameters of multiple relaxation components and gives a new way of estimating the spatial variations of myelin in the brain.