Quantitative susceptibility mapping of carotid arterial tissue ex vivo: Assessing sensitivity to vessel microstructural composition

Value of Quantitative Susceptibility Mapping in Clinical Neuroradiology

Quantitative susceptibility mapping (QSM) is a unique technique for providing quantitative information on tissue magnetic susceptibility using phase image data. QSM can provide valuable information regarding physiological and pathological processes such as iron deposition, hemorrhage, calcification, and myelin. QSM has been considered for use as an imaging biomarker to investigate physiological status and pathological changes. Although various studies have investigated the clinical applications of QSM, particularly regarding the use of QSM in clinical practice, have not been examined well. This review provides on an overview of the basics of QSM and its clinical applications in neuroradiology. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Investigating the effect of oblique image acquisition on the accuracy of QSM and a robust tilt correction method

PURPOSE

Quantitative susceptibility mapping (QSM) is used increasingly for clinical research where oblique image acquisition is commonplace, but its effects on QSM accuracy are not well understood.

THEORY AND METHODS

The QSM processing pipeline involves defining the unit magnetic dipole kernel, which requires knowledge of the direction of the main magnetic fieldB ^ 0 $$ {\hat{\boldsymbol{B}}}_{\mathbf{0}} $$ with respect to the acquired image volume axes. The direction ofB ^ 0 $$ {\hat{\boldsymbol{B}}}_{\mathbf{0}} $$ is dependent on the axis and angle of rotation in oblique acquisition. Using both a numerical brain phantom and in vivo acquisitions in 5 healthy volunteers, we analyzed the effects of oblique acquisition on magnetic susceptibility maps. We compared three tilt-correction schemes at each step in the QSM pipeline: phase unwrapping, background field removal and susceptibility calculation, using the RMS error and QSM-tuned structural similarity index.

RESULTS

Rotation of wrapped phase images gave severe artifacts. Background field removal with projection onto dipole fields gave the most accurate susceptibilities when the field map was first rotated into alignment withB ^ 0 $$ {\hat{\boldsymbol{B}}}_{\mathbf{0}} $$ . Laplacian boundary value and variable-kernel sophisticated harmonic artifact reduction for phase data background field removal methods gave accurate results without tilt correction. For susceptibility calculation, thresholded k-space division, iterative Tikhonov regularization, and weighted linear total variation regularization, all performed most accurately when local field maps were rotated into alignment withB ^ 0 $$ {\hat{\boldsymbol{B}}}_{\mathbf{0}} $$ before susceptibility calculation.

CONCLUSION

For accurate QSM, oblique acquisition must be taken into account. Rotation of images into alignment withB ^ 0 $$ {\hat{\boldsymbol{B}}}_{\mathbf{0}} $$ should be carried out after phase unwrapping and before background-field removal. We provide open-source tilt-correction code to incorporate easily into existing pipelines: https://github.com/o-snow/QSM_TiltCorrection.git.

Ex Vivo Study Using Diffusion Tensor Imaging to Identify Biomarkers of Atherosclerotic Disease in Human Cadaveric Carotid Arteries

BACKGROUND

This study aims to address the potential of ex vivo diffusion tensor imaging to provide insight into the microstructural composition and morphological arrangement of aged human atherosclerotic carotid arteries.

METHODS

In this study, whole human carotid arteries were investigated both anatomically and by comparing healthy and diseased regions. Nonrigid image registration was used with unsupervised segmentation to investigate the influence of elastin, collagen, cell density, glycosaminoglycans, and calcium on diffusion tensor imaging derived metrics (fractional anisotropy and mean diffusivity). Early stage atherosclerotic features were also investigated in terms of microstructural components and diffusion tensor imaging metrics.

RESULTS

All vessels displayed a dramatic decrease in fractional anisotropy compared with healthy animal arterial tissue, while the mean diffusivity was sensitive to regions of advanced disease. Elastin content strongly correlated with both fractional anisotropy (r>0.7, P<0.001) and mean diffusivity (r>-0.79, P<0.0002), and the thickened intima was also distinguishable from arterial media by these metrics.

CONCLUSIONS

These different investigations point to the potential of diffusion tensor imaging to identify characteristics of arterial disease progression, at early and late-stage lesion development.