Metallic Implant Geometry and Susceptibility Estimation Using Multispectral B0 Field Maps

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Abstract

Purpose:

To estimate the susceptibility and the geometry of metallic implants from multispectral imaging (MSI) information, to separate the metal implant region from the surrounding signal loss region.

Theory and Methods:

The susceptibility map of signal-void regions is estimated from MSI B0 field maps using total variation (TV) regularized inversion. Voxels with susceptibility estimates above a predetermined threshold are identified as metal. The accuracy of the estimated susceptibility and implant geometry was evaluated in simulations, phantom, and in vivo experiments.

Results:

The proposed method provided more accurate susceptibility estimation compared with a previous method without TV regularization, in both simulations and phantom experiments. In the phantom experiment where the actual implant was 40% of the signal-void region, the mean estimated susceptibility was close to the susceptibility in literature, and the precision and recall of the estimated geometry was 85% and 93%. In vivo studies in subjects with hip implants also demonstrated that the proposed method can distinguish implants from surrounding low-signal tissues, such as cortical bone.

Conclusion:

The proposed method can improve the delineation of metallic implant geometry by distinguishing metal voxels from artificial signal voids and low-signal tissues by estimating the susceptibility maps.

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