Dataset Information

Metallic implant geometry and susceptibility estimation using multispectral B0 field maps.

ABSTRACT: 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.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.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.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. Magn Reson Med 77:2402-2413, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

SUBMITTER: Shi X

PROVIDER: S-EPMC5529184 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Metallic implant geometry and susceptibility estimation using multispectral B<sub>0</sub> field maps.

Shi Xinwei X Yoon Daehyun D Koch Kevin M KM Hargreaves Brian A BA

Magnetic resonance in medicine 20160706 6

<h4>Purpose</h4>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.<h4>Theory and methods</h4>The susceptibility map of signal-void regions is estimated from MSI B<sub>0</sub> field maps using total variation (TV) regularized inversion. Voxels with susceptibility estimates above a predetermined threshold are identified as metal. The accuracy of the estimate ...[more]

PMID: 27385493

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Project description:PURPOSE:High resolution multi-gradient echo (MGE) scanning is typically used for detection of molecularly targeted iron oxide particles. The images of individual echoes are often combined to generate a composite image with improved SNR from the early echoes and boosted contrast from later echoes. In 3D implementations prolonged scanning at high gradient duty cycles induces a B0 shift that predominantly affects image alignment in the slow phase encoding dimension of 3D MGE images. The effect corrupts the composite echo image and limits the image resolution that is realised. A real-time adaptive B0 stabilisation during respiration gated 3D MGE scanning is shown to reduce image misalignment and improve detection of molecularly targeted iron oxide particles in composite images of the mouse brain. METHODS:An optional B0 measurement block consisting of a 16 ?s hard pulse with FA 1°, an acquisition delay of 3.2 ms, followed by gradient spoiling in all three axes was added to a respiration gated 3D MGE scan. During the acquisition delay of each B0 measurement block the NMR signal was routed to a custom built B0 stabilisation unit which mixed the signal to an audio frequency nominally centred around 1000 Hz to enable an Arduino based single channel receiver to measure frequency shifts. The frequency shift was used to effect correction to the main magnetic field via the B0 coil. The efficacy of B0 stabilisation and respiration gating was validated in vivo and used to improve detection of molecularly targeted microparticles of iron oxide (MPIO) in a mouse model of acute neuroinflammation. RESULTS:Without B0 stabilisation 3D MGE image data exhibit varying mixtures of translation, scaling and blurring, which compromise the fidelity of the composite image. The real-time adaptive B0 stabilisation minimises corruption of the composite image as the images from the different echoes are properly aligned. The improved detection of molecularly targeted MPIO easily compensates for the scan time penalty of 14% incurred by the B0 stabilisation method employed. Respiration gating of the B0 measurement and the MRI scan was required to preserve high resolution detail, especially towards the back of the brain. CONCLUSIONS:High resolution imaging for the detection of molecularly targeted iron oxide particles in the mouse brain requires good stabilisation of the main B0 field, and can benefit from a respiration gated image acquisition strategy.

Dataset Information

Metallic implant geometry and susceptibility estimation using multispectral B0 field maps.

Publications

Metallic implant geometry and susceptibility estimation using multispectral B<sub>0</sub> field maps.

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