Needle Artifact Prediction by Modeling Dephasing in MR-Guided Interventions

Motivation: MR-guided needle interventions benefit from prior knowledge of needle artifact size and shape, as the artifact is important for instrument visualization and localization. Goal(s): To investigate an analytical model for the dephasing artifact of a 20-gauge aspiration needle in GRE imaging based on material and imaging parameters. Approach: Model accuracy was evaluated in-vitro for B0 = 0.55T/1.5T/3T, res = (1mm)3/(2mm)3 and TE = 5ms/15ms/25ms using Dice score (DSC) and Hausdorff distance (dH) as metrics. Results: For isotropic voxel grids, the dephasing needle artifact could be well approximated by the model (DSC ≥ 86%, dH ≤ 2 voxels). Impact: The approximation of needle artifacts using an analytical model provides an instructive way for artifact size prediction and can potentially facilitate MR-guided intervention planning (e.g., the choice of imaging parameters, needle selection and system selection).

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Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/4940
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Needle Artifact Prediction by Modeling Dephasing in MR-Guided Interventions

Jonas Faust, Mark E. Ladd, Axel J. Krafft, Jianing Pang et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Needle Artifact Prediction by Modeling Dephasing in MR-Guided Interventions

Jonas Faust, Mark E. Ladd, Axel J. Krafft, Jianing Pang, Florian Maier
article en

Abstract

Motivation: MR-guided needle interventions benefit from prior knowledge of needle artifact size and shape, as the artifact is important for instrument visualization and localization. Goal(s): To investigate an analytical model for the dephasing artifact of a 20-gauge aspiration needle in GRE imaging based on material and imaging parameters. Approach: Model accuracy was evaluated in-vitro for B0 = 0.55T/1.5T/3T, res = (1mm)3/(2mm)3 and TE = 5ms/15ms/25ms using Dice score (DSC) and Hausdorff distance (dH) as metrics. Results: For isotropic voxel grids, the dephasing needle artifact could be well approximated by the model (DSC ≥ 86%, dH ≤ 2 voxels). Impact: The approximation of needle artifacts using an analytical model provides an instructive way for artifact size prediction and can potentially facilitate MR-guided intervention planning (e.g., the choice of imaging parameters, needle selection and system selection).

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 64%
Radiomics and Machine Learning in Medical Imaging
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Needle Artifact Prediction by Modeling Dephasing in MR-Guided Interventions — Jonas Faust, Mark E. Ladd, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024) | TGRS Research Map | TGRS