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Experimental study of sector and linear array ultrasound accuracy and the influence of navigated 3D-reconstruction as compared to MRI in a brain tumor model

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Abstract

Purpose

Currently, intraoperative ultrasound in brain tumor surgery is a rapidly propagating option in imaging technology. We examined the accuracy and resolution limits of different ultrasound probes and the influence of 3D-reconstruction in a phantom and compared these results to MRI in an intraoperative setting (iMRI).

Methods

An agarose gel phantom with predefined gel targets was examined with iMRI, a sector (SUS) and a linear (LUS) array probe with two-dimensional images. Additionally, 3D-reconstructed sweeps in perpendicular directions were made of every target with both probes, resulting in 392 measurements. Statistical calculations were performed, and comparative boxplots were generated.

Results

Every measurement of iMRI and LUS was more precise than SUS, while there was no apparent difference in height of iMRI and 3D-reconstructed LUS. Measurements with 3D-reconstructed LUS were always more accurate than in 2D-LUS, while 3D-reconstruction of SUS showed nearly no differences to 2D-SUS in some measurements. We found correlations of 3D-reconstructed SUS and LUS length and width measurements with 2D results in the same image orientation.

Conclusions

LUS provides an accuracy and resolution comparable to iMRI, while SUS is less exact than LUS and iMRI. 3D-reconstruction showed the potential to distinctly improve accuracy and resolution of ultrasound images, although there is a strong correlation with the sweep direction during data acquisition.

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Correspondence to Max Siekmann.

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Conflict of interest

Jan Coburger and Ralph König work as consultants for Brainlab and have received speaker fees. The other authors have declared no personal conflict of interest.

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Siekmann, M., Lothes, T., König, R. et al. Experimental study of sector and linear array ultrasound accuracy and the influence of navigated 3D-reconstruction as compared to MRI in a brain tumor model. Int J CARS 13, 471–478 (2018). https://doi.org/10.1007/s11548-018-1705-y

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  • DOI: https://doi.org/10.1007/s11548-018-1705-y

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