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Abstract #1652

Characterizing differences between white and gray matter T1W-based segmentations at 0.6T and 1.5T

Navid Jabarimani1,2, Ece Ercan3, Yiming Dong1, Nicola Pezzotti4, Andrew Webb1, Peter Börnert1,5, Marius Staring2, Matthias J.P van Osch1, and Martijn Nagtegaal1
1C.J. Gorter MRI Center, Radiology, Leiden University Medical Center, Leiden, Netherlands, 2Division of Image Processing, Radiology, Leiden University Medical Center, Leiden, Netherlands, 3MR Clinical Science, Philips Healthcare, Best, Netherlands, 4Philips Cardiologs, Paris, France, 5Philips Innovative Technologies, Hamburg, Germany

Synopsis

Keywords: Low-Field MRI, Brain, Segmentations, Biomarkers, Neurodegeneration, Screening, Low-field

Motivation: Mid-field MRI (0.1-1T) presents an accessible option to clinical brain imaging. Thus, it’s essential to determine the measurability of brain tissue volumes at this field strength.

Goal(s): This study examines the reliability of tissue segmentation and volume estimations of conventional segmentation methods at 0.6T compared to 1.5T.

Approach: T1-weighted scans and re-scans were acquired at 0.6T and 1.5T, these images were reconstructed with both compressed sense and AI. All images were segmented, and these results were analyzed for consistency across conditions.

Results: While 0.6T images allowed consistent segmentation, further refinement with advanced approaches, such as deep learning, may enhance accuracy in volume estimation.

Impact: This study confirms that mid-field MRI (0.6T) T1-weighted images can be used for white and gray matter segmentation with reproducible volume measures. These findings may enable longitudinal monitoring of brain volume and inspire future research into improved segmentations.

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Keywords