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Abstract #1927

The impact of data analysis method, scanner type and scan session on volume measurements of brain structures

Michael Amann1,2, Pavel Falkovskiy3,4,5, Alain Thoeni1, Tobias Kober3,4,5, Alexis Roche3,4,5, Bénédicte Maréchal3,4,5, Philippe Cattin6, Tobias Heye2, Oliver Bieri2, Till Sprenger7, Christoph Stippich2, Gunnar Krueger4,5,8, Ernst-Wilhelm Radue1, and Jens Wuerfel1

1Medical Image Analysis Center (MIAC), Basel, Switzerland, 2Department of Radiology, University Hospital of Basel, Basel, Switzerland, 3Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 4Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 5École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 6Department of Biomedical Engineering, University of Basel, Basel, Switzerland, 7Department of Neurology, DKD Helios Klinik, Wiesbaden, Germany, 8Siemens Medical Solutions USA, Boston, MA, United States

Performance of FreeSurfer and FSL was compared on T1-weighted 3D MRI data of 22 controls as function of scan session, scanner type and segmentation pipeline. Intra-class correlation coefficients and percentage volume differences were calculated for the segmentation results of both pipelines. Strong agreement was found for whole brain, white matter and cortex. For each pipeline, the impact of experimental factors was assessed by linear mixed effects analysis. We found significant scanner effect on the results of both segmentation pipelines. For subcortical structures, segmentation reliability was higher in FSL than in FreeSurfer, whereas for cortex and WM, FreeSurfer was more stable.

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