Abstract #1927

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

Michael Amann^1,2, Pavel Falkovskiy^3,4,5, Alain Thoeni¹, Tobias Kober^3,4,5, Alexis Roche^3,4,5, Bénédicte Maréchal^3,4,5, Philippe Cattin⁶, Tobias Heye², Oliver Bieri², Till Sprenger⁷, Christoph Stippich², Gunnar Krueger^4,5,8, 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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