Asymmetric Bias in User Guided Segmentations of Subcortical Brain Structures May 2007, UNC/BRIC Radiology 2007 Funding provided by UNC Neurodevelopmental Disorders Research Center HD 03110, the NIH Conte Center MH064065, and NIH RO1 MH61696 and NIMH MH We would like to thank Dale Purves, Duke University, and Donald Mershon, North Carolina State University, for insightful discussions about the origin of this bias. Segmentation Methods Summary: We show evidence of a previously unknown strong left-right asymmetric segmentation bias. This bias fundamentally influences left-right asymmetry analyses. Our work suggests that existing studies of hemispheric asymmetry need to be interpreted in a new, skeptical light. Neuroimaging for Brainmorphometry Pathology Structural segmentations from MRI images use varying degree of user guidance Asymmetric bias for left and right hemispheric structures? Yes, shown in relatively small scale study How to avoid this bias? Introduction Martin Styner, Rachel Gimpel Smith, Mike Graves, Matt Mosconi, Sarah Peterson, Scott White, Mohammed El-Sayed, Heather Cody Hazlett Department of Computer Science and Psychiatry, University of North Carolina at Chapel Hill, Mansoura University, Mansoura Egypt Fig. 1. Left: Subcortical brain structures of interest in a 3D rendering. Right: Snapshot of ITK-SNAP segmentation software employed in all segmentations but of the hippocampus. Fig 2. Results of the segmentation study: Left:Relative asymmetry analysis, Middle: Relative difference histogram orig - mirrored, Right: P-values and comments. Conclusions Varying degree of user interaction –Hippocampus: Landmark placement, landmark constrained fluid registration, ICC= 0.99 –Lateral ventricle: Active curve evolution (ITK-SNAP) on CSF tissue probability, ICC =0.99 –Caudate: Active curve evolution (ITK-SNAP) with manual post- processing in anterior-inferior border, ICC = 0.96 –Amygdala, putamen, globus pallidus: manual segmentation, ICC = 0.83, 0.93, 0.89 Protocols online: Hippocampus: five trained raters, Adult (5) + Pediatric (5) datasets Other structures: single rater, Pediatric (10) datasets Segmentation of original data Segmentation of left-right mirrored data –Re-mirroring for analysis, left segmented as on right hemisphere Randomized order of presentation 1.Relative asymmetry :  V asym = ( V L - V R ) / (( V L + V R ) / 2) 2.Relative difference original vs mirrored :  V diff =(V orig - V mirr )/((V orig + V mirr )/2) No bias =>  Vdiff should have 0 mean Evidence of a strong left-right asymmetric segmentation bias is novel and unknown to the imaging community Bias fundamentally influences any left-right asymmetry analyses. Less surprising to the visual perception community and its likely cause is differences in perception of oppositely curved 3D structures. Segmentation methods need to be adapted, e.g. applied only to one of the hemispheres and its left-right mirrored image Study Design Putamen Amygdala Hippocampus Caudate Lateral Ventricle GP Histogram  Vasym: p=0.12  Vdiff:  =3.4%, p=0.05 Variable segmentation Limited evidence for bias  Vasym: p=0.53;  Vdiff:  =-3%, p= Variable segmentation Clear evidence for bias  Vasym: p=0.13;  Vdiff:  =3.2%, p< Variable segmentation Clear evidence for bias  Vasym: p=0.42;  Vdiff:  =1.3%, p= Stable segmentation Clear evidence for bias  Vasym: p=0.18;  Vdiff:  =0.0%, p=0.991 Stable segmentation No evidence for bias  Vasym: p<  Vdiff: p< Stable segmentation Clear evidence for bias Asymmetry inversion! Hippocampus Caudate Ventricles Pallidus Putamen Amygdala Results Structural segmentations of caudate, putamen, globus pallidus, amygdala and hippocampus showed a highly significant asymmetric bias When considerable manual outlining or landmark placement. Only lateral ventricle segmentation shows no asymmetric bias due to the high degree of automation and a high intensity contrast on boundary.