title: Combining anatomical manifold information via diffeomorphic metric mappings for studying cortical thinning of the cingulate gyrus in schizophrenia.
abstract: Spatial normalization is a crucial step in assessing patterns of neuroanatomical structure and function associated with health and disease. Errors that occur during spatial normalization can influence hypothesis testing due to the dimensionalities of mapping algorithms and anatomical manifolds (landmarks, curves, surfaces, volumes) used to drive the mapping algorithms. The primary aim of this paper is to improve statistical inference using multiple anatomical manifolds and large deformation diffeomorphic metric mapping (LDDMM) algorithms. We propose that combining information generated by the various manifolds and algorithms improves the reliability of hypothesis testing. We used this unified approach to assess variation in the thickness of the cingulate gyrus in subjects with schizophrenia and healthy comparison subjects. Three different LDDMM algorithms for mapping landmarks, curves and triangulated meshes were used to transform thickness maps of the cingulate surfaces into an atlas coordinate system. We then tested for group differences by combining the information from the three types of anatomical manifolds and LDDMM mapping algorithms. The unified approach provided reliable statistical results and eliminated ambiguous results due to surface mismatches. Subjects with schizophrenia had non-uniform cortical thinning over the left and right cingulate gyri, especially in the anterior portion, as compared to healthy comparison subjects.
authors.affiliation: Division of Bioengineering, National University of Singapore, Singapore 117576. anqi@cis.jhu.edu
authors.forename: Anqi
authors.initials: A
authors.lastname: Qiu
authors.forename: Laurent
authors.initials: L
authors.lastname: Younes
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
authors.forename: J Tilak
authors.initials: JT
authors.lastname: Ratnanather
authors.forename: Sarah K
authors.initials: SK
authors.lastname: Gillepsie
authors.forename: Gillian
authors.initials: G
authors.lastname: Kaplan
authors.forename: John
authors.initials: J
authors.lastname: Csernansky
authors.forename: Michael I
authors.initials: MI
authors.lastname: Miller
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006179:Gyrus Cinguli / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012559:Schizophrenia / Q000473:pathology*; D012680:Sensitivity and Specificity; D013382:Subtraction Technique