title: Segmenting and validating brain tissue definitions in the presence of varying tissue contrast.
abstract: We propose a method for segmenting brain tissue as either gray matter or white matter in the presence of varying tissue contrast, which can derive from either differential changes in tissue water content or increasing myelin content of white matter. Our method models the spatial distribution of intensities as a Markov Random Field (MRF) and estimates the parameters for the MRF model using a maximum likelihood approach. Although previously described methods have used similar models to segment brain tissue, accurate model of the conditional probabilities of tissue intensities and adaptive estimates of tissue properties to local intensities generates tissue definitions that are accurate and robust to variations in tissue contrast with age and across illnesses. Robustness to variations in tissue contrast is important to understand normal brain development and to identify the brain bases of neurological and psychiatric illnesses. We used simulated brains of varying tissue contrast to compare both visually and quantitatively the performance of our method with the performance of prior methods. We assessed validity of the cortical definitions by associating cortical thickness with various demographic features, clinical measures, and medication use in our three large cohorts of participants who were either healthy or who had Bipolar Disorder (BD), Autism Spectrum Disorder (ASD), or familial risk for Major Depressive Disorder (MDD). We assessed validity of the tissue definitions using synthetic brains and data for three large cohort of individuals with various neuropsychiatric disorders. Visual inspection and quantitative analyses showed that our method accurately and robustly defined the cortical mantle in brain images with varying contrast. Furthermore, associating the thickness with various demographic and clinical measures generated findings that were novel and supported by histological analyses or were supported by previous MRI studies, thereby validating the cortical definitions generated by the proposed method: (1) Although cortical thickness decreased with age in adolescents, in adults cortical thickness did not correlate significantly with age. Our synthetic data showed that the previously reported thinning of cortex in adults is likely due to decease in tissue contrast, thereby suggesting that the method generated cortical definitions in adults that were invariant to tissue contrast. In adolescents, cortical thinning with age was preserved likely due to widespread dendritic and synaptic pruning, even though the effects of decreasing tissue contrast were minimized. (3) The method generated novel finding of both localized increases and decreases in thickness of males compared to females after controlling for the differing brain sizes, which are supported by the histological analyses of brain tissue in males and females. (4) The proposed method, unlike prior methods, defined thicker cortex in BD individuals using lithium. The novel finding is supported by the studies that showed lithium treatment increased dendritic arborization and neurogenesis, thereby leading to thickening of cortex. (5) In both BD and ASD participants, associations of more severe symptoms with thinner cortex showed that correcting for the effects of tissue contrast preserved the biological consequences of illnesses. Therefore, consistency of the findings across the three large cohorts of participants, in images acquired on either 1.5T or 3T MRI scanners, and with findings from prior histological analyses provides strong evidence that the proposed method generated valid and accurate definitions of the cortex while controlling for the effects of tissue contrast.
authors: The Saban Research Institute, Children's Hospital of Los Angeles, Los Angeles, CA 90027; Department of Pediatric, University of Southern California, Los Angeles, CA 90027. Electronic address: rabansal@chla.usc.edu.
authors: Ravi
authors: R
authors: Bansal
authors: Department of Psychiatry, Columbia College of Physicians and Surgeons, New York, NY 10032; New York State Psychiatric Institute, New York, NY 10032.
authors: Xuejun
authors: X
authors: Hao
authors: The Saban Research Institute, Children's Hospital of Los Angeles, Los Angeles, CA 90027; Department of Psychiatry, University of Southern California, Los Angeles, CA 90027.
authors: Bradley S
authors: BS
authors: Peterson
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D001921:Brain / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D001931:Brain Mapping / Q000379:methods*; D002648:Child; D003198:Computer Simulation; D005260:Female; D066128:Gray Matter / Q000000981:diagnostic imaging / Q000503:physiopathology; D006801:Humans; D016013:Likelihood Functions; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D001523:Mental Disorders / Q000503:physiopathology*; D008875:Middle Aged; D059906:Neuroimaging / Q000379:methods; D015203:Reproducibility of Results; D066127:White Matter / Q000000981:diagnostic imaging / Q000503:physiopathology; D055815:Young Adult
keywords: Brain; Cortex; Markov random field; Segmentation; T1-weighted; Validation