Manual MRI parcellation of the frontal lobe

Abstract

The ability to examine associations between neuropsychiatric conditions and functionally relevant frontal lobe sub-regions is a fundamental goal in neuropsychiatry, but methods for identifying frontal sub-regions in MR (magnetic resonance) images are not well established. Prior published techniques have principally defined gyral regions that do not necessarily correspond to known functional divisions. We present a method in which sulcal-gyral landmarks are used to manually delimit functionally relevant regions within the frontal lobe: primary motor cortex, anterior cingulate, deep white matter, premotor cortex regions (supplementary motor complex (SMC), frontal eye field and lateral premotor cortex) and prefrontal cortex (PFC) regions (medial PFC, dorsolateral PFC (DLPFC), inferior PFC, lateral orbitofrontal cortex (OFC) and medial OFC). Feasibility was tested by applying the protocol to brain MR data from 15 boys with ADHD and 15 typically developing controls, 8-12 years old. Intra-and inter-rater intraclass correlation coefficients were calculated using parcellation volumes from a subset of that group. Inter-rater results for the 22 hemisphere specific sub-regions ranged from 0.724 to 0.997, with all but six values above 0.9. Boys with ADHD showed significantly smaller left hemisphere SMC and DLPFC volumes after normalization for total cerebral volume. These findings support the method as a reliable and valid technique for parcellating the frontal lobe into functionally relevant subregions. KeywordsADHD; Children; Cortex; Prefrontal; Premotor; Segmentation; Supplementary Motor Complex Corresponding Author: Walter E. Kaufmann, Kennedy Krieger Institute, 3901 Greenspring Ave., Baltimore, MD 21211, Phone: 443-923-2789, Fax: 443-923-7696, Email: kaufmann@kennedykrieger.org. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access 1.) INTRODUCTIONThe frontal lobe is the region of the brain associated with executive control and planning, including functions such as response inhibition and working memory (Tekin & Cummings, 2002;Alvarez & Emory, 2006). The frontal lobe is also involved in motivational aspects of behavior and high-order motor control (Tekin et al., 2002;Ashe et al., 2006;Graziano & Aflalo, 2007). Due to this wide range of complex brain functions, abnormalities in frontal lobe structure and function have been hypothesized to contribute to many neuropsychiatric disorders, including obsessive-compulsive disorder (OCD), schizophrenia, depression and bipolar disorder (Tekin et al., 2002;Yamasue et al., 2004;Suzuki et al., 2005;Shad et al., 2006). F...

Overflow movements and white matter abnormalities in ADHD

“…Deficits in motor response inhibition in ADHD can be attributed to motor/premotor circuits . The volume reductions in these areas appear to be due to decreases in their white matter components (Ranta et al, 2009), suggesting a primarily axonal abnormality in ADHD patients. The presence of motor overflow supports the hypothesis that the brain abnormalities in ADHD have a developmental origin.…”

“…The definition of DWM allowed a distinction between short association fibers (gyral white matter) and long or projecting association fibers DWM (Makris et al, 1999). The volume reductions in the pre-SMA appear to be preferentially due to decreases in their white matter components, suggesting a primarily axonal abnormality in the ADHD group (Ranta et al, 2009).…”

Automated MRI Parcellation of the Frontal Lobe

“…The groups differed on diagnosis (X 2 =19.893, p<0.001) and total cerebral volume (TCV) (F=4.052, p=0.047), with the atlas group having no ADHD or ASD subjects and larger TCV than the analysis group. The group difference in TCV is in part due to the differing number of ADHD subjects, who have previously been shown to have lower TCV by 6-7% in this age range (Ranta, et al 2009;Wolosin, et al 2007). …”

“…The theoretical foundations for the divisions used in our protocol include the sometimes divergent relationships between gyral/sulcal landmarks and cytoarchitectonical and functional organization of the cortex (Fischl, et al 2008;Geyer, et al 2000;Ongur, et al 2003; Zilles 1990;Zilles, et al 1997) and the increasing body of information on the functional relevance of discrete frontal sub-regions for neuropsychiatric disorders. The premotor and prefrontal modules are divided into several anatomo-physiologic sub-regions based on the foundations of traditional and more recent anatomical and functional literature (Bouret and Richmond 2010;Costafreda, et al 2006;Graziano and Aflalo 2007;Howard, et al 2003;Lacerda, et al 2003;McGlinchey-Berroth, et al 1995;Ongur, et al 2003;Rushworth, et al 2007;Rypma 2006;Tekin and Cummings 2002;Tzourio-Mazoyer, et al 2002).In two prior studies (Kates, et al 2002b;Ranta, et al 2009) we presented a manual frontal lobe parcellation protocol that relies on sulcal-gyral landmarks to delineate functionally distinct frontal sub-regions: i.e., primary motor cortex, anterior cingulate, deep white matter, premotor cortex regions (supplementary motor complex (SMC), frontal eye field (FEF) and lateral premotor cortex (LPM)) and prefrontal cortex (PFC) regions (medial PFC, dorsolateral PFC (DLPFC), inferior PFC, lateral orbitofrontal cortex (OFC) and medial OFC) (see Figures 1 and 2, Table I). Instead of relying only on prominent gyri and sulci, this …”

“…Continuing debate on the best methods for evaluating the relative reliability, sensitivity and validity of manual versus automated parcellations exists. However, in papers that have addressed the question it is generally agreed that automated methods provide important gains in efficiency, consistency, statistical power and reproducibility compared to manual parcellation, which is inherently timeconsuming and subject to rater error (Barnes, et al 2007;Cherbuin, et al 2009;Dewey, et al 2010;Fischl, et al 2002;Hasboun, et al 1996;Lehmann, et al 2010;Morey, et al 2009;Pardoe, et al 2009;Tae, et al 2008).In pursuance of the goal of examining the roles of functionally relevant frontal lobe regions in a variety of neuropsychological disorders, we have incorporated the Ranta et al (Ranta, et al 2009) parcellation scheme into two automated programs: FreeSurfer (FS) ) and TOADS-CRUISE (T-C) (Topology-preserving, AnatomyDriven Segmentation-Cortical Reconstruction Using Implicit Surface Evolution) (Bazin and Pham 2008;Han, et al 2004;Wan, et al 2008). We selected two programs in order to allow a more powerful examination of validity and reliability of the automated methods.…”