Literature DB >> 20600974

Fractal dimension analysis of the cortical ribbon in mild Alzheimer's disease.

Richard D King1, Brandon Brown, Michael Hwang, Tina Jeon, Anuh T George.   

Abstract

Fractal analysis methods are used to quantify the complexity of the human cerebral cortex. Many recent studies have focused on high resolution three-dimensional reconstructions of either the outer (pial) surface of the brain or the junction between the gray and white matter, but ignore the structure between these surfaces. This study uses a new method to incorporate the entire cortical thickness. Data were obtained from the Alzheimer's Disease (AD) Neuroimaging Initiative database (Control N=35, Mild AD N=35). Image segmentation was performed using a semi-automated analysis program. The fractal dimension of three cortical models (the pial surface, gray/white surface and entire cortical ribbon) were calculated using a custom cube-counting triangle-intersection algorithm. The fractal dimension of the cortical ribbon showed highly significant differences between control and AD subjects (p<0.001). The inner surface analysis also found smaller but significant differences (p<0.05). The pial surface dimensionality was not significantly different between the two groups. All three models had a significant positive correlation with the cortical gyrification index (r>0.55, p<0.001). Only the cortical ribbon had a significant correlation with cortical thickness (r=0.832, p<0.001) and the Alzheimer's Disease Assessment Scale cognitive battery (r=-0.513, p=0.002). The cortical ribbon dimensionality showed a larger effect size (d=1.12) in separating control and mild AD subjects than cortical thickness (d=1.01) or gyrification index (d=0.84). The methodological change shown in this paper may allow for further clinical application of cortical fractal dimension as a biomarker for structural changes that accrue with neurodegenerative diseases. Copyright 2010 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 20600974      PMCID: PMC2942777          DOI: 10.1016/j.neuroimage.2010.06.050

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  34 in total

1.  Mapping cortical asymmetry and complexity patterns in normal children.

Authors:  R E Blanton; J G Levitt; P M Thompson; K L Narr; L Capetillo-Cunliffe; A Nobel; J D Singerman; J T McCracken; A W Toga
Journal:  Psychiatry Res       Date:  2001-07-01       Impact factor: 3.222

2.  Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

Authors:  Bruce Fischl; David H Salat; Evelina Busa; Marilyn Albert; Megan Dieterich; Christian Haselgrove; Andre van der Kouwe; Ron Killiany; David Kennedy; Shuna Klaveness; Albert Montillo; Nikos Makris; Bruce Rosen; Anders M Dale
Journal:  Neuron       Date:  2002-01-31       Impact factor: 17.173

3.  Analysis of the hemispheric asymmetry using fractal dimension of a skeletonized cerebral surface.

Authors:  Jong-Min Lee; Uicheul Yoon; Jae-Jin Kim; In Young Kim; Dong Soo Lee; Jun Soo Kwon; Sun I Kim
Journal:  IEEE Trans Biomed Eng       Date:  2004-08       Impact factor: 4.538

4.  Geometrically accurate topology-correction of cortical surfaces using nonseparating loops.

Authors:  Florent Ségonne; Jenni Pacheco; Bruce Fischl
Journal:  IEEE Trans Med Imaging       Date:  2007-04       Impact factor: 10.048

5.  A robust and accurate algorithm for estimating the complexity of the cortical surface.

Authors:  Jiefeng Jiang; Wanlin Zhu; Feng Shi; Yuanchao Zhang; Lei Lin; Tianzi Jiang
Journal:  J Neurosci Methods       Date:  2008-04-25       Impact factor: 2.390

6.  Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system.

Authors:  B Fischl; M I Sereno; A M Dale
Journal:  Neuroimage       Date:  1999-02       Impact factor: 6.556

7.  Three-dimensional fractal analysis of the white matter surface from magnetic resonance images of the human brain.

Authors:  S L Free; S M Sisodiya; M J Cook; D R Fish; S D Shorvon
Journal:  Cereb Cortex       Date:  1996 Nov-Dec       Impact factor: 5.357

8.  Fractal dimension analysis for quantifying cerebellar morphological change of multiple system atrophy of the cerebellar type (MSA-C).

Authors:  Yu-Te Wu; Kuo-Kai Shyu; Chii-Wen Jao; Zun-Yun Wang; Bing-Wen Soong; Hsiu-Mei Wu; Po-Shan Wang
Journal:  Neuroimage       Date:  2009-07-25       Impact factor: 6.556

9.  Shape analysis of the middle cranial fossa of schizophrenic patients. A computerized tomographic study.

Authors:  M F Casanova; D G Daniel; T E Goldberg; R L Suddath; D R Weinberger
Journal:  Schizophr Res       Date:  1989 Jul-Oct       Impact factor: 4.939

10.  Fractal dimension in human cerebellum measured by magnetic resonance imaging.

Authors:  Jing Z Liu; Lu D Zhang; Guang H Yue
Journal:  Biophys J       Date:  2003-12       Impact factor: 4.033

View more
  46 in total

Review 1.  The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Enchi Liu; John C Morris; Ronald C Petersen; Andrew J Saykin; Mark E Schmidt; Leslie Shaw; Judith A Siuciak; Holly Soares; Arthur W Toga; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2011-11-02       Impact factor: 21.566

2.  Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility.

Authors:  Joaquín Goñi; Olaf Sporns; Hu Cheng; Maite Aznárez-Sanado; Yang Wang; Santiago Josa; Gonzalo Arrondo; Vincent P Mathews; Tom A Hummer; William G Kronenberger; Andrea Avena-Koenigsberger; Andrew J Saykin; María A Pastor
Journal:  Neuroimage       Date:  2013-07-03       Impact factor: 6.556

3.  Evaluation of the 3D fractal dimension as a marker of structural brain complexity in multiple-acquisition MRI.

Authors:  Stephan Krohn; Martijn Froeling; Alexander Leemans; Dirk Ostwald; Pablo Villoslada; Carsten Finke; Francisco J Esteban
Journal:  Hum Brain Mapp       Date:  2019-05-15       Impact factor: 5.038

4.  Cortical complexity as a measure of age-related brain atrophy.

Authors:  Christopher R Madan; Elizabeth A Kensinger
Journal:  Neuroimage       Date:  2016-04-19       Impact factor: 6.556

5.  Universality in human cortical folding in health and disease.

Authors:  Yujiang Wang; Joe Necus; Marcus Kaiser; Bruno Mota
Journal:  Proc Natl Acad Sci U S A       Date:  2016-10-24       Impact factor: 11.205

Review 6.  2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Jesse Cedarbaum; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Johan Luthman; John C Morris; Ronald C Petersen; Andrew J Saykin; Leslie Shaw; Li Shen; Adam Schwarz; Arthur W Toga; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2015-06       Impact factor: 21.566

7.  The association of grey matter volume and cortical complexity with individual differences in children's arithmetic fluency.

Authors:  Brecht Polspoel; Maaike Vandermosten; Bert De Smedt
Journal:  Neuropsychologia       Date:  2019-12-03       Impact factor: 3.139

Review 8.  A healthy dose of chaos: Using fractal frameworks for engineering higher-fidelity biomedical systems.

Authors:  Anastasia Korolj; Hau-Tieng Wu; Milica Radisic
Journal:  Biomaterials       Date:  2019-07-15       Impact factor: 12.479

9.  Voxel and surface-based topography of memory and executive deficits in mild cognitive impairment and Alzheimer's disease.

Authors:  Kwangsik Nho; Shannon L Risacher; Paul K Crane; Charles DeCarli; M Maria Glymour; Christian Habeck; Sungeun Kim; Grace J Lee; Elizabeth Mormino; Shubhabrata Mukherjee; Li Shen; John D West; Andrew J Saykin
Journal:  Brain Imaging Behav       Date:  2012-12       Impact factor: 3.978

10.  Complexity analysis of cortical surface detects changes in future Alzheimer's disease converters.

Authors:  Juan Ruiz de Miras; Víctor Costumero; Vicente Belloch; Joaquín Escudero; César Ávila; Jorge Sepulcre
Journal:  Hum Brain Mapp       Date:  2017-08-30       Impact factor: 5.038

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.