Literature DB >> 7991759

Fractal analysis of the boundary between white matter and cerebral cortex in magnetic resonance images: a controlled study of schizophrenic and manic-depressive patients.

E Bullmore1, M Brammer, I Harvey, R Persaud, R Murray, M Ron.   

Abstract

This paper reports development of a computerized ('box-counting') method for estimation of fractal dimension (FD) of the magnetic resonance image (MRI) boundary between cerebral cortex and white matter; and the application of this method to MRIs of 39 schizophrenics (SZs), 23 manic-depressives (MDs) and 31 controls (CONs). Mean FD across all diagnostic groups was 1.402; 95% confidence interval (CI) 1.399 to 1.406. Mean FD was greater in boundaries extracted from manic-depressive patients than in boundaries extracted from controls (difference between MD and CON mean FDs = 0.008; 95% CI -0.002 to +0.018); and less in schizophrenics than in controls (difference between SZ and CON mean FDs = -0.003; 95% CI -0.011 to +0.005). Mean FD was positively correlated with subcortical volume and anterior cerebral volume, and negatively correlated with sulcal cerebrospinal fluid volume. Significant differences in mean FD between diagnostic groups were demonstrated by analysis of covariance (ANCOVA; P < 0.01), with age and volumetric measures of brain size as covariates; and manic-depressive boundaries were shown to have significantly greater values for residual FD (after controlling for effects of brain size) than boundaries extracted from controls (t test; P < 0.05). It is proposed that FD is a useful measure of clinically relevant differences in the complexity of MRI boundaries.

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Year:  1994        PMID: 7991759     DOI: 10.1017/s0033291700027926

Source DB:  PubMed          Journal:  Psychol Med        ISSN: 0033-2917            Impact factor:   7.723


  16 in total

1.  Colored noise and computational inference in neurophysiological (fMRI) time series analysis: resampling methods in time and wavelet domains.

Authors:  E Bullmore; C Long; J Suckling; J Fadili; G Calvert; F Zelaya; T A Carpenter; M Brammer
Journal:  Hum Brain Mapp       Date:  2001-02       Impact factor: 5.038

2.  Fractal dimension in human cortical surface: multiple regression analysis with cortical thickness, sulcal depth, and folding area.

Authors:  Kiho Im; Jong-Min Lee; Uicheul Yoon; Yong-Wook Shin; Soon Beom Hong; In Young Kim; Jun Soo Kwon; Sun I Kim
Journal:  Hum Brain Mapp       Date:  2006-12       Impact factor: 5.038

3.  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

4.  Complexity of low-frequency blood oxygen level-dependent fluctuations covaries with local connectivity.

Authors:  Jeffrey S Anderson; Brandon A Zielinski; Jared A Nielsen; Michael A Ferguson
Journal:  Hum Brain Mapp       Date:  2013-02-18       Impact factor: 5.038

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

Authors:  Richard D King; Brandon Brown; Michael Hwang; Tina Jeon; Anuh T George
Journal:  Neuroimage       Date:  2010-06-25       Impact factor: 6.556

Review 6.  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

7.  An entorhinal cortex sulcal pattern is associated with Alzheimer's disease.

Authors:  Jiong Zhan; Miroslaw Brys; Lidia Glodzik; Wai Tsui; Elizabeth Javier; Jerzy Wegiel; Izabela Kuchna; Elizabeth Pirraglia; Yi Li; Lisa Mosconi; Leslie A Saint Louis; Remigiusz Switalski; Susan De Santi; Byeong C Kim; Thomas Wisniewski; Barry Reisberg; Matthew Bobinski; Mony J de Leon
Journal:  Hum Brain Mapp       Date:  2009-03       Impact factor: 5.038

8.  Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.

Authors:  Danielle S Bassett; Daniel L Greenfield; Andreas Meyer-Lindenberg; Daniel R Weinberger; Simon W Moore; Edward T Bullmore
Journal:  PLoS Comput Biol       Date:  2010-04-22       Impact factor: 4.475

9.  Fractal dimension assessment of brain white matter structural complexity post stroke in relation to upper-extremity motor function.

Authors:  Luduan Zhang; Andrew J Butler; Chang-Kai Sun; Vinod Sahgal; George F Wittenberg; Guang H Yue
Journal:  Brain Res       Date:  2008-06-11       Impact factor: 3.252

10.  Morphometric analysis of the C57BL/6J mouse brain.

Authors:  A Badea; A A Ali-Sharief; G A Johnson
Journal:  Neuroimage       Date:  2007-06-07       Impact factor: 6.556

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