Literature DB >> 22562047

Mapping inter-regional connectivity of the entire cortex to characterize major depressive disorder: a whole-brain diffusion tensor imaging tractography study.

Mayuresh S Korgaonkar1, Nicholas J Cooper, Leanne M Williams, Stuart M Grieve.   

Abstract

Diffusion tensor imaging (DTI) can be used to study the organization of brain white matter noninvasively. The aim of this study was to present a proof of concept for integrating DTI with high-resolution anatomical (T1) images to map and assess inter-regional connectivity across the entire cortex in a cohort of healthy participants and compared with patients with major depressive disorder. We used MRI data of 23 patients and 23 matched controls, assessed as part of baseline testing in the International Study to Predict Optimized Treatment in Depression (iSPOT-D). Freesurfer was used to analyze the T1 images to automatically label 35 gyral-based areas for each hemisphere. DTI tractography was performed to parcellate intercortical tracts using each of these areas in seed-target combinations. We quantified fractional anisotropy, number-of-fiber connections, and fiber path length for each DTI connection, with the goal of identifying the best measure or combination of measures to characterize major depression. The best classification accuracy for the individual measures was achieved using the number-of-fibers data, whereas the combination model provided a slight improvement. The most discriminant features between the two groups were for white matter associated with the limbic, frontal, and thalamic projection fibers and as part of cortical connections between the left inferior temporal and the postcentral cortex; the left parstriangularis and the left superior frontal; the left cuneus and the corpus callosum; the left lingual and the right lateral occipital, the right superior parietal and the right superior temporal cortices; and the right inferior parietal and the right insula and postcentral cortices.

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Year:  2012        PMID: 22562047     DOI: 10.1097/WNR.0b013e3283546264

Source DB:  PubMed          Journal:  Neuroreport        ISSN: 0959-4965            Impact factor:   1.837


  25 in total

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2.  Group differences in MEG-ICA derived resting state networks: Application to major depressive disorder.

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3.  Edge-Centered DTI Connectivity Analysis: Application to Schizophrenia.

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Journal:  Neuroinformatics       Date:  2015-10

Review 4.  Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging.

Authors:  Jing Jiang; You-Jin Zhao; Xin-Yu Hu; Ming-Ying Du; Zi-Qi Chen; Min Wu; Kai-Ming Li; Hong-Yan Zhu; Poornima Kumar; Qi-Yong Gong
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5.  DTI tractography and white matter fiber tract characteristics in euthymic bipolar I patients and healthy control subjects.

Authors:  Carinna M Torgerson; Andrei Irimia; Alex D Leow; George Bartzokis; Teena D Moody; Robin G Jennings; Jeffry R Alger; John Darrell Van Horn; Lori L Altshuler
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6.  The ENGAGE study: Integrating neuroimaging, virtual reality and smartphone sensing to understand self-regulation for managing depression and obesity in a precision medicine model.

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Journal:  Behav Res Ther       Date:  2017-10-07

7.  MicroRNA-21: Expression in oligodendrocytes and correlation with low myelin mRNAs in depression and alcoholism.

Authors:  José Javier Miguel-Hidalgo; Katherine O Hall; Hannah Bonner; Anna M Roller; Maryam Syed; Casey J Park; Jana P Ball; Marc E Rothenberg; Craig A Stockmeier; Damian G Romero
Journal:  Prog Neuropsychopharmacol Biol Psychiatry       Date:  2017-08-09       Impact factor: 5.067

Review 8.  Age-Related Hearing Loss and the Development of Cognitive Impairment and Late-Life Depression: A Scoping Overview.

Authors:  Rahul K Sharma; Alexander Chern; Justin S Golub
Journal:  Semin Hear       Date:  2021-04-15

9.  Cortico-cortical white matter motor pathway microstructure is related to psychomotor retardation in major depressive disorder.

Authors:  Tobias Bracht; Andrea Federspiel; Susanne Schnell; Helge Horn; Oliver Höfle; Roland Wiest; Thomas Dierks; Werner Strik; Thomas J Müller; Sebastian Walther
Journal:  PLoS One       Date:  2012-12-20       Impact factor: 3.240

10.  Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial.

Authors:  Stuart M Grieve; Mayuresh S Korgaonkar; Amit Etkin; Anthony Harris; Stephen H Koslow; Stephen Wisniewski; Alan F Schatzberg; Charles B Nemeroff; Evian Gordon; Leanne M Williams
Journal:  Trials       Date:  2013-07-18       Impact factor: 2.279

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