16
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Multicenter stability of resting state fMRI in the detection of Alzheimer's disease and amnestic MCI

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          In monocentric studies, patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia exhibited alterations of functional cortical connectivity in resting-state functional MRI (rs-fMRI) analyses. Multicenter studies provide access to large sample sizes, but rs-fMRI may be particularly sensitive to multiscanner effects.

          Methods

          We used data from five centers of the “German resting-state initiative for diagnostic biomarkers” ( psymri.org), comprising 367 cases, including AD patients, MCI patients and healthy older controls, to assess the influence of the distributed acquisition on the group effects. We calculated accuracy of group discrimination based on whole brain functional connectivity of the posterior cingulate cortex (PCC) using pooled samples as well as second-level analyses across site-specific group contrast maps.

          Results

          We found decreased functional connectivity in AD patients vs. controls, including clusters in the precuneus, inferior parietal cortex, lateral temporal cortex and medial prefrontal cortex. MCI subjects showed spatially similar, but less pronounced, differences in PCC connectivity when compared to controls. Group discrimination accuracy for AD vs. controls (MCI vs. controls) in the test data was below 76% (72%) based on the pooled analysis, and even lower based on the second level analysis stratified according to scanner. Only a subset of quality measures was useful to detect relevant scanner effects.

          Conclusions

          Multicenter rs-fMRI analysis needs to employ strict quality measures, including visual inspection of all the data, to avoid seriously confounded group effects. While pending further confirmation in biomarker stratified samples, these findings suggest that multicenter acquisition limits the use of rs-fMRI in AD and MCI diagnosis.

          Highlights

          • Diagnostic accuracy of multicenter rs-fMRI in AD and MCI

          • Quality metrics for multicenter rs-fMRI that should be used

          • Quality metrics for multicenter rs-fMRI that should not be used

          • Multicenter rs-fMRI will have limited diagnostic use in clinical routine diagnosis

          Related collections

          Most cited references35

          • Record: found
          • Abstract: found
          • Article: not found

          Disruption of functional connectivity in clinically normal older adults harboring amyloid burden.

          Amyloid deposition is present in 20-50% of nondemented older adults yet the functional consequences remain unclear. The current study found that amyloid accumulation is correlated with functional disruption of the default network as measured by intrinsic activity correlations. Clinically normal participants (n = 38, aged 60-88 years) were characterized using (11)C-labeled Pittsburgh Compound B positron emission tomography imaging to estimate fibrillar amyloid burden and, separately, underwent functional magnetic resonance imaging (fMRI). The integrity of the default network was estimated by correlating rest-state fMRI time courses extracted from a priori regions including the posterior cingulate, lateral parietal, and medial prefrontal cortices. Clinically normal participants with high amyloid burden displayed significantly reduced functional correlations within the default network relative to participants with low amyloid burden. These reductions were also observed when amyloid burden was treated as a continuous, rather than a dichotomous, measure and when controlling for age and structural atrophy. Whole-brain analyses initiated by seeding the posterior cingulate cortex, a region of high amyloid burden in Alzheimer's disease, revealed significant disruption in the default network including functional disconnection of the hippocampal formation.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Resting-state fMRI changes in Alzheimer's disease and mild cognitive impairment.

            Regional functional connectivity (FC) of 39 patients with Alzheimer's disease (AD), 23 patients with mild cognitive impairment (MCI), and 43 healthy elderly controls was studied using resting-state functional magnetic resonance imaging (rs-fMRI). After a mean follow-up of 2.8 ± 1.9 years, 7 MCI patients converted to AD, while 14 patients remained cognitively stable. Resting-state functional magnetic resonance imaging scans were analyzed using independent component analysis (ICA), followed by a "dual-regression" technique to create and compare subject-specific maps of each independent spatiotemporal component, correcting for age, sex, and gray matter atrophy. AD patients displayed lower FC within the default-mode network (DMN) in the precuneus and posterior cingulate cortex compared with controls, independent of cortical atrophy. Regional FC values of MCI patients were numerically in between AD patients and controls, but only the difference between AD and stable MCI patients was statistically significant. Correlation with cognitive dysfunction demonstrated the clinical relevance of FC changes within the DMN. In conclusion, clinically relevant decreased FC within the DMN was observed in AD. Copyright © 2012 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Volumetry of hippocampus and amygdala with high-resolution MRI and three-dimensional analysis software: minimizing the discrepancies between laboratories.

              Within the medial temporal lobe, both the hippocampus and amygdala are frequently targeted by researchers and clinicians for volumetric analysis based on magnetic resonance imaging (MRI). However, different data acquisition techniques, analysis software and anatomical boundaries have in the past made it difficult to compare results of MRI studies from different laboratories. In order to reduce these differences, a segmentation protocol was established with 40 healthy normal control subjects recently scanned in our laboratory. Data acquisition was performed with a three-dimensional gradient echo technique, and scans were corrected for non-uniformity and registered into standard stereotaxic space prior to segmentation. Volumetric analysis was performed manually using three-dimensional software that allows simultaneous analysis of sagittal, coronal and horizontal images. Intra- and inter-rater coefficients yielded correlation coefficients comparable with other protocols. The hippocampal volume was larger in the right hemisphere (3324 versus 3208 mm(3)), while no interhemispheric differences for the amygdala (1154 versus 1160 mm(3)) could be observed. Most importantly, results from recent segmentation protocols for hippocampus and amygdala seem to approach each other with regard to mean volumes and interhemispheric differences. This indicates that the advances in scanning technique, volume preparation and segmentation protocols allow a more precise definition of medial temporal lobe structures with MRI, and that results for mean volumes for hippocampus and amygdala from different laboratories will eventually become comparable.
                Bookmark

                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                18 January 2017
                2017
                18 January 2017
                : 14
                : 183-194
                Affiliations
                [a ]Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany
                [b ]DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany
                [c ]Institute of Cognitive Neurology and Dementia Research (IKND), Department of Psychiatry and Psychotherapy, Otto von Guericke University, Germany and German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
                [d ]Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
                [e ]Department of Neuroradiology of Klinikum rechts der Isar, Technische Universität München, Department of Psychiatry of Klinikum rechts der Isar, TUM-Neuroimaging Center, Einsteinstr. 1, 81675 Munich, Germany
                [f ]Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
                [g ]Department of Psychiatry, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
                [h ]Department of Psychiatry and Psychotherapy, Section of Gerontopsychiatry and Neuropsychology, Faculty of Medicine, University of Freiburg, Germany
                [i ]Leibniz Institute for Neurobiology, Magdeburg, Germany
                [j ]Department of Psychiatry, University Tübingen, Germany
                [k ]University Hospital of Old Age Psychiatry, Bern, Switzerland
                Author notes
                [* ]Corresponding author at: Department of Psychosomatic Medicine, University Medicine Rostock, DZNE, Gehlsheimer Str. 20, 18147 Rostock, Germany.Department of Psychosomatic MedicineUniversity Medicine RostockDZNEGehlsheimer Str. 20Rostock18147Germany stefan.teipel@ 123456med.uni-rostock.de
                Article
                S2213-1582(17)30018-9
                10.1016/j.nicl.2017.01.018
                5279697
                28180077
                f3f88048-d352-4522-9d96-de146e36f70f
                © 2017 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 6 June 2016
                : 30 November 2016
                : 17 January 2017
                Categories
                Regular Article

                Comments

                Comment on this article