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      Neuroimaging in Parkinson’s disease dementia: connecting the dots

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          Abstract

          Dementia is a common and devastating symptom of Parkinson’s disease but the anatomical substrate remains unclear. Some evidence points towards hippocampal involvement but neuroimaging abnormalities have been reported throughout the brain and are largely inconsistent across studies. Here, we test whether these disparate neuroimaging findings for Parkinson’s disease dementia localize to a common brain network. We used a literature search to identify studies reporting neuroimaging correlates of Parkinson’s dementia (11 studies, 385 patients). We restricted our search to studies of brain atrophy and hypometabolism that compared Parkinson’s patients with dementia to those without cognitive involvement. We used a standard coordinate-based activation likelihood estimation meta-analysis to assess for consistency in the neuroimaging findings. We then used a new approach, coordinate-based network mapping, to test whether neuroimaging findings localized to a common brain network. This approach uses resting-state functional connectivity from a large cohort of normative subjects (n = 1000) to identify the network of regions connected to a reported neuroimaging coordinate. Activation likelihood estimation meta-analysis failed to identify any brain regions consistently associated with Parkinson’s dementia, showing major heterogeneity across studies. In contrast, coordinate-based network mapping found that these heterogeneous neuroimaging findings localized to a specific brain network centred on the hippocampus. Next, we tested whether this network showed symptom specificity and stage specificity by performing two further analyses. We tested symptom specificity by examining studies of Parkinson’s hallucinations (9 studies, 402 patients) that are frequently co-morbid with Parkinson’s dementia. We tested for stage specificity by using studies of mild cognitive impairment in Parkinson’s disease (15 studies, 844 patients). Coordinate-based network mapping revealed that correlates of visual hallucinations fell within a network centred on bilateral lateral geniculate nucleus and correlates of mild cognitive impairment in Parkinson’s disease fell within a network centred on posterior default mode network. In both cases, the identified networks were distinct from the hippocampal network of Parkinson’s dementia. Our results link heterogeneous neuroimaging findings in Parkinson’s dementia to a common network centred on the hippocampus. This finding was symptom and stage-specific, with implications for understanding Parkinson’s dementia and heterogeneity of neuroimaging findings in general.

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          Most cited references81

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          Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases.

          Few detailed clinico-pathological correlations of Parkinson's disease have been published. The pathological findings in 100 patients diagnosed prospectively by a group of consultant neurologists as having idiopathic Parkinson's disease are reported. Seventy six had nigral Lewy bodies, and in all of these Lewy bodies were also found in the cerebral cortex. In 24 cases without Lewy bodies, diagnoses included progressive supranuclear palsy, multiple system atrophy, Alzheimer's disease, Alzheimer-type pathology, and basal ganglia vascular disease. The retrospective application of recommended diagnostic criteria improved the diagnostic accuracy to 82%. These observations call into question current concepts of Parkinson's disease as a single distinct morbid entity.
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            Diagnostic criteria for Parkinson disease.

            The clinical diagnosis of Parkinson disease (PD) is based on the identification of some combination of the cardinal motor signs of bradykinesia, rigidity, tremor, and postural instability, but few attempts have been made to develop explicit diagnostic criteria. We propose a clinical diagnostic classification based on a comprehensive review of the literature regarding the sensitivity and specificity of the characteristic clinical features of PD. Three levels of diagnostic confidence are differentiated: Definite, Probable, and Possible. The diagnoses of Possible and Probable PD are based on clinical criteria alone. Neuropathologic confirmation is required for the diagnosis of Definite PD in patients with the clinical diagnosis of Possible or Probable PD. Criteria for histopathologic confirmation of PD are also presented.
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              Connectivity Predicts deep brain stimulation outcome in Parkinson disease.

              The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort.
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                Author and article information

                Journal
                Brain Communications
                Oxford University Press (OUP)
                2632-1297
                2019
                January 01 2019
                2019
                January 01 2019
                July 08 2019
                : 1
                : 1
                Affiliations
                [1 ]Dementia Research Centre, UCL, London
                [2 ]Wellcome Centre for Human Neuroimaging, UCL, London
                [3 ]Berenson-Allen Center, Beth Israel Deaconess Medical Center, Harvard Medical Center, Boston, MA, USA
                [4 ]Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
                [5 ]Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
                [6 ]Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
                Article
                10.1093/braincomms/fcz006
                46a6a221-3b8c-451e-87c7-933401051d7a
                © 2019

                http://creativecommons.org/licenses/by/4.0/

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