Brain microstructural changes and cognitive function in non-demented essential tremor patients: a diffusion tensor imaging study

Şengül, Yıldızhan; Temur, Hafize Otcu; Corakci, Zeynep; Şengül, Hakan Serdar; Dowd, Hollie; Üstün, İsmet; Alkan, Alpay; Louis, Elan D.

doi:10.1080/00207454.2020.1803859

Cited by 11 publications

(9 citation statements)

References 64 publications

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“…Meanwhile, machine learning in the paper also found that the abnormalities of bilateral thalamus in both ET and PD, which may confirm that the compensatory effect on the CTC circuit and the occurrence of tremor is related to the abnormality of the CTC circuit. Moreover, this paper also found abnormalities of basal ganglia of ET and PD (such as putamen and caudate) with machine learning, which is consistent with [ 12 , 44 ]. In addition, the increase of gray matter volume of MTG in the paper is partially consistent with [ 10 ], which has proposed that the function of MTG involved motion perception and eye movement, and some ET patients have long-term head tremor, which may need to be supplemented by maintaining visual stability.…”

Section: Discussionsupporting

confidence: 89%

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

et al. 2022

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Background Since both essential tremor (ET) and Parkinson’s disease (PD) are movement disorders and share similar clinical symptoms, it is very difficult to recognize the differences in the presentation, course, and treatment of ET and PD, which leads to misdiagnosed commonly. Purpose Although neuroimaging biomarker of ET and PD has been investigated based on statistical analysis, it is unable to assist the clinical diagnosis of ET and PD and ensure the efficiency of these biomarkers. The aim of the study was to identify the neuroimaging biomarkers of ET and PD based on structural magnetic resonance imaging (MRI). Moreover, the study also distinguished ET from PD via these biomarkers to validate their classification performance. Methods This study has developed and implemented a three-level machine learning framework to identify and distinguish ET and PD. First of all, at the model-level assessment, the searchlight-based machine learning method has been used to identify the group differences of patients (ET/PD) with normal controls (NCs). And then, at the feature-level assessment, the stability of group differences has been tested based on structural brain atlas separately using the permutation test to identify the robust neuroimaging biomarkers. Furthermore, the identified biomarkers of ET and PD have been applied to classify ET from PD based on machine learning techniques. Finally, the identified biomarkers have been compared with the previous findings of the biology-level assessment. Results According to the biomarkers identified by machine learning, this study has found widespread alterations of gray matter (GM) for ET and large overlap between ET and PD and achieved superior classification performance (PCA + SVM, accuracy = 100%). Conclusions This study has demonstrated the significance of a machine learning framework to identify and distinguish ET and PD. Future studies using a large data set are needed to confirm the potential clinical application of machine learning techniques to discern between PD and ET.

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Section: Discussionsupporting

confidence: 89%

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

et al. 2022

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“…attention, executive functions, language, and verbal and visual memory, compared to HS, although neuropsychological examination showed that the global scores were within normal range. More recently, Sengul et al [36] found altered DTI measures in the prefrontal cortical areas, paralimbic and limbic structures, and WM associative bundles, which correlated with various cognitive domains, e.g. attention, visuospatial and executive function, and verbal memory, in non-demented ET patients.…”

Section: White Mattermentioning

confidence: 98%

“…The possible correlation between WM abnormalities and cognitive profile was also investigated [24,[34][35][36]. Bhalsing et al [34] found that ET patients with cognitive impairment had significant WM abnormalities in the bilateral frontoparietal regions and in the cingulum, inferior and superior longitudinal and uncinate fasciculi, anterior thalamic radiations, and posterior lobe of the cerebellum.…”

Section: White Mattermentioning

confidence: 99%

The Contribution of Neuroimaging to the Understanding of Essential Tremor Pathophysiology: a Systematic Review

et al. 2021

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Essential tremor (ET) is one of the most common movement disorders. Over the last 10 years, magnetic resonance imaging (MRI) has shed light on the structural and functional abnormalities possibly involved in ET pathophysiology. In this systematic review, we aimed to identify the cortical and subcortical structures involved and the role that different brain areas play in the pathophysiology of motor and non-motor ET features. We found that structural (grey and white matter) cerebellar damage and connectivity alterations between the cerebellum and various cortical areas play a role in both motor and nonmotor symptoms of ET. In particular, many studies found an association between MRI findings and non-motor symptoms.

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“…In line with our findings, task‐based fMRI studies using the Stroop test and working memory paradigms have revealed increased activation of the prefrontal cortex in ET (Cerasa et al, 2010; Passamonti et al, 2011). A diffusion tensor imaging study in ET found that abnormal projections of the insula were significantly related to memory and executive function (Sengul et al, 2020). Thus, regional activity changes in medial frontal cortex and insula may be related to emotional and cognitive dysfunction in patients with ET.…”

Section: Discussionmentioning

confidence: 99%

Abnormalities of intrinsic brain activity in essential tremor: A meta‐analysis of resting‐state functional imaging

Lan

Suo

et al. 2021

Human Brain Mapping

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Neuroimaging studies using a variety of techniques have demonstrated abnormal patterns of spontaneous brain activity in patients with essential tremor (ET). However, the findings are variable and inconsistent, hindering understanding of underlying neuropathology. We conducted a meta‐analysis of whole‐brain resting‐state functional neuroimaging studies in ET compared to healthy controls (HC), using anisotropic effect‐size seed‐based d mapping, to identify the most consistent brain activity alterations and their relation to clinical features. After systematic literature search, we included 13 studies reporting 14 comparisons, describing 286 ET patients and 254 HC. Subgroup analyses were conducted considering medication status, head tremor status, and methodological factors. Brain activity in ET is altered not only in the cerebellum and cerebral motor cortex, but also in nonmotor cortical regions including prefrontal cortex and insula. Most of the results remained unchanged in subgroup analyses of patients with head tremor, medication‐naive patients, studies with statistical threshold correction, and the large subgroup of studies using functional magnetic resonance imaging. These findings not only show consistent and robust abnormalities in specific brain regions but also provide new information on the biology of patient heterogeneity, and thus help to elucidate the pathophysiology of ET.

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Brain microstructural changes and cognitive function in non-demented essential tremor patients: a diffusion tensor imaging study

Abstract: Group 1 * (N=17) Group 2 (N=23) p value * ATTENTION

Cited by 11 publications

References 64 publications

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

The Contribution of Neuroimaging to the Understanding of Essential Tremor Pathophysiology: a Systematic Review

Abnormalities of intrinsic brain activity in essential tremor: A meta‐analysis of resting‐state functional imaging

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Brain microstructural changes and cognitive function in non-demented essential tremor patients: a diffusion tensor imaging study

Abstract: Group 1 * (N=17) Group 2 ** (N=23) p value *** ATTENTION

Cited by 11 publications

References 64 publications

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

The Contribution of Neuroimaging to the Understanding of Essential Tremor Pathophysiology: a Systematic Review

Abnormalities of intrinsic brain activity in essential tremor: A meta‐analysis of resting‐state functional imaging

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Abstract: Group 1 * (N=17) Group 2 (N=23) p value * ATTENTION