Evidence map›Paper›PMID 39463819›Full record

ArticleFrontiers in aging neuroscience2024

Diffusion and functional MRI reveal microstructural and network connectivity impairment in adult-onset neuronal intranuclear inclusion disease.

Rui Zhu, Junyu Qu, Yongsheng Wu, Guihua Xu, Dawei Wang

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Evolutionary implications ofBrain communications · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Rui ZhuDepartment of Radiology, Qilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong University, Jinan, China.
Junyu QuDepartment of Radiology, Qilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong University, Jinan, China.
Yongsheng WuDepartment of Radiology, Qilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong University, Jinan, China.
Guihua XuDepartment of Radiology, Qilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong University, Jinan, China.
Dawei WangDepartment of Radiology, Qilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Neuronal intranuclear inclusion disease (NIID) is a rare neurodegenerative disorder lacking reliable neuroimaging biomarkers. This study aimed to evaluate microstructural and functional connectivity alterations using diffusion kurtosis imaging (DKI) and resting-state fMRI (rs-fMRI), and to investigate their diagnostic potential as biomarkers. Methods: Twenty-three patients with NIID and 40 matched healthy controls (HCs) were recruited. Firstly, gray matter (GM) and white matter (WM) changes were assessed by voxel-based analysis (VBA) and tract-based spatial statistics (TBSS). Then we explored modifications in brain functional networks connectivity by independent component analysis. And the relationship between the altered DKI parameters and neuropsychological evaluation was analyzed. Finally, a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of different gray matter and white matter parameters. Results: Compared with the HCs, NIID patients showed reduced mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), and kurtosis fractional anisotropy (KFA) values in deep gray matter regions. Significantly decreased MK, RK, AK, KFA and fractional anisotropy (FA), and increased mean diffusivity (MD) values were observed in extensive white matter fiber tracts. Notable alterations in functional connectivity were also detected. Among all DKI parameters, the diagnostic efficiency of AK in GM and FA in WM regions was the highest. Conclusion: Adult-onset NIID patients exhibited altered microstructure and functional network connectivity. Our findings suggest that DKI parameters may serve as potential imaging biomarkers for diagnosing adult-onset NIID.

Indexed as

cognitive declinediffusion kurtosis imagingfunctional connectivityneuroimaging biomarkersneuronal intranuclear inclusion disease

Identifiers

PMID39463819
PMCPMC11502314

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.