Evidence map›Paper›PMID 38426222›Full record

ArticleBrain : a journal of neurology2024

Atrophy network mapping of clinical subtypes and main symptoms in frontotemporal dementia.

Min Chu, Deming Jiang, Dan Li, Shaozhen Yan, Li Liu, Haitian Nan, Yingtao Wang, Yihao Wang, Ailing Yue, Liankun Ren and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Brain : a journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
8.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Depression and apathy in frontotemporal dementia: a short assessment of facts and outlook.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Review
  5. Free water changes and their correlations with multimodal biomarkers in frontotemporal dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
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  16. Action-mode subnetworks for decision-making, action control, and feedback.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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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

14 authors at 3 institutions in 3 countries.

Min ChuDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.ORCID 0000-0001-7572-6162
Deming JiangDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Dan LiDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Shaozhen YanDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Li LiuDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Haitian NanDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Yingtao WangDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Yihao WangDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Ailing YueDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Liankun RenDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.ORCID 0000-0001-5147-3068
Kewei ChenSchool of Mathematics and Statistics, Banner Alzheimer's Institute, University of Arizona, Arizona Alzheimer's Consortium, Arizona State University, Tempe, AZ 85014-3666, USA.
Pedro Rosa-NetoMcGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Montreal H4H 1R3, Canada.ORCID 0000-0001-9116-1376
Jie LuDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Liyong WuDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Capital Medical University · CNMcGill University Health Centre · CAUniversity of Arizona · US

Funding

Research Education ComponentP30AG072980 · NIA · BANNER HEALTH · PI ALIREZA ATRI · 2021 to 2026
$24.9M
National Natural Science Foundation of China 82271464NIA NIH HHS P30 AG072980
6 · The paper itself

Abstract

Frontotemporal dementia (FTD) is a disease of high heterogeneity, apathy and disinhibition present in all subtypes of FTD and imposes a significant burden on families/society. Traditional neuroimaging analysis has limitations in elucidating the network localization due to individual clinical and neuroanatomical variability. The study aims to identify the atrophy network map associated with different FTD clinical subtypes and determine the specific localization of the network for apathy and disinhibition. Eighty FTD patients [45 behavioural variant FTD (bvFTD) and 35 semantic variant progressive primary aphasia (svPPA)] and 58 healthy controls at Xuanwu Hospital were enrolled as Dataset 1; 112 FTD patients including 50 bvFTD, 32 svPPA and 30 non-fluent variant PPA (nfvPPA) cases, and 110 healthy controls from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) dataset were included as Dataset 2. Initially, single-subject atrophy maps were defined by comparing cortical thickness in each FTD patient versus healthy controls. Next, the network of brain regions functionally connected to each FTD patient's location of atrophy was determined using seed-based functional connectivity in a large (n = 1000) normative connectome. Finally, we used atrophy network mapping to define clinical subtype-specific network (45 bvFTD, 35 svPPA and 58 healthy controls in Dataset 1; 50 bvFTD, 32 svPPA, 30 nfvPPA and 110 healthy controls in Dataset 2) and symptom-specific networks [combined Datasets 1 and 2, apathy without depression versus non-apathy without depression (80:26), disinhibition versus non-disinhibition (88:68)]. We compare the result with matched symptom networks derived from patients with focal brain lesions or conjunction analysis. Through the analysis of two datasets, we identified heterogeneity in atrophy patterns among FTD patients. However, these atrophy patterns are connected to a common brain network. The primary regions affected by atrophy in FTD included the frontal and temporal lobes, particularly the anterior temporal lobe. bvFTD connects to frontal and temporal cortical areas, svPPA mainly impacts the anterior temporal region and nfvPPA targets the inferior frontal gyrus and precentral cortex regions. The apathy-specific network was localized in the orbital frontal cortex and ventral striatum, while the disinhibition-specific network was localized in the bilateral orbital frontal gyrus and right temporal lobe. Apathy and disinhibition atrophy networks resemble known motivational and criminal lesion networks, respectively. A significant correlation was found between the apathy/disinhibition scores and functional connectivity between atrophy maps and the peak of the networks. This study localizes the common network of clinical subtypes and main symptoms in FTD, guiding future FTD neuromodulation interventions.

Indexed as

AtrophyFrontotemporal DementiaMagnetic Resonance ImagingAgedApathyBrainBrain MappingConnectomeFemaleHumansMaleMiddle AgedNerve Netapathyatrophy network mapdisinhibitionfrontotemporal dementia

Identifiers

PMID38426222
PMCPMC11370799
OpenAlexW4392340342

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.