Evidence map›Paper›PMID 32470024›Full record

ArticlePloS one2020

Alterations of functional and structural connectivity in patients with brain metastases.

Bo Hua, Xin Ding, Minghua Xiong, Fanyu Zhang, Yi Luo, Jurong Ding, Zhongxiang Ding

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 40% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Automated treatment planning for brain and spinal metastases.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 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

7 authors at 3 institutions in 1 country.

Bo HuaArtificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China.
Xin DingDepartment of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Minghua XiongArtificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China.
Fanyu ZhangArtificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China.
Yi LuoArtificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China.
Jurong DingArtificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China.ORCID 0000-0001-6708-5131
Zhongxiang DingDepartment of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Sichuan University of Science and Engineering · CNFirst Affiliated Hospital of Chengdu Medical College · CNHangzhou First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metastases are the most prevalent tumors in the brain and are commonly associated with high morbidity and mortality. Previous studies have suggested that brain tumors can induce a loss of functional connectivity and alter the brain network architecture. Little is known about the effect of brain metastases on whole-brain functional and structural connectivity networks. In this study, 14 patients with brain metastases and 16 healthy controls underwent resting state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI). We constructed functional connectivity network using rs-fMRI signal correlations and structural connectivity network using DTI tractography. Graph theoretical analysis was employed to calculate network properties. We further evaluated the performance of brain networks after metastases resection by a simulated method. Compared to healthy controls, patients with brain metastases showed an altered "small-world" architecture in both functional and structural connectivity networks, shifting to a more randomness organization. Besides, the coupling strength of functional-structural connectivity was decreased in patients. After removing nodes infiltrated by metastases, aggravated disruptions were found in both functional and structural connectivity networks, and the alterations of network properties correlated with the removed hubs number. Our findings suggest that brain metastases interfere with the optimal network organization and relationship of functional and structural connectivity networks, and tumor resection involving hubs could cause a worse performance of brain networks. This study provides neuroimaging guidance for neurosurgical planning and postoperative assessment of brain metastases from the aspect of brain networks.

Indexed as

AlgorithmsArea Under CurveBrain NeoplasmsCase-Control StudiesFemaleHumansMaleMiddle AgedNerve Net

Identifiers

PMID32470024
PMCPMC7259727
OpenAlexW3031118934

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.