Evidence map›Paper›PMID 36656455›Full record

ArticleBrain informatics2023

Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage.

Di Zang, Xiangyu Zhao, Yuanfang Qiao, Jiayu Huo, Xuehai Wu, Zhe Wang, Zeyu Xu, Ruizhe Zheng, Zengxin Qi, Ying Mao and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Brain informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

11 authors at 5 institutions in 2 countries.

Di Zang *Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
Xiangyu Zhao *School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China.
Yuanfang Qiao *School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China.
Jiayu HuoSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China.
Xuehai WuDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
Zhe WangDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
Zeyu XuDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
Ruizhe ZhengDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
Zengxin QiDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China. qizengxin@huashan.org.cn.
Ying MaoDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China. maoying@fudan.edu.cn.
Lichi ZhangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China. lichizhang@sjtu.edu.cn.
Shanghai Jiao Tong University · CNFudan University · CNShanghai Center for Brain Science and Brain-Inspired Technology · CNShanghai Clinical Research Center · CNState Key Laboratory of Medical Neurobiology

Funding

Lingang Laboratory LG202105-02-03National Natural Science Foundation of China 62001292National Natural Science Foundation of China 82271224Shanghai Municipal Science and Technology Major Project and ZJLab 2018SHZDZX01
6 · The paper itself

Abstract

Brain network analysis based on structural and functional magnetic resonance imaging (MRI) is considered as an effective method for consciousness evaluation of hydrocephalus patients, which can also be applied to facilitate the ameliorative effect of lumbar cerebrospinal fluid drainage (LCFD). Automatic brain parcellation is a prerequisite for brain network construction. However, hydrocephalus images usually have large deformations and lesion erosions, which becomes challenging for ensuring effective brain parcellation works. In this paper, we develop a novel and robust method for segmenting brain regions of hydrocephalus images. Our main contribution is to design an innovative inpainting method that can amend the large deformations and lesion erosions in hydrocephalus images, and synthesize the normal brain version without injury. The synthesized images can effectively support brain parcellation tasks and lay the foundation for the subsequent brain network construction work. Specifically, the novelty of the inpainting method is that it can utilize the symmetric properties of the brain structure to ensure the quality of the synthesized results. Experiments show that the proposed brain abnormality inpainting method can effectively aid the brain network construction, and improve the CRS-R score estimation which represents the patient's consciousness states. Furthermore, the brain network analysis based on our enhanced brain parcellation method has demonstrated potential imaging biomarkers for better interpreting and understanding the recovery of consciousness in patients with secondary hydrocephalus.

Indexed as

Brain parcellationConsciousnessHydrocephalusStructural imagingTraumatic brain injury

Identifiers

PMID36656455
PMCPMC9852379
OpenAlexW4317436237

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.