Evidence map›Paper›PMID 40384689›Full record

ArticleQuantitative imaging in medicine and surgery2025

Segmentation of hippocampal subregion via 5-Tesla magnetic resonance imaging: a comparative study.

Lixian Zou, Yijun Zhou, Shuo Chen, Jun Ni, Ye Li, Dong Liang, Xin Liu, Yining Wang, Hairong Zheng

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. 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
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  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

9 authors.

Lixian ZouPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.
Yijun ZhouDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Shuo ChenUnited Imaging Healthcare Co., Ltd., Shanghai, China.
Jun NiDepartment of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ye LiPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.
Dong LiangPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.
Xin LiuPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.
Yining Wang *Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Hairong Zheng *Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Small voxel sizes in two-dimensional (2D) hippocampal magnetic resonance imaging (MRI) facilitate subfield segmentation. However, thinner slices remain challenging despite the advancements in in-plane resolution due to the tradeoffs in image quality. A higher signal-to-noise ratio (SNR) at 5 Tesla (T) compared to 3 T could enable thinner slices; however, the effects of changes in tissue contrast and inhomogeneous B1 variation may be weaken the SNR and contrast-to-noise ratio (CNR). However, the effectiveness of current automatic segmentation tools in handling 5-T images, particularly for thinner slices, remains to be fully elucidated. This study thus aimed to assess hippocampus image quality improvement from 3 to 5 T and to evaluate the autosegmentation of the hippocampal subregion on 5 T with different slice thicknesses. Methods: This prospective study included 28 healthy participants (14 females, with a mean age of 31.8±8.96 years). T2-weighted series with 2-, 1-, and 0.7-mm slice thicknesses were acquired on 3 T and 5T. CNR, SNR, and visual scores of the molecular layer were compared. Hippocampal subregions were segmented with 5-T data using FreeSurfer and HippUnfold toolboxes. Dice coefficients of stratum radiatum, lacunosum, and moleculare (SRLM) were compared between FreeSurfer and HippUnfold. Fleiss' Kappa, the Kruskal-Wallis test, and the pairwise Wilcoxon signed-rank test were used for statistical analyses, with a P value <0.05 being considered statistically significant. Results: SNR, CNR, and visual scores were higher on 5 T than on 3 T at the same slice thickness. The SNR of the 1-mm T2 images on 5 T was comparable to that of 2-mm images on 3 T, and the CNR of the 0.7-mm images on 5 T was comparable to that of the 2-mm images on 3 T. With a reduction in slice thickness, the Dice coefficients of SRLM between HippUnfold and manual segmentation increased, while those between FreeSurfer and manual segmentation decreased. Conclusions: The 5-T magnetic resonance system offers higher SNR and CNR values for hippocampal imaging as compared to 3-T imaging. A slice thickness of 0.7-1 mm is recommended for 2D T2-weighted imaging. However, in the selection of automatic segmentation tools for hippocampal subregions, caution is advised if the slice thickness is less than 2 mm.

Indexed as

brainhippocampal subregionshippocampusMagnetic resonance imaging (MRI)ultrahigh field

Identifiers

PMID40384689
PMCPMC12084766

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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.