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通过5特斯拉磁共振成像对海马亚区进行分割:一项比较研究。

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

作者信息

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

机构信息

Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.

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.

出版信息

Quant Imaging Med Surg. 2025 May 1;15(5):3861-3874. doi: 10.21037/qims-24-2169. Epub 2025 Apr 10.

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.

摘要

背景

二维(2D)海马磁共振成像(MRI)中的小体素大小有助于亚区域分割。然而,尽管平面分辨率有所提高,但由于图像质量的权衡,更薄的切片仍然具有挑战性。与3T相比,5特斯拉(T)时更高的信噪比(SNR)可以实现更薄的切片;然而,组织对比度变化和不均匀B1变化的影响可能会削弱SNR和对比噪声比(CNR)。然而,目前自动分割工具在处理5T图像,特别是更薄切片方面的有效性仍有待充分阐明。因此,本研究旨在评估从3T到5T时海马图像质量的改善情况,并评估不同切片厚度下5T上海马亚区域的自动分割情况。

方法

这项前瞻性研究纳入了28名健康参与者(14名女性,平均年龄31.8±8.96岁)。在3T和5T上采集了层厚为2mm、1mm和0.7mm的T加权序列。比较了分子层的CNR、SNR和视觉评分。使用FreeSurfer和HippUnfold工具箱对5T数据进行海马亚区域分割。比较了FreeSurfer和HippUnfold之间辐射层、腔隙层和分子层(SRLM)的骰子系数。采用Fleiss' Kappa检验、Kruskal-Wallis检验和两两Wilcoxon符号秩检验进行统计分析,P值<0.05被认为具有统计学意义。

结果

在相同切片厚度下,5T时的SNR、CNR和视觉评分高于3T。5T上1mm T2图像的SNR与3T上2mm图像的SNR相当,5T上0.7mm图像的CNR与3T上2mm图像的CNR相当。随着切片厚度的减小,HippUnfold与手动分割之间SRLM的骰子系数增加,而FreeSurfer与手动分割之间的骰子系数减小。

结论

与3T成像相比,5T磁共振系统为海马成像提供了更高的SNR和CNR值。二维T加权成像建议切片厚度为0.7-1mm。然而,在选择海马亚区域的自动分割工具时,如果切片厚度小于2mm,建议谨慎使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c03f/12084766/fcb7b1cebcde/qims-15-05-3861-f1.jpg

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