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结合多频磁共振弹性成像与自动分割技术评估慢性肾脏病患者的肾功能

Combining Multifrequency Magnetic Resonance Elastography With Automatic Segmentation to Assess Renal Function in Patients With Chronic Kidney Disease.

作者信息

Liang Qiumei, Lin Haiwei, Li Junfeng, Luo Peiyin, Qi Ruirui, Chen Qiuyi, Meng Fanqi, Qin Haodong, Qu Feifei, Zeng Youjia, Wang Wenjing, Lu Jiandong, Huang Bingsheng, Chen Yueyao

机构信息

Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, China.

Department of Radiology, The Sixth School of Clinical Medicine, the Affiliated Qingyuan Hospital (Qingyuan People's Hospital), Guangzhou Medical University, Qingyuan, China.

出版信息

J Magn Reson Imaging. 2025 Jun;61(6):2543-2555. doi: 10.1002/jmri.29719. Epub 2025 Jan 28.

Abstract

BACKGROUND

Multifrequency MR elastography (mMRE) enables noninvasive quantification of renal stiffness in patients with chronic kidney disease (CKD). Manual segmentation of the kidneys on mMRE is time-consuming and prone to increased interobserver variability.

PURPOSE

To evaluate the performance of mMRE combined with automatic segmentation in assessing CKD severity.

STUDY TYPE

Prospective.

PARTICIPANTS

A total of 179 participants consisting of 95 healthy volunteers and 84 participants with CKD.

FIELD STRENGTH/SEQUENCE: 3 T, single shot spin echo planar imaging sequence.

ASSESSMENT

Participants were randomly assigned into training (n = 58), validation (n = 15), and test (n = 106) sets. Test set included 47 healthy volunteers and 58 CKD participants with different stages (21 stage 1-2, 22 stage 3, and 16 stage 4-5) based on estimated glomerular filtration rate (eGFR). Shear wave speed (SWS) values from mMRE was measured using automatic segmentation constructed through the nnU-Net deep-learning network. Standard manual segmentation was created by a radiologist. In the test set, the automatically segmented renal SWS were compared between healthy volunteers and CKD subgroups, with age as a covariate. The association between SWS and eGFR was investigated in participants with CKD.

STATISTICAL TESTS

Dice similarity coefficient (DSC), analysis of covariance, Pearson and Spearman correlation analyses. P < 0.05 was considered statistically significant.

RESULTS

Mean DSCs between standard manual and automatic segmentation were 0.943, 0.901, and 0.970 for the renal cortex, medulla, and parenchyma, respectively. The automatically quantified cortical, medullary, and parenchymal SWS were significantly correlated with eGFR (r = 0.620, 0.605, and 0.640, respectively). Participants with CKD stage 1-2 exhibited significantly lower cortical SWS values compared to healthy volunteers (2.44 ± 0.16 m/second vs. 2.56 ± 0.17 m/second), after adjusting age.

CONCLUSION

mMRE combined with automatic segmentation revealed abnormal renal stiffness in patients with CKD, even with mild renal impairment.

PLAIN LANGUAGE SUMMARY

The renal stiffness of patients with chronic kidney disease varies according to the function and structure of the kidney. This study integrates multifrequency magnetic resonance elastography with automated segmentation technique to assess renal stiffness in patients with chronic kidney disease. The findings indicate that this method is capable of distinguishing between patients with chronic kidney disease, including those with mild renal impairment, while simultaneously reducing the subjectivity and time required for radiologists to analyze images. This research enhances the efficiency of image processing for radiologists and assists nephrologists in detecting early-stage damage in patients with chronic kidney disease.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

摘要

背景

多频磁共振弹性成像(mMRE)能够对慢性肾脏病(CKD)患者的肾脏硬度进行无创定量分析。在mMRE上手动分割肾脏既耗时,又容易增加观察者间的变异性。

目的

评估mMRE联合自动分割技术在评估CKD严重程度方面的性能。

研究类型

前瞻性研究。

参与者

共有179名参与者,包括95名健康志愿者和84名CKD患者。

场强/序列:3T,单次激发自旋回波平面成像序列。

评估

参与者被随机分为训练组(n = 58)、验证组(n = 15)和测试组(n = 106)。测试组包括47名健康志愿者和58名不同分期的CKD患者(根据估计肾小球滤过率(eGFR),21例为1-2期,22例为3期,16例为4-5期)。使用通过nnU-Net深度学习网络构建的自动分割技术测量mMRE的剪切波速度(SWS)值。由一名放射科医生进行标准手动分割。在测试组中,以年龄作为协变量,比较健康志愿者和CKD亚组之间自动分割的肾脏SWS。在CKD患者中研究SWS与eGFR之间的关联。

统计检验

Dice相似系数(DSC)、协方差分析、Pearson和Spearman相关性分析。P < 0.05被认为具有统计学意义。

结果

肾脏皮质、髓质和实质的标准手动分割与自动分割之间的平均DSC分别为0.943、0.901和0.970。自动定量的皮质、髓质和实质SWS与eGFR显著相关(r分别为0.620、0.605和0.640)。校正年龄后,1-2期CKD患者的皮质SWS值显著低于健康志愿者(2.44 ± 0.16米/秒 vs. 2.56 ± 0.17米/秒)。

结论

mMRE联合自动分割显示CKD患者即使存在轻度肾功能损害也存在肾脏硬度异常。

通俗易懂的总结

慢性肾脏病患者的肾脏硬度根据肾脏的功能和结构而有所不同。本研究将多频磁共振弹性成像与自动分割技术相结合,以评估慢性肾脏病患者的肾脏硬度。研究结果表明,该方法能够区分慢性肾脏病患者,包括轻度肾功能损害患者,同时减少放射科医生分析图像的主观性和所需时间。本研究提高了放射科医生的图像处理效率,并有助于肾病学家检测慢性肾脏病患者的早期损伤。

证据水平

2 技术效能:2级

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61ee/12063765/a2870e3e51bc/JMRI-61-2543-g004.jpg

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