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

医学 磁共振弹性成像 肾功能 肾脏疾病 分割 磁共振成像 卡帕 阶段(地层学) 内科学 放射科 弹性成像 人工智能 超声波 计算机科学 数学 生物 古生物学 几何学
作者
Qiumei Liang,Haiwei Lin,Junfeng Li,Peiyin Luo,Ruirui Qi,Qiuyi Chen,Fanqi Meng,Haodong Qin,Feifei Qu,Youjia Zeng,Wenjing Wang,Jiandong Lu,Bingsheng Huang,Yueyao Chen
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
被引量:1
标识
DOI:10.1002/jmri.29719
摘要

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

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