Back to Search Start Over

Predicting Progression of Kidney Injury Based on Elastography Ultrasound and Radiomics Signatures.

Authors :
Zhu, Minyan
Tang, Lumin
Yang, Wenqi
Xu, Yao
Che, Xiajing
Zhou, Yin
Shao, Xinghua
Zhou, Wenyan
Zhang, Minfang
Li, Guanghan
Zheng, Min
Wang, Qin
Li, Hongli
Mou, Shan
Source :
Diagnostics (2075-4418). Nov2022, Vol. 12 Issue 11, p2678. 17p.
Publication Year :
2022

Abstract

Background: Shear wave elastography ultrasound (SWE) is an emerging non-invasive candidate for assessing kidney stiffness. However, its prognostic value regarding kidney injury is unclear. Methods: A prospective cohort was created from kidney biopsy patients in our hospital from May 2019 to June 2020. The primary outcome was the initiation of renal replacement therapy or death, while the secondary outcome was eGFR < 60 mL/min/1.73 m2. Ultrasound, biochemical, and biopsy examinations were performed on the same day. Radiomics signatures were extracted from the SWE images. Results: In total, 187 patients were included and followed up for 24.57 ± 5.52 months. The median SWE value of the left kidney cortex (L_C_median) is an independent risk factor for kidney prognosis for stage 3 or over (HR 0.890 (0.796–0.994), p < 0.05). The inclusion of 9 out of 2511 extracted radiomics signatures improved the prognostic performance of the Cox regression models containing the SWE and the traditional index (chi-square test, p < 0.001). The traditional Cox regression model had a c-index of 0.9051 (0.8460–0.9196), which was no worse than the machine learning models, Support Vector Machine (SVM), SurvivalTree, Random survival forest (RSF), Coxboost, and Deepsurv. Conclusions: SWE can predict kidney injury progression with an improved performance by radiomics and Cox regression modeling. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20754418
Volume :
12
Issue :
11
Database :
Academic Search Index
Journal :
Diagnostics (2075-4418)
Publication Type :
Academic Journal
Accession number :
160144019
Full Text :
https://doi.org/10.3390/diagnostics12112678