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Review
. 2024 Dec;46(2):2367021.
doi: 10.1080/0886022X.2024.2367021. Epub 2024 Jun 28.

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

Shanshan Wan  1 , Shiping Wang  2 , Xinyu He  2 , Chao Song  2 , Jiaping Wang  1
Affiliations
Review

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

Shanshan Wan et al. Ren Fail. 2024 Dec.

Abstract

Rationale and objectives: Researchers have delved into noninvasive diagnostic methods of renal fibrosis (RF) in chronic kidney disease, including ultrasound (US), magnetic resonance imaging (MRI), and radiomics. However, the value of these diagnostic methods in the noninvasive diagnosis of RF remains contentious. Consequently, the present study aimed to systematically delineate the accuracy of the noninvasive diagnosis of RF.

Materials and methods: A systematic search covering PubMed, Embase, Cochrane Library, and Web of Science databases for all data available up to 28 July 2023 was conducted for eligible studies.

Results: We included 21 studies covering 4885 participants. Among them, nine studies utilized US as a noninvasive diagnostic method, eight studies used MRI, and four articles employed radiomics. The sensitivity and specificity of US for detecting RF were 0.81 (95% CI: 0.76-0.86) and 0.79 (95% CI: 0.72-0.84). The sensitivity and specificity of MRI were 0.77 (95% CI: 0.70-0.83) and 0.92 (95% CI: 0.85-0.96). The sensitivity and specificity of radiomics were 0.69 (95% CI: 0.59-0.77) and 0.78 (95% CI: 0.68-0.85).

Conclusions: The current early noninvasive diagnostic methods for RF include US, MRI, and radiomics. However, this study demonstrates that US has a higher sensitivity for the detection of RF compared to MRI. Compared to US, radiomics studies based on US did not show superior advantages. Therefore, challenges still exist in the current radiomics approaches for diagnosing RF, and further exploration of optimized artificial intelligence (AI) algorithms and technologies is needed.

Keywords: Noninvasive diagnosis; chronic kidney disease (CKD); meta-analysis; renal fibrosis.

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