Abstract
Objective
Although the guideline indicates that total kidney volume (TKV) is an important detection indicator in patients with autosomal dominant polycystic kidney disease (ADPKD), this study attempted to demonstrate that renal parenchymal information, combined with parenchymal volume and radiomics features, may have more valuable clinical guiding significance.
Methods
A totals of 340 ADPKD patients with normal renal function were prospectively collected and followed-up for five years, with renal function tests and non-contrast computed tomography (CT) performed every six months. The relationship between renal function impairment and renal parenchymal volume (RPV) as along with radiomics features was explored using a multiple linear regression model and multiple logistic regression. Then, a combined model of RPV with radiomics features was constructed to comprehensively evaluate its predictive value.
Results
Compared with TKV, decreased RPV presented a closer relationship with renal function impairment, namely, with the impairment rate (RPV: 82.3% vs. TVK: 67.1%) and eGFR (RPV: r = 0.614, p < 0.001 vs. TKV: r = -0.452, p < 0.001), and showed higher predictive power (RPV: AUC = 0.752 [95%CI 0.692–0.805], p < 0.001 vs. TKV: AUC = 0.711 [95%CI 0.649–0.768], p < 0.001). Correspondingly, the radiomics analysis that was derived from the renal parenchyma also showed a satisfactory result (AUC = 0.849 [95%Cl 0.797–0.892], p < 0.001). Importantly, the predictive power for renal function impairment was further improved in the combined model of RPV and radiomics features (AUC = 0.902 [95%Cl 0.857–0.937], p < 0.001).
Conclusion
Renal parenchyma information may be a sensitive biomarker of renal function impairment in ADPKD, which can provide a new approach for clinically monitoring renal function, and may greatly improve the pre-hospital prevention and treatment effects.
Graphical abstract
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Abbreviations
- ADPKD:
-
Autosomal dominant polycystic kidney disease
- TKV:
-
Total kidney volume
- CT:
-
Computed tomography
- RPV:
-
Renal parenchymal volume
- GFR:
-
Glomerular filtration rate
- Scr:
-
Serum creatinine
- VOI:
-
Volume of interest
- IG:
-
Impairment group
- NIG:
-
Non-impairment group
- ICCs:
-
Intraclass correlation coefficients
- ROC:
-
Receiver operating characteristic
- AUC:
-
Area under the curve
- AI:
-
Artificial intelligence
- DL:
-
Deep learning
- TA:
-
Texture analysis
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Funding
This work was supported by National Natural Science Foundation of China (81871343); Jiangsu Provincial Key Research and Development Plan (BE2017698, BE2018693); the Natural Science Foundation of Jiangsu Province (BK20181226, BK20171311).
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All authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: YX, MX, XZ, SJ, YL. Acquisition of data: YX, MX, YC. Analysis, interpretation of data, and drafting of the manuscript: YX, MX, XZ, SJ. Critical revision of the manuscript for important intellectual content: all authors. Obtained funding: YL.
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Xie, Y., Xu, M., Chen, Y. et al. The predictive value of renal parenchymal information for renal function impairment in patients with ADPKD: a multicenter prospective study. Abdom Radiol 47, 2845–2857 (2022). https://doi.org/10.1007/s00261-022-03554-w
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DOI: https://doi.org/10.1007/s00261-022-03554-w