Huang X, Hu Y, Zhang Y, Zhou Q. Two-Dimensional Ultrasound-Based Radiomics Nomogram for Diabetic Kidney Disease: A Pilot Study.
Int J Gen Med 2024;
17:1877-1885. [PMID:
38736665 PMCID:
PMC11086428 DOI:
10.2147/ijgm.s462896]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Accepted: 04/21/2024] [Indexed: 05/14/2024] Open
Abstract
Objective
To establish a radiomics nomogram based on two-dimensional ultrasound for risk assessment of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM).
Methods
This study retrospectively collected two-dimensional ultrasound images and clinical data from 52 patients with T2DM who underwent renal biopsy in our hospital from January 2023 to August 2023. Based on the pathological results, all patients were categorized into two groups: DKD (n=33) and non-DKD (n=19). The radiomic features of the segmented kidney in ultrasound pictures were retrieved and selected to calculate each patient's rad-score. A predictive nomogram based on rad-score and clinical features was then constructed and validated based on the calibration curve.
Results
The rad-score for all patients were computed based on five imaging characteristics extracted from the ultrasound images. The predictive nomogram was developed with the rad-score, diabetic retinopathy, duration of diabetes, and glycosylated hemoglobin. Moreover, This radiomics nomogram showed outstanding calibration capability, discrimination as well as therapeutic usefulness.
Conclusion
We constructed a nomogram based on two-dimensional ultrasound for DKD in T2DM patientsThe model has been proven to have good predictive performance, showing its potential in identifying DKD in T2DM patients and assisting in making appropriate early interventions.
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