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Published on: July 3, 2013
Association of quantitative renal surface nodularity with the renal dysfunction progression in patients with arterial
Qiong Wu1,2, Jun Zhou3, Haotian Yang1,4
1Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China.
Background:
Hypertensive nephropathy, a major cause of end-stage renal disease, lacks reliable noninvasive biomarkers. Renal surface nodularity (RSN) on CT may reflect nephrosclerosis, but existing methods fail to quantify nodularity heterogeneity or predict renal decline. This study developed a novel CT-based RSN metric and assessed its prognostic value in hypertensive patients.
Methods:
This retrospective cohort study included hypertensive patients who underwent contrast-enhanced CT. Patients with bilateral renal surface irregularities were assigned to the RSN group, with age- (± 2 year) and sex-matched controls (non-RSN group) randomly selected at a 1:1 ratio. RSN was quantified using three surface roughness metrics. A semi-quantitative RSN score was also calculated based on the distribution and depth (> 50% cortical thickness) of localized surface defects. The primary endpoint was composite renal dysfunction progression (≥ 25% eGFR decline or initiation of renal replacement therapy). The secondary endpoint was defined as an annual decline in eGFR > 5 ml/min/1.73 m² per year.
Results:
A total of 242 patients were included (median age, 64 years; 70.25% male). Strong linear correlations were observed between quantitative RSN metrics and semi-quantitative score (all ρ > 0.9, P < 0.001). Over a median follow-up of 38.00 months (Interquartile range: 22.00-56.25), patients in the RSN group had a significantly higher risk of renal dysfunction progression (33 vs. 5 events; HR = 5.22, P < 0.001). After adjusting sex, age, hypertension grade, diabetes, hyperlipidemia, eGFR, and renal volume, renal dysfunction progression was independently associated with arithmetic mean deviation (HR = 1.798, 95% CI: 1.296-2.495, P < 0.001), maximum height (HR = 1.606, 95% CI: 1.177-2.191, P = 0.003), and ten-point unevenness height (HR = 2.239, 95%CI: 1.567-3.197, P < 0.001), respectively. The similar statistical results trend was present between RSN and the secondary endpoint.
Conclusions:
CT-based quantitative RSN was developed as a novel imaging biomarker for renal dysfunction progression in patients with arterial hypertension.
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