Texture analysis based on quantitative magnetic resonance imaging to assess kidney function: a preliminary study

Abstract

BACKGROUND: Magnetic resonance imaging (MRI) has demonstrated its potential in the evaluation of renal function. Texture analysis (TA) is a novel technique to quantify tissue heterogeneity. We aim to investigate the feasibility of using TA based on the apparent diffusion coefficient (ADC), as well as T1 and T2 maps to evaluate renal function. METHODS: ): normal (eGFR ≥90), mildly impaired (60≤ eGFR <90), moderately impaired (30≤ eGFR <60), and severely impaired (eGFR <30) renal function groups. Texture features quantified from the renal cortex or medulla were selected to build classifiers to discriminate different renal function groups by plotting receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: In total, 116 candidates were included (94 patients and 22 healthy volunteers, mean age 37.9±14.9 years). There were 46 participants in the normal renal function group, 14 in the mildly impaired renal function group, 27 in the moderately impaired renal function group, and 29 in the severely impaired renal function group. Texture features from the ADC and T1 maps exhibited a good correlation to eGFR. The AUC, sensitivity, specificity, PPV, and NPV to differentiate between the normal and impaired renal function groups were 0.835, 0.792, 0.867, 0.905, and 0.722, respectively; to differentiate between the mildly impaired and moderately impaired groups were 0.937, 0.889, 0.857, 0.923, and 0.800, respectively; and to differentiate between the moderately impaired and severely impaired groups was 0.940, 0.759, 0.889, 0.880, and 0.774, respectively. CONCLUSIONS: TA based on ADC and T1 maps is feasible for evaluating renal function with relatively good accuracy.