Elizabeth Marie Hollis
University of Louisville, USA
: J Kidney
The aim of this study is to determine which parameters are correlated with a more accurate diagnosis of rejection in patient who has undergone kidney transplantation. The study included 16 patients with stable renal allograft function (Group 1) and 37 patients with rejected allografts, determined by renal biopsy (Group 2), post transplantation. All patientsâ?? kidneys were evaluated using diffusion weighted MRI coupled with a computer aided diagnostic (CAD) system. Statistical analysis was performed to investigate possible correlations between allograft biomarkers and the biopsy diagnosis. The statistical analysis examined four categories of parameters: (1) Clinical biomarkers (i.e., plasma creatinine and creatinine clearness) alone, (2) The mean apparent diffusion coefficient (ADC) at 11 different individual b-values (b50 to b1000) s/mm2, (3) The mean ADCs of certain groups of individual b-value (sub-model) and, (4) The fusion of the clinical biomarkers with the mean ADC of fused b-values (the full model). Continuing the analysis of the mean ADC at 11 different individual b-values (b50 to b1000) s/mm2 of rejected and non-rejected patients, were significantly different at b-values of 500 s/mm2, 600 s/mm2, 700 s/mm2 and 900 s/ mm2. The statistical analysis of certain fused groups of individual b-vales yielded that the fusion of b=100 s/mm2 and b=700 s/mm2 provided an Akaike Information Criterion (AIC) of 58.6. The statistical analysis for the full model AIC was 65.0. It was concluded that the least accurate parameters were the full model while the most accurate parameters were the sub model which fused b=100 s/mm2 and b=700 s/mm2.
