Quantitative assessment of renal allograft pathologic changes: comparisons of mono-exponential and bi-exponential models using diffusion-weighted imaging

Abstract

Background: Diffusion-weighted imaging (DWI) can noninvasively assess renal allograft pathologic changes that provide useful information for clinical management and prognostication. However, it is still unknown whether the bi-exponential model analysis of DWI signals is superior to that of the monoexponential model.Methods: Pathologic and DWI data from a total of 47 allografts were prospectively collected and analyzed. Kidney transplant interstitial fibrosis was quantified digitally. The severity of acute and chronic pathologic changes was semi-quantified by calculating the acute composite scores (ACS) and chronic composite score (CCS). Mono-exponential total apparent diffusion coefficient (ADCT), and the bi-exponential parameters of true diffusion (D) and perfusion fraction (fp) were acquired. The diagnostic performances of both monoexponential and bi-exponential parameters were assessed and compared by calculating the area under the curve (AUC) from receiver-operating characteristic (ROC) curve analysis.Results: ADCT, D, and fp were all significantly correlated with interstitial fibrosis, ACS, and CCS.Cortical fp discriminated mild from moderate and severe ACS with the largest AUC of 0.89 [95% confidence interval (CI), 0.77-0.96]. Noticeably, only cortical fp could differentiate severe ACS from mild-to-moderate ACS (P<0.001) with an AUC of 0.80 (95% CI, 0.65-0.90) and a sensitivity of 100% (95% CI, 66.4-100%).Strikingly, the joint use of D and fp in either the cortex or the medulla could achieve a sensitivity of 100% for identifying either mild or severe interstitial fibrosis. Meanwhile, the serial use of cortical D and cortical fp showed the largest specificity for identifying both mild [88.9% (95% CI, 70.8-97.6%)] and severe [84.4% (95% CI, 67.2-94.7%)] interstitial fibrosis. For identifying mild CCS, the AUC of medullary ADCT (0.90, 95% CI, 0.78-0.97) was similar to that of cortical D (0.81, 95% CI, 0.67-0.91) and fp (0.86, 95% CI, 0.73-0.94), but statistically larger than that of medullary D (P=0.005) and fp (P=0.01). Furthermore, the parallel use of cortical D and cortical fp could increase the sensitivity to 95.0% (95% CI, 75.1-99.9%), whereas serial use of medullary D and medullary fp could increase the specificity to 100% (95% CI, 87.2-100%).The AUCs for differentiating severe from mild and moderate CCS were statistically insignificant among all parameters in the cortex and medulla (P≥0.15).Conclusions: Cortical fp was superior to the ADCT for identifying both mild and severe acute pathologic changes. Nevertheless, ADCT was equal to or better than single D or fp for evaluating chronic pathologic changes. Thus, both monoexponential and bi-exponential analysis of DWI images are complementary for evaluating kidney allograft pathologic changes, and the combined use of D and fp can increase the sensitivity and specificity for discriminating allograft pathologic changes severity. MRI acquisitionAll patients underwent MRI imaging using a 3.0 Tesla clinical MRI imaging unit (Discovery MR 750; General

Continuous diffusion spectrum computation for diffusion-weighted magnetic resonance imaging of the kidney tubule system

“…NNLS, non-negative least squares; AUC, area under the curve; AUC, area under the curve; SNR, signal-to-noise ratio. (32)(33)(34)(35)(36)(37)(38).…”

“…Diffusion-weighted MRI (DWI) probes self-diffusion of water in tissue on a microscopic level and reflects micro-morphological and (patho)physiological changes in renal tissue and renal diseases (30,31). When performing DWI of the kidney, the incoherent blood flow in the renal microvasculature contributes to pseudo-diffusion (32)(33)(34)(35)(36)(37)(38) resulting in a fast signal decay component. The displacement of water molecules in the renal tissue contributes a slow water diffusion component, according to the two-compartment model (32)(33)(34)(35)(36)(37)(38).…”

“…When performing DWI of the kidney, the incoherent blood flow in the renal microvasculature contributes to pseudo-diffusion (32)(33)(34)(35)(36)(37)(38) resulting in a fast signal decay component. The displacement of water molecules in the renal tissue contributes a slow water diffusion component, according to the two-compartment model (32)(33)(34)(35)(36)(37)(38). Acknowledging the morphological and physiological importance of renal tubules, recent studies have shown that the intra-tubular fluid compartment introduces a third component in the renal DWI signal decay.…”

Multiparametric MRI of Solid Renal Masses: Principles and Applications of Advanced Quantitative and Functional Methods for Tumor Diagnosis and Characterization

“…21,22 More recent knowledge suggests that this biexponential fitting of data over a wide array of b-values may serve as a more accurate representation of proton diffusion by differentiating true diffusion (D) from "pseudo-diffusion" (D*) and perfusion fraction (f) caused by capillary microcirculation. 23 IMPLEMENTATION. DWI/IVIM has shown promise for SRM characterization due to its ability to probe tumor cellularity, microcirculation, and microstructure.…”

Kidney Allograft Fibrosis: Diagnostic and Therapeutic Strategies

“…217,218 Second, diffusion-weighted imaging (DWI) quantified tissue water molecule free movement, which is restricted in areas with increased extracellular deposition. 219,220 Third, arterial spin labeling was used to measure tissue microvascular perfusion, 221 known to be decreased in native and kidney transplants with fibrosis. 222,223 Blood oxygen level-dependent has been frequently used for evaluation of kidney fibrosis, but mixed results have been reported because of many factors influencing blood flow and oxygenation.…”