MRI Assessment of Renal Lipid Deposition and Abnormal Oxygen Metabolism of Type 2 diabetes Mellitus Based on mDixon-Quant.

BACKGROUND

Diabetic nephropathy (DN) is the main cause of end-stage renal failure. Multiecho Dixon-based imaging utilizes chemical shift for water-fat separation that may be valuable in detecting changes both fat and oxygen content of the kidney from a single dataset.

PURPOSE

To investigate whether multiecho Dixon-based imaging can assess fat and oxygen metabolism of the kidney in a single breath-hold acquisition for patients with type 2 diabetes mellitus (DM).

STUDY TYPE

Prospective.

SUBJECTS

A total of 40 DM patients with laboratory examination of biochemical parameters and 20 age- and body mass index (BMI)-matched healthy volunteers (controls).

FIELD STRENGTH/SEQUENCE: 3D multiecho Dixon gradient-echo sequence at 3.0 T.

ASSESSMENT

The DM patients were divided into two groups based on urine albumin-to-creatinine ratio (ACR): type 2 diabetes mellitus (DM, 20 patients, ACR < 30 mg/g) and diabetic nephropathy (DN, 20 patients, ACR ≥ 30 mg/g). In all subjects, fat fraction (FF) and relaxation rate (R2*) maps were derived from the Dixon-based imaging dataset, and mean values in manually drawn regions of interest in the cortex and medulla compared among groups. Associations between MRI and biochemical parameters, including β2-microglobulin, were investigated.

STATISTICAL TESTS

Kruskal-Wallis tests, Spearman correlation analysis, and receiver operating characteristic (ROC) curve analysis.

RESULTS

FF and R2* values of the renal cortex and medulla were significantly different among the three groups with control group < DM < DN (FF: control, 1.11± 0.30, 1.10 ± 0.39; DM, 1.52 ± 0.32, 1.57 ± 0.35; DN, 1.99 ± 0.66, 2.21 ± 0.59. R2*: Control, 16.88 ± 0.77, 20.70 ± 0.86; DM, 17.94 ± 0.75, 22.10 ± 1.12; DN, 19.20 ± 1.24, 23.63 ± 1.33). The highest correlation between MRI and biochemical parameters was that between cortex R2* and β2-microglobulin (r = 0.674). A medulla R2* cutoff of 21.41 seconds resulted in a sensitivity of 80%, a specificity of 85% and achieved the largest area under the ROC curve (AUC) of 0.83 for discriminating DM from the controls. A cortex FF of 1.81% resulted in a sensitivity of 80%, a specificity of 100% and achieved the largest AUC of 0.83 for discriminating DM from DN.

DATA CONCLUSION

Multiecho Dixon-based imaging is feasible for noninvasively distinguishing DN, DM and healthy controls by measuring FF and R2* values.

EVIDENCE LEVEL

TECHNICAL EFFICACY

Stage 2.