Kidney Week

Abstract: SA-PO474

An Analysis of Novel Quantitative MRI Parameters to Evaluate Cystic Burden in Autosomal-Dominant Polycystic Kidney Disease

Session Information

• ADPKD: Clinical Studies
  October 27, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Genetic Diseases of the Kidney

• 1001 Genetic Diseases of the Kidney: Cystic

Authors

• Mueller, Roman-Ulrich, Dept. 2 of Internal Medicine, University of Cologne, Koeln, Germany

Roman-Ulrich Mueller,

• Siedek, Florian, University of Cologne, Cologne, Germany

Florian Siedek,

• Pinto dos santos, Daniel, University of Cologne, Cologne, Germany

Daniel Pinto dos santos,

• Haneder, Stefan, University of Cologne, Cologne, Germany

Stefan Haneder,

• Benzing, Thomas, Dept. 2 of Internal Medicine, University of Cologne, Koeln, Germany

Thomas Benzing,

• Persigehl, Thorsten, University of Cologne, Cologne, Germany

Thorsten Persigehl,

• Baessler, Bettina, University of Cologne, Cologne, Germany

Bettina Baessler,

• Grundmann, Franziska, Dept. 2 of Internal Medicine, University of Cologne, Koeln, Germany

Franziska Grundmann,

Background

In ADPKD, parameters that correlate with severity of disease are of crucial importance in guiding the management. To date, these rely primarily on genetics, clinical evaluation and kidney volumetry (TKV). Whilst TKV has been shown to be a very useful tool to predict future outcome, measuring the cyst fraction would be favorable. However, this is currently not feasible in the everyday clinical setting. Here, we present a novel approach employing MRI T2 mapping.

Methods

141 ADPKD patients from the AD(H)PKD-cohort and 10 healthy controls underwent MRI (1.5T system). HtTKV was calculated on coronary T2-weighted images using semi-automatic segmentation. Renal T2 relaxation times [ms] were generated using a Gradient-Spin-Echo (GraSE) T2 mapping sequence. Cyst fractions and mean T2 relaxation times (kidney-T2) were calculated using a plugin in Osirix. For analysis of T2-times of the remaining renal parenchyma (parenchyma-T2) a single ROI was chosen manually in 3 slices of each kidney and the results were averaged. Based on the cyst fraction patients were separated into three groups (<35%, 36-70%,> 70%).

Results

Obtaining parenchyma-T2 required 6-10fold less time than kidney-T2 or htTKV by semiautomatic segmentation (0,78±0,14 vs. 4,78±1,17 min, p<0,001, 0,78 ±0,14 vs. 7,59±1,57 min, p<.001). Importantly, parenchyma-T2 showed a similarly strong correlation to the cyst fraction (r=0,77, p<0,001) as kidney-T2 (r=0,77, p<0,001) and resulted in the clearest separation of patient groups. HtTKV showed only a moderate correlation to cyst fraction (r= 0,48, p<0,001) and did not allow for a clear group separation. Limiting the analysis to CKD stage 1 (n = 47) increased this discriminatory power whilst maintaining a similar correlation to the cyst fraction (parenchyma-T2: r=0,81; kidney-T2: r=0,79; htTKV: r = 0,48, p<0,001 for all).

Conclusion

Renal T2-mapping allows the determination of novel imaging parameters which show a high correlation to the cyst fraction. Whilst currently used methods for measuring TKV and cyst fraction are time-consuming, parenchyma-T2 can be measured within one minute. The high correlation with cyst fraction makes this parameter a promising biomarker, the power of which regarding disease progression will now be examined.

Funding

• Commercial Support –