Reliability of Total Renal Volume Computation in Polycystic Kidney Disease From Magnetic Resonance Imaging

Dario Turco, Stefano Severi, Renzo Mignani, Valeria Aiello, Riccardo Magistroni, Cristiana Corsi

Research output: Contribution to journalArticlepeer-review


Rationale and Objectives: Total renal volume (TRV) is an important quantitative indicator of the progression of autosomal dominant polycystic kidney disease (ADPKD). The Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease proposes a method for TRV computation based on manual tracing and geometric modeling. Alternative approaches for TRV computation are represented by the application of advanced image processing techniques. In this study, we aimed to compare TRV estimates derived from these two different approaches. Materials and Methods: The nearly automated technique for the analysis of magnetic resonance (MR) images was tested on 30 ADPKD patients. TRV was computed from both axial (KVax) and coronal (KVcor) acquisitions and compared to measurements based on geometric modeling (KVap) by linear regression and Bland-Altman analysis. In addition, to assess reproducibility, intraobserver and interobserver variabilities were computed. Results: Linear regression analysis between KVax and KVcor resulted in an excellent correlation (KVax = 1KVcor - 0.78; r2 = 0.997). Bland-Altman analysis showed a negligible bias and narrow limits of agreement (bias: -11.7 mL; SD: 54.3 mL). Similar results were obtained by comparison of volumes obtained applying the nearly automated method and the one based on geometric modeling (y = 0.98x + 75.9; r2 = 0.99; bias: -53.7 mL; SD: 108.1 mL). Importantly, geometric modeling does not provide reliable TRV estimates in huge kidney affected by regional deformation. Intraobserver and interobserver variability resulted in very small percentage error

Original languageEnglish
Pages (from-to)1376-1384
Number of pages9
JournalAcademic Radiology
Issue number11
Publication statusPublished - Nov 1 2015


  • Autosomal dominant polycystic kidney disease
  • Kidney segmentation
  • Magnetic resonance imaging
  • Renal volume

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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