Literature DB >> 22826401

Intraobserver and interobserver variability of renal volume measurements in polycystic kidney disease using a semiautomated MR segmentation algorithm.

Benjamin A Cohen1, Irina Barash, Danny C Kim, Matthew D Sanger, James S Babb, Hersh Chandarana.   

Abstract

OBJECTIVE: Total renal volume and changes in kidney volume are markers of disease progression in autosomal-dominant polycystic kidney disease (ADPKD) but are not used in clinical practice in part because of the complexity of manual measurements. This study aims to assess the intra- and interobserver reproducibility of a semiautomated renal volumetric algorithm using fluid-sensitive MRI pulse sequences. SUBJECTS AND METHODS: Renal volumes of 17 patients with ADPKD were segmented from high-resolution coronal HASTE and true fast imaging with steady-state precession (FISP) MR acquisitions. Measurements performed independently by four readers were repeated, typically after 7 days. Intraobserver agreement indexes were calculated for total kidney volume for each patient. Interobserver agreement indexes were obtained for the six paired combinations of readers as well as for two readers after rigorous formalized training. Pearson and concordance correlation coefficients, coefficients of variation (CVs), and 95% limits of agreement were determined.
RESULTS: The HASTE and true FISP sequences performed similarly with a median intraobserver agreement of greater than 98.1% and a CV of less than 2.4% across all readers. The median interobserver agreement was greater than 95.2% and the CV was less than 7.1%, across all reader pairs. Reader training further lowered interobserver CV. The mean total kidney volume was 1420 mL (range, 331-3782 mL) for HASTE imaging and 1445 mL (range, 301-3714 mL) for true FISP imaging, with mean image processing times per patient of 43 and 28 minutes, respectively.
CONCLUSION: This semiautomated MR volumetric algorithm provided excellent intraobserver and very good interobserver reproducibility using fluid-sensitive pulse sequences that emphasize cyst conspicuity.

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Year:  2012        PMID: 22826401     DOI: 10.2214/AJR.11.8043

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  8 in total

1.  Development and Evaluation of a Semi-automated Segmentation Tool and a Modified Ellipsoid Formula for Volumetric Analysis of the Kidney in Non-contrast T2-Weighted MR Images.

Authors:  Hannes Seuss; Rolf Janka; Marcus Prümmer; Alexander Cavallaro; Rebecca Hammon; Ragnar Theis; Martin Sandmair; Kerstin Amann; Tobias Bäuerle; Michael Uder; Matthias Hammon
Journal:  J Digit Imaging       Date:  2017-04       Impact factor: 4.056

2.  Automated segmentation and volumetric analysis of renal cortex, medulla, and pelvis based on non-contrast-enhanced T1- and T2-weighted MR images.

Authors:  Susanne Will; Petros Martirosian; Christian Würslin; Fritz Schick
Journal:  MAGMA       Date:  2014-01-30       Impact factor: 2.310

3.  Image texture features predict renal function decline in patients with autosomal dominant polycystic kidney disease.

Authors:  Timothy L Kline; Panagiotis Korfiatis; Marie E Edwards; Kyongtae T Bae; Alan Yu; Arlene B Chapman; Michal Mrug; Jared J Grantham; Douglas Landsittel; William M Bennett; Bernard F King; Peter C Harris; Vicente E Torres; Bradley J Erickson
Journal:  Kidney Int       Date:  2017-05-20       Impact factor: 10.612

4.  Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images.

Authors:  Timothy L Kline; Marie E Edwards; Panagiotis Korfiatis; Zeynettin Akkus; Vicente E Torres; Bradley J Erickson
Journal:  AJR Am J Roentgenol       Date:  2016-06-24       Impact factor: 3.959

5.  Intra- and inter-observer variability of functional MR urography (fMRU) assessment in children.

Authors:  Dmitry Khrichenko; David Saul; Melkamu Adeb; Camilo Jaimes; Khalil N Betts; Stephanie M Barron; J Christopher Edgar; Sarah M Lambert; Pasquale Casale; Kassa Darge
Journal:  Pediatr Radiol       Date:  2016-01-21

6.  Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

Authors:  Youngwoo Kim; Yinghui Ge; Cheng Tao; Jianbing Zhu; Arlene B Chapman; Vicente E Torres; Alan S L Yu; Michal Mrug; William M Bennett; Michael F Flessner; Doug P Landsittel; Kyongtae T Bae
Journal:  Clin J Am Soc Nephrol       Date:  2016-01-21       Impact factor: 8.237

7.  Novel semi-automated kidney volume measurements in autosomal dominant polycystic kidney disease.

Authors:  Satoru Muto; Haruna Kawano; Shuji Isotani; Hisamitsu Ide; Shigeo Horie
Journal:  Clin Exp Nephrol       Date:  2017-11-03       Impact factor: 2.801

8.  Kidney volume measurement methods for clinical studies on autosomal dominant polycystic kidney disease.

Authors:  Kanishka Sharma; Anna Caroli; Le Van Quach; Katja Petzold; Michela Bozzetto; Andreas L Serra; Giuseppe Remuzzi; Andrea Remuzzi
Journal:  PLoS One       Date:  2017-05-30       Impact factor: 3.240

  8 in total

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