[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

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

  • Published:
Journal of Digital Imaging Aims and scope Submit manuscript

Abstract

Volumetric analysis of the kidney parenchyma provides additional information for the detection and monitoring of various renal diseases. Therefore the purposes of the study were to develop and evaluate a semi-automated segmentation tool and a modified ellipsoid formula for volumetric analysis of the kidney in non-contrast T2-weighted magnetic resonance (MR)-images. Three readers performed semi-automated segmentation of the total kidney volume (TKV) in axial, non-contrast-enhanced T2-weighted MR-images of 24 healthy volunteers (48 kidneys) twice. A semi-automated threshold-based segmentation tool was developed to segment the kidney parenchyma. Furthermore, the three readers measured renal dimensions (length, width, depth) and applied different formulas to calculate the TKV. Manual segmentation served as a reference volume. Volumes of the different methods were compared and time required was recorded. There was no significant difference between the semi-automatically and manually segmented TKV (p = 0.31). The difference in mean volumes was 0.3 ml (95% confidence interval (CI), −10.1 to 10.7 ml). Semi-automated segmentation was significantly faster than manual segmentation, with a mean difference = 188 s (220 vs. 408 s); p < 0.05. Volumes did not differ significantly comparing the results of different readers. Calculation of TKV with a modified ellipsoid formula (ellipsoid volume × 0.85) did not differ significantly from the reference volume; however, the mean error was three times higher (difference of mean volumes −0.1 ml; CI −31.1 to 30.9 ml; p = 0.95). Applying the modified ellipsoid formula was the fastest way to get an estimation of the renal volume (41 s). Semi-automated segmentation and volumetric analysis of the kidney in native T2-weighted MR data delivers accurate and reproducible results and was significantly faster than manual segmentation. Applying a modified ellipsoid formula quickly provides an accurate kidney volume.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Abraham G, et al.: Chronic kidney disease hotspots in developing countries in South Asia. Clinical kidney journal 9:135–141, 2016

    Article  PubMed  Google Scholar 

  2. Grams ME, et al.: Trends in the prevalence of reduced GFR in the United States: a comparison of creatinine- and cystatin C-based estimates. American journal of kidney diseases : the official journal of the National Kidney Foundation 62:253–260, 2013

    Article  CAS  Google Scholar 

  3. Coresh J, et al.: Prevalence of chronic kidney disease in the United States. Jama 298:2038–2047, 2007

    Article  CAS  PubMed  Google Scholar 

  4. White SL, Polkinghorne KR, Atkins RC, Chadban SJ: Comparison of the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study. American journal of kidney diseases : the official journal of the National Kidney Foundation 55:660–670, 2010

    Article  Google Scholar 

  5. Matsushita K, Tonelli M, Lloyd A, Levey AS, Coresh J, Hemmelgarn BR: Clinical risk implications of the CKD Epidemiology Collaboration (CKD-EPI) equation compared with the Modification of Diet in Renal Disease (MDRD) Study equation for estimated GFR. American journal of kidney diseases : the official journal of the National Kidney Foundation 60:241–249, 2012

    Article  Google Scholar 

  6. Keller G, Zimmer G, Mall G, Ritz E, Amann K: Nephron number in patients with primary hypertension. The New England journal of medicine 348:101–108, 2003

    Article  PubMed  Google Scholar 

  7. Ritz E, Amann K, Koleganova N, Benz K: Prenatal programming-effects on blood pressure and renal function. Nature reviews Nephrology 7:137–144, 2011

    Article  PubMed  Google Scholar 

  8. Jones RA, Easley K, Little SB, Scherz H, Kirsch AJ, Grattan-Smith JD: Dynamic contrast-enhanced MR urography in the evaluation of pediatric hydronephrosis: Part 1, functional assessment. AJR American journal of roentgenology 185:1598–1607, 2005

    Article  PubMed  Google Scholar 

  9. Bakker J, Olree M, Kaatee R, de Lange EE, Beek FJ: In vitro measurement of kidney size: comparison of ultrasonography and MRI. Ultrasound in medicine & biology 24:683–688, 1998

    Article  CAS  Google Scholar 

  10. Bakker J, et al.: Renal volume measurements: accuracy and repeatability of US compared with that of MR imaging. Radiology 211:623–628, 1999

    Article  CAS  PubMed  Google Scholar 

  11. Li S, et al.: Wavelet-based segmentation of renal compartments in DCE-MRI of human kidney: initial results in patients and healthy volunteers. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society 36:108–118, 2012

    Article  Google Scholar 

  12. Grenier N, Basseau F, Ries M, Tyndal B, Jones R, Moonen C: Functional MRI of the kidney. Abdominal imaging 28:164–175, 2003

    Article  CAS  PubMed  Google Scholar 

  13. Coulam CH, Bouley DM, Sommer FG: Measurement of renal volumes with contrast-enhanced MRI. Journal of magnetic resonance imaging : JMRI 15:174–179, 2002

    Article  PubMed  Google Scholar 

  14. de Bazelaire CM, Duhamel GD, Rofsky NM, Alsop DC: MR imaging relaxation times of abdominal and pelvic tissues measured in vivo at 3.0 T: preliminary results. Radiology 230:652–659, 2004

    Article  PubMed  Google Scholar 

  15. Di Leo G, Di Terlizzi F, Flor N, Morganti A, Sardanelli F: Measurement of renal volume using respiratory-gated MRI in subjects without known kidney disease: intraobserver, interobserver, and interstudy reproducibility. European journal of radiology 80:e212–216, 2011

    Article  PubMed  Google Scholar 

  16. Kanki A, et al.: Corticomedullary differentiation of the kidney: evaluation with noncontrast-enhanced steady-state free precession (SSFP) MRI with time-spatial labeling inversion pulse (time-SLIP). Journal of magnetic resonance imaging : JMRI 37:1178–1181, 2013

    Article  PubMed  Google Scholar 

  17. Cohen BA, Barash I, Kim DC, Sanger MD, Babb JS, Chandarana H: Intraobserver and interobserver variability of renal volume measurements in polycystic kidney disease using a semiautomated MR segmentation algorithm. AJR American journal of roentgenology 199:387–393, 2012

    Article  PubMed  Google Scholar 

  18. Tang Y, Jackson HA, Filippo RED, Nelson MD, Jr, Moats RA: Automatic renal segmentation applied in pediatric MR Urography. IJIIP 1:12–19, 2010

    Article  Google Scholar 

  19. Borgelt C, Timm H, Kruse R: Using fuzzy clustering to improve naive Bayes classifiers and probabilistic networks. Proc. Fuzzy Systems, 2000 FUZZ IEEE 2000 The Ninth IEEE International Conference on: City, 7-10 May 2000

  20. Sun Y, et al.: Improving spatiotemporal resolution of USPIO-enhanced dynamic imaging of rat kidneys. Magnetic resonance imaging 21:593–598, 2003

    Article  PubMed  Google Scholar 

  21. Vivier PH, Dolores M, Gardin I, Zhang P, Petitjean C, Dacher JN: In vitro assessment of a 3D segmentation algorithm based on the belief functions theory in calculating renal volumes by MRI. AJR American journal of roentgenology 191:W127–134, 2008

    Article  PubMed  Google Scholar 

  22. Karstoft K, Lodrup AB, Dissing TH, Sorensen TS, Nyengaard JR, Pedersen M: Different strategies for MRI measurements of renal cortical volume. Journal of magnetic resonance imaging : JMRI 26:1564–1571, 2007

    Article  PubMed  Google Scholar 

  23. Cheong B, Muthupillai R, Rubin MF, Flamm SD: Normal values for renal length and volume as measured by magnetic resonance imaging. Clinical journal of the American Society of Nephrology : CJASN 2:38–45, 2007

    Article  PubMed  Google Scholar 

  24. Gloger O, Tonies KD, Liebscher V, Kugelmann B, Laqua R, Volzke H: Prior shape level set segmentation on multistep generated probability maps of MR datasets for fully automatic kidney parenchyma volumetry. IEEE transactions on medical imaging 31:312–325, 2012

    Article  PubMed  Google Scholar 

  25. Will S, Martirosian P, Wurslin C, Schick F: Automated segmentation and volumetric analysis of renal cortex, medulla, and pelvis based on non-contrast-enhanced T1- and T2-weighted MR images. Magma (New York, NY) 27:445–454, 2014

    CAS  Google Scholar 

  26. Gonzalez Ballester MA, Zisserman AP, Brady M: Estimation of the partial volume effect in MRI. Medical image analysis 6:389–405, 2002

    Article  PubMed  Google Scholar 

  27. Pham D, Kron T, Foroudi F, Schneider M, Siva S: A review of kidney motion under free, deep and forced-shallow breathing conditions: implications for stereotactic ablative body radiotherapy treatment. Technology in cancer research & treatment 13:315–323, 2014

    CAS  Google Scholar 

  28. Gadeberg P, Gundersen HJ, Tagehoj F: How accurate are measurements on MRI? A study on multiple sclerosis using reliable 3D stereological methods. Journal of magnetic resonance imaging : JMRI 10:72–79, 1999

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank the participants of this study.

Author information

Authors and Affiliations

  1. Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Maximiliansplatz 1, 91054, Erlangen, Germany

    Hannes Seuss, Rolf Janka, Alexander Cavallaro, Ragnar Theis, Martin Sandmair, Tobias Bäuerle, Michael Uder & Matthias Hammon

  2. Chimaera GmbH, Am Weichselgarten 7, 91058, Erlangen, Germany

    Marcus Prümmer

  3. Department of Neurology, Klinikum Nuremberg, Breslauer Str. 201, 90471, Nuremberg, Germany

    Rebecca Hammon

  4. Department of Nephropathology, University Hospital Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Krankenhausstr. 8-10, 91054, Erlangen, Germany

    Kerstin Amann

Authors
  1. Hannes Seuss
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rolf Janka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marcus Prümmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alexander Cavallaro
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rebecca Hammon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ragnar Theis
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Martin Sandmair
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Kerstin Amann
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Tobias Bäuerle
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Michael Uder
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Matthias Hammon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthias Hammon.

Ethics declarations

The institutional review board of the University Hospital Erlangen/Germany approved the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Funding

This research has been supported by the Smart Data Program in the KDI project of the Federal Ministry for Economic Affairs and Energy, Germany (01MT14001E).

Conflict of Interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Seuss, H., Janka, R., Prümmer, M. et al. 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. J Digit Imaging 30, 244–254 (2017). https://doi.org/10.1007/s10278-016-9936-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10278-016-9936-3

Keywords

Search

Navigation