Skip to main content

Advertisement

SpringerLink
Log in

New technique for prostate volume assessment

  • Original Article
  • Published:
World Journal of Urology Aims and scope Submit manuscript

Abstract

Purpose

The prostate-specific antigen density (PSAD) helps distinguish between benign prostatic hyperplasia (BPH) and prostate cancer. Accurate prostate volume (PV) assessment is necessary for PSAD calculation and both BPH diagnosis and treatment response monitoring; therefore, accurate PV measurement is increasingly becoming an essential step in the urology.

Methods

Magnetic resonance imaging was used for PV estimation. A new technique based on single-class support-vector machines (S SVM) for accurate PV estimation was realized. Three estimation methods were compared; method 1: planimetry (reference), method 2: S SVM based, and method 3: prolate ellipsoid.

Results

Method 1 and method 2 depict a strong correlation (Spearman’s rank correlation coefficient ρ = 0.965, p > 0.001). The interrater reliability for method 1 and method 2 readings as expressed by the intraclass correlation coefficient (ICC) was 0.975 (p > 0.001). Comparison between method 3 and the two other methods shows ρ = 0.873 (p > 0.001), and ρ = 0.795 (p > 0.001), respectively. ICC was 0.54 and 0.505, respectively. The mean difference between method 1 and method 2 was −0.05 ml. The limits of agreement with the 95 % confidence interval were −3.8 to 3.7 ml. Comparing method 3 and the two other methods shows a worse agreement with mean difference of 8.6 ml (95 % confidence interval of 1.0–16.2 ml) and 8.6 ml (95 % confidence interval of −0.7 to 18.0 ml), respectively.

Conclusions

The prostate volumes obtained by our technique agreed excellently with the planimetry (reference) method. This new technique would be clinically useful for urologists in prostate volumetric analysis.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

BPH:

Benign prostatic hyperplasia

TRUS:

Transrectal ultrasound

PV:

Whole prostate volume

PSA:

Prostate-specific antigen

MRI:

Magnetic resonance imaging

PSAD:

Prostate-specific antigen density

References

  1. Zoltan E, Lee R, Staskin DR et al (2008) Combination therapy for benign prostatic hyperplasia: does size matter? Curr Bladder Dysfunct Rep 3(2):102–108

    Article  Google Scholar 

  2. Stamey TA, Yang N, Hay AR et al (1987) Prostate specific antigen as a serum marker for adenocarcinoma of the prostate. N Engl J Med 317(15):909–916

    Article  CAS  PubMed  Google Scholar 

  3. Vesely S, Knutson T, Damber JE et al (2003) Relationship between age, prostate volume, prostate-specific antigen, symptom score and uroflowmetry in men with lower urinary tract symptoms. Scand J Urol Nephrol 37(4):322–328

    Article  PubMed  Google Scholar 

  4. Kim JM, Song PH, Kim HT et al (2011) Effect of obesity on prostate-specific antigen, prostate volume, and international prostate symptom score in patients with benign prostatic hyperplasia. Korean J Urol 52(6):401–405

    Article  PubMed Central  PubMed  Google Scholar 

  5. Milonas D, Trumbeckas D, Juska P (2003) The importance of prostatic measuring by transseptal ultrasound in surgical management of patients with clinically benign prostatic hyperplasia. Medicina (Kaunas) 39(9):860–866

    Google Scholar 

  6. Völzke H, Alte D, Schmidt CO et al (2011) Cohort profile: the study of health in Pomerania. Int J Epidemiol 40(2):294–307

    Article  PubMed  Google Scholar 

  7. Hegenscheid K, Kühn JP, Völzke H et al (2009) Whole-body magnetic resonance imaging of healthy volunteers: pilot study results from the population-based SHIP study. Rofo 181(8):748–759

    Article  CAS  PubMed  Google Scholar 

  8. Schneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9(7):671–675

    Article  CAS  PubMed  Google Scholar 

  9. Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273–297

    Google Scholar 

  10. Schölkopf B, Smola AJ (2001) Learning with Kernels: support vector machines, regularization, optimization, and beyond. MIT Press, Massachusetts (USA)

    Google Scholar 

  11. Habes M, Schiller T, Rosenberg C et al (2013) Automated prostate segmentation in whole-body MRI scans for epidemiological studies. Phys Med Biol 58:5899–5916

    Article  PubMed  Google Scholar 

  12. Schölkopf B, Platt JC, Shawe-Taylor J et al (2001) Estimating the support of a high-dimensional distribution. Neural Comput 13(7):1443–1471

    Article  PubMed  Google Scholar 

  13. Bland MJ, Altman D (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327(8476):307–310

    Article  Google Scholar 

  14. Shrout PE, Fleiss JL (1979) Estimating the support of a high-dimensional distribution. Psychol Bull 86(2):420–428

    Article  CAS  PubMed  Google Scholar 

  15. Portney LG, Watkins MP (1993) Foundations of Clinical Research: applications to Practice Pearson/Prentice Hal, USA

  16. Benson M, Whang I, Pantuck A et al (1992) Prostate septic antigen density: a means of distinguishing benign prostatic hypertrophy and prostate cancer. J Urol 147(3 Pt 2):815

    CAS  PubMed  Google Scholar 

  17. Stephan C, Stroebel G, Heinau M et al (2005) The ratio of prostate-septic antigen (PSA) to prostate volume (PSA density) as a parameter to improve the detection of prostate carcinoma in PSA values in the range of <4 ng/ml. Cancer 104(5):993

    Article  PubMed  Google Scholar 

  18. Roehrborn CG, Boyle P, Gould AL, Waldstreicher J (1999) Serum prostate-specific antigen as a predictor of prostate volume in men with benign prostatic hyperplasia. Urology 53(3):581–589

    Article  CAS  PubMed  Google Scholar 

  19. Morote J, Encabo G, Lopez M, de Torres IM (2000) Prediction of prostate volume based on total and free serum prostate–specific antigen: is it reliable? Eur Urol 38(1):91–95

    Article  CAS  PubMed  Google Scholar 

  20. Park T, Chae JY, Kim JW et al (2013) Prostate-specific antigen mass and free prostate-specific antigen mass for predicting the prostate volume of Korean men with biopsy-proven benign prostatic hyperplasia. Korean J Urol 54(9):609–614

    Article  PubMed Central  PubMed  Google Scholar 

  21. Di Silverio F, Bosman C, Salvatori M et al (2005) Combination therapy with rofecoxib and finasteride in the treatment of men with lower urinary tract symptoms (LUTS) and benign prostatic hyperplasia (BPH). Eur Urol 47(1):72–79

    Article  PubMed  Google Scholar 

  22. MacMahon PJ, Kennedy AM, Murphy DT et al (2009) Modified prostate volume algorithm improves transseptal US volume estimation in men presenting for prostate brachytherapy. Radiology 250(1):273–280

    Article  PubMed  Google Scholar 

  23. Kimura A, Kurooka Y, Kitamura T et al (1997) Biplane planimetry as a new method for prostatic volume calculation in transseptal. Int J Urol 4(2):152

    Article  CAS  PubMed  Google Scholar 

  24. Al-Rimawi M, Griffiths DJ, Boake RC et al (1994) Transseptal ultrasound versus magnetic resonance imaging in the estimation of prostatoc volume. BJU Int 74(5):596–600

    Article  CAS  Google Scholar 

  25. Weiss BE, Wein AJ, Malkowicz SB et al (2012) Comparison of prostate volume measured by transrectal ultrasound and magnetic resonance imaging: is transrectal ultrasound suitable to determine which patients should undergo active surveillance? Urol Oncol 31(8):1436–1440

    Article  PubMed  Google Scholar 

  26. Turkbey B, Huang R, Vourganti S et al (2012) Age-related changes in prostate zonal volumes as measured by high-resolution magnetic resonance imaging (MRI): a cross-sectional study in over 500 patients. BJU Int 110(11):1642–1647

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The present work has been supported by a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the “Center of Knowledge Interchange” program of Siemens AG.

Conflict of interest

No conflict of interest to be declared.

Author information

Authors and Affiliations

  1. Institute for Community Medicine, University of Greifswald, Ellernholzstr. 1-2, 17487, Greifswald, Germany

    Mohamad Habes, Jeanette Bahr & Wolfgang Hoffmann

  2. Institute for Urology, University of Greifswald, Greifswald, Germany

    Thilo Schiller, Laura Hoppe & Martin Burchardt

  3. Department of Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany

    Jens-Peter Kühn

Authors
  1. Mohamad Habes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeanette Bahr
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thilo Schiller
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jens-Peter Kühn
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Laura Hoppe
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Martin Burchardt
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wolfgang Hoffmann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohamad Habes.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 32 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Habes, M., Bahr, J., Schiller, T. et al. New technique for prostate volume assessment. World J Urol 32, 1559–1564 (2014). https://doi.org/10.1007/s00345-013-1220-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00345-013-1220-2

Keywords

Search

Navigation