International Urogynecology Journal

, Volume 26, Issue 5, pp 707–713 | Cite as

Quantitative assessment of new MRI-based measurements to differentiate low and high stages of pelvic organ prolapse using support vector machines

  • S. Onal
  • S. Lai-Yuen
  • P. Bao
  • A. Weitzenfeld
  • D. Hogue
  • S. Hart
Original Article
  • 184 Downloads

Abstract

Introduction and hypothesis

The objective of this study was to quantitatively assess the ability of new MRI-based measurements to differentiate low and high stages of pelvic organ prolapse. New measurements representing pelvic structural characteristics are proposed and analyzed using support vector machines (SVM).

Methods

This retrospective study used data from 207 women with different types and stages of prolapse. Their demographic information, clinical history, and dynamic MRI data were obtained from the database. New MRI measurements were extracted and analyzed based on these reference lines: pubococcygeal line (PCL), mid-pubic line (MPL), true conjugate line (TCL), obstetric conjugate line (OCL), and diagonal conjugate line (DCL). A classification model using SVM was designed to assess the impact of the features (variables) in classifying prolapse into low or high stage.

Results

The classification model using SVM can accurately identified anterior prolapse with very high accuracy (>0.90), and apical and posterior prolapse with good accuracy (0.80 – 0.90). Two newly proposed MRI-based features were found to be significant in the identification of anterior and posterior prolapse: the angle between TCL and MPL for anterior prolapse, and the angle between DCL and PCL for posterior prolapse. The overall accuracy of posterior prolapse identification increased from 47 % to 80 % when the newly proposed MRI-based features were taken into consideration.

Conclusions

The proposed MRI-based measurements are effective in differentiating low and high stages of pelvic organ prolapse, particularly for posterior prolapse.

Keywords

Pelvic organ prolapse Dynamic MRI Classification 

Notes

Conflicts of interest

S. Onal: None.

S. Lai-Yuen: None.

P. Bao: None.

A. Weitzenfeld: None.

D. Hogue: None.

S. Hart: Speaker and Consultant for Boston Scientific, Covidien, Cooper Surgical, and Stryker.

Authors’ participation

S Onal: manuscript writing, model building, and data analysis

S Lai-Yuen: project development, manuscript writing/editing

P Bao: project development

A Weitzenfeld: project development

D Hogue: data collection

S Hart: project development, data collection, manuscript editing

Supplementary material

192_2014_2582_MOESM1_ESM.docx (66 kb)
(DOCX 66 kb)

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Copyright information

© The International Urogynecological Association 2014

Authors and Affiliations

  • S. Onal
    • 1
  • S. Lai-Yuen
    • 2
  • P. Bao
    • 3
  • A. Weitzenfeld
    • 3
  • D. Hogue
    • 4
  • S. Hart
    • 4
    • 5
  1. 1.Department of Mechanical and Industrial EngineeringSouthern Illinois University-EdwardsvilleEdwardsvilleUSA
  2. 2.Department of Industrial & Management Systems EngineeringUniversity of South FloridaTampaUSA
  3. 3.Department of Computer Science and EngineeringUniversity of South FloridaTampaUSA
  4. 4.Department of Obstetrics & Gynecology, Division of Female Pelvic Medicine and Reconstructive SurgeryUniversity of South FloridaTampaUSA
  5. 5.USF Health Center for Advanced Medical Learning and Simulation (CAMLS)TampaUSA

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