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Reproductive Imaging

  • Miriam S. Krause
  • Tiffany D. Justice
  • Rhiana D. Saunders
  • R. Ashley Milam
  • Steven T. Nakajima
Chapter

Abstract

Several different techniques are available to image the female reproductive tract. These include transvaginal ultrasonography (TVU), saline infusion sonography (SIS), hysterosalpingo-contrast sonography (HyCoSy), or performing a hysterosalpingogram (HSG) or magnetic resonance imaging (MRI) procedure. Each method has its indications, technical considerations, and limitations. TVU is easily available, relatively inexpensive, and gives information about uterine size, shape, location of leiomyomatas, and ovarian morphology. It gives limited information, however, on tubal and endometrial pathology. The SIS procedure is able to evaluate the endometrial cavity for polyps and/or an intracavitary leiomyoma. The SIS does not directly evaluate tubal patency. The HyCoSy procedure extends the SIS procedure by evaluating the fallopian tubes. The HyCoSy procedure may cause patient discomfort, can be limited in obese individuals, and requires a trained support staff and special equipment. The HSG procedure allows visualization of the entire fallopian tube, may increase post-procedure pregnancy rate, and is not limited by body habitus. It is a more invasive procedure, exposes the patient to radiation, may be associated with a reaction to contrast material, and is not available in all facilities. MRI gives additional information on the location of uterine leiomyomata, adenomyosis, and congenital anomalies and is not limited by body habitus, but it is expensive and not available in all facilities. This chapter will seek to differentiate these different methods and highlight the timely and appropriate use of each reproductive imaging procedure.

Keywords

Fallopian Tube Uterine Cavity Recurrent Pregnancy Loss Pelvic Magnetic Resonance Imaging Lower Uterine Segment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Miriam S. Krause
    • 1
  • Tiffany D. Justice
    • 1
  • Rhiana D. Saunders
    • 1
  • R. Ashley Milam
    • 2
  • Steven T. Nakajima
    • 1
  1. 1.Division of Reproductive Endocrinology and Infertility, Department of Obstetrics, Gynecology and Women’s HealthUniversity of LouisvilleLouisvilleUSA
  2. 2.Department of Diagnostic RadiologyUniversity of LouisvilleLouisvilleUSA

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