344
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Histopathological and biochemical assessment of a novel diagnostic method for ovarian torsion

, ORCID Icon, , , , & ORCID Icon show all
Pages 203-209 | Published online: 01 Oct 2019
 

ABSTRACT

Ovarian torsion is agynecologic emergency that affects females of all ages. Early diagnosis is important to preserve ovarian function. The false positive rate for sonographic diagnosis of ovarian torsion is 50%; therefore, a new real-time approach is required to improve diagnostic accuracy. We investigated diffuse reflectance spectroscopy for diagnosing ovarian torsion. Spectroscopic measurements were performed in vivo prior to, during and after detorsion. After bilateral oophorectomy, hemoxygenase and myeloperoxidase enzyme activity in ovarian tissue was evaluated and the tissues were examined for pathology. Spectroscopic data were compared to histopathological and biochemical data to assess the diagnostic value of the spectroscopic method for differentiating healthy and damaged ovarian tissue. We found a good correlation between spectroscopy and histopathology. We also found a correlation between the spectroscopic data and heme oxygenase enzyme activity. We found no correlation between the histopathological tissue damage score and myeloperoxidase enzyme activity. Diffuse reflectance spectroscopy may be of prognostic and diagnostic value for ovarian torsion in vivo.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 203.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.