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Improved endoscope for imaging and cell collection in the fallopian tubes

  • Dominique Gálvez
  • , Andrew Daniel Rocha
  • , Alana G. Gonzales
  • , Dilara J. Long
  • , Photini Faith Rice
  • , Makayla R. Johnson
  • , Ethan Tovar
  • , Bo Lwin
  • , Helen Varghese
  • , Kongit Amaha
  • , David Fishman
  • , John M. Heusinkveld
  • , Jennifer Kehlet Barton

Research output: Contribution to journal › Article › peer-review

Abstract

Significance: Early detection of ovarian cancer requires the observation of subtle changes within the fallopian tubes, where serous tubal intraepithelial carcinoma lesions, the putative precursor of high-grade ovarian serous carcinoma, may be present and detectable. Aim: The cell-acquiring fallopian endoscope was designed to detect and interrogate potentially pathological sites in the fallopian tubes via alterations in fluorescence signal and the collection of epithelial cells. Approach: We performed a comprehensive redesign of a first-generation endoscope prototype and demonstrated its performance in whole, human ex vivo fallopian tubes. Through the iterative improvements to the design, the endoscope features improved imaging, cell collection, and general ease of use. Specifically, improvements included a larger core count fiber imaging bundle, a redesigned close-focus lens, more flexible materials, an altered cell collection method, and a lighter-weight handle. Results: With benign fallopian tube samples from three patients, we demonstrate cell collection on the order of 104 cells per collection and imaging capabilities that result in average image intensity ratios. Conclusions: This second-generation endoscope is suitable for the study of intact fallopian tubes.

Original languageEnglish (US)
Article number025001
JournalBiophotonics Discovery
Volume3
Issue number2
DOIs
StatePublished - Apr 1 2026

Keywords

  • biopsy
  • endoscope
  • endoscopy
  • fallopian tubes.
  • fluorescence
  • ovarian cancer

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • Medicine (miscellaneous)
  • Radiology Nuclear Medicine and imaging
  • Biomedical Engineering
  • Artificial Intelligence

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