96 Computerized morphometry of epithelial fimbriae combined with artificial intelligence in BRCA carriers may identify patients at risk for developing ovarian cancer; a preliminary study. (18th September 2019)
- Record Type:
- Journal Article
- Title:
- 96 Computerized morphometry of epithelial fimbriae combined with artificial intelligence in BRCA carriers may identify patients at risk for developing ovarian cancer; a preliminary study. (18th September 2019)
- Main Title:
- 96 Computerized morphometry of epithelial fimbriae combined with artificial intelligence in BRCA carriers may identify patients at risk for developing ovarian cancer; a preliminary study
- Authors:
- Amit, A
Sabo, E
Petruseva, A
Reiss, A
Klorin, G - Abstract:
- Abstract : Objectives: Some ovarian tumors may originate in epithelial cells of the fallopian tubes. Computerized morphometry was able to find significant alterations in the fallopian tube epithelium of healthy BRCA carriers. The purpose of this study was to identify a subgroup of BRCA carriers that may be at risk to develop ovarian cancer by evaluation of the epithelium of fallopian tubes using artificial intelligence. Methods: Four groups of patients were analyzed. Healthy patients and ovarian cancer patients, BRCA carriers and non -carriers. All fallopian tubes were normal by H&E examination. Using ImageProPlus software and Neural Network analysis the nuclear symmetry of 65 fimbriae epithelium cells was analyzed. Further evaluation using artificial intelligence was applied in order to detect a subpopulation among fimbriae of healthy BRCA carriers, at risk for ovarian cancer. Results: Significant differences were found between healthy patients and ovarian cancer patients and between BRCA carriers and non-carriers. The artificial intelligence algorithm was able to accurately predict BRCA carriers with associated ovarian cancer based on fallopian tubes nuclear morphometry. Conclusions: These results reinforce the hypothesis that fimbriae epithelium cells of BRCA carriers' may undergo early-stage changes that may predict progression toward malignancy. Artificial intelligence may identify patients at high risk for malignancy initiated in the fallopian tubes.
- Is Part Of:
- International journal of gynecological cancer. Volume 29(2019)Supplement 3
- Journal:
- International journal of gynecological cancer
- Issue:
- Volume 29(2019)Supplement 3
- Issue Display:
- Volume 29, Issue 3 (2019)
- Year:
- 2019
- Volume:
- 29
- Issue:
- 3
- Issue Sort Value:
- 2019-0029-0003-0000
- Page Start:
- A49
- Page End:
- A49
- Publication Date:
- 2019-09-18
- Subjects:
- Generative organs, Female -- Cancer -- Periodicals
616.99465 - Journal URLs:
- http://journals.lww.com/ijgc/pages/default.aspx ↗
http://www3.interscience.wiley.com/journal/118544021/toc ↗
https://ijgc.bmj.com/ ↗
http://journals.lww.com ↗ - DOI:
- 10.1136/ijgc-2019-IGCS.96 ↗
- Languages:
- English
- ISSNs:
- 1048-891X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.273500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19726.xml