ArticleJournal of biophotonics2019
Histogram analysis of en face scattering coefficient map predicts malignancy in human ovarian tissue.
Article in Journal of biophotonics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Optical coherence tomography enables optical biopsy of endometrial tissue for early cancer detection.Npj imaging · 2026Article
- Multiclass risk models for ovarian malignancy: an illustration of prediction uncertainty due to the choice of algorithm.BMC medical research methodology · 2023Article
- Enhanced 3D visualization of human fallopian tube morphology using a miniature optical coherence tomography catheter.Biomedical optics express · 2023Article
- Depth-resolved attenuation mapping of the human ovary and fallopian tube using optical coherence tomography.Journal of biophotonics · 2023Article
- Optical coherence tomography for dynamic investigation of mammalian reproductive processes.Molecular reproduction and development · 2023Review
- Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning.Journal of biophotonics · 2022Article
- Diagnosing colorectal abnormalities using scattering coefficient maps acquired from optical coherence tomography.Journal of biophotonics · 2021Article
- Optical Resolution Photoacoustic Microscopy of Ovary and Fallopian Tube.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
Ovarian cancer is a heterogeneous disease at the molecular and histologic level. Optical coherence tomography (OCT) is able to map ovarian tissue optical properties and heterogeneity, which has been proposed as a feature to aid in diagnosis of ovarian cancer. In this manuscript, depth-resolved en face scattering maps of malignant ovaries, benign ovaries, and benign fallopian tubes obtained from 20 patients are provided to visualize the heterogeneity of ovarian tissues. Six features are extracted from histograms of scattering maps. All features are able to statistically distinguish benign from malignant ovaries. Two prediction models were constructed based on these features: a logistic regression model (LR) and a support vector machine (SVM). The optimal set of features is mean scattering coefficient and scattering map entropy. The LR achieved a sensitivity and specificity of 97.0% and 97.8%, and SVM demonstrated a sensitivity and specificity of 99.6% and 96.4%. Our initial results demonstrate the feasibility of using OCT as an "optical biopsy tool" for detecting the microscopic scattering changes associated with neoplasia in human ovarian tissue.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.