ArticleJournal of biomedical optics2012
Wide-field spectral imaging of human ovary autofluorescence and oncologic diagnosis via previously collected probe data.
Article in Journal of biomedical optics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Intraoperative multispectral and hyperspectral label-free imaging: A systematic review of in vivo clinical studies.Journal of biophotonics · 2019Pooled it
- From Image-Guided Surgery to Computer-Assisted Real-Time Diagnosis with Hyperspectral and Multispectral Imaging: A Systematic Review in Gynecologic Oncology.Diagnostics (Basel, Switzerland) · 2026Review
- Compact and ultracompact spectral imagers: technology and applications in biomedical imaging.Journal of biomedical optics · 2023Review
- An ultra-small nine-color spectrometer with a two-layer biparted ten-dichroic-mirror array and an image sensor.Scientific reports · 2022Article
- Label-free hyperspectral imaging and deep-learning prediction of retinal amyloid β-protein and phosphorylated tau.PNAS nexus · 2022Article
- Microscopy is better in color: development of a streamlined spectral light path for real-time multiplex fluorescence microscopy.Biomedical optics express · 2022Article
- Single-Cell Analysis Using Hyperspectral Imaging Modalities.Journal of biomechanical engineering · 2018Review
- Ultraminiature optical design for multispectral fluorescence imaging endoscopes.Journal of biomedical optics · 2017Article
- Multispectral fluorescence imaging of human ovarian and fallopian tube tissue for early-stage cancer detection.Journal of biomedical optics · 2016Article
- Medical hyperspectral imaging: a review.Journal of biomedical optics · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
With no sufficient screening test for ovarian cancer, a method to evaluate the ovarian disease state quickly and nondestructively is needed. The authors have applied a wide-field spectral imager to freshly resected ovaries of 30 human patients in a study believed to be the first of its magnitude. Endogenous fluorescence was excited with 365-nm light and imaged in eight emission bands collectively covering the 400- to 640-nm range. Linear discriminant analysis was used to classify all image pixels and generate diagnostic maps of the ovaries. Training the classifier with previously collected single-point autofluorescence measurements of a spectroscopic probe enabled this novel classification. The process by which probe-collected spectra were transformed for comparison with imager spectra is described. Sensitivity of 100% and specificity of 51% were obtained in classifying normal and cancerous ovaries using autofluorescence data alone. Specificity increased to 69% when autofluorescence data were divided by green reflectance data to correct for spatial variation in tissue absorption properties. Benign neoplasm ovaries were also found to classify as nonmalignant using the same algorithm. Although applied ex vivo, the method described here appears useful for quick assessment of cancer presence in the human ovary.
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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 OpenQuestion graph.