ArticleJournal of medical imaging (Bellingham, Wash.)2017
Toward real-time quantification of fluorescence molecular probes using target/background ratio for guiding biopsy and endoscopic therapy of esophageal neoplasia.
Article in Journal of medical imaging (Bellingham, Wash.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
9 citing papers in PubMed, 13 citations in OpenAlex.
- Flexible fiber cholangioscope for detection of near-infrared fluorescence.VideoGIE : an official video journal of the American Society for Gastrointestinal Endoscopy · 2023Article
- Development of Advanced Imaging and Molecular Imaging for Barrett's Neoplasia.Diagnostics (Basel, Switzerland) · 2022Review
- Deep-Learning-Based Real-Time and Automatic Target-to-Background Ratio Calculation in Fluorescence Endoscopy for Cancer Detection and Localization.Diagnostics (Basel, Switzerland) · 2022Article
- Predictive effect of J waves on cardiac compression and clinical prognosis of esophageal tumors: a retrospective study.Journal of gastrointestinal oncology · 2022Article
- Optical Biopsy of the Upper GI Tract Using Fluorescence Lifetime and Spectra.Frontiers in physiology · 2020Article
- Calibration of fluorescence imaging for tumor surgical margin delineation: multistep registration of fluorescence and histological images.Journal of medical imaging (Bellingham, Wash.) · 2019Article
- Early esophageal adenocarcinoma detection using deep learning methods.International journal of computer assisted radiology and surgery · 2019Article
- Bimodal reflectance and fluorescence multispectral endoscopy based on spectrally resolving detector arrays.Journal of biomedical optics · 2018Article
- Real-time endoscopic optical properties imaging.Biomedical optics express · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Multimodal endoscopy using fluorescence molecular probes is a promising method of surveying the entire esophagus to detect cancer progression. Using the fluorescence ratio of a target compared to a surrounding background, a quantitative value is diagnostic for progression from Barrett's esophagus to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC). However, current quantification of fluorescent images is done only after the endoscopic procedure. We developed a Chan-Vese-based algorithm to segment fluorescence targets, and subsequent morphological operations to generate background, thus calculating target/background (T/B) ratios, potentially to provide real-time guidance for biopsy and endoscopic therapy. With an initial processing speed of 2 fps and by calculating the T/B ratio for each frame, our method provides quasireal-time quantification of the molecular probe labeling to the endoscopist. Furthermore, an automatic computer-aided diagnosis algorithm can be applied to the recorded endoscopic video, and the overall T/B ratio is calculated for each patient. The receiver operating characteristic curve was employed to determine the threshold for classification of HGD/EAC using leave-one-out cross-validation. With 92% sensitivity and 75% specificity to classify HGD/EAC, our automatic algorithm shows promising results for a surveillance procedure to help manage esophageal cancer and other cancers inspected by endoscopy.
Indexed as
Identifiers
What OpenQuestion holds
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.