ArticleBiomedical optics express2021
Colon phantoms with cancer lesions for endoscopic characterization with optical coherence tomography.
Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 16 citations in OpenAlex.
- Fabrication of an Anatomically Realistic Intestinal Phantom with Villous Microstructure.Bioengineering (Basel, Switzerland) · 2026Article
- Endoscopic iso-pathlength self-calibration for direction-resolved retrieval of tissue optical properties.Journal of biomedical optics · 2026Article
- Optical phantoms for the characterization and validation of imaging and spectroscopy: a review.Biophotonics discovery · 2026Review
- Advances and Opportunities in NIR-II Endoscopy: From Diagnosis to Therapeutic Applications.Diagnostics (Basel, Switzerland) · 2026Review
- Hydraulic endorectal actuator for prostate radiotherapy reduces variations in motion in a silicone rectal phantom.Frontiers in oncology · 2026Article
- Sodium alginate-based tissue-mimicking phantom with tunable optical properties for laser thermotherapy.Biomedical optics express · 2025Article
- Segmental airway adenocarcinoma-simulating phantom for endoscopic near-infrared optical coherence tomography.Journal of biomedical optics · 2025Article
- The LMIT: Light-mediated minimally-invasive theranostics in oncology.Theranostics · 2024Review
- Optical Tissue Phantoms for Quantitative Evaluation of Surgical Imaging Devices.Advanced photonics research · 2023Article
- Standardization and implementation of fluorescence molecular endoscopy in the clinic.Journal of biomedical optics · 2022Article
- Birefringent tissue-mimicking phantom for polarization-sensitive optical coherence tomography imaging.Journal of biomedical optics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Optical coherence tomography (OCT) is a growing imaging technique for real-time early diagnosis of digestive system diseases. As with other well-established medical imaging modalities, OCT requires validated imaging performance and standardized test methods for performance assessment. A major limitation in the development and testing of new imaging technologies is the lack of models for simultaneous clinical procedure emulation and characterization of healthy and diseased tissues. Currently, the former can be tested in large animal models and the latter can be tested in small animal disease models or excised human biopsy samples. In this study, a 23 cm by 23 cm optical phantom was developed to mimic the thickness and near-infrared optical properties of each anatomical layer of a human colon, as well as the surface topography of colorectal polyps and visual appearance compatible with white light endoscopy.
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.