ArticleHNO2016
[Early recognition of cancerous lesions in the mouth and oropharynx: Automated evaluation of hyperspectral image stacks].
Article in HNO, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Intraoperative multispectral and hyperspectral label-free imaging: A systematic review of in vivo clinical studies.Journal of biophotonics · 2019Pooled it
- Review on the Application of Hyperspectral Imaging Technology of the Exposed Cortex in Cerebral Surgery.Frontiers in bioengineering and biotechnology · 2022Review
- Automatic Recognition of Colon and Esophagogastric Cancer with Machine Learning and Hyperspectral Imaging.Diagnostics (Basel, Switzerland) · 2021Article
- Review
- Article
- In-Vivo and Ex-Vivo Tissue Analysis through Hyperspectral Imaging Techniques: Revealing the Invisible Features of Cancer.Cancers · 2019Review
- An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation.Sensors (Basel, Switzerland) · 2018Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly detection of cancerous lesions is still crucial for a patient's prognosis. Although diagnostic access to the oral cavity and oropharynx is comparably easy, the incidence of resulting disease remains high. This is due to the fact that in many cases, malignity is recognized too late on a purely visual basis. Previously, we discussed the application of hyperspectral imaging for early detection of precancerous and cancerous lesions of the larynx. This time, we evaluate the method in the oral cavity and oropharynx. MATERIALS AND
methodsIn 85 patients scheduled for endoscopy, hyperspectral imaging was performed. We used a rigid 0-degree endoscope, a light-adjustable monochromator, and a hyperspectral camera. For evaluation of the method, 3 patients were chosen exemplarily. Training sites from physiological and cancerous tissues were marked. Hyperspectral data from 1 patient were used to train a classifier, which was then used for automatic detection of precancerous and cancerous lesions in another 2 patients.
resultsIntraoperative hyperspectral imaging was performed without any problems. Classification showed sensitivities of 61 and 43%, and a specificity of 100%.
conclusionThis proof-of-concept study underscores the high potential of hyperspectral imaging for early recognition of cancer in the mouth and oropharynx. Besides a better prognosis for cancer patients, this approach could lead to higher cost efficiency in the health system.
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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.