ArticleCancer prevention research (Philadelphia, Pa.)2019
Autofluorescence Imaging to Monitor the Progression of Oral Potentially Malignant Disorders.
Article in Cancer prevention research (Philadelphia, Pa.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 13 citations in OpenAlex.
- Transcriptomic Profile of Oral Cancer Lesions: A Proof-of-Concept Pilot Study of FFPE Tissue Sections.International journal of molecular sciences · 2025Article
- Emerging Trends in Point-of-Care Technology Development for Oncology in Low- and Middle-Income Countries.JCO global oncology · 2025Review
- Recent advance in early oral lesion diagnosis: the application of artificial intelligence-assisted endoscopy.Frontiers in oncology · 2025Review
- Optical imaging for screening and early cancer diagnosis in low-resource settings.Nature reviews bioengineering · 2024Article
- Band-Selection of a Portal LED-Induced Autofluorescence Multispectral Imager to Improve Oral Cancer Detection.Sensors (Basel, Switzerland) · 2021Article
- Recent Advances and the Potential for Clinical Use of Autofluorescence Detection of Extra-Ophthalmic Tissues.Molecules (Basel, Switzerland) · 2020Review
- Prospective evaluation of oral premalignant lesions using a multimodal imaging system: a pilot study.Head & neck · 2020Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
Patients with oral potentially malignant disorders (OPMD) must undergo regular clinical surveillance to ensure that any progression to malignancy is detected promptly. Autofluorescence imaging (AFI) is an optical modality that can assist clinicians in detecting early cancers and high-grade dysplasia. Patients with OPMD undergoing surveillance for the development of oral cancer were examined using AFI at successive clinic visits. Autofluorescence images acquired at 133 clinical visits from sites in 15 patients who met inclusion criteria were analyzed quantitatively using an algorithm to calculate the red-to-green pixel intensity (RG ratio). A quantitative AFI threshold for high risk of progression was defined based on the RG ratio and was compared with expert clinical impression and with histopathology when available. Patients were divided into two groups based on their endpoint: surveillance (
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Registered trials
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