Literature DB >> 31451520

Autofluorescence Imaging to Monitor the Progression of Oral Potentially Malignant Disorders.

Katelin D Cherry1, Richard A Schwarz1, Eric C Yang1,2, Imran S Vohra1, Hawraa Badaoui3, Michelle D Williams4, Nadarajah Vigneswaran5, Ann M Gillenwater3, Rebecca Richards-Kortum6.   

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 (n = 6) or surgery (n = 9). In the surveillance group, 0 of 6 (0%) of patients were clinically identified as high risk for progression prior to the study endpoint, whereas 1 of 6 (17%) of patients were deemed at high risk for progression based on AFI during the same time period. In the surgery group, 9 of 9 (100%) of patients were clinically identified as high risk prior to the study endpoint, whereas 8 of 9 (89%) of patients were at high risk for progression based on AFI during the same time period. AFI results tracked over time were comparable with expert clinical impression in these patient groups. AFI has the potential to aid clinicians in noninvasively monitoring oral precancer and evaluating OPMDs that require increased surveillance. ©2019 American Association for Cancer Research.

Entities:  

Year:  2019        PMID: 31451520      PMCID: PMC7319038          DOI: 10.1158/1940-6207.CAPR-19-0321

Source DB:  PubMed          Journal:  Cancer Prev Res (Phila)        ISSN: 1940-6215


  23 in total

1.  The binary oral dysplasia grading system: validity testing and suggested improvement.

Authors:  Paul Nankivell; Hazel Williams; Paul Matthews; Sari Suortamo; David Snead; Christopher McConkey; Hisham Mehanna
Journal:  Oral Surg Oral Med Oral Pathol Oral Radiol       Date:  2013-01

2.  Oral premalignancy: new methods of detection and treatment.

Authors:  Ann Gillenwater; Vali Papadimitrakopoulou; Rebecca Richards-Kortum
Journal:  Curr Oncol Rep       Date:  2006-03       Impact factor: 5.075

3.  Accuracy of in vivo multimodal optical imaging for detection of oral neoplasia.

Authors:  Mark C Pierce; Richard A Schwarz; Vijayashree S Bhattar; Sharon Mondrik; Michelle D Williams; J Jack Lee; Rebecca Richards-Kortum; Ann M Gillenwater
Journal:  Cancer Prev Res (Phila)       Date:  2012-05-02

Review 4.  Potentially malignant disorders of the oral and oropharyngeal mucosa; terminology, classification and present concepts of management.

Authors:  Isaäc van der Waal
Journal:  Oral Oncol       Date:  2008-07-31       Impact factor: 5.337

Review 5.  Treatment and follow-up of oral dysplasia - a systematic review and meta-analysis.

Authors:  Hisham M Mehanna; Tim Rattay; Joel Smith; Christopher C McConkey
Journal:  Head Neck       Date:  2009-12       Impact factor: 3.147

Review 6.  Prognosis of oral pre-malignant lesions: significance of clinical, histopathological, and molecular biological characteristics.

Authors:  Jesper Reibel
Journal:  Crit Rev Oral Biol Med       Date:  2003

7.  Understanding the biological basis of autofluorescence imaging for oral cancer detection: high-resolution fluorescence microscopy in viable tissue.

Authors:  Ina Pavlova; Michelle Williams; Adel El-Naggar; Rebecca Richards-Kortum; Ann Gillenwater
Journal:  Clin Cancer Res       Date:  2008-04-15       Impact factor: 12.531

8.  Nomenclature and classification of potentially malignant disorders of the oral mucosa.

Authors:  S Warnakulasuriya; Newell W Johnson; I van der Waal
Journal:  J Oral Pathol Med       Date:  2007-11       Impact factor: 4.253

9.  Development of an integrated multimodal optical imaging system with real-time image analysis for the evaluation of oral premalignant lesions.

Authors:  Eric C Yang; Imran S Vohra; Hawraa Badaoui; Richard A Schwarz; Katelin D Cherry; Timothy Quang; Justin Jacob; Alex Lang; Nancy Bass; Jessica Rodriguez; Michelle D Williams; Nadarajah Vigneswaran; Ann M Gillenwater; Rebecca R Richards-Kortum
Journal:  J Biomed Opt       Date:  2019-02       Impact factor: 3.170

Review 10.  Noninvasive diagnostic adjuncts for the evaluation of potentially premalignant oral epithelial lesions: current limitations and future directions.

Authors:  Eric C Yang; Melody T Tan; Richard A Schwarz; Rebecca R Richards-Kortum; Ann M Gillenwater; Nadarajah Vigneswaran
Journal:  Oral Surg Oral Med Oral Pathol Oral Radiol       Date:  2018-03-09
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  3 in total

Review 1.  Recent Advances and the Potential for Clinical Use of Autofluorescence Detection of Extra-Ophthalmic Tissues.

Authors:  Jonas Wizenty; Teresa Schumann; Donna Theil; Martin Stockmann; Johann Pratschke; Frank Tacke; Felix Aigner; Tilo Wuensch
Journal:  Molecules       Date:  2020-04-30       Impact factor: 4.411

2.  Band-Selection of a Portal LED-Induced Autofluorescence Multispectral Imager to Improve Oral Cancer Detection.

Authors:  Yung-Jhe Yan; Nai-Lun Cheng; Chia-Ing Jan; Ming-Hsui Tsai; Jin-Chern Chiou; Mang Ou-Yang
Journal:  Sensors (Basel)       Date:  2021-05-06       Impact factor: 3.576

3.  Prospective evaluation of oral premalignant lesions using a multimodal imaging system: a pilot study.

Authors:  Eric C Yang; Imran S Vohra; Hawraa Badaoui; Richard A Schwarz; Katelin D Cherry; Justin Jacob; Jessica Rodriguez; Michelle D Williams; Nadarajah Vigneswaran; Ann M Gillenwater; Rebecca R Richards-Kortum
Journal:  Head Neck       Date:  2019-10-17       Impact factor: 3.147

  3 in total

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