𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Discriminant analysis of autofluorescence spectra for classification of oral lesions in vivo

✍ Scribed by J.L. Jayanthi; Rupananda J. Mallia; Sara Thomas Shiny; Kamalsanan V. Baiju; Anitha Mathews; Rejnish Kumar; Paul Sebastian; Jayaprakash Madhavan; G.N. Aparna; Narayanan Subhash


Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
95 KB
Volume
41
Category
Article
ISSN
0196-8092

No coin nor oath required. For personal study only.

✦ Synopsis


Abstract

Background and Objectives

Low survival rate of individuals with oral cancer emphasize the significance of early detection and treatment. Optical spectroscopic techniques are under various stages of development for diagnosis of epithelial neoplasm. This study evaluates the potential of a multivariate statistical algorithm to classify oral mucosa from autofluorescence spectral features recorded in vivo.

Study Design/Methods

Autofluorescence spectra were recorded in a clinical trial from 15 healthy volunteers and 34 patients with diode laser excitation (404 nm) and pre‐processed by normalization, mean‐scaling and its combination. Linear discriminant analysis (LDA) based on leave‐one‐out (LOO) method of cross validation was performed on spectral data for tissue characterization. The sensitivity and specificity were determined for different lesion pairs from the scatter plot of discriminant function scores.

Results

Autofluorescence spectra of healthy volunteers consists of a broad emission at 500 nm that is characteristic of endogenous fluorophores, whereas in malignant lesions three additional peaks are observed at 635, 685, and 705 nm due to the accumulation of porphyrins in oral lesions. It was observed that classification design based on discriminant function scores obtained by LDA‐LOO method was able to differentiate pre‐malignant dysplasia from squamous cell carcinoma (SCC), benign hyperplasia from dysplasia and hyperplasia from normal with overall sensitivities of 86%, 78%, and 92%, and specificities of 90%, 100%, and 100%, respectively.

Conclusions

The application of LDA‐LOO method on the autofluorescence spectra recorded during a clinical trial in patients was found suitable to discriminate oral mucosal alterations during tissue transformation towards malignancy with improved diagnostic accuracies. Lasers Surg. Med. 41:345–352, 2009. © 2009 Wiley‐Liss, Inc.


📜 SIMILAR VOLUMES


In vivo autofluorescence spectroscopy of
✍ Tsuimin Tsai; Hsin-Ming Chen; Chih-Yu Wang; Jui-Chang Tsai; Dr. Chin-Tin Chen; C 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 331 KB 👁 1 views

## Abstract ## Background and Objectives To test whether autofluorescence spectroscopy can be used for the diagnosis of oral neoplasia in a high‐risk population, we characterized the in vivo autofluorescence spectra from oral submucous fibrosis (OSF) lesions and oral premalignant and malignant les

Porphyrin-like fluorescence in oral canc
✍ Masahiro Inaguma; Kenji Hashimoto 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 344 KB 👁 2 views

## BACKGROUND. Red fluorescence from malignant tumors was observed in experimentally induced rat sarcoma by Policard (1924) and in ulcerated human oral carcinoma by Harris et al. (1987) by examination with ultraviolet (UV) irradiation. The objective of the current study was twofold: to examine in

Independent component analysis for autom
✍ Christophe Ladroue; Franklyn A. Howe; John R. Griffiths; A. Rosemary Tate 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 312 KB

## Abstract Fully automated methods for analyzing MR spectra would be of great benefit for clinical diagnosis, in particular for the extraction of relevant information from large databases for subsequent pattern recognition analysis. Independent component analysis (ICA) provides a means of decompos

An automated iterative algorithm for the
✍ Robert E. Lenkinski; Tim Allman; Jacob D. Scheiner; Stanley N. Deming 📂 Article 📅 1989 🏛 John Wiley and Sons 🌐 English ⚖ 533 KB

The success in utilizing in vivo NMR to identify and/or monitor metabolic abnormalities will be determined in large part on the reliability with which the spectral parameters of the metabolites present can be measured. For these reasons it is clear that there is a need for the development of algorit