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Spectroscopy
Volume 18, Issue 1, Pages 75-84
http://dx.doi.org/10.1155/2004/975105

Raman spectroscopy for diagnosis of calcification in human heart valves

Enrique Uceda Otero,1 Sokki Sathaiah,1,4 Landulfo Silveira Jr.,1 Pablo Maria Alberto Pomerantzeff,2 and Carlos Augusto Gonçalves Pasqualucci3

1Biomedical Engineering Division, Institute for Research and Development, University of Vale do Paraíba ‒ UNIVAP, Av. Shishima Hifumi, 2911 Urbanova, ZIP: 12244-456, São José dos Campos, SP, Brazil
2Institute of Heart, University of São Paulo ‒ USP, Av. Dr. Enéas de Carvalho Aguiar, 44 Cerqueira César, ZIP: 05403-000, São Paulo, SP, Brazil
3Department of Cardiovascular Pathology, Faculty of Medicine, University of São Paulo ‒ USP, Av. Dr. Arnaldo, 455, Cerqueira César, ZIP: 01246-903, São Paulo, SP, Brazil
4Group of Diagnosis and Laser Therapy, Biomedical Engineering Division, Instituto de Pesquisa e Desenvolvimento ‒ IP&D, University of Vale do Paraíba ‒ UNIVAP, Av. Shishima Hifumi, Urbanova, 2911, ZIP: 12244-456, São José dos Campos, SP, Brazil

Copyright © 2004 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Near-Infrared Raman Spectroscopy (NIRS) has an excellent potential for a rapid, a less invasive and real time diagnosis of various human diseases. The objective of the present study was to apply NIRS for diagnosis of human heart valves and to develop a feasible algorithm to classify the valvular lesions. For Raman studies, a Ti:sapphire laser pumped by an argon laser provided 830 nm excitation. A spectrograph in conjunction with a liquid N2-cooled CCD detected Raman spectra. A total of 97 fragments of human heart valves were scanned and Raman results were compared with histopathology. Spectra were randomly separated into training and prospective groups. Raman data along with Principal Components Analysis (PCA) and Mahalanobis distance were used to model an algorithm for tissue classification, into two categories: normal (N), and calcified (C) heart valves. It has been found that, for N valves, the algorithm has sensitivities of 95%, 100% and specificities of 100%, 100% for training and prospective groups, respectively. For C valves the algorithm provided sensitivities of 100 and 100% and specificities of 95 and 100% for training and prospective groups, respectively. In conclusion, an algorithm has been developed and successfully applied for NIRS diagnosis of human heart valves with high sensitivities and specificities.