Literature DB >> 11235596

A novel optical imaging method for the early detection, quantitative grading, and mapping of cancerous and precancerous lesions of cervix.

C Balas1.   

Abstract

This paper describes a novel optical imaging method for the in vivo early detection, quantitative staging, and mapping of cervical cancer and precancer. A multispectral imaging system was developed, which is capable of performing time-resolved imaging spectroscopy. The system was used in order to assess quantitatively the alterations in the light scattering properties of the cervix, induced selectively and reversibly in cervical neoplasias, after the application of acetic acid solution. Spectral imaging and analysis of cervix show that the maximum contrast between acetic acid responsive and nonresponsive areas is obtained at 525 +/- 15 nm, which is further enhanced by cutting off the regular component of tissue reflection, with the aid of two linear cross polarizers. Successive snapshot imaging at this spectral band enables the quantitative assessment of the temporal alterations in the intensity of the backscattered light, in any spatial location of the examined area. Initial clinical trials show that optical contrast enhancement results in a notable improvement of the sensitivity in detecting incipient lesions. It was also shown that the measured temporal characteristics of the phenomenon contain specific information, which enables the differentiation between neoplastic and nonneoplastic lesions, as well as between neoplasias of different grade. The demonstrated improved sensitivity and specificity highlight the potential of the method in both clinical research and noninvasive diagnosis.

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Year:  2001        PMID: 11235596     DOI: 10.1109/10.900259

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  11 in total

1.  Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy.

Authors:  Vivide Tuan-Chyan Chang; Peter S Cartwright; Sarah M Bean; Greg M Palmer; Rex C Bentley; Nirmala Ramanujam
Journal:  Neoplasia       Date:  2009-04       Impact factor: 5.715

2.  Model-based analysis of reflectance and fluorescence spectra for in vivo detection of cervical dysplasia and cancer.

Authors:  Crystal Redden Weber; Richard A Schwarz; E Neely Atkinson; Dennis D Cox; Calum Macaulay; Michele Follen; Rebecca Richards-Kortum
Journal:  J Biomed Opt       Date:  2008 Nov-Dec       Impact factor: 3.170

3.  Wide-field spectral imaging of human ovary autofluorescence and oncologic diagnosis via previously collected probe data.

Authors:  Timothy E Renkoski; Kenneth D Hatch; Urs Utzinger
Journal:  J Biomed Opt       Date:  2012-03       Impact factor: 3.170

Review 4.  Optical imaging for cervical cancer detection: solutions for a continuing global problem.

Authors:  Nadhi Thekkek; Rebecca Richards-Kortum
Journal:  Nat Rev Cancer       Date:  2008-09       Impact factor: 60.716

5.  Modular video endoscopy for in vivo cross-polarized and vital-dye fluorescence imaging of Barrett's-associated neoplasia.

Authors:  Nadhi Thekkek; Mark C Pierce; Michelle H Lee; Alexandros D Polydorides; Raja M Flores; Sharmila Anandasabapathy; Rebecca R Richards-Kortum
Journal:  J Biomed Opt       Date:  2013-02       Impact factor: 3.170

6.  An image registration method for colposcopic images.

Authors:  Efrén Mezura-Montes; Héctor-Gabriel Acosta-Mesa; Darío-del-Sinaí Ramírez-Garcés; Nicandro Cruz-Ramírez; Rodolfo Hernández-Jiménez
Journal:  Comput Math Methods Med       Date:  2013-09-24       Impact factor: 2.238

7.  Intelligent screening systems for cervical cancer.

Authors:  Yessi Jusman; Siew Cheok Ng; Noor Azuan Abu Osman
Journal:  ScientificWorldJournal       Date:  2014-05-11

8.  Optimization of Classification Strategies of Acetowhite Temporal Patterns towards Improving Diagnostic Performance of Colposcopy.

Authors:  Karina Gutiérrez-Fragoso; Héctor Gabriel Acosta-Mesa; Nicandro Cruz-Ramírez; Rodolfo Hernández-Jiménez
Journal:  Comput Math Methods Med       Date:  2017-07-04       Impact factor: 2.238

Review 9.  Optical techniques for cervical neoplasia detection.

Authors:  Tatiana Novikova
Journal:  Beilstein J Nanotechnol       Date:  2017-09-06       Impact factor: 3.649

10.  Application of deep learning to the classification of images from colposcopy.

Authors:  Masakazu Sato; Koji Horie; Aki Hara; Yuichiro Miyamoto; Kazuko Kurihara; Kensuke Tomio; Harushige Yokota
Journal:  Oncol Lett       Date:  2018-01-10       Impact factor: 2.967

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