Literature DB >> 17477736

Real-time reflectance confocal microscopy: comparison of two-dimensional images and three-dimensional image stacks for detection of cervical precancer.

Tom Collier1, Martial Guillaud, Michele Follen, Anais Malpica, Rebecca Richards-Kortum.   

Abstract

Confocal microscopy can provide real-time, 2-D and 3-D images of the cellular morphology and tissue architecture features that pathologists use to detect precancerous lesions without the need for tissue removal, sectioning, and staining. The utility of 3-D confocal image stacks of epithelial tissue for detecting dysplasia has not yet been explored. We aim to extract morphometry and tissue architecture information from 2-D confocal reflectance images and 3-D image stacks from fresh, unstained cervical biopsies and compare their potential for detecting dysplasia. Nine biopsies are obtained from eight patients; confocal images are acquired pre- and postacetic acid at multiple epithelial depths in 1.5 mum-intervals. Postacetic acid images are processed to segment cell nuclei; after segmentation, 2-D images taken at 50 mum below the tissue surface, and the entire 3-D image stacks are processed to extract morphological and architectural features. Data are analyzed to determine which features gave the best separation between normal and high-grade cervical precancer. Most significant differences are obtained from parameters extracted from the 3-D image stacks. However, in all cases where the 2-D features were multiplicatively scaled by the depth of acquisition divided by the epithelial thickness or scaled by the scattering coefficient, the significance level is equal to or greater than the comparable feature extracted from the 3-D image stacks. A linear discriminant function previously developed to separate 19 samples of normal tissue and high-grade cervical precancer based on the nuclear-to-cytoplasm (N/C) ratio and epithelial scattering coefficient is prospectively applied to the nine biopsies examined to determine the accuracy with which it could separate normal tissue from cervical intra epithelial neoplasia (CIN) 23. For the entire data set of 28 biopsies, a sensitivity and specificity of 100% is produced using this discriminant function; the scattering coefficient provides more discriminative capacity than the N/C ratio. The success of the scaled 2-D image features has important implications for using confocal microscopy to detect precancer in the clinic. Acquisition of the epithelial thickness or scattering coefficient requires less time than 3-D image sets and little additional effort is required to gain the added information compared to 2-D images alone.

Entities:  

Mesh:

Year:  2007        PMID: 17477736     DOI: 10.1117/1.2717899

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  17 in total

1.  Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett's esophagus.

Authors:  Timothy J Muldoon; Nadhi Thekkek; Darren Roblyer; Dipen Maru; Noam Harpaz; Jonathan Potack; Sharmila Anandasabapathy; Rebecca Richards-Kortum
Journal:  J Biomed Opt       Date:  2010 Mar-Apr       Impact factor: 3.170

Review 2.  Optical contrast agents and imaging systems for detection and diagnosis of cancer.

Authors:  Mark C Pierce; David J Javier; Rebecca Richards-Kortum
Journal:  Int J Cancer       Date:  2008-11-01       Impact factor: 7.396

3.  Reflection-contrast limit of fiber-optic image guides.

Authors:  Pierre M Lane; Calum E MacAulay
Journal:  J Biomed Opt       Date:  2009 Nov-Dec       Impact factor: 3.170

4.  Optical technologies and molecular imaging for cervical neoplasia: a program project update.

Authors:  Timon P H Buys; Scott B Cantor; Martial Guillaud; Karen Adler-Storthz; Dennis D Cox; Clement Okolo; Oyedunni Arulogon; Oladimeji Oladepo; Karen Basen-Engquist; Eileen Shinn; José-Miguel Yamal; J Robert Beck; Michael E Scheurer; Dirk van Niekerk; Anais Malpica; Jasenka Matisic; Gregg Staerkel; Edward Neely Atkinson; Luc Bidaut; Pierre Lane; J Lou Benedet; Dianne Miller; Tom Ehlen; Roderick Price; Isaac F Adewole; Calum MacAulay; Michele Follen
Journal:  Gend Med       Date:  2011-09-22

Review 5.  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

6.  A fiber-optic fluorescence microscope using a consumer-grade digital camera for in vivo cellular imaging.

Authors:  Dongsuk Shin; Mark C Pierce; Ann M Gillenwater; Michelle D Williams; Rebecca R Richards-Kortum
Journal:  PLoS One       Date:  2010-06-23       Impact factor: 3.240

Review 7.  Optical imaging techniques for point-of-care diagnostics.

Authors:  Hongying Zhu; Serhan O Isikman; Onur Mudanyali; Alon Greenbaum; Aydogan Ozcan
Journal:  Lab Chip       Date:  2012-10-09       Impact factor: 6.799

8.  Comprehensive imaging of gastroesophageal biopsy samples by spectrally encoded confocal microscopy.

Authors:  DongKyun Kang; Melissa J Suter; Caroline Boudoux; Hongki Yoo; Patrick S Yachimski; William P Puricelli; Norman S Nishioka; Mari Mino-Kenudson; Gregory Y Lauwers; Brett E Bouma; Guillermo J Tearney
Journal:  Gastrointest Endosc       Date:  2009-11-17       Impact factor: 9.427

9.  Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study.

Authors:  Vasumathi Gopala Prabitha; Sambasivan Suchetha; Jayaraj Lalitha Jayanthi; Kamalasanan Vijayakumary Baiju; Prabhakaran Rema; Koyippurath Anuraj; Anita Mathews; Paul Sebastian; Narayanan Subhash
Journal:  Lasers Med Sci       Date:  2015-10-31       Impact factor: 3.161

10.  Precancerous esophageal epithelia are associated with significantly increased scattering coefficients.

Authors:  Jing-Wei Su; Yang-Hsien Lin; Chun-Ping Chiang; Jang-Ming Lee; Chao-Mao Hsieh; Min-Shu Hsieh; Pei-Wen Yang; Chen-Ping Wang; Ping-Huei Tseng; Yi-Chia Lee; Kung-Bin Sung
Journal:  Biomed Opt Express       Date:  2015-09-03       Impact factor: 3.732

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.