DocumentCode :
270518
Title :
A Novel Automated Microscopy Platform for Multiresolution Multispectral Early Detection of Lung Cancer Cells in Bronchoalveolar Lavage Samples
Author :
Pengo, Thomas ; Muñoz-Barrutía, Arrate ; Ortiz-de-Solórzano, Carlos
Author_Institution :
Center for Appl. Med. Res., Univ. of Navarra, Pamplona, Spain
Volume :
8
Issue :
3
fYear :
2014
fDate :
Sept. 2014
Firstpage :
985
Lastpage :
994
Abstract :
Lung cancer is the deadliest form of cancer mainly because of the absence of reliable early diagnostic protocols. Therefore, there is increasing interest in the development of novel diagnostic noninvasive technologies that may improve the early detection of the disease. Bronchoscope-guided bronchoalveolar lavage (BAL) is a minimally invasive diagnostic technique that is based on the extraction and analysis of cellular material from the bronchial epithelium of patients that present suspicious lung masses on low-dose screening X-ray-computed tomography images. Together with a novel staining technique that combines immunophenotyping of a lung cancer biomarker with fluorescent in situ hybridization of genetically abnormal DNA loci, BAL promises a powerful early diagnostic tool for lung carcinomas. The sensitivity of this method, however, is highly dependent on the pathologist´s ability to reliably and repeatedly examine thousands of cells under the microscope. This is an extremely labor-intensive and error-prone task. We have developed a multiscale multidimensional integrated microscopy computer-aided detection platform that autonomously scans and analyzes BAL samples. In this paper, we describe its software architecture and validate the specific image analysis protocols that are developed for this particular application.
Keywords :
DNA; biochemistry; biomedical optical imaging; cancer; cellular biophysics; computerised tomography; data analysis; diagnostic radiography; endoscopes; feature extraction; fluorescence; genetics; image resolution; lung; medical image processing; molecular biophysics; optical microscopy; protocols; BAL sample analysis; automated microscopy platform; autonomous BAL sample scanning; bronchoalveolar lavage samples; bronchoscope-guided BAL; cellular material analysis; cellular material extraction; computer-aided detection platform; diagnostic noninvasive technology development; early diagnostic protocols; early diagnostic tool; early lung cancer cell detection; error-prone cell examination; fluorescent in situ hybridization; genetically abnormal DNA loci hybridization; image analysis protocol development; immunophenotyping; labor-intensive cell examination; low-dose screening X-ray-computed tomography images; lung cancer biomarker; lung carcinomas; minimally invasive diagnostic technique; multiresolution multispectral detection; multiscale multidimensional integrated microscopy platform; patient bronchial epithelium; software architecture; staining technique; suspicious lung masses; Cancer; Image analysis; Lungs; MATLAB; Microscopy; Probes; Automated microscopy; computer-aided detection (CAD); fluorescence microscopy; fluorescent in situ hybridization (FISH); immunofluorescence; lung cancer; minimal samples;
fLanguage :
English
Journal_Title :
Systems Journal, IEEE
Publisher :
ieee
ISSN :
1932-8184
Type :
jour
DOI :
10.1109/JSYST.2013.2289152
Filename :
6671418
Link To Document :
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