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Quantitative Nuclear Characteristics of Lung Cancer Cells Using Image Analysis
김문경, 김정열, 정운용, 이지혜, 이응석, 하승연, 김영식, 김한겸, 김인선,
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김문경 ( Kim Moon-Kyoung )
고려대학교 의과대학 병리학교실
김정열 ( Kim Chung-Yeul )
고려대학교 의과대학 병리학교실
정운용 ( Jeong Woon-Yong )
고려대학교 의과대학 병리학교실
이지혜 ( Lee Ji-Hye )
고려대학교 의과대학 병리학교실
이응석 ( Lee Eung-Seok )
고려대학교 의과대학 병리학교실
하승연 ( Ha Seung-Yeon )
가천의대 길병원 해부병리학과
김영식 ( Kim Young-Sik )
고려대학교 의과대학 병리학교실
김한겸 ( Kim Han-Kyeom )
고려대학교 의과대학 병리학교실
김인선 ( Kim In-Sun )
고려대학교 의과대학 병리학교실
KMID : 0357920030370020115
Abstract
Background: The usefulness of quantitative nuclear image analysis in the classification of lung carcinoma is widely investigated and published. In this study, we tried to measure the nuclear characteristics of primary lung carcinomas by image analysis and to find the possibility of differential diagnoses.
Methods: Seventeen cases of adenocarcinomas (not including bronchioloalveolar carcinoma), seven of bronchioloalveolar carcinomas, eight of large cell neuroendocrine carcinomas, five of small cell carcinamas, and 26 of squamous cell carcinomas were analysed. Three different images of each case were captured by digital camera, and we analyzed the nuclear area, perimeter, circularity, and density using the Optimas 6.5 Image Analyser software package. Statistical analyses were done using the statistical program STATISTICA kernel release 5.5.
Results: The mean nuclear area was 0.52+/-0.25 micro m2 in the adenocarcinomas, 0.50+/-1.82 micro m2 in the squamous cell carcinomas, 0.45+/-0.20 micro m2 in the large cell neuroendocrine carcinomas, 0.42+/-0.16 micro m2 in the bronchioloalveolar carcinomas, and 0.31+/-0.12 micro m2 in the small cell carcinamas. The nuclear area was significantly different between the small cell carcinomas and the non-small cell carcinomas (p < 0.01) and between the adenocarcinomas and the bronchioloalveolar carcinomas (p = 0.02). The mean nuclear perimeter was 3.36+/-0.92 micro m2 in the adenocarcinomas, 3.24+/-0.67 micro m2 the squamous cell carcinomas, 3.16+/-0.82 micro m2 in the large cell neuroendocrine carcinomas, 3.05+/- 0.80 micro m2 in the bronchioloalveolar carcinomas, and 2.54+/-0.62 micro m2 in the small cell carcinamas. The nuclear perimeter was significantly different between the small cell carcinomas and the non-small cell carcinomas (p < 0.04). The nuclear circularity showed no statistical difference. Nuclear density was the highest in the squamous cell carcinomas, and the lowest in the small cell carcinomas. The large cell neuroendocrine carcinomas showed the lowest standard deviation in nuclear density.
Conclusion: The analysis of nuclear characteristics using an image analyser can be used as an objective method in the classification of lung carcinomas.
키워드
Lung carcinoma;Quantitative nuclear image features;Image analysis
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