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ID 32443
JaLCDOI
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Author
Tanaka, Toshio
Yamamoto, Michiko
Tamura, Tetsuo
Moritani, Yoshiaki
Miyai, Masahiro
Hiraki, Shunkichi
Ohnoshi, Taisuke
Kimura, Ikuro
Abstract

In order to increase the accuracy of diagnosis in lung cancer, analysis concerning cytological and histological correlation was attempted. The present study consists of 106 patients, who were seen during the past approximately five years and underwent radical surgery to remove tumors completely; mere biopsy specimens were excluded. These patients were 63 years old on the average, 78 males and 28 females, 29 cases of the hilar type (H) and 77 of the peripheral type (P), and 27 and 76 cases of the clinical stage I in H and P, respectively. Histologically, there were 53 adenocarcinomas (Ad), 38 squamous cell carcinomas (Sq), 4 adenosquamous cell carcinomas (Ad + Sq), 5 large cell carcinomas (LCC), and 6 small cell carcinomas (SCC); among them, 3 Ad and 21 Sq in H, and 50 Ad and 17 Sq in P. The overall positive percentages were 65.5 (H) and 26.0 (P) by combination of spontaneous, airsol-induced and Saccomanno's methods, against 96.6 (H) and 72.8 (P) with inclusion of brushing method. 94.8% of Sq in H and 66.7% of Ad and 70.6% of Sq in P were positive by the brushing. A comparative study of these four methods, performed at least once on the same patient, also confirmed the superiority of brushing. Cyto- and histological agreement was 21/21 (100%) for Sq in H, whereas 30/34 (88.2%) for Ad and 13/15 (86.7%) for Sq in P. In conclusion, cyto- and histological findings in H and P corresponded well, and as far as cytology of peripheral type is concerned, a combined method, especially with brushing, is strongly recommended.

Keywords
primary lung cancer
cytology
histology
Amo Type
Article
Publication Title
Acta Medica Okayama
Published Date
1983-02
Volume
volume37
Issue
issue1
Publisher
Okayama University Medical School
Start Page
11
End Page
19
ISSN
0386-300X
NCID
AA00508441
Content Type
Journal Article
language
English
File Version
publisher
Refereed
True
PubMed ID
Web of Science KeyUT