분화도가 높은 간세포암종의 세침흡인 세포학적 소견 - 비종양성 병변과의 감별

The fine needle aspiration biopsy(FNAB) has become a popular method to diagnose mass lesions of the liver. Although many reports have listed FNAB criteria to be used to diagnose hepatocellular carcinoma(HCC), a diagnostic dilemma still exists at the extreme ends of the spectrum, particularly for wel...

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Veröffentlicht in:Taehan Sepo Pyŏngri Hakhoe chi 1997, Vol.8 (1), p.1-10
Hauptverfasser: 강신광, 이승숙, 조경자, 하화정, Khang, Shin-Kwang, Lee, Seung-Sook, Cho, Kyung-Ja, Ha, Hwa-Jeong
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Sprache:kor
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Zusammenfassung:The fine needle aspiration biopsy(FNAB) has become a popular method to diagnose mass lesions of the liver. Although many reports have listed FNAB criteria to be used to diagnose hepatocellular carcinoma(HCC), a diagnostic dilemma still exists at the extreme ends of the spectrum, particularly for well differentiated HCC. The authors reviewed a series of FNAB specimens of the liver to distinguish well differentiated HCC from nonneoplastic liver. Fifteen cytologic features were examined in this study: high cellularity, large sheet formation, trabecular pattern, acinar pattern, dispersed pattern, irregular arrangement, increased nuclear/cytoplasmic ratio, naked nuclei, irregular chromatin, irregular nuclear contour, multinucleation, uniform macronucleoli, multiple nuclei, uniform small cytoplasm and monotony of atypia. These features were examined in a series of 76 FNAB specimens. Fifty two specimens were from patients with HCC and 24 specimens were from patients with nonneoplastic lesion or tumors other than HCC containg adequate amount of nonneoplastic hepatocytes in smear. All specimens were coded as to the presence or absence of the above cytologic features. With the use of step-wise logistic regression analysis, three features were identified as the key cytologic features predictive of HCC: irregular chromatin, monotony of atypia and absence of large sheet formation. When these criteria were used, the sensitivity diagnosing HCC by FNAB was 94.2%, specificity 100%, positive predictive value 100% and negative predictive value was 88.9%.
ISSN:1017-0391