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Journal of Cytology & Histology

ISSN: 2157-7099

Open Access

The Cytomorphological Characteristics of Non-small Cell Lung Cancer are Associated with Its Radiological Features

Abstract

Ryota Tanaka*, Norihiko Sakamoto, Hitomi Suzuki, Keisei Tachibana, Hidefumi Takei, Koji Kishimoto, Masachika Fujiwara, Hiroshi Kamma, Junji Shibahara and Haruhiko Kondo

Background: Distinguishing the histological subtype of lung cancer is extremely important because chemotherapy agents may have different chemotherapeutic effects in different histological subtypes. This study retrospectively evaluated the characteristic differences in the cytomorphological and radiological features of nonsmall cell lung cancer.
Methods: This study population included 50 lung cancer patients who were diagnosed based on bronchoscopic biopsy findings and underwent surgery from April 2011 to May 2016. Cyotological specimens (Papanicolaou’s staining) were separately analyzed by two experienced cytotechnicians. The associations between the clinicopathological data, as well as the preoperative radiological features on computed tomography (CT) and positron emission tomography (PET) and cytomorphological analyses were analyzed.
Results: Forty-five specimens were analyzed (adenocarcinoma [ADC] [n=38], squamous cell carcinomas [SQCC] [n=7]). The ADCs were cytomorphologically sub-classified as follows: acinar (n=25), solid (n=10), lepidic (n=2) and papillary (n=1). Among specimens with a solid pattern of ADC, there was a significantly greater percentage of samples with a necrotic background (50%), predominant 3D clusters (100%) and conspicuous nucleoli (80%) compared to specimens with a nonsolid pattern of ADC. The CT images of patients with solid ADC (90%) and SQCC (100%) tended to show solid nodules on CT. On PET, the maximum standardized uptake values at 120 minutes in solid ADC and SQCC were significantly higher in comparison to nonsolid ADC (12.8 ± 6.1 and 17.2 ± 7.3 versus 8.9 ± 4.4, respectively).
Conclusions: The differentiation of the cytomorphological characteristics might predict the values of radiological features, and thereby provide information that can be used when determining the treatment strategies.

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