Related Experiment Video For adenocarcinoma
Updated: Jan 22, 2026

Development of Compendium for Esophageal Squamous Cell Carcinoma
Published on: April 12, 2024
Cytomorphological criteria for separation of pulmonary adenocarcinomas from squamous cell carcinomas: A statistical
Lester J Layfield1, Magda Esebua1, Lei Sun1
1Department of Pathology & Anatomical Sciences, University of Missouri, Columbia, MO, USA.
Background:
Current therapy requires separation of non-small cell carcinomas into adenocarcinomas (AC) and squamous cell carcinomas (SCC). A meta-analysis has shown a pooled diagnostic sensitivity of 63% and specificity of 95% for the diagnosis of AC. While a number of cytomorphological features have been proposed for separation of AC from SCC, we are unaware of a statistically based analysis of cytomorphological features useful for separation of these two carcinomas. We performed logistic regression analysis of cytological features useful in classifying SCC and AC.
Design:
Sixty-one Papanicolaou-stained fine needle aspiration specimens (29 AC/32 SCC) were reviewed by two board-certified cytopathologists for nine features (eccentric nucleoli, vesicular chromatin, prominent nucleoli, vacuolated cytoplasm, 3-dimensional cell balls, dark non-transparent chromatin, central nucleoli, single malignant cells and spindle-shaped cells). All cytological specimens had surgical biopsy results. Inter-rater agreement was assessed by Cohen's κ. Association between features and AC was determined using hierarchical logistic regression model where feature scores were nested within reviewers. A model to classify cases as SCC or AC was developed and verified by k-fold verification (k = 5). Classification performance was assessed using the area under the receiver operating characteristic curve.
Results:
Observed rater agreement for scored features ranged from 49% to 82%. Kappa scores were clustered in three groups. Raters demonstrated good agreement for prominent nucleoli, vesicular chromatin and eccentric nuclei. Fair agreement was seen for 3-dimensional cell balls, dark non-transparent chromatin, and presence of spindle-shaped cells. Association of features with adenocarcinoma showed four statistically significant associations (P < 0.001) with adenocarcinoma. These features were prominent nucleoli, vesicular chromatin, eccentric nuclei and three-dimensional cell balls. Spindle-shaped cells and dark non-transparent chromatin were negatively associated with adenocarcinoma.
Conclusions:
Logistic regression analysis demonstrated six features helpful in separation of AC from SCC. Prominent nucleoli, vesicular chromatin, cell balls and eccentric nucleoli were positively associated with AC and demonstrated a P value of 0.001 or less. The presence of dark, non-transparent chromatin and spindle-shaped cells favoured the diagnosis of SCC.
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