What question did this study set out to answer?

To explore how cell aggregation and nuclear overlap can differentiate between benign and malignant pleural effusion specimens.

March 26, 2026Open Access

A Two‐Dimensional Plot of Cell Aggregates and Their Largest Nuclei Distinguishes Benign From Malignant Pleural Effusion Cytology Specimens

Key Points

To explore how cell aggregation and nuclear overlap can differentiate between benign and malignant pleural effusion specimens.
Analyzed pleural cytology specimens from lung cancer patients.
Employed CAIA approaches for interpretability.
Utilized AI-based image analysis for evaluation.
Observations showed significant differences in cell aggregation levels between benign and malignant samples.
Nuclear overlap was a key indicator in classification.
Findings suggest that traditional methods complement AI advancements.

Abstract

In pleural cytology specimens from patients with lung cancer, the degree of cell aggregation and nuclear overlap is an important factor for distinguishing benign from malignant lesions. Moreover, although AI-based image analysis has advanced rapidly in recent years, this study emphasizes the continued value of CAIA approaches that employ algorithms readily interpretable by humans.

A Two‐Dimensional Plot of Cell Aggregates and Their Largest Nuclei Distinguishes Benign From Malignant Pleural Effusion Cytology Specimens

Key Points

Abstract

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