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A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

Transient part-solid nodules detected at screening thin-section CT for lung cancer: comparison with persistent

Sang Min Lee¹, Chang Min Park, Jin Mo Goo

¹Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, 101 Daehangno, Jongno-gu, Seoul 110-744, Korea.

|February 23, 2010

Summary

A significant number of part-solid nodules (PSNs) found during lung cancer screening CT scans were transient. Features like young age, blood eosinophilia, and specific lesion characteristics can predict these transient PSNs accurately.

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Area of Science:

Radiology
Pulmonology
Oncology

Background:

Part-solid nodules (PSNs) are frequently detected during lung cancer screening with thin-section computed tomography (CT).
Differentiating transient PSNs from persistent ones is crucial for appropriate patient management and avoiding unnecessary interventions.

Purpose of the Study:

To identify clinical and CT features that distinguish transient PSNs from persistent PSNs.
To determine predictive factors for transient PSNs detected during lung cancer screening.

Main Methods:

Retrospective analysis of 126 PSNs in 93 individuals from a lung cancer screening CT cohort (January 2006 - August 2008).
Comparison of clinical and CT characteristics between transient and persistent PSNs.
Logistic regression and C statistic analysis to identify predictive factors and evaluate model performance.

Main Results:

69.8% of detected PSNs were transient.
Significant differences between transient and persistent PSNs included patient age, sex, lung cancer risk, eosinophilia, detection mode, lesion size, multiplicity, solid portion size, and border characteristics.
Multivariate analysis identified young age, follow-up detection, eosinophilia, lesion multiplicity, large solid portion, and ill-defined border as independent predictors of transient PSNs.

Conclusions:

A substantial proportion of PSNs detected in screening CT are transient.
A combination of clinical factors (young age, eosinophilia) and CT features (lesion multiplicity, large solid portion, ill-defined border) accurately predicts transient PSNs.