Quantitative computed tomography texture analyses for anterior mediastinal masses: Differentiation between solid...

Area of Science:

• Radiology
• Medical Imaging
• Oncology

Background:

• Anterior mediastinal masses present a diagnostic challenge.
• Distinguishing solid masses from cysts is crucial for appropriate management.
• Computed tomography (CT) is a primary imaging modality for mediastinal lesions.

Purpose of the Study:

• To evaluate the efficacy of quantitative CT texture analysis in differentiating solid anterior mediastinal masses from cystic lesions.
• To compare the diagnostic performance of texture analysis in unenhanced CT (UECT) and contrast-enhanced CT (CECT).

Main Methods:

• Retrospective analysis of 76 UECT and 84 CECT scans of anterior mediastinal masses.
• Application of CT histogram analyses with and without Laplacian of Gaussian filters.
• Logistic regression and receiver operating characteristic analyses to determine diagnostic performance (Area Under the Curve - AUC).

Main Results:

• A combination of mean attenuation and coarse texture features in UECT achieved an AUC of 0.869.
• A combination of mean attenuation and fine texture features in CECT achieved an AUC of 0.997.
• Texture analysis significantly improved diagnostic performance compared to mean attenuation alone in UECT (AUC 0.780 vs 0.869) and CECT (AUC 0.983 vs 0.997).

Conclusions:

• Quantitative CT texture analysis effectively differentiates solid anterior mediastinal masses from cysts.
• The diagnostic performance is moderate in UECT and high in CECT.
• Texture analysis offers a valuable tool for characterizing anterior mediastinal masses.