Computer-based quantitative computed tomography image analysis in idiopathic pulmonary fibrosis: A mini review

Area of Science:

• Radiology
• Pulmonary Medicine
• Medical Imaging Analysis

Background:

• Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease.
• Chest computed tomography (CT) is crucial for IPF diagnosis and management.
• Current image analysis methods for IPF on CT scans include various quantitative techniques.

Purpose of the Study:

• To review current computer-based CT image analysis methods for IPF.
• To discuss the limitations of existing methods.
• To explore future directions in IPF imaging analysis.

Main Methods:

• Review of current literature on computer-based CT image analysis in IPF.
• Discussion of techniques such as mean CT value, histogram analysis, density mask, and texture classification.
• Comparison of different methods' utility in assessing pulmonary function, disease progression, and mortality.

Main Results:

• Various computer-based CT analysis methods provide good assessment of IPF.
• Texture classification methods demonstrate superiority over visual CT scoring for correlating with pulmonary function and predicting mortality.
• Each method has unique merits for clinical application.

Conclusions:

• Computer-based CT image analysis is valuable for IPF management.
• Texture classification offers significant advantages in IPF assessment.
• Further research is needed to address limitations and advance IPF imaging analysis.