Quantitative Imaging for Interstitial Lung Disease

Area of Science:

• Radiology and Medical Imaging
• Artificial Intelligence in Medicine
• Pulmonology

Background:

• Quantitative imaging provides objective and reproducible measurements of lung abnormalities in interstitial lung disease (ILD).
• Accurate ILD classification and detection of subtle changes enable personalized treatment strategies and improved patient outcomes.
• Computed tomography (CT) is the primary imaging modality for ILD, leading to the development of quantitative CT (qCT) tools.

Purpose of the Study:

• To review current applications of quantitative CT in fibrotic ILDs.
• To highlight emerging quantitative MRI techniques for ILD assessment.
• To emphasize the growing importance of quantitative imaging in clinical radiology workflows.

Main Methods:

• Review of current literature on quantitative CT applications in fibrotic ILDs.
• Discussion of advancements in quantitative MRI techniques for ILD.
• Exploration of artificial intelligence's role in developing quantitative imaging tools.

Main Results:

• Quantitative CT is valuable for evaluating fibrotic ILDs like idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, and connective tissue disease-related ILD.
• Emerging quantitative MRI techniques show promise for enhanced ILD assessment.
• AI-driven tools are advancing the capabilities of quantitative imaging in ILD.

Conclusions:

• Quantitative imaging, particularly qCT, is crucial for ILD diagnosis, classification, and prognostication.
• Quantitative MRI techniques are emerging as valuable complements to CT for ILD evaluation.
• Radiologists need familiarity with quantitative imaging tools as they integrate into routine clinical practice.