Unveiling the radiological odyssey: Navigating the interstitial with artificial intelligence

Area of Science:

• Pulmonology
• Radiology
• Medical Imaging

Background:

• Idiopathic pulmonary fibrosis (IPF) and chronic hypersensitivity pneumonitis (cHP) are interstitial lung diseases with overlapping features.
• Differentiating between IPF and cHP can be challenging due to similar clinical and radiological presentations.

Purpose of the Study:

• To examine the radiological and clinical evolution of a patient with mixed IPF and cHP.
• To assess the utility of conventional CT imaging and artificial intelligence (AI) in managing this complex case.
• To emphasize the importance of a multidisciplinary approach in diagnosing and managing interstitial lung diseases.

Main Methods:

• Longitudinal follow-up of a single patient over 3 years.
• Conventional computed tomography (CT) imaging for radiological assessment.
• Application of an artificial intelligence (AI) tool for enhanced analysis.
• Regular clinical assessments and correlation with imaging findings.

Main Results:

• Radiological progression towards pulmonary fibrosis was observed and correlated with clinical symptoms.
• The study highlights the diagnostic challenges in differentiating IPF and cHP.
• AI and conventional CT imaging provided a comprehensive framework for patient management.

Conclusions:

• A multidisciplinary approach is crucial for managing mixed IPF and cHP.
• Early diagnosis and regular follow-up are essential for optimal patient outcomes.
• Advanced technologies, including AI, enhance the understanding and management of complex interstitial lung diseases.