Evaluation of interstitial lung disease: An algorithmic review using ILD-RADS

Area of Science:

• Pulmonology
• Radiology
• Medical Diagnostics

Background:

• Interstitial lung diseases (ILDs) present diagnostic difficulties due to complex classifications and similar imaging results.
• Accurate ILD diagnosis is crucial for effective patient management and treatment.

Purpose of the Study:

• To present an algorithmic approach for assessing ILDs.
• To aid clinicians in narrowing differential diagnoses or achieving specific ILD diagnoses.
• To utilize the Interstitial Lung Disease Reporting And Data System (ILD-RADS) as a diagnostic framework.

Main Methods:

• Review of current literature and diagnostic guidelines for ILDs.
• Development of an assessment algorithm based on key imaging features.
• Application of the ILD-RADS framework to guide the diagnostic process.

Main Results:

• The proposed algorithm effectively categorizes ILDs based on characteristic imaging findings.
• Integration of ILD-RADS provides a standardized approach to ILD assessment.
• The approach facilitates a more systematic and accurate diagnostic pathway for ILDs.

Conclusions:

• An algorithmic approach, guided by ILD-RADS and key imaging features, can simplify ILD diagnosis.
• This strategy helps overcome the diagnostic challenges posed by the heterogeneity of ILDs.
• Improved diagnostic accuracy can lead to more timely and appropriate patient care.