Diffuse lung disease of infancy: a pattern-based, algorithmic approach to histological diagnosis

Area of Science:

• Pediatric Pathology
• Pulmonary Medicine
• Histopathology

Background:

• Diffuse lung disease (DLD) in infancy presents unique challenges due to its distinct etiology and prognosis compared to older age groups.
• Accurate diagnosis is critical, as many DLD cases in infants carry a poor prognosis and significantly impact management decisions.
• Referrals to specialist centers suggest that initial diagnoses are often made by pathologists with less experience in infant DLD.

Purpose of the Study:

• To present an algorithmic, histological, pattern-based diagnostic approach for diffuse lung disease of infancy.
• To assist pathologists in generating accurate interim reports and excluding inappropriate diagnoses.
• To facilitate timely and effective multidisciplinary decision-making for infant DLD cases.

Main Methods:

• Development of an algorithmic approach to DLD diagnosis based on histological patterns.
• Integration of clinical, radiological, and ancillary diagnostic studies.
• Emphasis on multidisciplinary team (MDT) input for case evaluation.

Main Results:

• The proposed histological pattern-based approach can lead to accurate and useful interim diagnostic reports for DLD of infancy.
• This method aids in the timely exclusion of incorrect diagnoses.
• It supports informed decisions regarding the need for referral to specialist centers.

Conclusions:

• A histological pattern-based diagnostic strategy, combined with multidisciplinary expertise, offers a valuable framework for managing DLD of infancy.
• This approach enhances diagnostic accuracy and efficiency, particularly for pathologists managing initial cases.
• It empowers MDTs to make better-informed decisions regarding patient care and further investigations.