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Quantification of progressive pulmonary fibrosis by visual scoring of HRCT images: recommendations from Italian chest radiology experts

  • E Baratella*
  • , A Borghesi
  • , Lucio Calandriello
  • , G Cortese
  • , Casa G Della
  • , C Giraudo
  • , E Grassedonio
  • , Anna Rita Larici
  • , S Palmucci
  • , C Romei
  • , Plastina UR
  • , N Sverzellati
  • *Corresponding author

Research output: Contribution to journal › Article

Abstract

Interstitial lung diseases (ILD) constitute a large and heterogeneous group of disorders affecting the lung parenchyma. While idiopathic pulmonary fibrosis (IPF), the most common type of ILD, is the prototype of progressive fibrosis, other forms, collectively termed “progressive pulmonary fibrosis” (PPF), can show a similar clinical course. Detecting chronic fibrosing ILD progression necessitates radiological evidence using high-resolution computed tomography (HRCT), which determines eligibility for treatment. However, assessing the extent of fibrosis and progression on HRCT images is difficult and lacks specific guidelines. Therefore, expert oversight and high-quality visual assessment/scoring of complex disease patterns is essential to monitor disease changes. Twelve Italian chest radiologists deliberated on the current state of quantifying lung fibrosis using existing literature to develop practice-oriented consensus statements to assist radiologists in visually assessing/scoring lung fibrosis on HRCT images in patients with PPF. The resulting statements cover three key areas: (1) technical requirements necessary for accurate HRCT image assessment; (2) an easy-to-use quantification protocol for routine clinical practice; and (3) a multiple specialist approach by combining radiological, clinical, and histopathological findings for the correct diagnosis, prompt detection of PPF, and timely start of antifibrotic treatment. In future, automated quantitative HRCT evaluation will lead to new clinical assessment tools.
Original languageEnglish
Pages (from-to)965-977
Number of pages13
JournalRadiologia Medica
Volume130
Issue number6
DOIs
Publication statusPublished - 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

Keywords

  • Consensus statements
  • Fibrosis extent
  • Fibrosis progression
  • High-resolution computerized tomography
  • Progressive pulmonary fibrosis

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