Quantification of MRI T2 Interstitial Lung Disease Signal-Intensity Volume in Idiopathic Pulmonary Fibrosis: A Pilot

Ilyes Benlala1,2, Agnes Albat2, Elodie Blanchard2

  • 1Centre de Recherche Cardio-Thoracique de Bordeaux, Univ. Bordeaux, INSERM U1045, CIC 1401, Bordeaux, France.

Abstract

Insights

This study introduces a new semiautomated method to quantify T2 signal intensity in idiopathic pulmonary fibrosis (IPF) lungs using MRI. The T2-ISIV method shows high reproducibility and correlates with disease severity, offering a promising tool for IPF assessment.

Area of Science:

  • Medical Imaging
  • Pulmonary Medicine
  • Radiology

Background:

  • Idiopathic pulmonary fibrosis (IPF) diagnosis relies heavily on imaging.
  • T2-weighted MRI shows potential for monitoring lung parenchyma signal changes related to IPF activity.
  • A need exists for automated tools to quantify disease extent using MRI in IPF.

Purpose of the Study:

  • To evaluate the feasibility of a semiautomated method for quantifying T2 interstitial lung disease signal-intensity volume (ISIV) in IPF patients.

Main Methods:

  • A semiautomated segmentation approach using 3D-UTE MRI was registered to T2-BLADE images.
  • Interstitial lung disease signal-intensity volume (ISIV) was quantified using Gaussian mixture model clustering and normalized to lung volume (T2-ISIV).
  • Reproducibility was assessed using ICC and Bland-Altman analysis; correlations with composite physiological index (CPI) and forced vital capacity (FVC) were evaluated.

Main Results:

  • The T2-ISIV method demonstrated high reproducibility (ICC = 0.99) with minimal mean differences (-0.8 to 0.1).
  • T2-ISIV showed significant correlations with CPI (rho = 0.48) and FVC (rho = 0.50) (P < 0.05).
  • T2-ISIV values were significantly higher in IPF patients compared to controls (P < 0.05).

Conclusions:

  • T2-ISIV is a reproducible method for assessing the volumetric extent of abnormal interstitial lung signal intensity in IPF.
  • The T2-ISIV quantification method correlates with established biomarkers of IPF disease severity.
  • This technique offers a promising approach for monitoring IPF progression and treatment response.