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IBs of oedema and fibrosis in rat DIILD

Biological- and imaging biomarkers of oedema and fibrosis in a rat model of Drug-Induced Interstitial Lung Disease (DIILD) (Conference Abstract)

Irma Mahmutovic Persson, Hanna Falk Håkansson, Anders Örbom, Per-Ola Önnervik, Janne Persson, Karin Von Wachenfeldt, Lars E. Olsson.


European Respiratory Journal 2019 54: PA2417. doi: 10.1183/13993003.congress-2019.PA2417.

Abstract

A large number of systemically administered drugs have the potential to cause DIILD. We aim to characterize a model of DIILD in the rat and develop imaging biomarkers for detection and quantification of DIILD.

Methods: Sprague-Dawley rats received one single dose of intratracheal bleomycin and were longitudinally imaged at day 0, 3, 7, 14, 21 and 28 post dosing, applying imaging techniques MRI and PET/CT. Bronchoalveolar lavage fluid (BALF) was analyzed for total protein and inflammatory cells. Lungs were taken for further analyses by histology, and stained for inflammation and collagen deposition.

Results: Bleomycin induced significant increase in total protein concentration and total cell count in BALF, peaking at day3 (p>0.001) and day7 (p>0.001) compared to control, respectively. The lesion measured by MRI and the FDG-PET signal in the lungs of bleomycin challenged rats was significantly increased during day3-14, peaking at day7. Two subgroups of animals were identified as low- and high responders to bleomycin challenge, by their different change in total lung volume. Both groups showed signs of inflammation initially, while at later time points the low-responder group recovered towards control, and the high-responder group showed progressive fibrosis with significant increase of lesion volume (p<0.001), compared to control.

Conclusion: Bleomycin-induced lung injury with MRI and PET readout in rats, is an adequate and translational animal model for DIILD studies. The scenario comprised different disease responses, with different fractions of inflammation and fibrosis. Thereby, this study improved the understanding biological- and imaging biomarkers in DIILD.