THU0345 TEXTURE-BASED RADIOMICS FEATURES DISCRIMINATE DIFFERENT STAGES OF EXPERIMENTAL INTERSTITIAL LUNG DISEASE
Authors: Janine Schniering, Matthias Brunner, Oliver Distler, Matthias Guckenberger, Marta Bogowicz, Diem Vuong, Cristina Müller, Thomas Frauenfelder, Stephanie Tanadini-Lang, Britta Maurer
Journal: Annals of the Rheumatic Diseases (2019)

<h3>Background:</h3> Interstitial lung disease (ILD) is a life-threating complication of systemic sclerosis (SSc). There is an unmet need for validated, routinely available biomarkers for disease staging and individualized patient stratification. In that respect, high-resolution computed tomography (HRCT), routinely performed in the work-up of SSc-ILD patients, has great potential as a source for non-invasive imaging biomarkers. Recently, radiomics, the quantitative extraction of hundreds of radiologic image features, has emerged as a powerful tool for biomarker research and precision medicine approaches; however, so far, it has been applied predominantly in oncology. <h3>Objectives:</h3> To evaluate the performance of CT-based radiomics for disease detection, staging and as surrogate marker for tissue pathophysiology in the model of bleomycin (BLM)-induced lung fibrosis. <h3>Methods:</h3> To mimic different stages of SSc-ILD, small-animal CT imaging was performed at days 3, 7, and 14 after instillation of BLM or saline solution, respectively (n=5-6 mice/group). Trained observers manually segmented the left and right mouse lungs in the CT images, and 154 radiomics features were extracted including 17 histogram- and 137 texture-based features using the in-house developed software Z-Rad (Python 2.7). To link the radiomics features with the underlying pathophysiology, Pearson correlation analysis between radiomics and histological features (Ashcroft score, Sirius red and CD45 staining positivity) was performed. <h3>Results:</h3> CT imaging visualized morphological changes of the lung architecture in BLM-treated mice, as evidenced by a time-dependent increase of grey areas on chest CT images and a gradual increase in tissue density on density-masked lungs. Accordingly, 6 out of 17 classical histogram features (e.g. mean CT density, skewness and kurtosis) precisely distinguished diseased from healthy mice with area under the curve values (AUCs) of &gt;0.87 (p&lt;0.05) and thus detected lung remodelling. However, histogram-based features failed to differentiate between the different time points and thus stages of experimental lung fibrosis as investigated by receiver operating characteristic curve analysis and by hierarchical clustering. In contrast, 59 out of 137 texture-based radiomics features, including features describing image homogeneity or contrast detected ILD and distinguished the different stages with excellent accuracy (AUCs&gt;0.84; p&lt;0.05) thus outperforming the classical histogram features. In addition, texture-based, but not histogram-based features were associated (R<sup>2</sup>&gt;0.5, p&lt;0.05) with histological parameters, thereby possibly reflecting changes in lung (micro-)architecture, which may result from both inflammatory and/or fibrotic changes. <h3>Conclusion:</h3> If confirmed in human SSc-ILD, texture-based radiomics features have great potential to provide biological and stage-specific quantitative information on lung (micro-)architecture and thus could serve as quantitative imaging biomarkers for guided decision making in SSc-ILD. <h3><b>Disclosure of Interests:</b>&nbsp;:</h3> Janine Schniering: None declared, Matthias Brunner: None declared, Oliver Distler Grant/research support from: Prof. Distler received research funding from Actelion, Bayer, Boehringer Ingelheim and Mitsubishi Tanabe to investigate potential treatments of scleroderma and its complications, Consultant for: Prof. Distler has/had consultancy relationship within the last 3 years with Actelion, AnaMar, Bayer, Boehringer Ingelheim, ChemomAb, espeRare foundation, Genentech/Roche, GSK, Inventiva, Italfarmaco, iQvia, Lilly, medac, MedImmune, Mitsubishi Tanabe Pharma, Pharmacyclics, Novartis, Pfizer, Sanofi, Serodapharm and UCB in the area of potential treatments of scleroderma and its complications. In addition, he had/has consultancy relationship within the last 3 years with A. Menarini, Amgen, Abbvie, GSK, Mepha, MSD, Pfizer and UCB in the field of arthritides and related disorders, Matthias Guckenberger Grant/research support from: Grant/research support by Varian Medical Systems and Siemens Healthcare, Marta Bogowicz: None declared, Diem Vuong: None declared, Cristina Müller: None declared, Thomas Frauenfelder: None declared, Stephanie Tanadini-Lang Grant/research support from: Grant/research support by Varian Medical Systems and Siemens Healthcare, Britta Maurer Grant/research support from: Grant/research support from AbbVie, Protagen, Novartis; congress support from MSD, Pfizer, Roche, and Actelion&nbsp;