scholarly journals SAT0286 BIOLOGICAL CORRELATES OF RADIOGRAPHIC FEATURES OF INTERSTITIAL LUNG DISEASE IN SYSTEMIC SCLEROSIS: AN IN DEPTH ANALYSIS OF BRONCHOALVEOLAR PROTEINS OF SCLERODERMA LUNG STUDY I PARTICIPANTS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1087.1-1088
Author(s):  
E. Volkmann ◽  
D. Tashkin ◽  
N. Li ◽  
G. Kim ◽  
J. Goldin ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Growth Factor ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Research Support ◽  
Radiographic Features ◽  
Depth Analysis ◽  
Specific Proteins ◽  
Clinical Measures ◽  
The Relationship

Background:Systemic sclerosis-related interstitial lung disease (SSc-ILD) involves a combination of inflammation, fibrosis and vascular pathology that is typically assessed on CT imaging as a mixture of ground-glass opacification (GGO) and fibrotic changes. We hypothesized that proteins recovered from bronchoalveolar lavage (BAL) could be used to probe the underlying pathobiology associated with GGO and fibrotic changes.Objectives:(1) To assess the relationship between 68 unique BAL proteins measured in participants of Scleroderma Lung Study (SLS) I1and radiographic and physiologic measures of ILD; (2) To identify inter-correlations among specific proteins to enlighten our understanding of how specific biological pathways contribute to SSc-ILD.Methods:Bronchoscopy was performed on 144 of the 158 participants in SLS I with 103 BAL samples available for analysis. BAL was lyophilized, concentrated 10X and used in a multiplex protein analysis for 68 different cytokines, chemokines and other factors. Kendall tau correlations were performed to assess the relationship between individual proteins and baseline measures of pulmonary function and quantitative CT scores for fibrosis, GGO and total ILD. Those proteins found to correlate significantly with at least 2 clinical measures of ILD were entered into a cluster analysis with inter-correlations expressed as a heatmap.Results:Significant correlations were observed between fibrosis scores and several biologic pathways including pro-fibrotic factors (transforming growth factor beta [TGF-β], platelet-derived growth factor [PDGF]), proteins involved in tissue remodeling (Matrix metallopeptidase [MMP]-1,7,8,9; Hepatocyte growth factor [HGF]), and those involved in monocyte/macrophage migration and activation (Monocyte chemoattractant protein [MCP]-1,3; macrophage colony-stimulating factor [MCSF]). These same pathways correlated with the diffusing capacity for carbon monoxide (DLCO). In contrast, GGO scores correlated primarily with immune and inflammatory mediators (interleukin [IL]-5,8,13,15, IL-1 receptor antagonist and interferon gamma) with only limited overlap to proteins that related to fibrosis. Vascular endothelial growth factor (VEGF) levels were lower in patients with more extensive GGO, fibrosis and diffusion impairment, suggesting that vascular changes are a central feature of SSc-ILD. Specific proteins were highly correlated with one another in a pattern suggesting biologically-related networks (Figure) that might provide additional insight regarding disease pathogenesis.Conclusion:Combining a diverse analysis of BAL proteins with the rich dataset available from SSc-ILD patients participating in SLS I, the study findings suggest the involvement of distinct biologic pathways, inter-related networks, and specific biologic signatures associated with unique radiographic features of ILD. The relationship of these factors to other SSc disease features, patient outcomes and as predictors of treatment responses will be studied in future analyses.References:[1]Tashkin DP, et al. NEJM 2006.Figure.Correlation heatmap of BAL proteins associated with at least 2 clinical measures of ILD in SSc patients. Absolute correlations are depicted, and darker colors signify stronger correlations.Disclosure of Interests:Elizabeth Volkmann Grant/research support from: Forbius, Corbus Pharmaceuticals, Consultant of: Boehringer Ingelheim, Forbius, Speakers bureau: Boehringer Ingelheim, Donald Tashkin: None declared, Ning Li: None declared, Grace Kim: None declared, Jonathan Goldin: None declared, Airi Harui: None declared, Michael Roth Grant/research support from: Genentech/Roche

scholarly journals OP0268 TREATMENT STATUS AFFECTS HOW PULMONARY BIOMARKERS PREDICT PROGRESSION OF SYSTEMIC SCLEROSIS-RELATED INTERSTITIAL LUNG DISEASE

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 163.1-163
Author(s):  
E. Volkmann ◽  
D. Tashkin ◽  
M. Leng ◽  
N. LI ◽  
G. Kim ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Growth Factor ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Transforming Growth Factor ◽  
Selection Process ◽  
Linear Regression Models ◽  
Research Support ◽  
Gm Csf ◽  
Treatment Status

Background:The course of interstitial lung disease (ILD) varies considerably in patients with systemic sclerosis (SSc), and no biomarkers have been found to consistently predict ILD progression in this population. Treatment may affect how a candidate biomarker correlates with improvement/worsening of SSc-ILD. We hypothesized that specific proteins recovered from bronchoalveolar lavage (BAL) would differentially predict progression of SSc-ILD based on whether a patient was receiving ILD therapy.Objectives:(1) To assess the relationship between 68 unique BAL proteins measured in participants of Scleroderma Lung Study (SLS) I1 and changes in radiographic extent of SSc-ILD; (2) To determine if treatment affects whether a specific protein predicts improvement or worsening of SSc-ILD.Methods:Bronchoscopy was performed on 144 of the 158 participants in SLS I (Cyclophosphamide [CYC] vs. placebo) with 103 BAL samples available for analysis. BAL was lyophilized, concentrated 10X and used in a multiplex protein analysis of 68 distinct cytokines, chemokines and growth factors. Quantitative imaging analysis (QIA) was used to calculate the extent of radiographic fibrosis (QLF) in the whole lung using HRCT of the chest at baseline and 12 months. Multivariable linear regression models were created to determine the key BAL proteins associated with change in QLF scores using a backward selection process adjusting for treatment arm and ILD severity. The bootstrap procedure was employed for internal validation.Results:A number of BAL proteins were significantly associated with change in QLF scores at 12 months; however, the directionality of these associations was often based on the presence/absence of treatment. For example, increased levels of granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin (IL)-1, monocyte chemoattractant protein (MCP)-3, chemokine ligand (CCL)-5, transforming growth factor (TGF)-β, hepatocyte growth factor (HGF), stem cell factor (SCF), IL-4, TGF-α, were associated with worse QLF scores in patients who received placebo; whereas, increased levels of these same proteins were associated with improved QLF scores in patients who received CYC (Figure). Increased levels of Fractalkine were associated with worse in QLF scores, and increased levels of IL-7 were associated with improved QLF scores, regardless of treatment arm. In the multivariable model adjusting for treatment arm and baseline severity of ILD, IL-1, MCP-3, surfactant protein C, IL-7, and CCL-5 were independently associated with change in QLF scores.Figure 1.Example of a specific BAL protein (GM-CSF) that predicts worse QLF scores in patients receiving placebo (Group B, Red dotted line) and improved QLF scores in patients receiving CYC (Group A, Blue solid line). Shaded areas represent 95% confidence intervals.Conclusion:Proteins that mediate both inflammation and fibrosis differentially affected progression of SSc-ILD based on treatment status. Higher levels of certain proteins predicted worsening of ILD in patients receiving placebo, but improvement in patients receiving CYC. Measuring these proteins could help to identify patients who: (1) are at risk for ILD progression, and (2) may preferentially benefit from treatment with immunosuppression.References:[1]Tashkin DP, et al. NEJM 2006.Disclosure of Interests:Elizabeth Volkmann Consultant of: Boehringer Ingelheim, Grant/research support from: Corbus, Forbius, Donald Tashkin: None declared, Mei Leng: None declared, Ning Li: None declared, Grace Kim: None declared, Jonathan Goldin: None declared, Airi Harui: None declared, Michael Roth Grant/research support from: Genentech/Roche

scholarly journals POS0866 TWO-DIMENSIONAL HRCT-BASED RADIOMIC FEATURES IN SSC-ILD DISTINGUISH DRUG RESPONDERS FROM NON-RESPONDERS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 688-689
Author(s):  
C. Meier ◽  
M. Maciukiewicz ◽  
M. Brunner ◽  
J. Schniering ◽  
H. Gabrys ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Linear Regression ◽  
Lung Disease ◽  
Treatment Response ◽  
Two Dimensional ◽  
Research Support ◽  
Pre Treatment

Background:Management of patients with systemic sclerosis-associated interstitial lung disease (SSc-ILD) is complicated by high inter-patient variability. To date, no validated predictors of treatment response are available for routine use. High resolution computed tomography (HRCT)-based radiomics, i.e. the high-dimensional, quantitative analysis of imaging metadata, have previously been shown to be successful in discriminating (SSc-)ILD phenotypes in preclinical and clinical studies1. Since HRCT is an integral part of the routine work-up in SSc, HRCT-based radiomic features may hold potential as non-invasive biomarkers.Objectives:To predict treatment response using two-dimensional (2D) HRCT-based radiomics in SSc-ILD patients from a prospectively followed cohort.Methods:Inclusion criteria were diagnosis of SSc-ILD in HRCT, availability of a suitable chest HRCT scan within 12 months prior to initiation of a new treatment, and availability of clinical baseline and follow-up information. Treatment response was defined as the absence of all of the following over a follow-up period of 12-24 months: relative decrease in forced vital capacity (FVC) ≥5%, increase of ILD in HRCT as assessed by a radiologist, change in treatment regimen due to insufficient response, ILD-related death or lung transplantation. Of each pre-treatment HRCT, 6 slices (15±5 mm apart, starting from the basal lung margin) were manually segmented and 1513 2D radiomic features were extracted using the in-house software Z-Rad (Python 2.7). Features were Z-score transformed and pre-filtered for inter- and intra-reader robustness (intraclass correlation coefficient >0.85) and inter-feature correlation (Spearman’s rho <0.9). A categorical linear regression model was created using 3-fold cross-validated elastic nets for feature selection. Features were then summarized and divided by their number. For generation of a score cut-off, Youden’s score was used. For two-group analyses of continuous variables, Wilcoxon’s test was performed, whereas categorical data was assessed using Fisher’s exact test.Results:A total of 64 pre-treatment HRCTs from 54 patients were analyzed. In 9 patients, >1 asynchronous treatments were assessed, while 45 patients had only 1 eligible treatment approach. The response rate within the assessed follow-up period was 45.3% (n=29). For score generation, 13 radiomic features were selected and an optimal cut-off value of -0.1589 was determined. Univariate linear regression showed significant association between our categorical radiomics-based score and treatment response (p=0.007, area under the curve = 0.65 (0.51-0.79), sensitivity=0.90, specificity=0.43), whereby a high score was predictive for treatment response.No differences between patients with high (n=46) or low (n=18) scores were detected for baseline age (mean±SD=55.5±12.0 and 55.5±13.6 years, p=0.84), duration of SSc (mean±SD=6.2±8.4 and 4.7±4.4 years, p=0.79), time since ILD diagnosis (2.7±2.9 and 2.4±3.1 years, p=0.59), FVC (77.6±20.6 and 80.1±17.9, p=0.41) or DLco (54.4±21.0 and 57.6±18.9, p=0.40). Distribution of anti-Scl-70 positivity (45.7% vs. 55.6%, p=0.58) and diffuse cutaneous disease (47.7% vs. 61.1%, p=0.41) was not significantly different between patients with high and low scores, respectively, although a trend towards higher percentages in the high score group was observed.Conclusion:Our results indicate that, following validation in external cohorts, radiomics may be a promising tool for future pre-treatment patient stratification. Moreover, our radiomics-based score seems not to be associated with commonly studied clinical predictors such as anti-Scl-70 positivity or lung function, underlining a possible additive value to ‘traditional’ clinical parameters.References:[1]Schniering, J., et al. Resolving phenotypic and prognostic differences in interstitial lung disease related to systemic sclerosis by computed tomography-based radiomics. medRxiv [Preprint] doi:10.1101/2020.06.09.20124800 (2020).Disclosure of Interests:Chantal Meier: None declared, Malgorzata Maciukiewicz: None declared, Matthias Brunner: None declared, Janine Schniering: None declared, Hubert Gabrys: None declared, Anja Kühnis: None declared, Oliver Distler Speakers bureau: Speaker fee on Scleroderma and related complications: Bayer, Boehringer Ingelheim, Medscape, Novartis, Roche. Speaker fee on rheumatology topic other than Scleroderma: MSD, iQone, Novartis, Pfizer, Roche, Consultant of: Consultancy fee for Scleroderma and its complications: Abbvie, Acceleron Pharma, Amgen, AnaMar, Arxx Therapeutics, Bayer, Baecon Discovery, Boehringer, CSL Behring, ChemomAb, Corbus Pharmaceuticals, Horizon Pharmaceuticals, Galapagos NV, GSK, Glenmark Pharmaceuticals, Inventiva, Italfarmaco, iQvia, Kymera, Medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Roche, Roivant Sciences, Sanofi, UCB. Consultancy fee for rheumatology topic other than Scleroderma: Abbvie, Amgen, Lilly, Pfizer, Grant/research support from: Research Grants to investigate the pathophysiology and potential treatment of Scleroderma and its complications: Kymera Therapeutics, Mitsubishi Tanabe, Thomas Frauenfelder: None declared, Stephanie Tanadini-Lang: None declared, Britta Maurer Speakers bureau: Speaker fees from Boehringer-Ingelheim, Grant/research support from: Grant/research support from AbbVie, Protagen, Novartis Biomedical Research, congress support from Pfizer, Roche, Actelion, mepha, and MSD

scholarly journals Impact of Lung Function Decline on Time to Hospitalisation Events in Systemic Sclerosis-associated Interstitial Lung Disease (SSc-ILD): a Joint Model Analysis

2021 ◽  
Author(s):  
Michael Kreuter ◽  
Francesco Del Galdo ◽  
Corinna Miede ◽  
Dinesh Khanna ◽  
Wim A. Wuyts ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Function ◽  
Lung Disease ◽  
Fold Increase ◽  
Phase Iii ◽  
Lung Function Decline ◽  
Related Hospitalisation ◽  
The Relationship ◽  
Increase In Risk

Abstract Background: Interstitial lung disease (ILD) is a common organ manifestation in systemic sclerosis (SSc) and is the leading cause of death in patients with SSc. A decline in forced vital capacity (FVC) is an indicator of ILD progression and is associated with mortality in patients with SSc-associated ILD (SSc-ILD). However, the relationship between FVC decline and hospitalisation events in patients with SSc-ILD is largely unknown. The objective of this post-hoc analysis was to investigate the relationship between FVC decline and clinically important hospitalisation endpoints.Methods: We used data from SENSCIS®, a Phase III trial investigating the efficacy and safety of nintedanib in patients with SSc-ILD. Joint models for longitudinal and time-to-event data were used to assess the association between rate of decline in FVC% predicted and hospitalisation-related endpoints (including time to first all-cause hospitalisation or death; time to first SSc-related hospitalisation or death; and time to first admission to an emergency room [ER] or admission to hospital followed by admission to intensive care unit [ICU] or death) during the treatment period, over 52 weeks in patients with SSc-ILD.Results: There was a statistically significant association between FVC decline and the risk of all-cause (n=78) and SSc-related (n=42) hospitalisations or death (both P<0.0001). A decrease of 3% in FVC corresponded to a 1.43-fold increase in risk of all-cause hospitalisation or death (95% confidence interval [CI] 1.24, 1.65) and a 1.48-fold increase in risk of SSc-related hospitalisation or death (95% CI 1.23, 1.77). No statistically significant association was observed between FVC decline and admission to ER or to hospital followed by admission to ICU or death (n=75; P=0.15). The estimated slope difference for nintedanib versus placebo in the longitudinal sub-model was consistent with the primary analysis in SENSCIS®.Conclusions: The association of lung function decline with an increased risk of hospitalisation suggests that slowing FVC decline in patients with SSc-ILD may prevent hospitalisations. Our findings also provide evidence that FVC decline may serve as a surrogate endpoint for clinically relevant hospitalisation-associated endpoints.Trial registration: Clinialtrials.gov, NCT02597933. Registered 8 October 2015, https://clinicaltrials.gov/ct2/show/study/NCT02597933.

FRI0454 UNDER DETECTION OF INTERSTITIAL LUNG DISEASE IN JUVENILE SYSTEMIC SCLEROSIS (JSSC) UTILIZING PULMONARY FUNCTION TESTS. RESULTS FROM THE JUVENILE SCLERODERMA INCEPTION COHORT

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 824.1-824
Author(s):  
I. Foeldvari ◽  
B. Hinrichs ◽  
K. Torok ◽  
M. J. Santos ◽  
O. Kasapcopur ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Pulmonary Function ◽  
Lung Disease ◽  
Pulmonary Function Tests ◽  
Disease Process ◽  
Systemic Scleroderma ◽  
Inception Cohort ◽  
Research Support ◽  
Juvenile Systemic Sclerosis

Background:Juvenile systemic sclerosis (jSSc) is an orphan disease with a prevalence in around 3 in a million children. Pulmonary involvement in jSSc occurs in approximately 40 % in the inception cohort. Traditionally in jSSc, pulmonary function testing (PFT) with FVC and DLCO are used for screening and computed tomography (HRCT) was more reserved for those with abnormal PFTs. More recently, it has become apparent that PFTs might not be sensitive enough for detecting ILD in children.Objectives:Utilizing a prospective international juvenile systemic scleroderma cohort (JSScC) [2], to determine if pulmonary screening with FVC and DLCO is sufficient enough to assess the presence of interstitial lung disease in comparison to CT evaluation.Methods:The international juvenile systemic scleroderma cohort database was queried for available patients with recorded PFT parameters and HRCT performed to determine sensitivity of PFTs detecting disease process.Results:Of 129 patients in the jSScC, 67 patients had both CT imaging and an FVC reading from PFTs for direct comparison. DLCO readings were also captured but not in as many patients with tandem HRCT (n =55 DCLO and HRCT scan). Therefore, initial analyses focused on the sensitivity, specificity and accuracy of the FVC value from the PFTs to capture the diagnosis of interstitial lung disease as determined by HRCT.Overall, 49% of the patients had ILD determined by HRCT, with 60% of patients having normal FVC (>80%) with positive HRCT findings, and 24% of patients having normal DLCO (> 80%) with positive HRCT findings. Fourteen percent (n = 3/21) of patients with both FVC and DLCO values within the normal range had a positive HRCT finding.Conclusion:The sensitivity of the FVC in the JSScC cohort in detecting ILD was only 39%. Relying on PFTs alone for screening for ILD in juvenile systemic sclerosis would have missed the detection of ILD in almost 2/3 of the sample cohort, supporting the use of HRCT for detection of ILD in children with SSc. In addition, the cut off utilized, of less than 80% of predicted FVC or DLCO could be too low for pediatric patients to exclude beginning ILD. This pilot data needs confirmation in a larger patient population.Supported by the “Joachim Herz Stiftung”Disclosure of Interests:Ivan Foeldvari Consultant of: Novartis, Bernd Hinrichs: None declared, Kathryn Torok: None declared, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Ozgur Kasapcopur: None declared, Amra Adrovic: None declared, Valda Stanevicha: None declared, Flávio R. Sztajnbok: None declared, Maria T. Terreri: None declared, Ana Paula Sakamoto: None declared, Ekaterina Alexeeva Grant/research support from: Roche, Pfizer, Centocor, Novartis, Speakers bureau: Roche, Novartis, Pfizer., Jordi Anton Grant/research support from: grants from Pfizer, abbvie, Novartis, Sobi. Gebro, Roche, Novimmune, Sanofi, Lilly, Amgen, Grant/research support from: Pfizer, abbvie, Novartis, Sobi. Gebro, Roche, Novimmune, Sanofi, Lilly, Amgen, Consultant of: Novartis, Sobi, Pfizer, abbvie, Consultant of: Novartis, Sobi, Pfizer, abbvie, Speakers bureau: abbvie, Pfizer, Roche, Novartis, Sobi, Gebro, Speakers bureau: abbvie, Pfizer, Roche, Novartis, Sobi, Gebro, Maria Katsikas: None declared, Vanessa Smith Grant/research support from: The affiliated company received grants from Research Foundation - Flanders (FWO), Belgian Fund for Scientific Research in Rheumatic diseases (FWRO), Boehringer Ingelheim Pharma GmbH & Co and Janssen-Cilag NV, Consultant of: Boehringer-Ingelheim Pharma GmbH & Co, Speakers bureau: Actelion Pharmaceuticals Ltd, Boehringer-Ingelheim Pharma GmbH & Co and UCB Biopharma Sprl, Rolando Cimaz: None declared, Mikhail Kostik: None declared, Simone Appenzeller: None declared, Mahesh Janarthanan: None declared, Monika Moll: None declared, Dana Nemcova: None declared, Dieneke Schonenberg: None declared, Cristina Battagliotti: None declared, Lillemor Berntson Consultant of: paid by Abbvie as a consultant, Speakers bureau: paid by Abbvie for giving speaches about JIA, Blanca Bica: None declared, Juergen Brunner Grant/research support from: Pfizer, Novartis, Consultant of: Pfizer, Novartis, Abbvie, Roche, BMS, Speakers bureau: Pfizer, Novartis, Abbvie, Roche, BMS, Patricia Costa Reis: None declared, Despina Eleftheriou: None declared, Liora Harel: None declared, Gerd Horneff Grant/research support from: AbbVie, Chugai, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Speakers bureau: AbbVie, Bayer, Chugai, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Dragana Lazarevic: None declared, Kirsten Minden Consultant of: GlaxoSmithKline, Sanofi, Speakers bureau: Roche, Susan Nielsen: None declared, Farzana Nuruzzaman: None declared, Anjali Patwardhan: None declared, Yosef Uziel: None declared, Nicola Helmus: None declared

scholarly journals SAT0569 “IMAGES ARE MORE THAN PICTURES, THEY ARE DATA” [1] – EXPLORATION OF RADIOMICS ANALYSIS FOR SYSTEMIC SCLEROSIS-ASSOCIATED INTERSTITIAL LUNG DISEASE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1242.2-1243
Author(s):  
J. Schniering ◽  
M. Maciukiewicz ◽  
H. Gabrys ◽  
M. Brunner ◽  
C. Blüthgen ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Function ◽  
Correlation Analysis ◽  
Lung Disease ◽  
Roc Curve ◽  
Wilcoxon Test ◽  
Grey Level ◽  
Research Support ◽  
Long Run

Background:Interstitial lung disease (ILD) affects 60% of patients with systemic sclerosis (SSc) and is the primary cause of death. Medical imaging is an integral part of the routine work-up for diagnosis and monitoring of SSc-ILD and includes high-resolution computed tomography (HRCT). Radiomics is a novel research area that describes the in-depth analysis of tissue phenotypes in medical images with computational retrieval of quantitative, mineable metadata appropriate for statistical analyses.Objectives:To explore the performance of HRCT-derived radiomic features for the assessment of SSc-associated ILD (i.e. diagnosis, staging, and lung function).Methods:Radiomics analysis was performed on HRCT scans from 98 SSc patients, including n=33 SSc patients without ILD, n=33 with limited and n=32 with extensive ILD as defined by 0%, <20% and ≥20% visual extent of fibrosis on HRCT, respectively. Following semi-automated segmentation of lung tissue on 3D reconstructed HRCT scans, 1386 radiomic features, including 17 intensity, 137 texture, and 1232 wavelet features were extracted using the in-house developed software Z-Rad (Python 2.7). In order to identify robust features, we conducted intra- and inter-reader correlation analysis (ICC) in a subgroup of patients. Only features with good reproducibility (ICC ≥ 0.75) entered subsequent analyses. We applied the Wilcoxon test, followed by Receiver Operating Characteristic ROC) curve analyses, to identify features significantly different between a) ILD and non-ILD and b) limited vs. extensive ILD patients. Spearman rank correlation was performed to reveal significant associations of radiomic features from a) and b) with lung function as measured by percentage of predicted forced vital capacity (FVC% predicted).Results:In total, 1355/1386 radiomic features passed the test of robustness and were eligible for further, exploratory analyses. Radiomic features with good performance (area under the ROC curve (AUC) ≥ 0.7 and p-value ≤ 0.05) were considered as potential candidate discriminators. Under this criterion, we identified 288/1355 (21.3%) radiomic features that were significantly different between ILD and non-ILD patients and 409/1355 (30.2%) features that significantly discriminated between limited and extensive ILD (Fig. 1). For diagnosis, the texture featuredependence count entropywas the top parameter to distinguish ILD patients from healthy controls (AUC = 0.89, p = 1.83x10-10), whereas for staging the wavelet featureHHH long run high grey level emphasisproved to be best suited to separate limited from extensive ILD (AUC = 0.88, p = 7.76x10-9).Fig 1.Correlation analysis of the most significant (best performing) discriminative radiomic features with lung function revealed a significant negative correlation ofdependence count entropy(rho = -0.51, p = 9.89x10-8) andHHH long run high grey level emphasis(rho = -0.51, p = 1.73x10-5) with FVC% predicted.Conclusion:Our study adds novelty to the field of SSc-ILD showing that radiomic features have great potential as quantitative imaging biomarkers for diagnosis and staging of SSc-ILD and that they may reflect lung function. As the next step, we are planning to build predictive models, using machine learning, for diagnosis, staging, and lung function and validate them in external patient cohorts. If validated such models will pave the way for computer-aided management in SSc-ILD and thus improve patients’ outcome.References:[1]Gillies, R. J., Kinahan, P. E. & Hricak, H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 278, 563-577, doi:10.1148/radiol.2015151169 (2016).Disclosure of Interests:Janine Schniering: None declared, Malgorzata Maciukiewicz: None declared, Hubert Gabrys: None declared, Matthias Brunner: None declared, Christian Blüthgen: None declared, Oliver Distler Grant/research support from: Grants/Research support from Actelion, Bayer, Boehringer Ingelheim, Competitive Drug Development International Ltd. and Mitsubishi Tanabe; he also holds the issued Patent on mir-29 for the treatment of systemic sclerosis (US8247389, EP2331143)., Consultant of: Consultancy fees from Actelion, Acceleron Pharma, AnaMar, Bayer, Baecon Discovery, Blade Therapeutics, Boehringer, CSL Behring, Catenion, ChemomAb, Curzion Pharmaceuticals, Ergonex, Galapagos NV, GSK, Glenmark Pharmaceuticals, Inventiva, Italfarmaco, iQvia, medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Roche, Sanofi and UCB, Speakers bureau: Speaker fees from Actelion, Bayer, Boehringer Ingelheim, Medscape, Pfizer and Roche, Matthias Guckenberger: None declared, Thomas Frauenfelder: None declared, Stephanie Tanadini-Lang: None declared, Britta Maurer Grant/research support from: AbbVie, Protagen, Novartis, congress support from Pfizer, Roche, Actelion, and MSD, Speakers bureau: Novartis

scholarly journals Genetic Susceptibility to Interstitial Lung Disease Associated with Systemic Sclerosis

2015 ◽  
Vol 9s1 ◽  
pp. CCRPM.S23312 ◽  
Author(s):  
Akiko Tochimoto ◽  
Yasushi Kawaguchi ◽  
Hisashi Yamanaka
Keyword(s):  
Systemic Sclerosis ◽  
Growth Factor ◽  
Interstitial Lung Disease ◽  
Connective Tissue ◽  
Human Leukocyte Antigen ◽  
Lung Disease ◽  
Genetic Susceptibility ◽  
Human Leukocyte ◽  
Tissue Growth ◽  
Leukocyte Antigen

Systemic sclerosis (SSc) is a connective tissue disease that is characterized by tissue fibrosis, microvasculopathy, and autoimmunity. Interstitial lung disease (ILD) is a common complication of SSc and is one of the frequent causes of mortality in SSc. Although the exact etiology of SSc remains unknown, clinical and experimental investigations have suggested that genetic and environmental factors are relevant to the pathogenesis of SSc and SSc-ILD. More than 30 genes have been identified as susceptibility loci for SSc, most of which are involved in immune regulation and inflammation. It is thought that the key pathogenesis of SSc-ILD is caused by the release of profibrotic mediators such as transforming growth factor β1 and connective tissue growth factor from lung cells induced by a persistent damage. This review presents the genetic susceptibility to SSc-ILD, including human leukocyte antigen and non-human leukocyte antigen genes, especially focusing on connective tissue growth factor.

scholarly journals AB0592 NAILFOLD CAPILLARY ABNORMALITIES PREDICT INTERSTITIAL LUNG DISEASE (ILD) COMPLICATION IN SYSTEMIC SCLEROSIS PATIENTS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1592.2-1593
Author(s):  
T. Miyagi ◽  
T. Kameda ◽  
S. Nakashima ◽  
H. Shimada ◽  
R. Wakiya ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Odds Ratio ◽  
Pulmonary Function Tests ◽  
Classification Criteria ◽  
Digital Ulcers ◽  
Number Of Patients ◽  
Multicenter Prospective Cohort Study ◽  
The Relationship

Background:Systemic sclerosis (SSc) have various organ involvements including pulmonary hypertension (PH), digital ulcers (DU), and interstitial lung disease (ILD). On the other hand, Nailfold capillary (NFC) abnormalities (enlarged/giant capillaries, fresh or old hemorrhages, avascular areas, ramified/bushy capillaries) detected by capillaroscopy are included in ACR/EULAR classification criteria for SSc as one of important findings. In addition, many studies have reported the relationship between NFC abnormalities and organ involvements (DU, PH) [1][2]. However, there are a few reports about the relationship between NFC abnormalities and ILD.Objectives:We clarify the association with NFC abnormalities and ILD in SSc patients.Methods:We enrolled SSc patients without PH from January 2016 to December 2019 in our institution. SSc patients were diagnosed according to EULAR classification criteria in 2013. ILD was detected by chest CT scans. We assessed severity of ILD with pulmonary function tests (PFT). Abnormal PFT was defined as vital capacity (%VC) or diffusion capacity (DLCO) < 70%. NFC abnormalities were detected with “OptiPiX capillaroscopy Clinic 1.7.x” and the number of capillaries was measured per 1mm in 2nd to 5th fingers of both hand. We defined enlarged and giant capillaries as >30 µm and >50 µm, respectively.Results:We enrolled 59 SSc patients (54 females, 5 males). Mean age is 65.0 ± 8.0 years. Thirty-one patients (52.5%) were complicated with ILD. Mean capillary counts are 6.6/mm. The number of patients with each NFC abnormalities (enlarged capillaries, giant capillaries, microhemorrhages, ramified, avascular areas) are 42, 32, 48, 38, and 33 cases, respectively. Two cases did not have NFC abnormalities. SSc patients with giant capillaries had fewer ILD complications (p <0.05, odds ratio 0.183 [0.059 – 0.57]). Other NFC abnormalities were not associated with ILD in SSc patients. We inspected %VC of 23 patients and DLCO of 20 patients with ILD. Eleven patients had abnormal PFT (5 patients had abnormal %VC and 9 patients had abnormal DLCO). Most of them had not enlarged capillaries than patient with normal PFT (odds ratio 0.11 [0.016 – 0.81]). Other NFC abnormalities including giant capillaries were not associated with abnormal PFT.Conclusion:We investigated the relationship between NFC abnormalities and ILD conplications in SSc patients. NFC abnormalities are associated with ILD complicacion and severity of ILD. It was suggested that no giant capillary in SSc patients may predict ILD complication. Moreover, no enlarged capillary may predict the severe ILD.References:[1]Valeria Riccieri et al. Systemic sclerosis patients with and without pulmonary arterial hypertension: a nailfold capillaroscopy study. Rheumatology, Volume 52, Issue 8, 1 August 2013, Pages 1525–1528[2]Maurizio Cutolo et al. Nailfold Videocapillaroscopic Features and Other Clinical Risk Factors for Digital Ulcers in Systemic Sclerosis: A Multicenter, Prospective Cohort Study. Arthritis Rheumatol. 2016 Oct; 68(10): 2527–2539.Disclosure of Interests:None declared

scholarly journals OP0272 68GA-FAPI-04 PET/CT STUDY EXTENSION FOR THE ASSESSMENT OF FIBROBLAST ACTIVATION AND RISK EVALUATION IN SYSTEMIC SCLEROSIS-RELATED INTERSTITIAL LUNG DISEASE

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 165.1-166
Author(s):  
C. Bergmann ◽  
J. H. W. Distler ◽  
C. Treutlein ◽  
K. Tascilar ◽  
A. T. Mueller ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Disease Progression ◽  
Forced Vital Capacity ◽  
Vital Capacity ◽  
Control Group ◽  
Research Support ◽  
Fibroblast Activation ◽  
Pet Ct

Background:Interstitial lung disease (ILD) is the most common cause of death in systemic sclerosis (SSc). To date, the progression of SSc-ILD is judged by the accrual of lung damage on computed tomography (CT) and functional decline (forced vital capacity). However, this approach does not directly assess the activity of tissue remodeling. Moreover, prediction of the course of ILD in individual SSc patients remains challenging. Fibroblast Activation Protein (FAP) is a specific, ex vivo validated marker for activated fibroblasts.Objectives:The aims of this study were: 1. To assess differences in the uptake of 68GA-FAPI 04 in SSc-ILD patients compared to controls, to analyze 2. whether 68GA-FAPI 04 uptake at baseline correlates with other risk factors of disease progression and 3. Whether 68GA-FAPI 04 uptake is associated with the course of SSc-ILD.Methods:Between September 2018 and April 2020, 21 patients with SSc-ILD confirmed by HRCT and onset of SSc-ILD within ≤ 5 years or signs of progressive ILD and 21 controls without ILD were consecutively enrolled. All participants underwent 68Ga-FAPI-04 PET/CT imaging and standard-of-care procedures including HRCT and lung function testing (PFT) at baseline. Patients with SSc-ILD patients were followed-up for 6 months with HRCT and PFT. Follow-up 68Ga-FAPI-04 PET/CT scans were obtained in a subset of patients treated with nintedanib. We compared baseline 68Ga-FAPI-04 PET/CT uptake to standard diagnostic tools and currently used predictors of ILD progression. The association of 68Ga-FAPI-04 uptake with changes in FVC was analyzed using mixed-effects models.Results:68Ga-FAPI-04 accumulated in fibrotic areas of the lungs in SSc-ILD compared to controls with a median (q1-q3 interval) wlSUVmean of 0.8 (0.6 to 2.1) in the SSc-ILD group and 0.5 (0.4 to 0.5) in the control group (p<0.0001 with Mann-Whitney test) and a median whole lung maximal standardized uptake value (wlSUVmax) of 4.4 (3.05 to 5.2) in the SSc-ILD group compared to 0.7 (0.65 to 0.7) in the control group (p<0.0001). wlFAPI-MAV and wlTL-FAPI were not measurable in control subjects, as no 68Ga-FAPI-04 uptake above background level was observed. In the SSc-ILD group the median wlFAPI-MAV was 254cm3 (163.4 to 442.3) and the median wlTL-FAPI was 183.6 cm3 (98.04 to 960.7). 68Ga-FAPI-04 uptake was higher in patients with extensive disease, with previous ILD progression or high EUSTAR activity scores. Increased 68Ga-FAPI-04 uptake at baseline was associated with progression of ILD independently of extent of involvement on HRCT scan and the forced vital capacity at baseline. In consecutive 68Ga-FAPI-04-PET/CTs, changes in 68Ga-FAPI-04 uptake was concordant with the observed response to the fibroblast-targeting antifibrotic agent nintedanib.Conclusion:Our study presents first in human evidence that 68Ga-FAPI-04-fibroblast uptake correlates with fibrotic activity and disease progression in the lungs of SSc-ILD patients and that 68Ga-FAPI-04-PET/CT may be of potential to improve risk assessment of SSc-ILD.Figure 1.A and B:68Ga-FAPI-04 PET/CT scan from a patient with SSc-ILD with selective 68Ga-FAPI-04 uptake in fibrotic areas of the left- and right lower lung lobes (red arrows), but not in non-fibrotic areas such as the middle lobe (green arrow). B Corresponding CT component.Acknowledgements:We gratefully acknowledge Prof. Uwe Haberkorn (University Hospital Heidelberg and DKFZ, Heidelberg, Germany) and iTheranostics Inc. (Dulles, VA, USA) for providing the precursor FAPI-04.Disclosure of Interests:Christina Bergmann: None declared, Jörg H.W. Distler Speakers bureau: Actelion, Anamar, ARXX, Pharma, Boehringer Ingelheim, Celgene, Galapagos, GSK, Inventiva, JB Therapeutics, and UCB, Grant/research support from: Anamar, Active Biotech, Array Biopharma, ARXX, aTyr, BMS, Bayer Pharma, Boehringer Ingelheim, Celgene, Galapagos, GSK, Inventiva, Novartis, Sanofi-Aventis, RedX, UCB, Christoph Treutlein: None declared, Koray Tascilar Speakers bureau: Gilead sciences GmbH, Pfizer Turkey, UCB Turkey, Anna-Theresa Mueller: None declared, Armin Atzinger: None declared, Alexandru-Emil Matei: None declared, Johannes Knitza: None declared, Andrea-Hermina Györfi: None declared, Anja Lueck: None declared, Clara Dees: None declared, Alina Soare: None declared, Andreas Ramming: None declared, Verena Schönau: None declared, Oliver Distler Speakers bureau: Arxx Therapeutics, Baecon Discovery, Blade Therapeutics,Bayer, Böhringer Ingelheim, Catenion,Competitive Drug Development International Ltd, Corbuspharma, CSL Behring, ChemomAb, Horizon Pharmaceuticals, Ergonex, Galaapagos NV, Glenmark Pharmaceuticals,GSK, Inventiva, Italfarmaco, IQvia, Kymera, Lilly, Medac, Medscape, MSD, Novartis, Pfizer, Roche, Sanofi, Taget Bio Sciencec, UCB, Grant/research support from: Bayer,Böhringer Ingelheim, Mitsubishi Tanabe Pharma, Olaf Prante: None declared, Philipp Ritt: None declared, Theresa Ida Goetz: None declared, Markus Koehner: None declared, Michael Cordes: None declared, Tobias Baeuerle: None declared, Torsten Kuwert Speakers bureau: Honoraria for occasional lectures by Siemens Healthineers, Grant/research support from: Research grant to the Clinic of Nuclear Medicine by this entity covering projects in the field of SPECT/CT, Georg Schett: None declared, Christian Schmidkonz: None declared

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