{
  "abstract": "Introduction Identifying distinct radiological phenotypes in systemic sclerosis-associated interstitial lung disease (SSc-ILD), namely a predominantly inflammatory and a predominantly fibrotic pattern, may capture disease heterogeneity and support therapeutic decisions. Automated quantitative CT (qCT) provides reproducible, operator-independent quantification of ILD and ILD-related features and could assist in defining such phenotypes. In parallel, several circulating biomarkers have been proposed for diagnosis, prognosis and progression in SSc-ILD, but their relationship with qCT-defined patterns is unclear. We therefore aimed to define radiological phenotypes using qCT and to explore their associations with circulating biomarkers, pulmonary function and clinical features.Material and Methods We conducted a cross-sectional study including 69 SSc-ILD patients (defined by ILD >=10% on HRCT). qCT with Lung Texture Analysis technology quantified lung% of GGO, reticulations, honeycombing, total fibrosis (reticulations + honeycombing), and total ILD. ILD patients were classified as inflammatory-predominant (GGO > fibrosis) or fibrotic-predominant (fibrosis > GGO). Serum biomarkers involved in SSc-ILD were measured by ELISA: SP-D, CCL-18, MMP-12, IL-33. Blood sampling, qCT and pulmonary function tests were performed on the same day.Results qCT identified 31 inflammatory- and 38 fibrotic-predominant phenotypes. Reticulations% was comparable between groups, whereas total ILD% was higher in the inflammatory group (11.2 vs 2.4 p 0.002). Clinical-demographic and functional characteristics are summarized in table 1, while qct parameters and biomarker profiles are reported in table 2. After adjusting for ILD% extent, SP-D resulted associated with the inflammatory predominant phenotype [OR 1.18 (95% CI 1.03 - 1.35), p 0.020]. CCL-18 correlated with total ILD% (rho 0.364, p 0.011) and fibrosis% (rho 0.343, p 0.017), IL-33 with GGO% and fibrosis% (p<0.05). MMP-12 showed higher levels in the inflammatory phenotype in univariate analysis, but this association was not independent of ILD extent. Regarding clinical features, anti-topoisomerase I antibodies were found to be more frequent in the fibrotic phenotype [OR 4.17 (95% CI 1.10 - 15.9), p 0.036]. While crude medians of DLCO% did not differ significantly between groups, after adjusting for ILD% extent, DLCO% was lower in the inflammatory phenotype [OR 0.96 (95% CI 0.93 - 0.99), p = 0.040].Conclusions Quantitative CT phenotyping in SSc-ILD defines radiological patterns with distinct biological associations rather than simply reflecting ILD extent. SP-D independently marks the inflammatory phenotype and functional restriction, while CCL-18 and IL-33 are linked to disease burden. These results highlight the potential of integrating qCT phenotyping with biomarker profiling to refine patient stratification.Abstract P.097 Table 1Demographic, clinical and functional characteristics of the study population (p-values from univariate comparisons)Abstract P.097 Table 2Automated quantitative CT parameters and circulating biomarkers (p-values from univariate comparisons)",
  "authors": [
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Davide Mohammad Reza Beigi"
    },
    {
      "affiliations": [
        "Italian National Institute of Health, Rome, Italy"
      ],
      "name": "Giuseppe Ocone"
    },
    {
      "affiliations": [
        "Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy"
      ],
      "name": "Greta Pellegrino"
    },
    {
      "affiliations": [
        "Department of Oncological, Radiological, and Pathological Sciences, Sapienza university of Rome, Rome, Italy"
      ],
      "name": "Nicholas Landini"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Ilaria Bisconti"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Francesca Romana Di Ciommo"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Marius Cadar"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Jacopo Landro"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Elena Platania"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Martina Salerno"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Beatrice De Girolamo"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Simona Truglia"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Fabrizio Conti"
    },
    {
      "affiliations": [
        "Italian National Institute of Health, Rome, Italy"
      ],
      "name": "Loredana Frasca"
    },
    {
      "affiliations": [
        "Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy"
      ],
      "name": "Valeria Riccieri"
    }
  ],
  "title": "P.097 Quantitative CT phenotyping and biomarker signatures in systemic sclerosis-associated interstitial lung disease",
  "uid": "9db9d07f-7608-5ebd-8e6d-7cc133ec5520"
}