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Quantitative chest tomography indexes are related to disease activity in systemic sclerosis: results from a cross-sectional study
D. Sambataro1, G. Sambataro2, S. Battisti3, S. Palmucci4, M. Colaci5, L. Malatino6, M. Orlandi7, A. Ariani8
- Artroreuma srl, Catania, and Department of Clinical and Experimental Rheumatology, University of Catania, Italy. domenico.sambataro@artroreuma.it
- Artroreuma srl, Catania, and Department of Clinical and Experimental Rheumatology, University of Catania, Italy.
- Department of Radiology, Maurizio Bufalini Hospital, Cesena, Italy.
- Department of Medical, Surgical Sciences and Advanced Technologies, University of Catania, Italy.
- Department of Clinical and Experimental Rheumatology, University of Catania, Italy.
- Department of Clinical and Experimental Rheumatology, University of Catania, Italy.
- Department of Experimental and Clinical Medicine, University of Florence, Italy.
- Department of Medicine, Internal Medicine and Rheumatology, Azienda Ospedaliero-Universitaria di Parma, Italy.
CER15384
2022 Vol.40, N°10
PI 1970, PF 1976
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PMID: 36189912 [PubMed]
Received: 01/12/2021
Accepted : 26/05/2022
In Press: 03/10/2022
Published: 17/10/2022
Abstract
OBJECTIVES:
The aim of this study is to verify if there are correlations between quantitative chest tomography (QCT) indexes and disease activity (DA) in a cohort of patients with systemic sclerosis (SSc).
METHODS:
SSc patients were assessed for DA and underwent high resolution chest tomography (CT). CT images were analysed with an operator-independent algorithm extracting the QCT indexes. DA assessment was conducted according to the EUSTAR index, where a score ≥2.5 indicates high DA (hDA). Correlations between clinical data and QCT indexes were investigated with the Spearman’s test. The Mann-Whitney test assessed the distribution of the QCT indexes among the groups. Receiver operating characteristics (ROC) curve and linear regression analysis were conducted in order to identify the best cut-off value and contribution for each QCT index in assessing hDA in SSc patients.
RESULTS:
Sixty patients (52 females, mean age 53.2 years, mean disease duration 5.3 years) were enrolled. A significant difference was found in QCT indexes distribution between patients with hDA and those with low DA. A mild strength correlation between QCT indexes and DA was observed. Once performed ROC curves and linear regression, Skewness on parenchymal lung <1.85 gave a significant contribution to the model in identifying subjects with hDA (p<0.001), showing sensitivity 79.5%, specificity 68.7%, and accuracy 76.6%.
CONCLUSIONS:
QCT indexes correlate with SSc DA. These data introduce new possibilities for QCT application in clinical practice, especially in patient’s follow-up. Moreover, QCT could be implemented in a new SSc DA score based on operator-independent parameters.
