Introduction: Interstitial lung disease (ILD) is the main cause of mortality in systemic sclerosis (SSc). Methods stratifying the prognosis of SSc-ILD are lacking in clinical practice. The quantification of ILD provides a paramount contribution to establishing prognosis and may assist in tailored treatment. Areas covered: In this review, we provide an overview of the main quantitative methods implemented in SSc-ILD (semi-quantitative assessment, volumetric, parametric, and textural quantitative evaluation). Even if they are different one from another, all of them have a prognostic value as they predict mortality as well as radiological and functional worsening. Expert opinion: Semi-quantitative rating of CT images (sQCT) is now the gold standard for SSc-ILD patient assessment and stratification. Furthermore, there are many software available for quantification objective quantification, and classification of ILD. These tools are barely burdened by inter- intra-reader variability and they are suitable for both trial and clinical application. It is therefore expected that in the next few years a better stratification of patients will be achieved by these tools, allowing to recognize patients with the worst prognosis. This, together with the availability of different treatments for pulmonary fibrosis, makes it possible to develop precision medicine also in the field of SSc-ILD.

Using quantitative computed tomography to predict mortality in patients with interstitial lung disease related to systemic sclerosis: implications for personalized medicine / Ariani, A.; Sverzellati, N.; Becciolni, A.; Milanese, G.; Silva, M.. - In: EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT. - ISSN 2380-8993. - 6:1(2021), pp. 31-40. [10.1080/23808993.2021.1858053]

Using quantitative computed tomography to predict mortality in patients with interstitial lung disease related to systemic sclerosis: implications for personalized medicine

Sverzellati N.
Writing – Review & Editing
;
Milanese G.
Writing – Review & Editing
;
Silva M.
Writing – Original Draft Preparation
2021-01-01

Abstract

Introduction: Interstitial lung disease (ILD) is the main cause of mortality in systemic sclerosis (SSc). Methods stratifying the prognosis of SSc-ILD are lacking in clinical practice. The quantification of ILD provides a paramount contribution to establishing prognosis and may assist in tailored treatment. Areas covered: In this review, we provide an overview of the main quantitative methods implemented in SSc-ILD (semi-quantitative assessment, volumetric, parametric, and textural quantitative evaluation). Even if they are different one from another, all of them have a prognostic value as they predict mortality as well as radiological and functional worsening. Expert opinion: Semi-quantitative rating of CT images (sQCT) is now the gold standard for SSc-ILD patient assessment and stratification. Furthermore, there are many software available for quantification objective quantification, and classification of ILD. These tools are barely burdened by inter- intra-reader variability and they are suitable for both trial and clinical application. It is therefore expected that in the next few years a better stratification of patients will be achieved by these tools, allowing to recognize patients with the worst prognosis. This, together with the availability of different treatments for pulmonary fibrosis, makes it possible to develop precision medicine also in the field of SSc-ILD.
2021
Using quantitative computed tomography to predict mortality in patients with interstitial lung disease related to systemic sclerosis: implications for personalized medicine / Ariani, A.; Sverzellati, N.; Becciolni, A.; Milanese, G.; Silva, M.. - In: EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT. - ISSN 2380-8993. - 6:1(2021), pp. 31-40. [10.1080/23808993.2021.1858053]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2887371
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact