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Transferring CT image biomarkers from fibrosing idiopathic interstitial pneumonia to COVID-19 analysis

  • Institut Polytechnique de Paris
  • University 'Politehnica' of Bucharest
  • University Paris 13
  • APHP

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

3 Citations (Scopus)

Résumé

Fibrosing idiopathic interstitial pneumonia (fIIP) is a subclass of interstitial lung diseases, which leads to fibrosis in a continuous and irreversible process of lung function decay. Patients with fIIP require regular quantitative follow-up with CT and several image biomarkers have already been proposed to grade the pathology severity and try to predict the evolution. Among them, we cite the spatial extent of the diseased lung parenchyma and airway and vascular remodeling markers. COVID-19 (Cov-19) presents several similarities with fIIP and this condition is moreover suspected to evolve to fIIP in 10-30% of severe cases. Note also that the main difference between Cov-19 and fIIP is the presence of peripheral ground glass opacities and less or no amount of fibrosis in the lung, as well as the absence of airway remodeling. This paper proposes a preliminary study to investigate how existing image markers for fIIP may apply to Cov-19 phenotyping, namely texture classification and vascular remodeling. In addition, since for some patients, the fIIP/Cov-19 follow-up protocol imposes CT acquisitions at both full inspiration and full expiration, this information could also be exploited to extract additional knowledge for each individual case. We hypothesize that taking into account the two respiratory phases to analyze breathing parameters through interpolation and registration might contribute to a better phenotyping of the pathology. This preliminary study, conducted on a reduced number of patients (eight Cov-19 of different severity degrees, two fIIP patients and one control), shows a great potential of the selected CT image markers.

langue originaleAnglais
titreMedical Imaging 2021
Sous-titreComputer-Aided Diagnosis
rédacteurs en chefMaciej A. Mazurowski, Karen Drukker
EditeurSPIE
ISBN (Electronique)9781510640238
Les DOIs
étatPublié - 1 janv. 2021
EvénementMedical Imaging 2021: Computer-Aided Diagnosis - Virtual, Online, États-Unis
Durée: 15 févr. 202119 févr. 2021

Série de publications

NomProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11597
ISSN (imprimé)1605-7422

Une conférence

Une conférenceMedical Imaging 2021: Computer-Aided Diagnosis
Pays/TerritoireÉtats-Unis
La villeVirtual, Online
période15/02/2119/02/21

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