title: [CT imaging of chronic interstitial lung diseases: from diagnosis to automated quantification].
abstract: Computed tomography is important for the diagnosis and follow-up of chronic diffuse interstitial lung diseases. Image quality has improved from each generation of scanner to the next and this continues to allow a better characterization of extent of pathology, or even the nature of the pathological process (potentially reversible inflammatory lesions compared to fibrotic lesions). The diagnostic imaging approach has evolved at the same time as technological developments. We initially thought in terms of the predominant lesions (nodular, alveolar consolidation, ground-glass opacity), and then moved to reasoning based on patterns, which are a combination of several elementary lesions (typically for the diagnosis of idiopathic pulmonary fibrosis). Nowadays, studies are focused on building models characterizing a specific disease and which combine several distinct patterns (typically for ground-glass opacity analysis). CT also allows a quantification of the extent of lung disease, which is linked to the prognosis of the disease and helps to monitor its progression. This quantification is usually based on visual criteria, the principles of which are summarized here. The development of automated quantification software could in the near future, be a support for the radiologist.
authors.affiliation: Service de radiologie, hôpital d'Avicenne, Assistance publique-Hôpitaux de Paris, 125 rue de Stalingrad, Bobigny, France.
authors.forename: M
authors.initials: M
authors.lastname: Wagner
authors.forename: K C
authors.initials: KC
authors.lastname: Chang Chien
authors.forename: O
authors.initials: O
authors.lastname: Aidara
authors.forename: C
authors.initials: C
authors.lastname: Fetita
authors.forename: M W
authors.initials: MW
authors.lastname: Brauner
authors.forename: H
authors.initials: H
authors.lastname: Nunes
authors.forename: D
authors.initials: D
authors.lastname: Valeyre
authors.forename: P Y
authors.initials: PY
authors.lastname: Brillet
mesh_terms: D003937:Diagnosis, Differential; D018450:Disease Progression; D005355:Fibrosis; D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging / Q000473:pathology; D008171:Lung Diseases / Q000150:complications / Q000175:diagnosis; D017563:Lung Diseases, Interstitial / Q000000981:diagnostic imaging* / Q000209:etiology / Q000473:pathology; D008176:Lung Volume Measurements / Q000379:methods; D008198:Lymph Nodes / Q000000981:diagnostic imaging / Q000473:pathology; D011379:Prognosis; D014057:Tomography, X-Ray Computed / Q000379:methods