title: Perfusion- and pattern-based quantitative CT indexes using contrast-enhanced dual-energy computed tomography in diffuse interstitial lung disease: relationships with physiologic impairment and prediction of prognosis.
abstract: OBJECTIVE
  To evaluate automated texture-based segmentation of dual-energy CT (DECT) images in diffuse interstitial lung disease (DILD) patients and prognostic stratification by overlapping morphologic and perfusion information of total lung.
  
  
  METHODS
  Suspected DILD patients scheduled for surgical biopsy were prospectively included. Texture patterns included ground-glass opacity (GGO), reticulation and consolidation. Pattern- and perfusion-based CT measurements were assessed to extract quantitative parameters. Accuracy of texture-based segmentation was analysed. Correlations between CT measurements and pulmonary function test or 6-minute walk test (6MWT) were calculated. Parameters of idiopathic pulmonary fibrosis/usual interstitial pneumonia (IPF/UIP) and non-IPF/UIP were compared. Survival analysis was performed.
  
  
  RESULTS
  Overall accuracy was 90.47% for whole lung segmentation. Correlations between mean iodine values of total lung, 50-97.5th (%) attenuation and forced vital capacity or 6MWT were significant. Volume of GGO, reticulation and consolidation had significant correlation with DLco or SpO2 on 6MWT. Significant differences were noted between IPF/UIP and non-IPF/UIP in 6MWT distance, mean iodine value of total lung, 25-75th (%) attenuation and entropy. IPF/UIP diagnosis, GGO ratio, DILD extent, 25-75th (%) attenuation and SpO2 on 6MWT showed significant correlations with survival.
  
  
  CONCLUSIONS
  DECT combined with pattern analysis is useful for analysing DILD and predicting survival by provision of morphology and enhancement.
  
  
  CONCLUSIONS
  • Dual-energy CT (DECT) produces morphologic and parenchymal enhancement information. • Automated lung segmentation enables analysis of disease extent and severity. • This prospective study showed value of DECT in DILD patients. • Parameters on DECT enable characterization and survival prediction of DILD.
authors.affiliation: Department of Radiology (J.W.M.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
authors.forename: Jung Won
authors.initials: JW
authors.lastname: Moon
authors.affiliation: Department of Radiology (J.P.B., N.K., Y.C., J.B.S.), Asan Medical Center, University of Ulsan College of Medicine, #88, Olympic-Ro, 43-gil, Songpa-gu, Seoul, 138-736, Korea.
authors.forename: Jang Pyo
authors.initials: JP
authors.lastname: Bae
authors.affiliation: Department of Radiology and Center for Imaging Science (H.Y.L., K.S.L.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul, 135-710, Korea. hoyunlee96@gmail.com.
authors.forename: Ho Yun
authors.initials: HY
authors.lastname: Lee
authors.affiliation: Department of Radiology (J.P.B., N.K., Y.C., J.B.S.), Asan Medical Center, University of Ulsan College of Medicine, #88, Olympic-Ro, 43-gil, Songpa-gu, Seoul, 138-736, Korea. namkugkim@gmail.com.
authors.forename: Namkug
authors.initials: N
authors.lastname: Kim
authors.affiliation: Department of Pulmonology (M.P.C, H.Y.P), Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
authors.forename: Man Pyo
authors.initials: MP
authors.lastname: Chung
authors.affiliation: Department of Pulmonology (M.P.C, H.Y.P), Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
authors.forename: Hye Yun
authors.initials: HY
authors.lastname: Park
authors.affiliation: Department of Radiology (J.P.B., N.K., Y.C., J.B.S.), Asan Medical Center, University of Ulsan College of Medicine, #88, Olympic-Ro, 43-gil, Songpa-gu, Seoul, 138-736, Korea.
authors.forename: Yongjun
authors.initials: Y
authors.lastname: Chang
authors.affiliation: Department of Radiology (J.P.B., N.K., Y.C., J.B.S.), Asan Medical Center, University of Ulsan College of Medicine, #88, Olympic-Ro, 43-gil, Songpa-gu, Seoul, 138-736, Korea.
authors.forename: Joon Beom
authors.initials: JB
authors.lastname: Seo
authors.affiliation: Department of Radiology and Center for Imaging Science (H.Y.L., K.S.L.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul, 135-710, Korea.
authors.forename: Kyung Soo
authors.initials: KS
authors.lastname: Lee
mesh_terms: D000328:Adult; D000368:Aged; D003287:Contrast Media; D005260:Female; D006801:Humans; D007455:Iodine; D008168:Lung / Q000000981:diagnostic imaging / Q000503:physiopathology; D017563:Lung Diseases, Interstitial / Q000000981:diagnostic imaging* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D011856:Radiographic Image Enhancement; D012129:Respiratory Function Tests; D016019:Survival Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; D007455:Iodine
keywords: DECT; DILD; IPF/UIP; Perfusion- or pattern-based CT quantification parameters; Survival