title: Diagnostic accuracy of controlled attenuation parameter measured by transient elastography for the non-invasive assessment of liver steatosis: a prospective study.
abstract: OBJECTIVE
  A novel non-invasive tool based on the evaluation of ultrasound attenuation using transient elastography (TE) has been developed, called controlled attenuation parameter (CAP). We aim to establish the histopathological parameters that significantly influence CAP, the cutoff values and their performance in predicting each steatosis grade on a group of biopsied patients with chronic liver diseases (CLD) from Romania.
  
  
  METHODS
  We prospectively analyzed 201 consecutive CLD patients who underwent CAP measurements using TE. Steatosis, liver fibrosis and necroinflammatory activity were staged and graded during the pathological analysis of bioptic specimens. Univariate and multivariate regression analyses were applied to identify the variables correlated with CAP values. The diagnostic performance of CAP for steatosis prediction was assessed using an AUC analysis.
  
  
  RESULTS
  Among the histopathological factors correlating with CAP, the multivariate analysis found steatosis as the only factor independently influencing CAP values (p < 0.001). Maximal diagnostic accuracy (DA) was obtained for the prediction of ≥ 34-66% (S2) fatty load and of 67-100% (S3) fatty load (82.06%, respectively 81.59%) while, for the prediction of ≥ 11-33% (S1) fatty load, DA reached only 76.11%. The negative predictive value for the exclusion of ≥ S2 and S3 was 93.5% and 98.7%, respectively. AUCs calculated between each two steatosis grades were: 0.772 (S0 vs S1), 0.874 (S0 vs S2), 0.904 (S0 vs S3), 0.659 (S1 vs S2), 0.777 (S1 vs S3), and 0.665 (S2 vs S3).
  
  
  CONCLUSIONS
  Steatosis is the only histopathological factor independently influencing CAP. Maximal DA could be obtained for the prediction of ≥ S2 and S3 (82.06% and 81.59%), while for the prediction of S1, the accuracy reached only 76.11%.
authors.affiliation: Department of Medical Imaging, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania. monica.lupsor@umfcluj.ro.
authors.forename: Monica
authors.initials: M
authors.lastname: Lupșor-Platon
authors.affiliation: Department of Medical Imaging, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Diana
authors.initials: D
authors.lastname: Feier
authors.affiliation: Department of Hepatology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Horia
authors.initials: H
authors.lastname: Stefănescu
authors.affiliation: Department of Medical Imaging, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Attila
authors.initials: A
authors.lastname: Tamas
authors.affiliation: Department of Pathology, Prof. Dr. Octavian Fodor Regional Institute of Gastroenterology and Hepatology; Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Emil
authors.initials: E
authors.lastname: Botan
authors.affiliation: Department of Hepatology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Zeno
authors.initials: Z
authors.lastname: Sparchez
authors.affiliation: Department of Medical Imaging, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Anca
authors.initials: A
authors.lastname: Maniu
authors.affiliation: Department of Medical Imaging, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Radu
authors.initials: R
authors.lastname: Badea
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D001706:Biopsy; D016009:Chi-Square Distribution; D002908:Chronic Disease; D054459:Elasticity Imaging Techniques / Q000379:methods*; D005234:Fatty Liver / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D006801:Humans; D008099:Liver / Q000000981:diagnostic imaging* / Q000473:pathology; D008103:Liver Cirrhosis / Q000000981:diagnostic imaging; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012383:Romania; D012720:Severity of Illness Index; D055815:Young Adult