CT predicts liver fibrosis: Prospective evaluation of morphology- and attenuation-based quantitative scores in routine portal venous abdominal scans.

Obmann, Verena Carola; Mertineit, Nando; Berzigotti, Annalisa; Marx, Christina Lynn; Ebner, Lukas; Kreis, Roland; Vermathen, Peter; Heverhagen, Johannes; Christe, Andreas; Huber, Adrian Thomas (2018). CT predicts liver fibrosis: Prospective evaluation of morphology- and attenuation-based quantitative scores in routine portal venous abdominal scans. PLoS ONE, 13(7), e0199611. Public Library of Science 10.1371/journal.pone.0199611

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OBJECTIVES

Our aim was to prospectively determine whether quantitative computed tomography (CT) scores, consisting of simplified indices for liver remodeling and attenuation, may predict liver fibrosis in abdominal CT scans.

MATERIALS AND METHODS

This cross-sectional, prospective study was approved by the local IRB (Kantonale Ethikkommission Bern). Written informed consent was given from all patients undergoing study-MR exams. Between 02/16 and 05/17, four different liver fibrosis scores (CRL-R = caudate-right-lobe ratio, LIMV-, LIMA- and LIMVA-fibrosis score, with "LIM" for liver imaging morphology, "V" for liver vein diameter and "A" for attenuation) were calculated in 1534 consecutive abdominal CT scans, excluding patients with prior liver surgery and liver metastasis. Patients were invited to undergo magnetic resonance (MR) elastography as the non-invasive gold standard to evaluate liver fibrosis. MR elastography shear modulus ≥2.8 kPa was defined as beginning liver fibrosis, while ≥3.5 kPa was defined as significant liver fibrosis (which would correspond to fibrosis stage F2 or higher in histology). Cutoff values, sensitivities and specificities obtained from the receiver operating characteristics (ROC) analysis were then calculated in 141 patients who followed the invitation for MR elastography. To mitigate selection bias, prevalence was estimated in the screened total population (n = 1534) by applying the cutoff values with sensitivities and specificities calculated in the MR elastography sub-group. Positive predictive values (PPV) and negative predictive values (NPV) were then calculated.

RESULTS

Fibrosis scores including liver vein attenuation LIMA-FS and LIMVA-FS showed higher areas under the ROC curves (0.96-0.97) than CRL-R (0.82) to detect significant liver fibrosis, while LIMV-FS showed good performance as well (0.92). The prevalence-corrected PPV were 29% for CRL-R, 70% for LIMV-FS, 76% for LIMA-FS and 82% for LIMVA-FS.

CONCLUSION

CT fibrosis scores, notably LIMA-FS and LIMVA-FS, may predict significant liver fibrosis on routine abdominal CT scans.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic, Interventional and Paediatric Radiology > DCR Magnetic Resonance Spectroscopy and Methodology (AMSM)
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic, Interventional and Paediatric Radiology
04 Faculty of Medicine > Department of Gastro-intestinal, Liver and Lung Disorders (DMLL) > Clinic of Visceral Surgery and Medicine > Hepatology
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR)
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Health and Nutrition
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Hepatologie
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Hepatologie

04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Radiologie
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Radiologie

UniBE Contributor:

Obmann, Verena Carola, Mertineit, Nando, Berzigotti, Annalisa, Marx, Christina Lynn, Ebner, Lukas, Kreis, Roland, Vermathen, Peter, Heverhagen, Johannes, Christe, Andreas, Huber, Adrian Thomas

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1932-6203

Publisher:

Public Library of Science

Language:

English

Submitter:

Nicole Rösch

Date Deposited:

19 Jul 2018 10:16

Last Modified:

05 Dec 2022 15:16

Publisher DOI:

10.1371/journal.pone.0199611

PubMed ID:

29990333

BORIS DOI:

10.7892/boris.118747

URI:

https://boris.unibe.ch/id/eprint/118747

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