Optimization of Point-Shear Wave Elastography by Skin-to-Liver Distance to Assess Liver Fibrosis in Patients Undergoing Bariatric Surgery.

NAFLD abdominal wall abdominal wall thickness bariatric surgery liver biopsy liver elastography liver fibrosis liver histology non-alcoholic fatty liver disease non-alcoholic steatohepatitis

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
07 Oct 2020
Historique:
received: 07 09 2020
revised: 01 10 2020
accepted: 03 10 2020
entrez: 10 10 2020
pubmed: 11 10 2020
medline: 11 10 2020
Statut: epublish

Résumé

Obesity is a primary limiting factor in liver stiffness measurement (LSM). The impact of obesity has always been evaluated in terms of body mass index (BMI), without studying the effects of skin-to-liver distance (SLD) on LSM. We studied the impact of SLD on LSM in a cohort of obese patients undergoing bariatric surgery and intra-operatory liver biopsy. 299 patients underwent LSM by point-shear wave elastography (ElastPQ protocol), with two different ultrasound machines. SLD was measured as the distance between the skin and the liver capsule, perpendicular to where the region of interest (ROI) was positioned. We used the following arbitrary cut-offs: <5.7 kPa, F0-1; 5.7-7.99 kPa, F2; ≥8 kPa, F3-4. We developed two logistic regression models using elastography-histology agreement (EHA) as the dependent variable and SLD as the independent variable. The model based on the second machine showed strongly more performant discriminative and calibration metrics (AIC 38.5, BIC 44.2, Nagelkerke Pseudo-R2 0.894, AUROC 0.90). The SLD cut-off value of 34.5 mm allowed a correct EHA with a sensitivity of 100%, a specificity of 93%, negative predictive value of 100%, positive predictive value of 87%, an accuracy of 96%, and positive likelihood ratio of 3.56. The impact of SLD is machine-dependent and should be taken into consideration when interpreting LSM. We believe that our findings may serve as a reference point for appropriate fibrosis stratification by liver elastography in obese patients.

Sections du résumé

BACKGROUND BACKGROUND
Obesity is a primary limiting factor in liver stiffness measurement (LSM). The impact of obesity has always been evaluated in terms of body mass index (BMI), without studying the effects of skin-to-liver distance (SLD) on LSM. We studied the impact of SLD on LSM in a cohort of obese patients undergoing bariatric surgery and intra-operatory liver biopsy.
MATERIALS AND METHODS METHODS
299 patients underwent LSM by point-shear wave elastography (ElastPQ protocol), with two different ultrasound machines. SLD was measured as the distance between the skin and the liver capsule, perpendicular to where the region of interest (ROI) was positioned. We used the following arbitrary cut-offs: <5.7 kPa, F0-1; 5.7-7.99 kPa, F2; ≥8 kPa, F3-4.
RESULTS RESULTS
We developed two logistic regression models using elastography-histology agreement (EHA) as the dependent variable and SLD as the independent variable. The model based on the second machine showed strongly more performant discriminative and calibration metrics (AIC 38.5, BIC 44.2, Nagelkerke Pseudo-R2 0.894, AUROC 0.90). The SLD cut-off value of 34.5 mm allowed a correct EHA with a sensitivity of 100%, a specificity of 93%, negative predictive value of 100%, positive predictive value of 87%, an accuracy of 96%, and positive likelihood ratio of 3.56.
CONCLUSION CONCLUSIONS
The impact of SLD is machine-dependent and should be taken into consideration when interpreting LSM. We believe that our findings may serve as a reference point for appropriate fibrosis stratification by liver elastography in obese patients.

Identifiants

pubmed: 33036418
pii: diagnostics10100795
doi: 10.3390/diagnostics10100795
pmc: PMC7601552
pii:
doi:

Types de publication

Journal Article

Langues

eng

Références

Hepatology. 2005 Jun;41(6):1313-21
pubmed: 15915461
Hepatology. 2016 Jun;63(6):1817-27
pubmed: 26659452
Korean J Radiol. 2016 Sep-Oct;17(5):750-7
pubmed: 27587964
Proc Natl Acad Sci U S A. 2005 Mar 15;102(11):4120-5
pubmed: 15738389
Theranostics. 2017 Mar 7;7(5):1303-1329
pubmed: 28435467
Clin Gastroenterol Hepatol. 2007 Nov;5(11):1329-32
pubmed: 17702661
PLoS One. 2015 Jul 01;10(7):e0127782
pubmed: 26131717
Hepatology. 1994 Jul;20(1 Pt 1):15-20
pubmed: 8020885
Ann Hepatol. 2020 Aug 20;:
pubmed: 32828852
J Clin Ultrasound. 1993 Sep;21(7):423-9
pubmed: 8370802
Am J Gastroenterol. 2007 Dec;102(12):2708-15
pubmed: 17894848
Hepatology. 2009 Jun;49(6):1954-61
pubmed: 19434742
J Gastroenterol Hepatol. 2011 Mar;26(3):492-500
pubmed: 21332545
Ann Hepatol. 2019 Sep - Oct;18(5):736-741
pubmed: 31054978
World J Gastroenterol. 2019 Oct 28;25(40):6053-6062
pubmed: 31686762
Front Endocrinol (Lausanne). 2014 Oct 27;5:164
pubmed: 25386164
PLoS One. 2015 Nov 03;10(11):e0141649
pubmed: 26528818
Diagnostics (Basel). 2020 Aug 21;10(9):
pubmed: 32825763
J Hepatol. 2006 Oct;45(4):600-6
pubmed: 16899321
J Ultrasound. 2020 Apr 17;:
pubmed: 32304009
Am J Physiol Gastrointest Liver Physiol. 2020 May 1;318(5):G889-G906
pubmed: 32146836
N Engl J Med. ;376(15):1490-1
pubmed: 28406282
Radiology. 1983 Sep;148(3):839-43
pubmed: 6878708
Lancet. 1986 Mar 8;1(8480):523-5
pubmed: 2869260
Hepatology. 2000 Sep;32(3):477-81
pubmed: 10960438
Liver Int. 2010 Aug;30(7):1043-8
pubmed: 20492500
Hepatology. 2012 Jan;55(1):199-208
pubmed: 21898479
Med Ultrason. 2014 Dec;16(4):309-14
pubmed: 25463883
Ann Hepatol. 2020 Jul - Aug;19(4):380-387
pubmed: 32451205
BMJ Open. 2018 Aug 23;8(8):e021787
pubmed: 30139901
Pharm Stat. 2010 Apr-Jun;9(2):125-32
pubmed: 19507134
PLoS One. 2018 Jan 2;13(1):e0189671
pubmed: 29293527
Stat Med. 2013 Jun 15;32(13):2235-49
pubmed: 23037691
Microorganisms. 2020 Feb 29;8(3):
pubmed: 32121404
J Mol Med (Berl). 2009 Jul;87(7):679-95
pubmed: 19352614
Ann Hepatol. 2020 Jan - Feb;19(1):53-61
pubmed: 31740162
Ultrasound Med Biol. 2019 Oct;45(10):2697-2703
pubmed: 31326160

Auteurs

Mauro Giuffrè (M)

Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy.
Italian Liver Foundation, 34149 Trieste, Italy.

Michela Giuricin (M)

General Surgery Clinic, Azienda Sanitaria Universitaria Giuliano-Isontina, 34149 Trieste, Italy.

Deborah Bonazza (D)

Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy.
Department of Pathology, Azienda Sanitaria Universitaria Giuliano-Isontina, Cattinara Hospital, 34149 Trieste, Italy.

Natalia Rosso (N)

Italian Liver Foundation, 34149 Trieste, Italy.

Pablo José Giraudi (PJ)

Italian Liver Foundation, 34149 Trieste, Italy.

Flora Masutti (F)

Liver Clinic, Azienda Sanitaria Universitaria Giuliano-Isontina, Cattinara Hospital, 34149 Trieste, Italy.

Stefano Palmucci (S)

Department of Medical Surgical Sciences and Advanced Technologies G.F. Ingrassia University of Catania, 95124 Catania, Italy.

Antonio Basile (A)

Department of Medical Surgical Sciences and Advanced Technologies G.F. Ingrassia University of Catania, 95124 Catania, Italy.

Fabrizio Zanconati (F)

Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy.
Department of Pathology, Azienda Sanitaria Universitaria Giuliano-Isontina, Cattinara Hospital, 34149 Trieste, Italy.

Nicolò de Manzini (N)

Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy.
General Surgery Clinic, Azienda Sanitaria Universitaria Giuliano-Isontina, 34149 Trieste, Italy.

Claudio Tiribelli (C)

Italian Liver Foundation, 34149 Trieste, Italy.

Silvia Palmisano (S)

Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy.
General Surgery Clinic, Azienda Sanitaria Universitaria Giuliano-Isontina, 34149 Trieste, Italy.

Lory Saveria Crocè (LS)

Department of Medical, Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy.
Italian Liver Foundation, 34149 Trieste, Italy.
Liver Clinic, Azienda Sanitaria Universitaria Giuliano-Isontina, Cattinara Hospital, 34149 Trieste, Italy.

Classifications MeSH