The mid-infrared spectroscopy: A novel non-invasive diagnostic tool for NASH diagnosis in severe obesity.

Fiber evanescent wave spectroscopy NASH chalcogenide glass metabolic fingerprint mid-infrared (MIR) spectroscopy non-alcoholic steatohepatitis non-invasive test severely obese patients

Journal

JHEP reports : innovation in hepatology
ISSN: 2589-5559
Titre abrégé: JHEP Rep
Pays: Netherlands
ID NLM: 101761237

Informations de publication

Date de publication:
Nov 2019
Historique:
received: 08 05 2019
revised: 23 09 2019
accepted: 28 09 2019
entrez: 11 2 2020
pubmed: 11 2 2020
medline: 11 2 2020
Statut: epublish

Résumé

There is an urgent medical need to develop non-invasive tests for non-alcoholic steatohepatitis (NASH). This study evaluates the diagnostic performance of an innovative model based on mid-infrared (MIR) spectroscopy for the diagnosis of NASH. Severely obese patients who underwent a bariatric procedure at the University Hospital of Nice, France (n = 395) were prospectively recruited. The clinico-biological characteristics were measured prior to surgery. Liver biopsies were collected during the surgical procedure and assessed by a pathologist. A training group (316 patients, NASH: 16.8%) and a validation group (79 patients, NASH: 16.5%) were randomly defined. MIR spectra were acquired by fiber evanescent wave spectroscopy, using chalcogenide glass fiber optic sensors and a spectrometer. This absorption spectroscopic technique delivers a spectrum that identifies the molecular composition of a sample, defining a patient's metabolic fingerprint. The areas under the receiver operating curve (AUROC) for the diagnosis of NASH were 0.82 and 0.77 in the training and validation groups, respectively. The best threshold was 0.15, which was associated with a sensitivity of 0.75 and 0.69, and a specificity of 0.72 and 0.76. Negative predictive values of 0.94 and 0.93 and positive predictive values of 0.35 and 0.36, as well as correctly classified patient rates of 72% and 75% were obtained in the training and validation groups, respectively. A composite model using aspartate aminotransferase level, triglyceride level and waist circumference alongside the MIR spectra led to an increase in AUROC (0.88 and 0.84 for the training and validations groups, respectively). MIR spectroscopy provides good sensitivity and negative predictive values for NASH screening in patients with severe obesity. There is an urgent need for tools to non-invasively diagnose and monitor non-alcoholic steatohepatitis (NASH). This study evaluates the performance of a new tool for fast NASH diagnosis based on mid-infrared (MIR) spectroscopy. Using serum samples from severely obese patients who underwent a bariatric procedure, which enabled a concomitant liver biopsy to be performed, the MIR spectroscopy model performed well in screening patients for NASH compared to a traditional, histological diagnosis.

Identifiants

pubmed: 32039387
doi: 10.1016/j.jhepr.2019.09.005
pii: S2589-5559(19)30110-7
pmc: PMC7005664
doi:

Types de publication

Journal Article

Langues

eng

Pagination

361-368

Informations de copyright

© 2019 The Authors.

Références

J Biophotonics. 2014 Apr;7(3-4):210-21
pubmed: 24395618
Anal Bioanal Chem. 2007 Mar;387(5):1801-7
pubmed: 17237926
Anal Bioanal Chem. 2014 Apr;406(9-10):2367-76
pubmed: 24481622
Hepatology. 2016 Jul;64(1):73-84
pubmed: 26707365
Hepatology. 2005 Jun;41(6):1313-21
pubmed: 15915461
Gut. 2017 Sep;66(9):1688-1696
pubmed: 27884920
PLoS One. 2017 Oct 11;12(10):e0185997
pubmed: 29020046
Gastroenterology. 2015 Aug;149(2):379-88; quiz e15-6
pubmed: 25917783
Gastroenterology. 2006 May;130(6):1617-24
pubmed: 16697725
Transl Res. 2013 Nov;162(5):279-86
pubmed: 23920432
J Biophotonics. 2014 Apr;7(3-4):189-99
pubmed: 24395599
Gastroenterology. 2019 May;156(6):1717-1730
pubmed: 30689971
Nat Med. 2018 Jul;24(7):908-922
pubmed: 29967350
Biometrics. 1988 Sep;44(3):837-45
pubmed: 3203132
Hepatology. 2012 Nov;56(5):1751-9
pubmed: 22707395
Aliment Pharmacol Ther. 2010 Dec;32(11-12):1315-22
pubmed: 21050233
J Gastroenterol. 2016 Mar;51(3):214-21
pubmed: 26112122
J Hepatol. 2016 Sep;65(3):570-8
pubmed: 27151181
Gastroenterology. 2009 Aug;137(2):532-40
pubmed: 19409898
J Biophotonics. 2014 Apr;7(3-4):222-31
pubmed: 24639420
Gastroenterology. 2015 Aug;149(2):389-97.e10
pubmed: 25935633
Circulation. 2009 Oct 20;120(16):1640-5
pubmed: 19805654
J Biomed Opt. 2009 Sep-Oct;14(5):054033
pubmed: 19895135
Appl Spectrosc. 2006 Jun;60(6):584-91
pubmed: 16808858
J Hepatol. 2013 May;58(5):1007-19
pubmed: 23183525
J Hepatol. 2012 Nov;57(5):1090-6
pubmed: 22820478
Gastroenterology. 2018 Aug;155(2):443-457.e17
pubmed: 29733831
Lancet. 2014 Aug 30;384(9945):766-81
pubmed: 24880830
Ann Intern Med. 1991 Dec 15;115(12):956-61
pubmed: 1952493
J Hepatol. 2016 Aug;65(2):425-43
pubmed: 27091791
J Hepatol. 2017 Oct;67(4):829-846
pubmed: 28545937
Am J Gastroenterol. 1999 Sep;94(9):2467-74
pubmed: 10484010
J Biophotonics. 2013 Jan;6(1):88-100
pubmed: 23225612
Chem Soc Rev. 2016 Apr 7;45(7):1803-18
pubmed: 26612430
Gastroenterology. 2019 Apr;156(5):1264-1281.e4
pubmed: 30660725
J Hepatol. 2011 Sep;55(3):660-665
pubmed: 21238518
J Biophotonics. 2014 Apr;7(3-4):241-53
pubmed: 24677747
Transl Res. 2008 Sep;152(3):103-12
pubmed: 18774539

Auteurs

Rodolphe Anty (R)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Marie Morvan (M)

University of Rennes, CNRS, IRMAR - UMR, 6625, Rennes, France.

Maëna Le Corvec (M)

DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes.

Clémence M Canivet (CM)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Stéphanie Patouraux (S)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Jean Gugenheim (J)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Stéphanie Bonnafous (S)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Béatrice Bailly-Maitre (B)

Université Côte d'Azur, INSERM, U1065, C3M, France.

Olivier Sire (O)

IRDL UMR CNRS 6027, Vannes.

Hugues Tariel (H)

DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes.

Jérôme Bernard (J)

DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes.

Thierry Piche (T)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Olivier Loréal (O)

INSERM, Univ Rennes, INRA, Nutrition Metabolisms and Cancer (NuMeCan), UMR-1241, Rennes, France.

Judith Aron-Wisnewsky (J)

Sorbonne Université/Inserm Unité UMRS NutriOmics, Assistance publique hôpitaux de Paris, service de Nutrition, Paris, France.

Karine Clément (K)

Sorbonne Université/Inserm Unité UMRS NutriOmics, Assistance publique hôpitaux de Paris, service de Nutrition, Paris, France.

Albert Tran (A)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Antonio Iannelli (A)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Philippe Gual (P)

Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.

Classifications MeSH