The mid-infrared spectroscopy: A novel non-invasive diagnostic tool for NASH diagnosis in severe obesity
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 procedu...
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| Veröffentlicht in: | JHEP reports Jg. 1; H. 5; S. 361 - 368 |
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.11.2019
Elsevier |
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| ISSN: | 2589-5559, 2589-5559 |
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| Abstract | 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.
[Display omitted]
•There is no validated non-invasive diagnostic tool for NASH in routine care.•NASH follow-up requires a non-invasive diagnostic method.•Using a simple drop of serum, the mid-infrared spectrum captures a patient’s metabolic fingerprint.•A model based on mid-infrared spectroscopy provides efficient NASH screening for patients with severe obesity. |
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| AbstractList | Background & AimsThere 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. MethodsSeverely 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. ResultsThe 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). ConclusionsMIR spectroscopy provides good sensitivity and negative predictive values for NASH screening in patients with severe obesity. Lay summaryThere 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. Background & Aims: 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. Methods: 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. Results: 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). Conclusions: MIR spectroscopy provides good sensitivity and negative predictive values for NASH screening in patients with severe obesity. Lay summary: 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. Keywords: Fiber evanescent wave spectroscopy, mid-infrared (MIR) spectroscopy, chalcogenide glass, non-alcoholic steatohepatitis, NASH, severely obese patients, non-invasive test, metabolic fingerprint 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. [Display omitted] •There is no validated non-invasive diagnostic tool for NASH in routine care.•NASH follow-up requires a non-invasive diagnostic method.•Using a simple drop of serum, the mid-infrared spectrum captures a patient’s metabolic fingerprint.•A model based on mid-infrared spectroscopy provides efficient NASH screening for patients with severe obesity. 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. Background & Aims: 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.Methods: 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.Results: 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).Conclusions: MIR spectroscopy provides good sensitivity and negative predictive values for NASH screening in patients with severe obesity. Unlabelled Image • There is no validated non-invasive diagnostic tool for NASH in routine care. • NASH follow-up requires a non-invasive diagnostic method. • Using a simple drop of serum, the mid-infrared spectrum captures a patient’s metabolic fingerprint. • A model based on mid-infrared spectroscopy provides efficient NASH screening for patients with severe obesity. 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.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.METHODSSeverely 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).RESULTSThe 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.CONCLUSIONSMIR 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.LAY SUMMARYThere 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. |
| Author | Patouraux, Stéphanie Gugenheim, Jean Bonnafous, Stéphanie Bernard, Jérôme Anty, Rodolphe Clément, Karine Sire, Olivier Le Corvec, Maëna Bailly-Maitre, Béatrice Loréal, Olivier Piche, Thierry Tran, Albert Iannelli, Antonio Tariel, Hugues Aron-Wisnewsky, Judith Canivet, Clémence M Gual, Philippe Morvan, Marie |
| AuthorAffiliation | 3 DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes 2 University of Rennes, CNRS, IRMAR - UMR, 6625, Rennes, France 7 Sorbonne Université/Inserm Unité UMRS NutriOmics, Assistance publique hôpitaux de Paris, service de Nutrition, Paris, France 5 IRDL UMR CNRS 6027, Vannes 4 Université Côte d’Azur, INSERM, U1065, C3M, France 1 Université Côte d’Azur, CHU, INSERM, U1065, C3M, France 6 INSERM, Univ Rennes, INRA, Nutrition Metabolisms and Cancer (NuMeCan), UMR-1241, Rennes, France |
| AuthorAffiliation_xml | – name: 4 Université Côte d’Azur, INSERM, U1065, C3M, France – name: 6 INSERM, Univ Rennes, INRA, Nutrition Metabolisms and Cancer (NuMeCan), UMR-1241, Rennes, France – name: 1 Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – name: 2 University of Rennes, CNRS, IRMAR - UMR, 6625, Rennes, France – name: 5 IRDL UMR CNRS 6027, Vannes – name: 3 DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes – name: 7 Sorbonne Université/Inserm Unité UMRS NutriOmics, Assistance publique hôpitaux de Paris, service de Nutrition, Paris, France |
| Author_xml | – sequence: 1 givenname: Rodolphe surname: Anty fullname: Anty, Rodolphe email: anty.r@chu-nice.fr organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 2 givenname: Marie surname: Morvan fullname: Morvan, Marie organization: University of Rennes, CNRS, IRMAR - UMR, 6625, Rennes, France – sequence: 3 givenname: Maëna surname: Le Corvec fullname: Le Corvec, Maëna organization: DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes – sequence: 4 givenname: Clémence M surname: Canivet fullname: Canivet, Clémence M organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 5 givenname: Stéphanie surname: Patouraux fullname: Patouraux, Stéphanie organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 6 givenname: Jean surname: Gugenheim fullname: Gugenheim, Jean organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 7 givenname: Stéphanie surname: Bonnafous fullname: Bonnafous, Stéphanie organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 8 givenname: Béatrice surname: Bailly-Maitre fullname: Bailly-Maitre, Béatrice organization: Université Côte d’Azur, INSERM, U1065, C3M, France – sequence: 9 givenname: Olivier surname: Sire fullname: Sire, Olivier organization: IRDL UMR CNRS 6027, Vannes – sequence: 10 givenname: Hugues surname: Tariel fullname: Tariel, Hugues organization: DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes – sequence: 11 givenname: Jérôme surname: Bernard fullname: Bernard, Jérôme organization: DIAFIR, Avenue Chardonnet, Parc Lorans 26 J, Rennes – sequence: 12 givenname: Thierry surname: Piche fullname: Piche, Thierry organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 13 givenname: Olivier surname: Loréal fullname: Loréal, Olivier organization: INSERM, Univ Rennes, INRA, Nutrition Metabolisms and Cancer (NuMeCan), UMR-1241, Rennes, France – sequence: 14 givenname: Judith surname: Aron-Wisnewsky fullname: Aron-Wisnewsky, Judith organization: Sorbonne Université/Inserm Unité UMRS NutriOmics, Assistance publique hôpitaux de Paris, service de Nutrition, Paris, France – sequence: 15 givenname: Karine surname: Clément fullname: Clément, Karine organization: Sorbonne Université/Inserm Unité UMRS NutriOmics, Assistance publique hôpitaux de Paris, service de Nutrition, Paris, France – sequence: 16 givenname: Albert surname: Tran fullname: Tran, Albert organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 17 givenname: Antonio surname: Iannelli fullname: Iannelli, Antonio organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France – sequence: 18 givenname: Philippe surname: Gual fullname: Gual, Philippe organization: Université Côte d’Azur, CHU, INSERM, U1065, C3M, France |
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| Keywords | non-invasive test Fiber evanescent wave spectroscopy metabolic fingerprint mid-infrared (MIR) spectroscopy severely obese patients NASH chalcogenide glass non-alcoholic steatohepatitis |
| Language | English |
| License | This is an open access article under the CC BY-NC-ND license. 2019 The Authors. Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
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| Snippet | There is an urgent medical need to develop non-invasive tests for non-alcoholic steatohepatitis (NASH). This study evaluates the diagnostic performance of an... Background & AimsThere is an urgent medical need to develop non-invasive tests for non-alcoholic steatohepatitis (NASH). This study evaluates the diagnostic... Background & Aims: There is an urgent medical need to develop non-invasive tests for non-alcoholic steatohepatitis (NASH). This study evaluates the diagnostic... Unlabelled Image • There is no validated non-invasive diagnostic tool for NASH in routine care. • NASH follow-up requires a non-invasive diagnostic method. •... |
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| SubjectTerms | Bioengineering chalcogenide glass Endocrinology and metabolism Fiber evanescent wave spectroscopy Gastroenterology and Hepatology Human health and pathology Hépatology and Gastroenterology Imaging Life Sciences metabolic fingerprint mid-infrared (MIR) spectroscopy NASH non-alcoholic steatohepatitis non-invasive test severely obese patients |
| Title | The mid-infrared spectroscopy: A novel non-invasive diagnostic tool for NASH diagnosis in severe obesity |
| URI | https://www.clinicalkey.com/#!/content/1-s2.0-S2589555919301107 https://www.clinicalkey.es/playcontent/1-s2.0-S2589555919301107 https://dx.doi.org/10.1016/j.jhepr.2019.09.005 https://www.ncbi.nlm.nih.gov/pubmed/32039387 https://www.proquest.com/docview/2353010663 https://hal.science/hal-04009608 https://pubmed.ncbi.nlm.nih.gov/PMC7005664 https://doaj.org/article/ba3189703cce4c9bae55318b06a0e86b |
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