MRI-Derived Biomarkers Related to Sarcopenia: A Systematic Review.


Journal

Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850

Informations de publication

Date de publication:
04 2020
Historique:
received: 21 05 2019
revised: 13 08 2019
accepted: 15 08 2019
pubmed: 14 9 2019
medline: 20 5 2021
entrez: 14 9 2019
Statut: ppublish

Résumé

MRI allows quantitatively assessing muscle quantity and quality. To summarize the role of MRI as a noninvasive technique for the identification of in vivo surrogate biomarker of sarcopenia. Systematic review. In April 2019, a systematic literature search (Medline/EMBASE) was performed to identify articles on the topic at issue. No field strength or sequence restrictions. After a literature search, study design, aim, sample size, demographics, magnetic field strength, imaged body region, MRI sequences, and imaging biomarker were extracted. Data are presented as frequencies and percentages. From 69 records identified through search query, 18 articles matched the inclusion criteria. All articles were published from 2012 and had a mainly prospective design (14/18, 78%). Sample size ranged from 9 to 284 subjects, for a total of 1706 enrolled subjects. Healthy subjects were enrolled or retrospectively selected in 8/18 (44%) articles, corresponding to 658 (39%) healthy subjects. Magnetic field strength was 1.5 or 3T in 14/18 (78%) studies. The most analyzed body regions were the thigh (7/18, 39%) and the trunk (6/18, 33%). Stratifying studies according to their aim, 13/18 (72%) studies focused on muscle quality and quantity, 3/18 (17%) studies on outcome prediction, and 2/18 articles (11%) addressed both aims. A wide set of MRI biomarkers have been proposed. Muscle cross-sectional area was the most used for muscle quantity estimation, while quantitative biomarkers of muscle fat content or fiber architecture were proposed to assess muscle quality. The proposed biomarkers were assessed using different MRI sequences for different body regions in different subjects/patient cohorts, pointing out a lack of standardization on this topic. Future studies should test and compare the performance of proposed MRI biomarkers for sarcopenia characterization and quantification using a standardized experimental setup. 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1117-1127.

Sections du résumé

BACKGROUND
MRI allows quantitatively assessing muscle quantity and quality.
PURPOSE
To summarize the role of MRI as a noninvasive technique for the identification of in vivo surrogate biomarker of sarcopenia.
STUDY TYPE
Systematic review.
POPULATION
In April 2019, a systematic literature search (Medline/EMBASE) was performed to identify articles on the topic at issue.
FIELD STRENGTH/SEQUENCE
No field strength or sequence restrictions.
ASSESSMENT
After a literature search, study design, aim, sample size, demographics, magnetic field strength, imaged body region, MRI sequences, and imaging biomarker were extracted.
STATISTICAL TESTS
Data are presented as frequencies and percentages.
RESULTS
From 69 records identified through search query, 18 articles matched the inclusion criteria. All articles were published from 2012 and had a mainly prospective design (14/18, 78%). Sample size ranged from 9 to 284 subjects, for a total of 1706 enrolled subjects. Healthy subjects were enrolled or retrospectively selected in 8/18 (44%) articles, corresponding to 658 (39%) healthy subjects. Magnetic field strength was 1.5 or 3T in 14/18 (78%) studies. The most analyzed body regions were the thigh (7/18, 39%) and the trunk (6/18, 33%). Stratifying studies according to their aim, 13/18 (72%) studies focused on muscle quality and quantity, 3/18 (17%) studies on outcome prediction, and 2/18 articles (11%) addressed both aims. A wide set of MRI biomarkers have been proposed. Muscle cross-sectional area was the most used for muscle quantity estimation, while quantitative biomarkers of muscle fat content or fiber architecture were proposed to assess muscle quality.
DATA CONCLUSION
The proposed biomarkers were assessed using different MRI sequences for different body regions in different subjects/patient cohorts, pointing out a lack of standardization on this topic. Future studies should test and compare the performance of proposed MRI biomarkers for sarcopenia characterization and quantification using a standardized experimental setup.
LEVEL OF EVIDENCE
1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1117-1127.

Identifiants

pubmed: 31515891
doi: 10.1002/jmri.26931
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

1117-1127

Informations de copyright

© 2019 International Society for Magnetic Resonance in Medicine.

Références

Rosenberg IH. Summary comments. Am J Clin Nutr 1989;50:1231-1233.
Santilli V, Bernetti A, Mangone M, Paoloni M. Clinical definition of sarcopenia. Clin Cases Miner Bone Metab 2014;11:177-180.
Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: Revised European consensus on definition and diagnosis. Age Ageing 2019;48:16-31.
Guerri S, Mercatelli D, Aparisi Gómez MP, et al. Quantitative imaging techniques for the assessment of osteoporosis and sarcopenia. Quant Imaging Med Surg 2018;8:60-85.
Cawthon PM, Lui L-Y, Taylor BC, et al. Clinical definitions of sarcopenia and risk of hospitalization in community-dwelling older men: The Osteoporotic Fractures in Men Study. J Gerontol Ser A 2017;72:1383-1389.
Cesari M, Landi F, Vellas B, Bernabei R, Marzetti E. Sarcopenia and physical frailty: Two sides of the same coin. Front Aging Neurosci 2014;6.
Bahat G, Ýlhan B. Sarcopenia and the cardiometabolic syndrome: A narrative review. Eur Geriatr Med 2016;7:220-223.
Bone AE, Hepgul N, Kon S, Maddocks M. Sarcopenia and frailty in chronic respiratory disease. Chron Respir Dis 2017;14:85-99.
Chang K-V, Hsu T-H, Wu W-T, Huang K-C, Han D-S. Association between sarcopenia and cognitive impairment: A systematic review and meta-analysis. J Am Med Dir Assoc 2016;17:1164.e7-1164.e15.
Schaap LA, van Schoor NM, Lips P, Visser M. Associations of sarcopenia definitions, and their components, with the incidence of recurrent falling and fractures: The Longitudinal Aging Study Amsterdam. J Gerontol Ser A 2018;73:1199-1204.
Landi F, Liperoti R, Fusco D, et al. Sarcopenia and mortality among older nursing home residents. J Am Med Dir Assoc 2012;13:121-126.
Chastin SFM, Ferriolli E, Stephens NA, Fearon KCH, Greig C. Relationship between sedentary behaviour, physical activity, muscle quality and body composition in healthy older adults. Age Ageing 2012;41:111-114.
Liu C-J, Latham NK. Progressive resistance strength training for improving physical function in older adults. Cochrane Database Syst Rev 2009;CD002759.
Ethgen O, Beaudart C, Buckinx F, Bruyère O, Reginster JY. The future prevalence of sarcopenia in Europe: A claim for public health action. Calcif Tissue Int 2017;100:229-234.
Malmstrom TK, Morley JE. SARC-F: A simple questionnaire to rapidly diagnose sarcopenia. J Am Med Dir Assoc 2013;14:531-532.
Nijholt W, Scafoglieri A, Jager-Wittenaar H, Hobbelen JSM, van der Schans CP. The reliability and validity of ultrasound to quantify muscles in older adults: A systematic review. J Cachexia Sarcopenia Muscle 2017;8:702-712.
Sconfienza LM. Sarcopenia: Ultrasound today, smartphones tomorrow? Eur Radiol 2019;29:1-2.
Messina C, Maffi G, Vitale JA, Ulivieri FM, Guglielmi G, Sconfienza LM. Diagnostic imaging of osteoporosis and sarcopenia: A narrative review. Quant Imaging Med Surg 2018;8:86-99.
Messina C, Monaco CG, Ulivieri FM, Sardanelli F, Sconfienza LM. Dual-energy X-ray absorptiometry body composition in patients with secondary osteoporosis. Eur J Radiol 2016;85:1493-1498.
Amini B, Boyle SP, Boutin RD, Lenchik L. Approaches to assessment of muscle mass and myosteatosis on computed tomography: A systematic review. J Gerontol Ser A 2019 [Epub ahead of print].
Erlandson MC, Lorbergs AL, Mathur S, Cheung AM. Muscle analysis using pQCT, DXA and MRI. Eur J Radiol 2016;85:1505-1511.
Grimm A, Nickel MD, Chaudry O, et al. Feasibility of Dixon magnetic resonance imaging to quantify effects of physical training on muscle composition-A pilot study in young and healthy men. Eur J Radiol 2019;114:160-166.
Fischer MA, Pfirrmann CWA, Espinosa N, Raptis DA, Buck FM. Dixon-based MRI for assessment of muscle-fat content in phantoms, healthy volunteers and patients with achillodynia: Comparison to visual assessment of calf muscle quality. Eur Radiol 2014;24:1366-1375.
Grimm A, Meyer H, Nickel MD, et al. A comparison between 6-point Dixon MRI and MR spectroscopy to quantify muscle fat in the thigh of subjects with sarcopenia. J Frailty Aging 2019;8:21-26.
Sinha U, Malis V, Csapo R, Moghadasi A, Kinugasa R, Sinha S. Age-related differences in strain rate tensor of the medial gastrocnemius muscle during passive plantarflexion and active isometric contraction using velocity encoded MR imaging: Potential index of lateral force transmission. Magn Reson Med 2015;73:1852-1863.
Boutin RD, Yao L, Canter RJ, Lenchik L. Sarcopenia: Current concepts and imaging implications. Am J Roentgenol 2015;205:W255-W266.
Abellan Van Kan G, Cedarbaum JM, Cesari M, et al. Sarcopenia: Biomarkers and imaging (International Conference on Sarcopenia research). J Nutr Health Aging 2011;15:834-846.
Ma J. Dixon techniques for water and fat imaging. J Magn Reson Imaging 2008;28:543-558.
Karampinos DC, Ruschke S, Dieckmeyer M, et al. Quantitative MRI and spectroscopy of bone marrow. J Magn Reson Imaging 2018;47:332-353.
Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA Statement. PLoS Med 2009;6:e1000097.
McGrath TA, Bossuyt PM, Cronin P, et al. Best practices for MRI systematic reviews and meta-analyses. J Magn Reson Imaging 2019;49:e51-64.
Burian E, Syväri J, Holzapfel C, et al. Gender-and age-related changes in trunk muscle composition using chemical shift encoding-based water-fat MRI. Nutrients 2018;10:1-13.
Grimm A, Meyer H, Nickel MD, et al. Repeatability of Dixon magnetic resonance imaging and magnetic resonance spectroscopy for quantitative muscle fat assessments in the thigh. J Cachexia Sarcopenia Muscle 2018;9:1093-1100.
Morrell GR, Ikizler TA, Chen X, et al. Psoas muscle cross-sectional area as a measure of whole-body lean muscle mass in maintenance hemodialysis patients. J Ren Nutr 2016;26:258-264.
Maden-Wilkinson TM, McPhee JS, Jones DA, Degens H. Age-related loss of muscle mass, strength, and power and their association with mobility in recreationally-active older adults in the United Kingdom. J Aging Phys Act 2015;23:352-360.
de la Maza MP, Hirsch S, Jara N, et al. Central obesity and not age increases skeletal muscle lipids, without influencing lean body mass and strength. Nutr Hosp 2014;31:1134-1141.
Azzabou N, Hogrel JY, Carlier PG. NMR based biomarkers to study age-related changes in the human quadriceps. Exp Gerontol 2015;70:54-60.
Power GA, Allen MD, Booth WJ, Thompson RT, Marsh GD, Rice CL. The influence on sarcopenia of muscle quality and quantity derived from magnetic resonance imaging and neuromuscular properties. Age 2014;36:9642.
Zoico E, Corzato F, Bambace C, et al. Myosteatosis and myofibrosis: Relationship with aging, inflammation and insulin resistance. Arch Gerontol Geriatr 2013;57:411-416.
Tandon P, Ney M, Irwin I, et al. Severe muscle depletion in patients on the liver transplant wait list: Its prevalence and independent prognostic value. Liver Transplant 2012;18:1209-1216.
Schautz B, Later W, Heller M, Müller MJ, Bosy-Westphal A. Total and regional relationship between lean and fat mass with increasing adiposity-Impact for the diagnosis of sarcopenic obesity. Eur J Clin Nutr 2012;66:1356-1361.
Jang M, Park HW, Huh J, et al. Predictive value of sarcopenia and visceral obesity for postoperative pancreatic fistula after pancreaticoduodenectomy analyzed on clinically acquired CT and MRI. Eur Radiol 2019;29:2417-2425.
Watanabe K, Ohashi M, Hirano T, et al. The influence of lumbar muscle volume on curve progression after skeletal maturity in patients with adolescent idiopathic scoliosis: A long-term follow-up study. Spine Deform 2018;6:691-698.e1.
Zilles M, Betz C, Jung O, et al. How to prevent renal cachexia? A clinical randomized pilot study testing oral supplemental nutrition in hemodialysis patients with and without human immunodeficiency virus infection. J Ren Nutr 2018;28:37-44.
Praktiknjo M, Book M, Luetkens J, et al. Fat-free muscle mass in magnetic resonance imaging predicts acute-on-chronic liver failure and survival in decompensated cirrhosis. Hepatology 2018;67:1014-1026.
Yang YX, Chong MS, Lim WS, et al. Validity of estimating muscle and fat volume from a single MRI section in older adults with sarcopenia and sarcopenic obesity. Clin Radiol 2017;72:427.e9-427.e14.
Baum T, Inhuber S, Dieckmeyer M, et al. Association of quadriceps muscle fat with isometric strength measurements in healthy males using chemical shift encoding-based water-fat magnetic resonance imaging. J Comput Assist Tomogr 2016;40:447-451.
Biolo G, Pišot R, Mazzucco S, et al. Anabolic resistance assessed by oral stable isotope ingestion following bed rest in young and older adult volunteers: Relationships with changes in muscle mass. Clin Nutr 2017;36:1420-1426.
Melville DM, Mohler J, Fain M, et al. Multi-parametric MR imaging of quadriceps musculature in the setting of clinical frailty syndrome. Skeletal Radiol 2016;45:583-589.
Calvani R, Marini F, Cesari M, et al. Biomarkers for physical frailty and sarcopenia: State of the science and future developments. J Cachexia Sarcopenia Muscle 2015;6:278-286.
Berglund J, Johansson L, Ahlström H, Kullberg J. Three-point Dixon method enables whole-body water and fat imaging of obese subjects. Magn Reson Med 2010;63:1659-1668.
Li K, Dortch RD, Welch EB, et al. Multi-parametric MRI characterization of healthy human thigh muscles at 3.0 T - Relaxation, magnetization transfer, fat/water, and diffusion tensor imaging. NMR Biomed 2014;27:1070-1084.
Kovanlikaya A, Guclu C, Desai C, Becerra R, Gilsanz V. Fat quantification using three-point dixon technique: in vitro validation. Acad Radiol 2005;12:636-639.
Rossi A, Zoico E, Goodpaster BH, et al. Quantification of intermuscular adipose tissue in the erector spinae muscle by MRI: Agreement with histological evaluation. Obesity 2010;18:2379-2384.
Artz NS, Haufe WM, Hooker CA, et al. Reproducibility of MR-based liver fat quantification across field strength: Same-day comparison between 1.5T and 3T in obese subjects. J Magn Reson Imaging 2015;42:811-817.
Houmard JA, Smith R, Jendrasiak GL. Relationship between MRI relaxation time and muscle fiber composition. J Appl Physiol 1995;78:807-809.
Simchick G, Yin A, Yin H, Zhao Q. Fat spectral modeling on triglyceride composition quantification using chemical shift encoded magnetic resonance imaging. Magn Reson Imaging 2018;52:84-93.
White LJ, Ferguson MA, McCoy SC, Kim H. Intramyocellular lipid changes in men and women during aerobic exercise: A (1)H-magnetic resonance spectroscopy study. J Clin Endocrinol Metab 2003;88:5638-5643.
Reeder SB, Hu HH, Sirlin CB. Proton density fat-fraction: A standardized MT-based biomarker of tissue fat concentration. J Magn Reson Imaging 2012;36:1011-1014.
Sardanelli F, Di Leo G. Reproducibility: Intraobserver and interobserver variability. In: Biostatistics for Radiologists. Milano, Italy: Springer Milan 2009;125-140.
Heymsfield SB, Gonzalez MC, Lu J, Jia G, Zheng J. Skeletal muscle mass and quality: Evolution of modern measurement concepts in the context of sarcopenia. Proc Nutr Soc 2015;74:355-366.
Trethewey SP, Brown N, Gao F, Turner AM. Interventions for the management and prevention of sarcopenia in the critically ill: A systematic review. J Crit Care 2019;50:287-295.

Auteurs

Marina Codari (M)

Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.

Moreno Zanardo (M)

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy.

Maria Eugenia di Sabato (ME)

Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy.

Elisabetta Nocerino (E)

Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy.

Carmelo Messina (C)

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy.
IRCCS Istituto Ortopedico Galeazzi, Milano, Italy.

Luca Maria Sconfienza (LM)

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy.
IRCCS Istituto Ortopedico Galeazzi, Milano, Italy.

Francesco Sardanelli (F)

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy.
Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy.

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