The Role of Imaging Biomarkers in the Assessment of Sarcopenia
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Patient Selection
2.3. Clinical and Functional Parameters
2.4. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Cruz-Jentoft, A.J.; Bahat, G.; Bauer, J.; Boirie, Y.; Bruyère, O.; Cederholm, T.; Cooper, C.; Landi, F.; Rolland, Y.; Sayer, A.A.; et al. Sarcopenia: Revised European consensus on definition and diagnosis. Age Ageing 2019, 48, 16–31. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cruz-Jentoft, A.J.; Baeyens, J.P.; Bauer, J.M.; Boirie, Y.; Cederholm, T.; Landi, F.; Martin, F.C.; Michel, J.-P.; Rolland, Y.; Schneider, S.M.; et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010, 39, 412–423. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Correa-de-Araujo, R.; Harris-Love, M.O.; Miljkovic, I.; Fragala, M.S.; Anthony, B.W.; Manini, T.M. The Need for Standardized Assessment of Muscle Quality in Skeletal Muscle Function Deficit and Other Aging-Related Muscle Dysfunctions: A Symposium Report. Front. Physiol. 2017, 8, 87. [Google Scholar] [CrossRef] [PubMed]
- Cruz-Jentoft, A.J.; Sayer, A.A. Sarcopenia. Lancet 2019, 393, 2636–2646. [Google Scholar] [CrossRef]
- Gonzalez, M.C.; Barbosa-Silva, T.G.; Heymsfield, S.B. Bioelectrical impedance analysis in the assessment of sarcopenia. Curr. Opin. Clin. Nutr. Metab. Care 2018, 21, 366–374. [Google Scholar] [CrossRef]
- Janssen, I.; Heymsfield, S.B.; Baumgartner, R.N.; Ross, R. Estimation of skeletal muscle mass by bioelectrical impedance analysis. J. Appl. Physiol. 2000, 89, 465–471. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yang, L.; Yao, X.; Shen, J.; Sun, G.; Sun, Q.; Tian, X.; Li, X.; Li, X.; Ye, L.; Zhang, Z.; et al. Comparison of revised EWGSOP criteria and four other diagnostic criteria of sarcopenia in Chinese community-dwelling elderly residents. Exp. Gerontol. 2020, 130, 110798. [Google Scholar] [CrossRef] [PubMed]
- Lee, W.-J.; Liu, L.-K.; Peng, L.-N.; Lin, M.-H.; Chen, L.-K. Comparisons of Sarcopenia Defined by IWGS and EWGSOP Criteria Among Older People: Results From the I-Lan Longitudinal Aging Study. J. Am. Med Dir. Assoc. 2013, 14, 528.e1–528.e7. [Google Scholar] [CrossRef] [PubMed]
- Batsis, J.A.; Villareal, D.T. Sarcopenic obesity in older adults: Aetiology, epidemiology and treatment strategies. Nat. Rev. Endocrinol. 2018, 14, 513–537. [Google Scholar] [CrossRef]
- Mayhew, A.J.; Raina, P. Sarcopenia: New definitions, same limitations. Age Ageing 2019, 613–614. [Google Scholar] [CrossRef]
- Sergi, G.; Trevisan, C.; Veronese, N.; Lucato, P.; Manzato, E. Imaging of sarcopenia. Eur. J. Radiol. 2016, 85, 1519–1524. [Google Scholar] [CrossRef] [PubMed]
- Mitchell, W.K.; Williams, J.; Atherton, P.; Larvin, M.; Lund, J.; Narici, M. Sarcopenia, dynapenia, and the impact of advancing age on human skeletal muscle size and strength; a quantitative review. Front. Physiol. 2012, 3, 260. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Carlier, P.G.; Marty, B.; Scheidegger, O.; Loureiro de Sousa, P.; Baudin, P.-Y.; Snezhko, E.; Vlodavets, D. Skeletal Muscle Quantitative Nuclear Magnetic Resonance Imaging and Spectroscopy as an Outcome Measure for Clinical Trials. J. Neuromuscul. Dis. 2016, 3, 1–28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Power, G.A.; Allen, M.D.; Booth, W.J.; Thompson, R.T.; Marsh, G.D.; Rice, C.L. The influence on sarcopenia of muscle quality and quantity derived from magnetic resonance imaging and neuromuscular properties. Age 2014, 36, 9642. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Varghese, J.; Scandling, D.; Joshi, R.; Aneja, A.; Craft, J.; Raman, S.V.; Rajagopalan, S.; Simonetti, O.P.; Mihai, G. Rapid assessment of quantitative T1, T2 and T2* in lower extremity muscles in response to maximal treadmill exercise. NMR Biomed. 2015, 28, 998–1008. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Marty, B.; Baudin, P.-Y.; Reyngoudt, H.; Azzabou, N.; Araujo, E.C.A.; Carlier, P.G.; de Sousa, P.L. Simultaneous muscle water T2 and fat fraction mapping using transverse relaxometry with stimulated echo compensation. NMR Biomed. 2016, 29, 431–443. [Google Scholar] [CrossRef] [PubMed]
- Codari, M.; Zanardo, M.; di Sabato, M.E.; Nocerino, E.; Messina, C.; Sconfienza, L.M.; Sardanelli, F. MRI-Derived Biomarkers Related to Sarcopenia: A Systematic Review. J. Magn. Reson. Imaging 2019, 1117–1127. [Google Scholar] [CrossRef]
- Masanes, F.; Culla, A.; Navarro-Gonzalez, M.; Navarro-Lopez, M.; Sacanella, E.; Torres, B.; Lopez-Soto, A. Prevalence of sarcopenia in healthy community-dwelling elderly in an urban area of Barcelona (Spain). J. Nutr. Health Aging 2012, 16, 184–187. [Google Scholar] [CrossRef]
- Marfell-Jones, M.; Stewart, T.O.A.; Carter, L.; International Society for Advancement of Kinanthropometry. International Standards for Anthropometric Assessment; International Society for the Advancement of Kinanthropometry: Potchefstroom, South Africa, 2006; ISBN 978-0-620-36207-8. [Google Scholar]
- Kelly, J.S.; Metcalfe, J. Validity and Reliability of Body Composition Analysis Using the Tanita BC418-MA. J. Exerc. Physiol. Online 2012, 15, 74. [Google Scholar]
- Martínez, E.G. Composición corporal: Su importancia en la práctica clínica y algunas técnicas relativamente sencillas para su evaluación. Rev. Salud Uninorte 2010, 26, 98–116. [Google Scholar]
- Horowitz, B.P.; Tollin, R.; Cassidy, G. Grip Strength. Phys. Occup. Ther. Geriatr. 1997, 15, 53–64. [Google Scholar] [CrossRef]
- Rubio Castañeda, F.J.; Tomás Aznar, C.; Muro Baquero, C. Validity, Reliability and Associated Factors of the International Physical Activity Questionnaire Adapted to Elderly (IPAQ-E). Rev. Esp. Salud Publica 2017, 91, e201701004. [Google Scholar] [PubMed]
- Mahoney, F.I.; Barthel, D.W. Functional Evaluation: The Barthel Index. Md. State Med. J. 1965, 14, 61–65. [Google Scholar] [PubMed]
- Kaiser, M.J.; Bauer, J.M.; Ramsch, C.; Uter, W.; Guigoz, Y.; Cederholm, T.; Thomas, D.R.; Anthony, P.; Charlton, K.E.; Maggio, M.; et al. Validation of the Mini Nutritional Assessment short-form (MNA-SF): A practical tool for identification of nutritional status. J. Nutr. Health Aging 2009, 13, 782–788. [Google Scholar] [CrossRef]
- Guralnik, J.M.; Simonsick, E.M.; Ferrucci, L.; Glynn, R.J.; Berkman, L.F.; Blazer, D.G.; Scherr, P.A.; Wallace, R.B. A short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. J. Gerontol. 1994, 49, M85–M94. [Google Scholar] [CrossRef]
- Duncan, M.J.; Al-Nakeeb, Y.; Scurr, J. Perceived exertion is related to muscle activity during leg extension exercise. Res. Sports Med. 2006, 14, 179–189. [Google Scholar] [CrossRef]
- Da Silva, E.M.; Brentano, M.A.; Cadore, E.L.; De Almeida, A.P.V.; Kruel, L.F.M. Analysis of muscle activation during different leg press exercises at submaximum effort levels. J. Strength Cond. Res. 2008, 22, 1059–1065. [Google Scholar] [CrossRef] [Green Version]
- Brzycki, M. Strength Testing—Predicting a One-Rep Max from Reps-to-Fatigue. J. Phys. Educ. Recreat. Danc. 1993, 64, 88–90. [Google Scholar] [CrossRef]
- Miller, M.R.; Hankinson, J.; Brusasco, V.; Burgos, F.; Casaburi, R.; Coates, A.; Crapo, R.; Enright, P.; van der Grinten, C.P.M.; Gustafsson, P.; et al. Standardisation of spirometry. Eur. Respir. J. 2005, 26, 319–338. [Google Scholar] [CrossRef] [Green Version]
- Laveneziana, P.; Albuquerque, A.; Aliverti, A.; Babb, T.; Barreiro, E.; Dres, M.; Dubé, B.-P.; Fauroux, B.; Gea, J.; Guenette, J.A.; et al. ERS statement on respiratory muscle testing at rest and during exercise. Eur. Respir. J. 2019, 53. [Google Scholar] [CrossRef] [Green Version]
- Reeder, S.B.; Pineda, A.R.; Wen, Z.; Shimakawa, A.; Yu, H.; Brittain, J.H.; Gold, G.E.; Beaulieu, C.H.; Pelc, N.J. Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): Application with fast spin-echo imaging. Magn. Reson. Med. 2005, 54, 636–644. [Google Scholar] [CrossRef] [PubMed]
- Sigmund, E.E.; Baete, S.H.; Luo, T.; Patel, K.; Wang, D.; Rossi, I.; Duarte, A.; Bruno, M.; Mossa, D.; Femia, A.; et al. MRI assessment of the thigh musculature in dermatomyositis and healthy subjects using diffusion tensor imaging, intravoxel incoherent motion and dynamic DTI. Eur. Radiol. 2018, 28, 5304–5315. [Google Scholar] [CrossRef] [PubMed]
- Sawant, A.; House, A.A.; Chesworth, B.M.; Connelly, D.M.; Lindsay, R.; Gati, J.; Bartha, R.; Overend, T.J. Association between muscle hydration measures acquired using bioelectrical impedance spectroscopy and magnetic resonance imaging in healthy and hemodialysis population. Physiol. Rep. 2015, 3. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yao, L.; Yip, A.L.; Shrader, J.A.; Mesdaghinia, S.; Volochayev, R.; Jansen, A.V.; Miller, F.W.; Rider, L.G. Magnetic resonance measurement of muscle T2, fat-corrected T2 and fat fraction in the assessment of idiopathic inflammatory myopathies. Rheumatology 2016, 55, 441–449. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yamada, Y. Muscle Mass, Quality, and Composition Changes During Atrophy and Sarcopenia. Adv. Exp. Med. Biol. 2018, 1088, 47–72. [Google Scholar] [CrossRef] [PubMed]
- Azzabou, N.; Hogrel, J.-Y.; Carlier, P.G. NMR based biomarkers to study age-related changes in the human quadriceps. Exp. Gerontol. 2015, 70, 54–60. [Google Scholar] [CrossRef] [Green Version]
- Houmard, J.A.; Smith, R.; Jendrasiak, G.L. Relationship between MRI relaxation time and muscle fiber composition. J. Appl. Physiol. 1995, 78, 807–809. [Google Scholar] [CrossRef]
- Hu, H.H.; Li, Y.; Nagy, T.R.; Goran, M.I.; Nayak, K.S. Quantification of Absolute Fat Mass by Magnetic Resonance Imaging: A Validation Study against Chemical Analysis. Int. J. Body Compos. Res. 2011, 9, 111–122. [Google Scholar]
- Burakiewicz, J.; Sinclair, C.D.J.; Fischer, D.; Walter, G.A.; Kan, H.E.; Hollingsworth, K.G. Quantifying fat replacement of muscle by quantitative MRI in muscular dystrophy. J. Neurol. 2017, 264, 2053–2067. [Google Scholar] [CrossRef] [Green Version]
- Kim, H.K.; Serai, S.; Lindquist, D.; Merrow, A.C.; Horn, P.S.; Kim, D.H.; Wong, B.L. Quantitative Skeletal Muscle MRI: Part 2, MR Spectroscopy and T2 Relaxation Time Mapping-Comparison Between Boys with Duchenne Muscular Dystrophy and Healthy Boys. AJR Am. J. Roentgenol. 2015, 205, W216–W223. [Google Scholar] [CrossRef]
- Grimm, A.; Meyer, H.; Nickel, M.D.; Nittka, M.; Raithel, E.; Chaudry, O.; Friedberger, A.; Uder, M.; Kemmler, W.; Engelke, K.; 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. [Google Scholar] [CrossRef]
- Lamminen, A.E. Magnetic resonance imaging of primary skeletal muscle diseases: Patterns of distribution and severity of involvement. Br. J. Radiol. 1990, 63, 946–950. [Google Scholar] [CrossRef] [PubMed]
- Slabaugh, M.A.; Friel, N.A.; Karas, V.; Romeo, A.A.; Verma, N.N.; Cole, B.J. Interobserver and intraobserver reliability of the Goutallier classification using magnetic resonance imaging: Proposal of a simplified classification system to increase reliability. Am. J. Sports Med. 2012, 40, 1728–1734. [Google Scholar] [CrossRef] [PubMed]
- Camina Martín, M.A.; de Mateo Silleras, B.; Redondo del Río, M.P. Body composition analysis in older adults with dementia. Anthropometry and bioelectrical impedance analysis: A critical review. Eur J. Clin. Nutr. 2014, 68, 1228–1233. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rösler, A.; Lehmann, F.; Krause, T.; Wirth, R.; von Renteln-Kruse, W. Nutritional and hydration status in elderly subjects: Clinical rating versus bioimpedance analysis. Arch. Gerontol. Geriatr. 2010, 50, e81–e85. [Google Scholar] [CrossRef]
- Bouchard, D.R.; Héroux, M.; Janssen, I. Association between muscle mass, leg strength, and fat mass with physical function in older adults: Influence of age and sex. J. Aging Health 2011, 23, 313–328. [Google Scholar] [CrossRef]
- Marcus, R.L.; Addison, O.; LaStayo, P.C. Intramuscular adipose tissue attenuates gains in muscle quality in older adults at high risk for falling. A brief report. J. Nutr. Health Aging 2013, 17, 215–218. [Google Scholar] [CrossRef]
- Yoshida, Y.; Marcus, R.L.; Lastayo, P.C. Intramuscular adipose tissue and central activation in older adults. Muscle Nerve 2012, 46, 813–816. [Google Scholar] [CrossRef]
- Kera, T.; Kawai, H.; Hirano, H.; Kojima, M.; Fujiwara, Y.; Ihara, K.; Obuchi, S. Relationships among peak expiratory flow rate, body composition, physical function, and sarcopenia in community-dwelling older adults. Aging Clin. Exp. Res. 2018, 30, 331–340. [Google Scholar] [CrossRef]
- Kera, T.; Kawai, H.; Hirano, H.; Kojima, M.; Watanabe, Y.; Motokawa, K.; Fujiwara, Y.; Ihara, K.; Kim, H.; Obuchi, S. Definition of Respiratory Sarcopenia with Peak Expiratory Flow Rate. J. Am. Med. Dir. Assoc. 2019, 20, 1021–1025. [Google Scholar] [CrossRef]
- Ohara, D.G.; Pegorari, M.S.; Oliveira Dos Santos, N.L.; de Fátima Ribeiro Silva, C.; Monteiro, R.L.; Matos, A.P.; Jamami, M. Respiratory Muscle Strength as a Discriminator of Sarcopenia in Community-Dwelling Elderly: A Cross-Sectional Study. J. Nutr. Health Aging 2018, 22, 952–958. [Google Scholar] [CrossRef] [PubMed]
- Schramm, C.M. Current concepts of respiratory complications of neuromuscular disease in children. Curr. Opin. Pediatr. 2000, 12, 203–207. [Google Scholar] [CrossRef]
- Kang, S.W.; Bach, J.R. Maximum insufflation capacity: Vital capacity and cough flows in neuromuscular disease. Am. J. Phys. Med. Rehabil. 2000, 79, 222–227. [Google Scholar] [CrossRef] [PubMed]
- Barnouin, Y.; Butler-Browne, G.; Voit, T.; Reversat, D.; Azzabou, N.; Leroux, G.; Behin, A.; McPhee, J.S.; Carlier, P.G.; Hogrel, J.-Y. Manual segmentation of individual muscles of the quadriceps femoris using MRI: A reappraisal. J. Magn. Reson. Imaging 2014, 40, 239–247. [Google Scholar] [CrossRef] [PubMed]
- Tanaka, N.I.; Kanehisa, H. Applicability of single muscle CSA for predicting segmental muscle volume in young men. Int. J. Sports Med. 2014, 35, 608–614. [Google Scholar] [CrossRef] [PubMed]
- Vidt, M.E.; Santago, A.C.; Tuohy, C.J.; Poehling, G.G.; Freehill, M.T.; Kraft, R.A.; Marsh, A.P.; Hegedus, E.J.; Miller, M.E.; Saul, K.R. Assessments of Fatty Infiltration and Muscle Atrophy from a Single Magnetic Resonance Image Slice Are Not Predictive of 3-Dimensional Measurements. Arthroscopy 2016, 32, 128–139. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yang, Y.X.; Chong, M.S.; Lim, W.S.; Tay, L.; Yew, S.; Yeo, A.; Tan, C.H. 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. [Google Scholar] [CrossRef] [PubMed]
- Heymsfield, S.B.; Gonzalez, M.C.; 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. [Google Scholar] [CrossRef] [Green Version]
- Rolland, Y.; Gallini, A.; Cristini, C.; Schott, A.-M.; Blain, H.; Beauchet, O.; Cesari, M.; Lauwers-Cances, V. Body-composition predictors of mortality in women aged ≥ 75 y: Data from a large population-based cohort study with a 17-y follow-up. Am. J. Clin. Nutr. 2014, 100, 1352–1360. [Google Scholar] [CrossRef]
- Gallagher, D.; Kuznia, P.; Heshka, S.; Albu, J.; Heymsfield, S.B.; Goodpaster, B.; Visser, M.; Harris, T.B. Adipose tissue in muscle: A novel depot similar in size to visceral adipose tissue. Am. J. Clin. Nutr. 2005, 81, 903–910. [Google Scholar] [CrossRef] [Green Version]
- Addison, O.; Marcus, R.L.; Lastayo, P.C.; Ryan, A.S. Intermuscular fat: A review of the consequences and causes. Int. J. Endocrinol. 2014, 2014, 309570. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Karlsson, A.; Rosander, J.; Romu, T.; Tallberg, J.; Grönqvist, A.; Borga, M.; Dahlqvist Leinhard, O. Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water-fat MRI. J. Magn. Reson. Imaging 2015, 41, 1558–1569. [Google Scholar] [CrossRef] [PubMed]
- Le Troter, A.; Fouré, A.; Guye, M.; Confort-Gouny, S.; Mattei, J.-P.; Gondin, J.; Salort-Campana, E.; Bendahan, D. Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches. MAGMA 2016, 29, 245–257. [Google Scholar] [CrossRef] [PubMed]
- Sikiö, M.; Harrison, L.C.V.; Nikander, R.; Ryymin, P.; Dastidar, P.; Eskola, H.J.; Sievänen, H. Influence of exercise loading on magnetic resonance image texture of thigh soft tissues. Clin. Physiol. Funct. Imaging 2014, 34, 370–376. [Google Scholar] [CrossRef] [PubMed]
- Nketiah, G.; Savio, S.; Dastidar, P.; Nikander, R.; Eskola, H.; Sievänen, H. Detection of exercise load-associated differences in hip muscles by texture analysis. Scand. J. Med. Sci. Sports 2015, 25, 428–434. [Google Scholar] [CrossRef]
- Yang, K.-C.; Liao, Y.-Y.; Chang, K.-V.; Huang, K.-C.; Han, D.-S. The Quantitative Skeletal Muscle Ultrasonography in Elderly with Dynapenia but Not Sarcopenia Using Texture Analysis. Diagnostics 2020, 10, 400. [Google Scholar] [CrossRef]
MRI Sequence | Relevant Acquisition Parameters | Imaging Biomarker | Muscle Quality Indicator (Clinical Endpoint) |
---|---|---|---|
T1-weighted turbo spin echo sequence (TSE-T1) | Standard parameters | Total thigh muscle volume Total muscle volume/total fat volume Total muscle volume/total bone volume Macroscopic fatty infiltration | Muscle volume Muscle vs. fat ratio Muscle vs. bone ratio Macroscopic muscle fat infiltration |
Multiecho sequence with chemical shift | Echo times: 0.88, 1.55, 2.22, 2.89, 3.56 and 4.23 ms | Microscopic proton density fat fraction (PDFF) [32] T2* relaxation time | Microscopic muscle fat infiltration Muscle hydration |
Diffusion-weighted sequence | b-values: 0, 50, 100, 400 and 1200 s/mm2 | Molecular diffusion of water: apparent diffusion coefficient (ADC) and diffusion coefficient (D) [33] | Muscle hydration |
Parameter | Mean ± Standard Deviation (5th and 95th Percentiles) |
---|---|
Cineanthropometric | |
Weight (kg) | 62.7 ± 11.7 (47.0, 85.8) |
Height (m) | 1.50 ± 0.05 (1.42, 1.60) |
BMI (kg/m2) | 27.4 ± 4.7 (21.3, 36.8) |
Thigh perimeter (cm) | 47.4 ± 5.6 (42.1, 59.7) |
Calf perimeter (cm) | 32.5 ± 3.5 (27.8, 35.9) |
Fat mass (kg) | 24.0 ± 8.1 (12.7, 40.3) |
Fat mass (%) | 38.2 ± 7.5 (20.3, 48.4) |
Muscle mass (total, kg) | 36.2 ± 4.4 (29.8, 45.7) |
Muscle mass (appendicular, kg) | 15.4 ± 2.3 (12.9, 20.3) |
Muscle mass (lower limbs, kg) | 12.2 ± 1.3 (10.1, 15.8) |
Skeletal muscle mass index (SMMI, kg/m2) | 6.0 ± 0.8 (4.5, 7.1) |
Functional | |
Barthel index score (points) | 95 ± 9 (65, 100) |
SPPB (points) | 7.0 ± 2.6 (3.4, 11.2) |
MNA score (points) | 14.0 ± 4.5 (12.0, 25.0) |
IPAQ (Low/Moderate) | 8/18 |
Gait speed (m/s) | 0.72 ± 0.23 (0.27, 1.14) |
Handgrip strength (kg) | 18.0 ± 3.9 (11.8, 25.2) |
Maximum isotonic knee extension (kg) | 8.37 ± 3.1 (5.7, 13.3) |
Maximum isotonic leg press (kg) | 56.7 ± 24.3 (0, 93.4) |
Maximum isometric knee extension (kg) | 18.7 ± 6.4 (10.8, 28.7) |
Mean isometric knee extension (kg) | 16.5 ± 6.4 (9.6, 27.1) |
Respiratory | |
FVCa (L/s) | 1.86 ± 0.57 (1.04, 2.71) |
FVCp (%) | 112.0 ± 24.5 (72.8, 150.8) |
FEV1a (L/s) | 1.46 ± 0.42 (0.82, 2.19) |
FEV1p (%) | 116.0 ± 26.6 (75.8, 172.3) |
FEV2575a (L/s) | 1.41 ± 0.69 (0.69, 2.81) |
FEV2575p (%) | 64.0 ± 29.5 (34.0, 125.5) |
PEF (L/s) | 3.7 ± 1.2 (1.5, 5.8) |
MIP (cm H2O) | 45.0 ± 20.3 (9.3, 74.5) |
MEP (cm H2O) | 77.0 ± 28.8 (35.3, 126.5) |
Muscle quality-related imaging biomarkers | |
Muscle hydration ADC (10−3 mm2/s) | 1.05 ± 0.1 (0.81, 1.30) |
Muscle hydration D (10−3 mm2/s) | 1.01 ± 0.1 (0.65, 1.23) |
Muscle hydration T2 (ms) | 31.6 ± 4.1 (24.9, 37.1) |
Muscle microscopic fat (PDFF, no units) | 0.13 ± 0.03 (0.09, 0.20) |
Macroscopic fatty infiltration (no units) | 0.34 ± 0.10 (0.18, 0.56) |
Muscle quantity-related imaging biomarkers | |
Muscle/fat ratio (no units) | 0.69 ± 0.30 (0.27, 1.23) |
Muscle/bone ratio (no units) | 13.0 ± 3.2 (8.1, 17.1) |
Absolute muscle volume (L) | 1.25 ± 0.4 (0.62, 2.05) |
BMI (kg/m2) | Thigh Perimeter (cm) | Fat Mass (%) | Muscle Mass (Total, kg) | SMMI (kg/m2) | |
---|---|---|---|---|---|
Muscle hydration ADC (10−3 mm2/s) | −0.71 *** | −0.32 | −0.69 *** | −0.35 | −0.23 |
Muscle hydration D (10−3 mm2/s) | −0.71 *** | −0.55 ** | −0.72 *** | −0.62** | −0.51 * |
Muscle hydration T2* (ms) | −0.62 ** | −0.73 *** | −0.60 ** | −0.25 | −0.24 |
Muscle microscopic fat (PDFF, no units) | 0.82 *** | 0.29 | 0.74 *** | 0.41* | 0.37 |
Macroscopic fatty infiltration (no units) | 0.67 *** | 0.46 * | 0.71 *** | 0.24 | 0.10 |
Muscle/fat ratio (no units) | −0.61 ** | −0.78 *** | −0.68 ** | −0.35 | −0.21 |
Muscle/bone ratio (no units) | −0.28 | −0.14 | −0.24 | −0.12 | 0.02 |
Handgrip (kg) | MeanISOMED (kg) | Max ISOMED (kg) | SPPB (Points) | MILP (kg) | |
---|---|---|---|---|---|
Muscle hydration ADC (10−3 mm2/s) | −0.28 | −0.36 | −0.23 | −0.28 | −0.36 |
Muscle hydration D (10−3 mm2/s) | −0.28 | −0.42 | −0.45 | 0.02 | −0.27 |
Muscle hydration T2* (ms) | − 0.27 | −0.02 | 0.03 | −0.23 | −0.51 * |
Muscle microscopic fat (PDFF, no units) | −0.51 * | −0.11 | −0.21 | −0.27 | 0.10 |
Macroscopic fatty infiltration (no units) | −0.10 | −0.15 | −0.20 | −0.60 ** | 0.01 |
Muscle/fat ratio (no units) | −0.18 | −0.57 * | −0.46 * | 0.11 | −0.18 |
Muscle/bone ratio (no units) | 0.22 | −0.42 | −0.42 * | 0.39 * | −0.28 |
Absolute muscle volume (L) | 0.50 ** | 0.25 | 0.26 | 0.47 ** | 0.10 |
FVCa (L/s) | FEV1a (L/s) | FEV2575a (L/s) | PEF (L/s) | MIP (H2Ocm) | MEP (H2Ocm) | |
---|---|---|---|---|---|---|
Muscle hydration ADC (10−3 mm2/s) | −0.44 * | −0.56 ** | −0.61 ** | −0.26 | −0.54 ** | −0.30 |
Muscle hydration D (10−3 mm2/s) | −0.26 | −0.33 | −0.55 ** | −0.18 | −0.10 | −0.10 |
Muscle hydration T2* (ms) | −0.36 | −0.30 | −0.54 * | −0.10 | 0.17 | −0.37 * |
Muscle microscopic fat (PDFF, no units) | −0.21 | −0.13 | −0.20 | 0.03 | 0.21 | 0.08 |
Macroscopic fatty infiltration (no units) | −0.65 *** | −0.48 * | −0.32 | −0.51 ** | −0.37 | −0.25 |
Muscle/fat ratio (no units) | −0.28 | −0.29 | −0.23 | −0.15 | −0.35 | −0.24 |
Muscle/bone ratio (no units) | 0.47 * | 0.38 | 0.29 | 0.18 | −0.28 | −0.01 |
Absolute muscle volume (L) | 0.53 ** | 0.09 | 0.18 | 0.47 * | 0.36 | 0.32 * |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sanz-Requena, R.; Martínez-Arnau, F.M.; Pablos-Monzó, A.; Flor-Rufino, C.; Barrachina-Igual, J.; García-Martí, G.; Martí-Bonmatí, L.; Pérez-Ros, P. The Role of Imaging Biomarkers in the Assessment of Sarcopenia. Diagnostics 2020, 10, 534. https://doi.org/10.3390/diagnostics10080534
Sanz-Requena R, Martínez-Arnau FM, Pablos-Monzó A, Flor-Rufino C, Barrachina-Igual J, García-Martí G, Martí-Bonmatí L, Pérez-Ros P. The Role of Imaging Biomarkers in the Assessment of Sarcopenia. Diagnostics. 2020; 10(8):534. https://doi.org/10.3390/diagnostics10080534
Chicago/Turabian StyleSanz-Requena, Roberto, Francisco Miguel Martínez-Arnau, Ana Pablos-Monzó, Cristina Flor-Rufino, Joaquín Barrachina-Igual, Gracián García-Martí, Luis Martí-Bonmatí, and Pilar Pérez-Ros. 2020. "The Role of Imaging Biomarkers in the Assessment of Sarcopenia" Diagnostics 10, no. 8: 534. https://doi.org/10.3390/diagnostics10080534