Assessment of Muscle Quality and Quantity for the Diagnosis of Sarcopenia Using Mid-Thigh Computed Tomography : A Cohort Study

doi:10.21203/rs.3.rs-64471/v1

Download PDF

Research article

Assessment of Muscle Quality and Quantity for the Diagnosis of Sarcopenia Using Mid-Thigh Computed Tomography : A Cohort Study

https://doi.org/10.21203/rs.3.rs-64471/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 13 Apr, 2021

Read the published version in BMC Geriatrics →

You are reading this older preprint version

Read the latest preprint version →

Background

Previously, sarcopenia was diagnosed based on walking speed, grip strength, and muscle mass. However, recent consensus has proposed a concern regarding the use of muscle mass measurement for sarcopenia diagnosis due to lack of accuracy; therefore, new assessment methods in clinical practice are required. We compared computed tomography (CT) with various motor function tests to determine the validity of CT as a potential diagnostic method for sarcopenia.

Methods

In total, 214 patients who were examined at our center during the study period (2016–2017) were included in the study. Single-slice CT scan of the mid-thigh region was performed, from which cross-sectional area (CSA) and CT attenuation value (CTV) of quadriceps femoris were evaluated for each subject. Other assessments included skeletal mass index, muscle strength and physical performance. Furthermore, subjects were classified into four groups: normal, low muscle mass (low mass), poor muscle function/strength (poor function), and sarcopenia.

Results

CSA and muscle strength exhibited the strongest correlation. Some physical performance tests showed the strongest correlation with CTV. CSA was significantly reduced both in men and women with low mass and sarcopenia group (p < 0.01), whereas CTV was significantly lower in men with sarcopenia group and in women with poor function and sarcopenia group (p < 0.01).

Conclusions

CSA mostly reflects muscle strength, whereas CTV mostly reflects physical performance. CT with measurements of CSA and CTV enables the evaluation of muscle mass and quality simultaneously. Thus, CT is thought to be useful for the assessment of motor function and diagnosis of sarcopenia.

Geriatrics & Gerontology

sarcopenia

mid-thigh computed tomography

muscle quality

computed tomography attenuation value

motor function

Muscle quality assessment is important to determine the severity of sarcopenia
Mid-thigh computed tomography (CT) cross-sectional area can reflect muscle mass and strength
Mid-thigh CT attenuation value can reflect muscle quality

As the adult population ages, the extension of healthy life expectancy has become a major issue. Sarcopenia is defined as a reduction in the skeletal muscle mass with aging. The term “sarcopenia” was first introduced by Rosemberg et al. [1] in 1989, from the Greek terms “sarx” (muscle) and “penia” (loss). In 1998, Baumgartner et al. [2] defined sarcopenia as a mean skeletal mass index (SMI) of − 2SD or less determined using dual energy X-ray absorption (DXA) in young individuals, and since then, sarcopenia has been determined using SMI. However, it has been reported that compared with muscle mass, muscle strength is more associated with falling and limited mobility [3, 4], and therefore, in determining sarcopenia, it is thought that muscle strength and physical performance should be included. The 2010 consensus report from the European Working Group on Sarcopenia in older people (EWGSOP) [5] proposed a diagnostic criteria for determining sarcopenia according to SMI, grip strength, and walking speed. In 2011, a condition “sarcopenia with limited mobility” was described in the United States of America in which muscle strength was lost despite maintaining muscle mass requiring treatment was proposed [6].

In 2014, the Asia Working Group of Sarcopenia (AWGS) 2014 presented diagnostic criteria for sarcopenia based on data obtained from various Asian countries [7]. Furthermore, In the EWGSOP2 revised in 2018, attention was focused on loss of muscle strength as the primary parameter of sarcopenia, and for a definite diagnosis of sarcopenia, it was reported that the assessment of muscle mass and quality is important [8]. AWGS 2019 updated the consensus of sarcopenia diagnosis in Asia [9].

Muscle mass is conventionally measured using DXA and bioelectrical impedance analysis (BIA). DXA can measure appendicular skeletal muscle mass; however, there are problems with this method, i.e., the values differ depending on the machine used [10], and in Asian women, this measurement does not change with age [11]. BIA is affected by the amount of bodily fluids; therefore, precise evaluations cannot be achieved [12]. Therefore, the EWGSOP2 described computed tomography (CT) and magnetic resonance imaging (MRI) as methods to verify the muscle mass and quality; however, there are only few reports of their use in clinical practice [13].

Motor function is evaluated using measurements of walking speed and grip strength; however, the reproducibility is poor depending on the physical and mental condition of the participant and the measurement methods and tool used [14]. CT and MRI are considered the gold standards of minimally invasive tests to measure muscle mass [15]; however, their use in the evaluation of muscle quality remains controversial. Goodpaster et al. [16] noted a good correlation between CT attenuation value (CTV) and intramuscular fat infiltration, whereas Ikemoto-Uezumi et al. [17] reported reduced muscle fibers and fatty tissue infiltration in the muscular tissue of the vastus medialis in patients with osteoarthritis. Therefore, it is inferred that CT can evaluate muscle mass and that CTV might be able to evaluate motor function, or in other words, muscle quality.

However, there are few reports of the use of CTV in CT scans of the mid-thigh and their use in evaluating motor function. The purpose of this study was to compare CT with a variety of motor function tests to determine the validity of CT as a potential assessment method for muscle quality as well as for the diagnosis of sarcopenia.

Of 300 patients who were examined at the outpatient services of the National Center for Geriatrics and Gerontology, Center for Frailty and Locomotive Syndrome between 2016 and 2017, 214 (78 male and 136 female; average age, 78.4 years) were included in the study after excluding those with gait impairment caused by severe osteoarthritis of the knee and hip and those with missing data. To assess the risk of falls, we investigated fall scores, as proposed by Toba et al. [18] To assess motor function, we measured walking speed (Walkway MW-1000, ANIMA, Tokyo Japan); grip strength using a new grip dynamometer developed at our institution with ZP-500N (Imada Co., Ltd., Toyohashi, Aichi, Japan) [19]; knee extension strength (ZP-500N, Imada Co., Ltd., Toyohashi, Aichi, Japan) that is the measure of the isometric muscle extension strength in the sitting position with knee at 90° of flexion, developed at our institution [20]; single-leg standing; timed up and go (TUG); short physical performance battery (SPPB) using stand-up test and two-step test. For single-leg standing, the participants were instructed to stand on a single leg with their eyes open as long as possible and the time was recorded. For TUG, we measured the time required to stand up from the chair and go back 3 m and to sit on the chair again. The stand-up and two-step tests were performed to assess the degree of locomotive syndrome. For the stand-up test, we measured whether the participants could stand up on both the legs from the sitting position on a platform of 10, 20, 30, and 40 cm [21]. For the two-step test, the participants stood at the starting line and took two strides as long as possible; then, the two legs were aligned and the distance of the two steps was measured. For SPPB, the test evaluated the balance, gait, strength, and endurance by examining an individual’s ability to stand on their feet together in side-by-side semi-tandem and tandem positions, time to walk 8 ft, and time to rise from a chair and return to the seated position five times [22]. Furthermore, the muscle mass of the four limbs from the whole-body scan was measured by DXA (Lunar iDXA, GE Healthcare, Chicago, Illinois, USA) and BIA (Inbody720, BIOSPACE, Iowa, USA). BIA provides an estimate of the muscle mass based on whole-body electrical conductivity [23].

For CT (SOMATOM Sensation 64; Siemens, Munich, Germany), the subject was placed in the supine position, and a single slice of the right mid-thigh. We defined the mid-thigh as the midpoint of the inguinal ligament and the superior pole of the patella manually. The scanning conditions were as follows: 120 kV, 120 mA, rotation time of 1 s, and field of view of 233 mm. From this single slice, the cross-sectional surface area (CSA) and CTV of the quadriceps femoris muscle were measured using SliceOmatic ver.5.0 (Tomovision, Canada) by a single examiner. CTV was defined as − 1,000 HU for air and 0 HU for water and indicated the degree of X-ray absorption of a substance. The average CTV is 40–100 HU for a muscle and approximately − 50 to − 100 HU for fat. For CSA and CTV, the imaging data of 21 subjects were measured by three examiners, and the associated interclass correlation was determined. The interclass correlation of CSA and CTV of the examiners was > 0.998, and the interclass correlation among the three examiners was 0.999.

The subjects were classified in accordance with the AWGS 2014 diagnostic criteria [7] into four groups. Among the subjects without reduced walking speed and grip strength, the group with normal muscle mass was defined as the “normal” group and that with reduced muscle mass as the “low muscle mass (low-mass)” group, that with reduced walking speed and/or grip strength but with normal muscle mass was defined as the “poor muscle function/strength (poor function)” group and that with reduced muscle mass as the “sarcopenia” group. According to AWGS 2014 criteria, the cutoff values [7] were as follows: walking speed, 0.8 m/s; grip strength, 26 kg for men and 16 kg for women; SMI with DXA 7.0 kg/m² for men and 5.4 kg/m² for women; and SMI with BIA 7.0 kg/m² for men and 5.7 kg/m² for women. For the four groups, we examined the results of muscle function measurements and CT.

Statistical analyses were performed via SPSS (IBM SPSS Statistics ver.24, Tokyo, Japan) using chi-square test for fall scores, analysis of variance for CSA of the quadriceps femoris muscle, and CTV. Tukey’s test was applied for post-hoc multiple testing, and normality test was not applied. Pearson’s correlation coefficient was used for the muscle strength test and physical performance tests, CSA, and CTV. The deference of correlation coefficient among the subjects were calculated, and then Bonferroni correction was performed. P values of < 0.05 were considered statistically significant. Power analysis was performed and the sample size was sufficient for the study.

Overall, 58 subjects were included in the normal group, 30 in the poor-function group, 65 in the low-mass group, and 61 in the sarcopenia group. Compared with the normal group, age and the fall risk index were significantly higher in the poor-function and sarcopenia groups, height was lower in poor-function and sarcopenia group and body weight was significantly lower in the low-mass and sarcopenia groups than in the normal group (Table 1).

Table 1

Demographic data by group
	n	sex	Age		Height (cm)		Weight (kg)		BMI		Fall risk score
		(Male:Female)	average	SD	average	SD	average	SD	average	SD	average	SD
Normal	58	15:43	75.9	3.33	155.3	7.53	60	9.34	24.84	2.94	7.71	3.33
Poor-function	30	8:22	78.5*	2.59	150.7*	8.61	60.6	13.06	26.49	4.15	10.37**	2.59
Low-mass	65	33: 32	77.4	3.07	155.7	8.89	51.3*	8.26	21.10	2.64	8.4	3.07
Sarcopenia	61	22:39	81.8**	3.22	149.9**	9.87	46.5**	9.14	20.63	3.14	10.5**	3.22
Total	214	78: 136	78.4	3.33	153.3	9.14	53.6	11.18	22.74	3.85	8.42	3.33
P < 0.05, *P < 0.01
Age and height were significantly higher in the poor-function and sarcopenia groups than in the normal group, whereas body weight was significantly lower in the low-mass and sarcopenia groups than in the normal group. (BMI : body mass index, SD : standard deviation)

Knee extension strength and grip strength were correlated with CSA, BIA, DXA and CTV. CSA had significantly stronger correlation with knee extension and grip strength than DXA and CTV, whereas CTV did not have significantly stronger correlation with others (Table 2).

Table 2

Correlation between CSA/CTV and muscle power and physical performance test Correlation between CSA/CTV and muscle power
	CSA			BIA			DXA			CTV
	r	95%CI		r	95%CI		r	95%CI		r	95%CI
	r	Lower	Upper	r	Lower	Upper	r	Lower	Upper	r	Lower	Upper
Muscle power
Knee extension strength	0.717	0.645	0.777	0.565	0.466	0.650	0.547*	0.445	0.635	0.354*	0.231	0.466
Grip strength	0.657	0.573	0.727	0.559	0.459	0.645	0.446*	0.331	0.548	0.376*	0.254	0.486
Physical performance
Single-leg standing	0.202	0.069	0.328	0.115	−0.020	0.246	0.057	−0.078	0.190	0.247	0.116	0.369
Walking speed	0.326	0.200	0.441	0.215	0.083	0.340	0.133†	−0.001	0.263	0.427	0.310	0.531
Standing up test	−0.240	−0.363	−0.109	−0.039†	−0.173	0.096	−0.014†	−0.148	0.121	−0.411	−0.517	−0.293
TUG	−0.232	−0.355	−0.101	−0.200	−0.326	−0.067	−0.155	−0.284	−0.021	−0.304	−0.421	−0.177
SPPB (total)	0.286	0.158	0.405	0.217	0.085	0.341	0.196	0.063	0.322	0.329	0.204	0.444
Two-step test	0.382	0.261	0.491	0.174	0.041	0.301	0.147†	0.013	0.276	0.384	0.263	0.493
r: Pearson's correlation coefficient
*P < 0.05 compared with CSA, †P < 0.05 compared with CTV
*or† means that CSA or CTV has significantly stronger correlation than the value. CSA showed the most association with muscle power, whereas CTV showed the most association with physical performance.

In contrast, for the physical performance measurements, the correlation coefficients for CSA and CTV showed that these were correlated with single-leg standing, walking speed, standing up test, TUG, SPPB, and two-step test. In some instances of BIA and DXA, CTV showed significantly stronger correlations, whereas CSA did not have significantly stronger correlation (Table 2).

Furthermore, when all groups (normal, low-mass, poor-function, and sarcopenia groups) were compared, CSAs of the quadriceps femoris muscle were significantly smaller in the low-mass and sarcopenia groups (both P < 0.001) for men and significantly smaller in the poor-function (P = 0.11), low-mass (P < 0.001), and sarcopenia (P < 0.001) groups for women (Fig. 1). Conversely, CTVs were significantly smaller in the sarcopenia group (P = 0.044) for men and significantly lower in the poor-function (P = 0.007) and sarcopenia (P < 0.001) groups for women (Fig. 1).

In this study, we investigated which inspection methods were superior for the assessment of motor function including muscle strength and physical performance, in other words, the muscle quality. The result indicated that CSA showed the most correlation with muscle strength, whereas CTV showed the most correlation with physical performance.

The concept of sarcopenia has considerably changed over time, and recently, the EWGSOP2 has stated that the importance of measuring muscle quality is expected to grow as a defining feature of sarcopenia; however, there is no universal consensus on the assessment method for routine clinical practice [8]. Patients with dynapenia and sarcopenia are considered to be at a high risk of falling [3]. Further, in the present study, patients with poor function and sarcopenia had a significantly high risk of falling, which we believe reflected their reduced motor function. There is a physical state in which muscle mass is maintained but with reduced functioning and muscle quality. McGregor et al. [24] referred that not only changes in muscle mass but also other factors underpinning muscle quality including composition, metabolism, aerobic capacity, insulin resistance, fat infiltration, fibrosis, and neural activation may play a role in the decline in muscle function and impaired mobility associated with aging.

To date, muscle quality is determined by evaluating intramuscular fat infiltration using highly sensitive measurement devices such as CT and MRI [25]. Moreover, in the recent years, muscle quality has been evaluated using ultrasound; however, there is no consensus for any of these assessments. There are few reports wherein CT of the mid-thigh has been used to evaluate the relationship of CSA and CTV using motor function. The present study was performed to evaluate the muscle quality by CTV and its relationship with motor function.

In the evaluation of simple muscle strength such as grip and quadriceps femoris muscle strength, we found the strongest correlation with CSA in all subjects. Furthermore, in the evaluation of physical performance test that combined physical movement (single-leg standing, walking speed, stand-up test, TUG, SPPB, and two-step test), the highest correlation was observed with CTV, and some test showed significant stronger correlation with CTV suggesting that physical performance could be evaluated using CTV.

Lang et al. [26] reported that a low CTV of the thigh indicated a higher risk of fall and hip fracture; the results of the present study are consistent with these results. In normal and low-mass group, there was no decrease in CTV, whereas the poor-function and sarcopenia groups showed a significant decline in CTV. Therefore, we believe that this indicated that reduced motor function was caused by the reduced muscle quality in patients with poor function and sarcopenia. In this study, we classified patients into four groups according to muscle mass and motor function; this classification method including an evaluation of muscle quality may be useful in assessing functional status in the aging population.

Ikemoto-Uezumi et al. [17] compared tissue in the vastus medialis muscle of patients with osteoarthritis and reported that intramuscular adipose tissue (IMAT) and an increased proportion of interstitial tissue were observed. Thus, a decline in CTV with an increased proportion of IMAT was associated with intramuscular fat infiltration [27]. Similarly, in sarcopenia, increased IMAT is observed [16], and owing to changes in muscle tissue, CTV is decreased. Reportedly, increased IMAT measured by MRI is a prognostic factor of gait ability [28], and IMAT is increased in young adults with reduced physical activity [29]. Therefore, reduced physical performance and activity could lead to increased IMAT.

As a minimally invasive tool, CT is considered as a gold standard to measure muscle mass; however, it is not used in general practice owing to the high costs, poor portability, and requirement of an experienced operator [15]. In patients with cancer, reduced muscle mass is an independent predictor of immobility and mortality [30]. Kasai et al. [31] reported that among the muscles in the mid-thigh CT, CSA decreased with age mainly in quadriceps femoris. Schweitzer et al. [32] reported that on MRI, the best estimates for skeletal muscle were shown in the thigh. CT of the femur was a useful method to evaluate muscle mass for the entire body [33].

Compared with other test equipment, DXA showed no change with age among Asian women [11]. Recently, we reported significant associations of thigh CT CSA with muscle strength [34].

For BIA, changes associated with the physical condition such as fluid balance and body temperature fluctuated during the day, resulting in reduced accuracy of BIA [35]. CT could be a better form of assessment because of its accuracy, reproducibility, and objectivity; it also enables the simultaneous measurement of the muscle mass and quality [36]. CT is useful in diagnosing the severity of sarcopenia by simultaneously evaluating CSA and CTV. Regarding the amount of radiation exposure, as only a single slice is scanned, we consider that there is no problem in terms of the radiation levels [10]. In addition single slice leg CT scanning takes only about five minutes.

There were limitations to the present study. First, the sample size was relatively small. Second, this was a cross-sectional study and changes caused by natural progress or therapeutic intervention could not be evaluated. Further study is required to determine whether or not the changes occurred as a result of exercise therapy, nutritional guidance, and pharmacotherapy. Third, this study did not include large-scale data of CSA and CTV from each age group of the general population without sarcopenia, and therefore, the healthy control information was weak. Thus, analysis using a large-scale epidemiological study is required.

As noted in the EWGSOP2, our results showed that CT may be used to diagnose sarcopenia more accurately and understand the pathology in greater detail [8].

This study was the first to report a relationship between mid-thigh CT and motor function in clinical setting. CT allows CSA and CTV to be measured simultaneously; CSA showed the most association with muscle strength, whereas CTV showed the most association with physical performance. Thereby enabling the precise evaluation of muscle mass and muscle quality, which is useful for diagnosing and considering severity of sarcopenia, low mass, and poor function. These results could be useful for the confirmation of the diagnosis of sarcopenia.

AWGS: Asia Working Group of Sarcopenia

BIA: Bioelectrical Impedance Analysis

CSA: Cross-Sectional Area

CT: Computed Tomography

CTV: CT Attenuation Value

DXA: Dual Energy X-ray Absorption

EWGSOP: European Working Group on Sarcopenia in Older People

MRI: Magnetic Resonance Imaging

SMI: Skeletal Mass Index

SPPB: Short Physical Performance Battery

TUP: Timed Up and Go

Ethics approval and consent to participate

The study was conducted with the approval of the Ethical Review Board of the National Center for Geriatrics and Gerontology, Japan and with the written consent of all the participants.

Consent for publication

Not applicable

Availability of data and materials

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests

Funding

This work was supported by a grant from Expenses for Research and Development of Geriatrics and Gerontology (26-12, 29-12) and Furuno Electronics; the funding agencies played no role in the study.

Authors’ contributions

HO analyzed and interpreted the participants date. YM suggested this study’s concept and design. HA supervised this study. YS analyzed mid-thigh CT date and calculated CSA and CTV. SY supervised about statistical analysis. TW, HI, TM, SI, HH and SI advised study design and results.

All authors read and approved the final manuscript.

Acknowledgements

We would like to express our gratitude to everyone who cooperated in the study at National Center for Geriatrics and Gerontology.

Rosenberg IH. Symposium: Sarcopenia: Diagnosis and Mechanisms Sarcopenia: Origins and Clinical Relevance 1. https://academic.oup.com/jn/article-abstract/127/5/990S/4724144.
Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol. 1998;147(8):755-63 doi: 10.1093/oxfordjournals.aje.a009520.
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 A Biol Sci Med Sci. 2018;73(9):1199-204 doi: 10.1093/gerona/glx245,
Alley DE, Shardell MD, Peters KW, McLean RR, Dam TT, Kenny AM, et al. Grip strength cutpoints for the identification of clinically relevant weakness. J Gerontol A Biol Sci Med Sci. 2014;69(5):559-66 doi: 10.1093/gerona/glu011.
Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39(4):412-23 doi: 10.1093/ageing/afq034.
Morley JE, Abbatecola AM, Argiles JM, Baracos V, Bauer J, Bhasin S, et al. Sarcopenia with limited mobility: an international consensus. J Am Med Dir Assoc. 2011;12(6):403-9 doi: 10.1016/j.jamda.2011.04.014.
Chen LK, Liu L, Woo J, Assantachai P, Auyeung T, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian working group for sarcopenia. J Am Med Dir Assoc. 2014;15(2):95-101 doi: 10.1016/j.jamda.2013.11.025.
Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16-31. doi:10.1093/ageing/afy169.
Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah SK, et al. Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15(2):95-101. doi: 10.1016/j.jamda.2013.11.025.
Buckinx F, Landi F, Cesari M, Fielding RA, Visser M, Engelke K, et al. Pitfalls in the measurement of muscle mass: a need for a reference standard. J Cachexia Sarcopenia Muscle. 2018;9(2):269-78 doi: 10.1002/jcsm.12268.
Shimokata H, Ando F, Yuki A, Otsuka R. Age-related changes in skeletal muscle mass among community-dwelling Japanese: A 12-year longitudinal study. Geriatr Gerontol Int. 2014;14;Suppl 1:85-92 doi: 10.1111/ggi.12219.
Gonzalez MC, Heymsfield SB. Bioelectrical impedance analysis for diagnosing sarcopenia and cachexia: what are we really estimating? J Cachexia Sarcopenia Muscle. 2017;8(2):187-9 doi: 10.1002/jcsm.12159.
Mourtzakis M, Prado CM, Lieffers JR, Reiman T, McCargar LJ, Baracos VE. A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl Physiol Nutr Metab. 2008;33(5):997-1006 doi: 10.1139/H08-075.
Beaudart C, Rolland Y, Cruz-Jentoft AJ, Bauer JM, Sieber C, Cooper C, et al. Assessment of muscle function and physical performance in daily clinical practice. Calcif Tissue Int. 2019;105(1):1-14 doi: 10.1007/s00223-019-00545-w.
Beaudart C, McCloskey E, Bruyère O, Cesari M, Rolland Y, Rizzoli R, et al. Sarcopenia in daily practice: assessment and management. BMC Geriatr. 2016;16(1):170 doi: 10.1186/s12877-016-0349-4.
Goodpaster BH, Kelley DE, Thaete FL, He J, Ross R. Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content. J Appl Physiol (1985). 2000;89(1):104-10 doi: 10.1152/jappl.2000.89.1.104.
Ikemoto-Uezumi M, Matsui Y, Hasegawa M, Fujita R, Kanayama Y, Uezumi A, et al. Disuse atrophy accompanied by intramuscular ectopic \adipogenesis in vastus medialis Musclevastus medialis muscle of advanced osteoarthritis patients. Am J Pathol. 2017;187(12):2674-85 doi: 10.1016/j.ajpath.2017.08.009.
Toba K, Kikuchi R, Iwata A, Kozaki K. "Fall risk index” helps clinicians identify high-risk individuals. Jpn Med Assoc J. 2009;52:237-42.
Matsui Y, Fujita R, Harada A, Sakurai T, Nemoto T, Noda N, Toba K. Association of grip strength and related indices with independence of activities of daily living in older adults, investigated by a newly-developed grip strength measuring device. Geriatr Gerontol Int. 2014;14;Suppl 2:77-86 doi: 10.1111/ggi.12262.
Fujita R, Matsui Y, Harada A, Takemura M, Kondo I, Nemoto T, et al. Does the Q − H index show a stronger relationship than the H:Q ratio in regard to knee pain during daily activities in patients with knee osteoarthritis? J Phys Ther Sci. 2016;28:3320-4 doi: 10.1589%2Fjpts.28.3320.
Nakamura K, Ogata T. Locomotive syndrome: Definition and Management. Clin Rev Bone Miner Metab. 2016;14:56-67. doi: 10.1007%2Fs12018-016-9208-2.
Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home Admission.nursing home admission. J Gerontol. 1994;49:85-94 doi: 10.1093/geronj/49.2.M85.
Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16-31 doi: 10.1093%2Fageing%2Fafy169.
McGregor RA, Cameron-Smith D, Poppitt SD. It is not just muscle mass: A review of muscle quality, composition and metabolism during ageing as determinants of muscle function and mobility in later life. Longev Heal. 2014;3:1-8.
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(4):355-66 doi: 10.1017/S0029665115000129.
Lang T, Cauley JA, Tylavsky F, Bauer D, Cummings S, Harris TB, Health ABC Study. Computed tomographic measurements of thigh muscle cross-sectional area and attenuation coefficient predict hip fracture: the health, aging, and body composition study. J Bone Miner Res. 2010;25(3):513-9 doi: 10.1359/jbmr.090807.
Aubrey J, Esfandiari N, Baracos VE, Buteau FA, Frenette J, Putman CT, et al. Measurement of skeletal muscle radiation attenuation and basis of its biological variation. Acta Physiol. 2014;210(3):489-97 doi: 10.1111/apha.12224.
Marcus RL, Addison O, Dibble LE, Foreman KB, Morrell G, Lastayo P. Intramuscular adipose tissue, sarcopenia, and mobility function in older individuals. J Aging Res. 2012;2012:629637 doi: 10.1155/2012/629637.
Manini TM, Clark BC, Nalls MA, Goodpaster BH, Ploutz-Snyder LL, Harris TB, et al. Reduced physical activity increases intermuscular adipose tissue in healthy young adults. Am J Clin Nutr. 2007;85(2):377-84 doi: 10.1093/ajcn/85.2.377.
Fearon K, Strasser F, Anker SD, Bosaeus I, Bruera E, Fainsinger RL, et al. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011;12(5):489-95 doi: 10.1016/S1470-2045(10)70218-7.
Kasai T, Ishiguro N, Matsui Y, Harada A, Takemura M, Yuki A, et al. Sex- and age-related differences in mid-thigh composition and muscle quality determined by computed tomography in middle-aged and elderly Japanese. Geriatr Gerontol Int. 2015;15(6):700-6 doi: 10.1111/ggi.12338.
Schweitzer L, Geisler C, Pourhassan M, Braun W, Glüer CC, Bosy-Westphal A, Müller MJ. What is the best reference site for a single MRI slice to assess whole body skeletal muscle and adipose tissue volumes in healthy adults? Am J Clin Nutr. 2015;102(1):58-65 doi: 10.3945/ajcn.115.111203.
Lee SJ, Janssen I, Heymsfield SB, Ross R. Relation between whole-body and regional measures of human skeletal muscle. Am J Clin Nutr. 2004;80(5):1215-21 doi: 10.1093/ajcn/80.5.1215.
Tsukasaki K, Matsui Y, Arai H, Harada A, Tomida M, Takemura M, et al. Association of muscle strength and gait speed with cross-sectional muscle area determined by mid-thigh computed tomography - a comparison with skeletal muscle mass measured by dual-energy x-ray absorptiometry. J Frailty Aging. 2020;9(2):2019 doi: 10.14283/jfa.2020.16.
Leenders M, Verdijk LB, van der Hoeven L, van Kranenburg J, Nilwik R, van Loon LJ. Elderly men and women benefit equally from prolonged resistance-type exercise training. J Gerontol A Biol Sci Med Sci. 2013;68(7):769-79 doi: 10.1093/gerona/gls241.
Goodpaster BH, Thaete FL, Kelley DE. Composition of skeletal muscle evaluated with computed tomography. Ann N Y Acad Sci. 2000;904:18-24 doi: 10.1111/j.1749-6632.2000.tb06416.x.

Download PDF

Journal Publication

published 13 Apr, 2021

Read the published version in BMC Geriatrics →

Review #3 received at journal
30 Oct, 2020
Reviewer #3 agreed at journal
22 Oct, 2020
Review #1 received at journal
28 Sep, 2020
Reviewer #2 agreed at journal
17 Sep, 2020
Reviewer #1 agreed at journal
07 Sep, 2020
Reviewers invited by journal
04 Sep, 2020
Submission checks completed at journal
27 Aug, 2020
Editor invited by journal
27 Aug, 2020
Editor assigned by journal
25 Aug, 2020
First submitted to journal
22 Aug, 2020

You are reading this older preprint version

Read the latest preprint version →

Assessment of Muscle Quality and Quantity for the Diagnosis of Sarcopenia Using Mid-Thigh Computed Tomography : A Cohort Study

Status:

Journal Publication

Version 1

Abstract

Figures

Key Points

Background

Methods

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Status:

Journal Publication

Version 1