Imaging of Sarcopenia in Rheumatoid Arthritis: State of the Art
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摘要:
类风湿关节炎(RA)早期便可并发肌少症,肌少症可增加RA患者骨质疏松、骨折等疾病的风险。RA患者处于活动期时,力量和功能的评估受限于关节活动,因此对肌肉量及肌肉质量的评估尤为重要。影像学检查技术可定量评估RA患者的肌肉量及肌肉质量,是诊断RA相关肌少症的重要手段。本文旨在对各种影像学技术在RA相关肌少症中的研究进展进行总结。
Abstract:Early-stage rheumatoid arthritis (RA) often harbors a hidden threat: sarcopenia, a silent contributor to osteoporosis and fractures. Assessing muscle mass and quality, particularly during active RA periods when joint mobility hinders strength and function evaluations, becomes crucial. Imaging techniques emerge as invaluable tools in this diagnostic puzzle, offering accurate quantification of muscle status in RA patients. This article delves into advancements of various imaging modalities in unraveling RA-related sarcopenia.
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Keywords:
- rheumatoid arthritis /
- sarcopenia /
- imaging techniques
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表 1 RA相关肌少症的影像学评估方法
Table 1 Comparison of imaging methods for sarcopenia assessment in rheumatoid arthritis
影像学检
查技术常用检查部位
或测量点常用测量指标或参数 优点 缺点 DXA 四肢(双上肢+双下肢) ALM、ALMI 应用广,快速、成本低、辐射剂量低、有确定的临界值 受患者体内水分变化的影响,难以对肌肉质量评估、难以准确测定躯干肌肉 CT 测定部位不统一,大腿中部层面应用广泛 肌肉量:SMA、SMI
肌肉质量:IMAT、SMD金标准,定量测量不同层面或区域的肌肉和脂肪组织,扫描仪器较小、扫描时间较短及辐射剂量较低 临界值争议大,无法准确区分IMAT和IntraMAT,辐射量较大 MRI 测定部位不统一,大腿中部层面应用广泛 肌肉量:SMA、SMI
肌肉质量:Dixon技术为最常用的定量测定脂肪的方法、DTI及MRE可评估肌纤维结构的微观变化等金标准,无辐射、多参数和软组织分辨率高的优势,且更好的区分IMAT和IntraMAT 其成本高、禁忌症多、扫描和后处理时间,缺乏标准化的成像方案和测定指标 US 测定部位不统一,股四头肌(尤股直肌) 肌肉量:肌肉厚度、横截面积、肌肉体积
肌肉质量:肌束长度、羽状角;回声强度、肌肉弹性、肌肉收缩潜力初筛,便携、快速、禁忌症少、无辐射 受患者检查体位、肌肉收缩状态及操作者探头位置、压力、倾斜角等影响,指标的临界点不明确 注:DXA:双能X线吸收测定法;ALM:四肢瘦体重;ALMI:四肢瘦体重指数;CT:计算机断层扫描;SMA:骨骼肌横截面积;SMI:骨骼肌指数;IMAT:肌间脂肪组织;SMD:骨骼肌密度;IntraMAT:肌内脂肪组织;MRI:磁共振成像;Dixon技术:水-脂分离技术;DTI:扩散峰度成像;MRE:磁共振弹性成像;US:超声。 -
[1] 耿研, 谢希, 王昱, 等. 类风湿关节炎诊疗规范[J]. 中华内科杂志, 2022, 61(1): 51−59. DOI: 10.3760/cma.j.cn112138-20210616-00426. GENG Y, XIE X, WANG Y, et al. The standardized diagnosis and treatment of rheumatoid arthritis[J]. Chinese Journal of Internal Medicine, 2022, 61(1): 51−59. DOI: 10.3760/cma.j.cn112138-20210616-00426. (in Chinese).
[2] JIN S, LI M, FANG Y, et al. Chinese Registry of rheumatoid arthritis (CREDIT): II. prevalence and risk factors of major comorbidities in Chinese patients with rheumatoid arthritis[J]. Arthritis research & therapy, 2017, 19(1): 1−8. DOI: 10.1186/s13075-017-1457-z.
[3] AN H J, TIZAOUI K, TERRAZZINO S, et al. Sarcopenia in autoimmune and rheumatic diseases: A comprehensive review[J]. International Journal of Molecular Sciences, 2020, 21(16): 5678. DOI:10.3390/ ijms21165678.
[4] ROSENBERG, IRWIN H. Symposium: arcopenia: diagnosis and mechanisms sarcopenia: origins and clinical relevance[J]. Journal of Nutrition, 1997, 127(5): 990S−991S. DOI: 10.1093/jn/127.5.990S.
[5] TONG J, XU S, WANG J, et al. Interactive effect of sarcopenia and falls on vertebral osteoporotic fracture in patients with rheumatoid arthritis[J]. Archives of Osteoporosis, 2021, 16(1): 1−9. DOI: 10.1007/s11657-021-01017-1.
[6] TADA M, YAMADA Y, MANDAI K, et al. Osteosarcopenia synergistically increases the risk of falls in patients with rheumatoid arthritis[J]. Osteoporosis and Sarcopenia, 2021, 7(4): 140−145. DOI: 10.1016/j.afos.2021.11.002.
[7] ANDONIAN B J, HUFFMAN K M. Skeletal muscle disease in rheumatoid arthritis: The center of cardiometabolic comorbidities?[J]. Current Opinion in Rheumatology, 2020, 32(3): 297−306. DOI:10.1097/ BOR.0000000000000697.
[8] CRUZ-JENTOFT A J, BAEYENS J P, BAUER J M, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People[J]. Age and Ageing, 2010, 39(4): 412−423. DOI: 10.1093/ageing/afy169.
[9] CORREA-de-ARAUJO R, ADDISON O, MILJKOVIC I, et al. Myosteatosis in the context of skeletal muscle function deficit: An interdisciplinary workshop at the national institute on aging[J]. Frontiers in Physiology, 2020, 11: 963. DOI: 10.3389/fphys.2020.00963.
[10] FARROW M, BIGLANDS J, TANNER S, et al. Muscle deterioration due to rheumatoid arthritis: Assessment by quantitative MRI and strength testing[J]. Rheumatology, 2021, 60(3): 1216−1225. DOI: 10.1093/rheumatology/keaa364.
[11] LETAROUILLY J G, FLIPO R M, CORTET B, et al. Body composition in patients with rheumatoid arthritis: A narrative literature review[J]. Therapeutic Advances in Musculoskeletal Disease, 2021, 13: 1759720X211015006. DOI: 10.1177/1759720X211015006.
[12] SHIN A, CHOI S R, HAN M, et al. Association between sarcopenia defined as low lean mass by dual-energy X-ray absorptiometry and comorbidities of rheumatoid arthritis: Results of a nationwide cross-sectional health examination[J/OL]. Seminars in Arthritis and Rheumatism, 2022, 57: 152090. DOI: 10.1016/j.semarthrit.2022.152090.
[13] MOSCHOU D, KRIKELIS M, GEORGAKOPOULOS C, et al. Sarcopenia in rheumatoid arthritis: A narrative review[J/OL]. Journal of Frailty, Sarcopenia and Falls, 2023, 8(1): 44-52. DOI: 10.22540/JFSF-08-044.
[14] BHASIN S, TRAVISON T G, MANINI T M, et al. Sarcopenia definition: The position statements of the sarcopenia definition and outcomes consortium[J]. Journal of the American Geriatrics Society, 2020, 68(7): 1410−1418. DOI: 10.1111/jgs.16372.
[15] TOLONEN A, PAKARINEN T, SASSI A, et al. Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review[J]. European Journal of Radiology, 2021, 145: 109943. DOI: 10.1016/j.ejrad.2021.109943.
[16] KHOJA S S, PATTERSON C G, GOODPASTER B H, et al. Skeletal muscle fat in individuals with rheumatoid arthritis compared to healthy adults[J]. Experimental Gerontology, 2020, 129: 110768. DOI: 10.1016/j.exger.2019.110768.
[17] DERSTINE B A, HOLCOMBE S A, ROSS B E, et al. Skeletal muscle cutoff values for sarcopenia diagnosis using T10 to L5 measurements in a healthy US population[J]. Scientific Reports, 2018, 8(1): 1−8. DOI: 10.1038/s41598-018-29825-5.
[18] MOLWITZ I, LEIDERER M, McDONOUGH R, et al. Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging[J]. European Radiology, 2021, 31(10): 7529−7539. DOI: 10.1007/s00330-021-07820-1.
[19] VILLEDON de NAIDE M, PEREIRA B, COURTEIX D, et al. Assessment of intramuscular fat and correlation with body composition in patients with rheumatoid arthritis and spondyloarthritis: A pilot study[J]. Nutrients, 2021, 13(12): 4533. DOI: 10.3390/nu13124533.
[20] ROOS F, FANKHAUSER N, COLLET T H, et al. Peripheral volumetric muscle area and total body volume in postmenopausal women with rheumatoid arthritis[J]. Journal of Clinical Densitometry, 2021, 24(4): 613−621. DOI: 10.1016/j.jocd.2020.11.004.
[21] CHOW S K H, van MOURIK M, HUNG V W Y, et al. Hr-pqct for the evaluation of muscle quality and intramuscular fat infiltration in ageing skeletal muscle[J]. Journal of Personalized Medicine, 2022, 12(6): 1016. DOI: 10.3390/jpm12061016.
[22] HINKLEY J M, CORNNELL H H, STANDLEY R A, et al. Older adults with sarcopenia have distinct skeletal muscle phosphodiester, phosphocreatine, and phospholipid profiles[J]. Aging Cell, 2020, 19(6): e13135. DOI: 10.1111/acel.13135.
[23] IWAYAMA K, TANABE Y, TANJI F, et al. Diurnal variations in muscle and liver glycogen differ depending on the timing of exercise[J]. The Journal of Physiological Sciences, 2021, 71(1): 1−8. DOI: 10.1186/s12576-021-00821-1.
[24] FRIEDBERGER A, FIGUEIREDO C, GRIMM A, et al. Quantification of hand muscle volume and composition in patients with rheumatoid arthritis, psoriatic arthritis and psoriasis[J]. BMC Musculoskeletal Disorders, 2020, 21(1): 1−11. DOI: 10.1186/s12891-020-03194-5.
[25] RAN J, DAI B, LIU C, et al. The diagnostic value of T2 map, diffusion tensor imaging, and diffusion kurtosis imaging in differentiating dermatomyositis from muscular dystrophy[J]. Acta Radiologica, 2022, 63(4): 467−473. DOI: 10.1177/0284185121999006.
[26] KENNEDY P, BARNHILL E, GRAY C, et al. Magnetic resonance elastography (MRE) shows significant reduction of thigh muscle stiffness in healthy older adults[J]. GeroScience, 2020, 42(1): 311−321. DOI: 10.1007/s11357-019-00147-2.
[27] PERKISAS S, BAUDRY S, BAUER J, et al. Application of ultrasound for muscle assessment in sarcopenia: towards standardized measurements[J]. European Geriatric Medicine, 2018, 9(6): 739−757. DOI: 10.1007/s41999-018-0104-9.
[28] PERKISAS S, BASTIJNS S, BAUDRY S, et al. Application of ultrasound for muscle assessment in sarcopenia: 2020 SARCUS update[J]. European Geriatric Medicine, 2021, 12(1): 45−59 DOI: 10.1007/s41999-020-00433-9.
[29] NIES I, ACKERMANS L, POEZE M, et al. The diagnostic value of ultrasound of the rectus femoris for the diagnosis of sarcopenia in adults: A systematic review[J]. Injury, 2022, 53: 23−29. DOI: 10.1016/j.injury.2022.06.004.
[30] BARBOSA-SILVA T G, GONZALEZ M C, BIELEMANN R M, et al. 2+2(+2)=4: A new approach for appendicular muscle mass assessment by ultrasound[J]. Nutrition, 2021, 83: 111056. DOI: 10.1016/j.nut.2020.111056.
[31] ALFURAIH A M, TAN A L, O’CONNOR P, et al. Muscle stiffness in rheumatoid arthritis is not altered or associated with muscle weakness: A shear wave elastography study[J]. Modern Rheumatology, 2020, 30(4): 617−625. DOI: 10.1080/14397595.2019.1645374.
[32] CHENG D T H, LEE K Y S, AHUJA A T, et al. Sonographic assessment of swallowing in irradiated nasopharyngeal carcinoma patients[J]. The Laryngoscope, 2018, 128(11): 2552−2559. DOI: 10.1002/lary.27222.
[33] MENESES A L, NAM M C Y, BAILEY T G, et al. Skeletal muscle microvascular perfusion responses to cuff occlusion and submaximal exercise assessed by contrast-enhanced ultrasound: The effect of age[J]. Physiological Reports, 2020, 8(19): e14580. DOI: 10.14814/phy2.14580.
[34] RUBY L, KUNUT A, NAKHOSTIN D N, et al. Speed of sound ultrasound: Comparison with proton density fat fraction assessed with Dixon MRI for fat content quantification of the lower extremity[J]. European Radiology, 2020, 30(10): 5272−5280. DOI: 10.1007/s00330-020-06885-8.
[35] MIYATAKE Y, MISHIMA Y, TSUTSUMI R, et al. Assessment of insulin resistance in the skeletal muscle of mice using positron emission tomography/computed tomography imaging[J]. Biochemical and Biophysical Research Communications, 2020, 528(3): 499−505. DOI: 10.1016/j.bbrc.2020.05.165.
[36] HADDOCK B, HOLM S, POULSEN J M, et al. Assessment of muscle function using hybrid PET/MRI: Comparison of 18F-FDG PET and T2-weighted MRI for quantifying muscle activation in human subjects[J]. European Journal of Nuclear Medicine and Molecular Imaging, 2017, 44(4): 704−711. DOI: 10.1007/s00259-016-3507-1.
[37] LEE Y S, HONG N, WITANTO J N, et al. Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment[J]. Clinical Nutrition, 2021, 40(8): 5038−5046. DOI: 10.1016/j.clnu.2021.06.025.
[38] NACHIT M, HORSMANS Y, SUMMERS R M, et al. AI-based CT body composition identifies myosteatosis as key mortality predictor in asymptomatic adults[J]. Radiology, 2023, 307(5): e222008. DOI: 10.1148/radiol.222008.
[39] KIM K, GU Y, WANG C Y, et al. Quantification of creatine kinase reaction rate in mouse hindlimb using phosphorus‐31 magnetic resonance spectroscopic fingerprinting[J]. NMR in Biomedicine, 2021, 34(2): e4435. DOI: 10.1002/nbm.4435.
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