McKay Marnee J, Weber Kenneth A, Wesselink Evert O, Smith Zachary A, Abbott Rebecca, Anderson David B, Ashton-James Claire E, Atyeo John, Beach Aaron J, Burns Joshua, Clarke Stephen, Collins Natalie J, Coppieters Michel W, Cornwall Jon, Crawford Rebecca J, De Martino Enrico, Dunn Adam G, Eyles Jillian P, Feng Henry J, Fortin Maryse, Franettovich Smith Melinda M, Galloway Graham, Gandomkar Ziba, Glastras Sarah, Henderson Luke A, Hides Julie A, Hiller Claire E, Hilmer Sarah N, Hoggarth Mark A, Kim Brian, Lal Navneet, LaPorta Laura, Magnussen John S, Maloney Sarah, March Lyn, Nackley Andrea G, O'Leary Shaun P, Peolsson Anneli, Perraton Zuzana, Pool-Goudzwaard Annelies L, Schnitzler Margaret, Seitz Amee L, Semciw Adam I, Sheard Philip W, Smith Andrew C, Snodgrass Suzanne J, Sullivan Justin, Tran Vienna, Valentin Stephanie, Walton David M, Wishart Laurelie R, Elliott James M
Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia.
Division of Pain Medicine, Stanford University School of Medicine, Stanford University, Stanford, CA 94304, USA.
J Imaging. 2024 Oct 22;10(11):262. doi: 10.3390/jimaging10110262.
Disorders affecting the neurological and musculoskeletal systems represent international health priorities. A significant impediment to progress in trials of new therapies is the absence of responsive, objective, and valid outcome measures sensitive to early disease changes. A key finding in individuals with neuromuscular and musculoskeletal disorders is the compositional changes to muscles, evinced by the expression of fatty infiltrates. Quantification of skeletal muscle composition by MRI has emerged as a sensitive marker for the severity of these disorders; however, little is known about the composition of healthy muscles across the lifespan. Knowledge of what is 'typical' age-related muscle composition is essential to accurately identify and evaluate what is 'atypical'. This innovative project, known as the MuscleMap, will achieve the first important steps towards establishing a world-first, normative reference MRI dataset of skeletal muscle composition with the potential to provide valuable insights into various diseases and disorders, ultimately improving patient care and advancing research in the field.
影响神经和肌肉骨骼系统的疾病是国际卫生重点关注的问题。新疗法试验取得进展的一个重大障碍是缺乏对疾病早期变化敏感、客观且有效的反应性结局指标。神经肌肉和肌肉骨骼疾病患者的一个关键发现是肌肉成分发生变化，表现为脂肪浸润。通过磁共振成像（MRI）对骨骼肌成分进行量化已成为这些疾病严重程度的敏感标志物；然而，人们对健康肌肉在整个生命周期中的组成知之甚少。了解什么是“典型的”与年龄相关的肌肉组成对于准确识别和评估什么是“非典型的”至关重要。这个名为“肌肉图谱”（MuscleMap）的创新项目将朝着建立世界首个骨骼肌成分规范性参考MRI数据集迈出重要的第一步，该数据集有可能为各种疾病和紊乱提供有价值的见解，最终改善患者护理并推动该领域的研究。
