Adkins Amy N, Murray Wendy M
Department of Biomedical Engineering, Northwestern University; Shirley Ryan AbilityLab; Edward Hines, Jr. VA Hospital.
Department of Biomedical Engineering, Northwestern University; Department of Physical Medicine & Rehabilitation, Northwestern University Feinberg School of Medicine; Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine; Shirley Ryan AbilityLab; Edward Hines, Jr. VA Hospital;
J Vis Exp. 2020 Dec 14(166). doi: 10.3791/61765.
Muscle fascicle length, which is commonly measured in vivo using traditional ultrasound, is an important parameter defining a muscle's force generating capacity. However, over 90% of all upper limb muscles and 85% of all lower limb muscles have optimal fascicle lengths longer than the field-of-view of common traditional ultrasound (T-US) probes. A newer, less frequently adopted method called extended field-of-view ultrasound (EFOV-US) can enable direct measurement of fascicles longer than the field-of-view of a single T-US image. This method, which automatically fits together a sequence of T-US images from a dynamic scan, has been demonstrated to be valid and reliable for obtaining muscle fascicle lengths in vivo. Despite the numerous skeletal muscles with long fascicles and the validity of the EFOV-US method for making measurements of such fascicles, few published studies have utilized this method. In this study, we demonstrate both how to implement the EFOV-US method to obtain high quality musculoskeletal images and how to quantify fascicle lengths from those images. We expect that this demonstration will encourage the use of the EFOV-US method to increase the pool of muscles, both in healthy and impaired populations, for which we have in vivo muscle fascicle length data.
肌肉束长度通常在体内使用传统超声进行测量,是定义肌肉力量产生能力的一个重要参数。然而,超过90%的上肢肌肉和85%的下肢肌肉的最佳肌肉束长度长于普通传统超声(T-US)探头的视野范围。一种更新的、较少采用的方法,称为扩展视野超声(EFOV-US),可以直接测量长于单个T-US图像视野范围的肌肉束。这种方法能自动拼接动态扫描得到的一系列T-US图像,已被证明在体内获取肌肉束长度方面是有效且可靠的。尽管有众多具有长肌肉束的骨骼肌,且EFOV-US方法在测量此类肌肉束方面具有有效性,但很少有已发表的研究使用该方法。在本研究中,我们展示了如何实施EFOV-US方法以获得高质量的肌肉骨骼图像,以及如何从这些图像中量化肌肉束长度。我们期望这一展示将鼓励使用EFOV-US方法,以增加我们拥有体内肌肉束长度数据的健康和受损人群的肌肉数量。