Maurits Natalia Maria, Bollen Anna Elizabeth, Windhausen Alphons, De Jager Aeiko Eppo Jurjen, Van Der Hoeven Johannes Harmen
Groningen University Hospital, Department of Neurology, Groningen, The Netherlands.
Ultrasound Med Biol. 2003 Feb;29(2):215-25. doi: 10.1016/s0301-5629(02)00758-5.
In this study, 145 healthy adults (20 to 94 years old, 69 women) were examined using ultrasound (US) imaging to obtain reference values of muscle parameters that were previously not available. We measured biceps and quadriceps sizes and subcutaneous fat thickness. To quantify muscle aspect, we defined and calculated the muscle aspect parameters muscle density, inhomogeneity and white-area index by digital image analysis. All muscle aspect parameters were found to increase with age, which may be due to age-related muscle replacement by fatty tissue and collagen. Other age-, weight- and gender-dependencies are also discussed. The complete set of muscle parameters was used to differentiate between typical myopathies and neuropathies in a group of 32 patients (24 to 79 years old, 18 women). We were successful in almost completely separating the two types of disorders based on abnormality of muscle aspect parameters alone. These preliminary results show that this set of normal muscle parameters can be used to help diagnose neuromuscular disorders. It will also facilitate follow-up in disease progression and therapy.
在本研究中，使用超声（US）成像检查了145名健康成年人（20至94岁，69名女性），以获取以前无法获得的肌肉参数参考值。我们测量了肱二头肌和股四头肌的大小以及皮下脂肪厚度。为了量化肌肉特征，我们通过数字图像分析定义并计算了肌肉特征参数肌肉密度、不均匀性和白色区域指数。发现所有肌肉特征参数均随年龄增长而增加，这可能是由于与年龄相关的肌肉被脂肪组织和胶原蛋白替代所致。还讨论了其他与年龄、体重和性别相关的因素。在一组32例患者（24至79岁，18名女性）中，使用全套肌肉参数区分典型的肌病和神经病。我们几乎仅基于肌肉特征参数的异常就成功地将这两种类型的疾病完全区分开。这些初步结果表明，这套正常肌肉参数可用于帮助诊断神经肌肉疾病。它还将有助于疾病进展和治疗的随访。
