Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA; Department of Ultrasound, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
Ultrasound Med Biol. 2022 Nov;48(11):2292-2301. doi: 10.1016/j.ultrasmedbio.2022.06.022. Epub 2022 Aug 26.
Accurate detection of liver steatosis is important for liver disease management. Ultrasound attenuation coefficient estimation (ACE) has great potential in quantifying liver fat content. The ACE methods commonly assume uniform tissue characteristics. However, in vivo tissues typically contain non-uniform structures, which may bias the attenuation estimation and lead to large standard deviations. Here we propose a series of non-uniform structure detection and removal (NSDR) methods to reduce the impact from non-uniform structures during ACE analysis. The effectiveness of NSDR was validated through phantom and in vivo studies. In a pilot clinical study, ACE with NSDR provided more robust in vivo performance as compared with ACE without NSDR, indicating its potential for in vivo applications.
准确检测肝脂肪变对于肝病管理非常重要。超声衰减系数估计（ACE）在定量肝脂肪含量方面具有很大的潜力。ACE 方法通常假设组织具有均匀的特性。然而，体内组织通常包含不均匀的结构，这可能会使衰减估计产生偏差，并导致较大的标准偏差。在这里，我们提出了一系列非均匀结构检测和去除（NSDR）方法，以减少 ACE 分析过程中非均匀结构的影响。通过体模和体内研究验证了 NSDR 的有效性。在一项初步临床研究中，与不使用 NSDR 的 ACE 相比，使用 NSDR 的 ACE 提供了更稳健的体内性能，表明其在体内应用中的潜力。
