Oelze Michael L, Mamou Jonathan
IEEE Trans Ultrason Ferroelectr Freq Control. 2016 Feb;63(2):336-51. doi: 10.1109/TUFFC.2015.2513958. Epub 2016 Jan 8.
Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and preclinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.
多年来，包括超声在内的传统医学成像技术一直在不断改进。例如，在肿瘤学中，医学成像的特点是灵敏度高，即能够检测到异常的组织特征，但从图像中对这些组织特征进行分类的能力往往缺乏特异性。因此，每年都会对大量具有可疑图像结果的组织进行活检，其中绝大多数活检结果为阴性。为了提高癌症成像的特异性，定量成像技术可以发挥重要作用。传统的超声B模式成像本质上主要是定性的。然而，定量超声（QUS）成像可以提供与组织特征相关的具体数值，从而提高图像结果的特异性，进而改善诊断超声。QUS成像可以涵盖多种技术，包括基于频谱的参数化、弹性成像、剪切波成像、血流估计和包络统计。目前，大多数传统临床超声机器上都没有基于频谱的参数化和包络统计功能。然而，近年来，涉及基于频谱的参数化和包络统计的QUS技术在许多应用中都取得了成功，提供了额外的诊断能力。基于频谱的技术包括背向散射系数（BSC）的估计、衰减的估计以及散射体特性的估计，如与有效散射体直径（ESD）相关的相关长度和散射体的有效声浓度（EAC）。包络统计包括散射体数量密度的估计以及组织产生的相干信号与非相干信号的量化。临床应用面临的挑战包括正确考虑衰减效应和传输损耗，以及在临床设备上实现QUS。成功的临床和临床前应用证明了QUS改善医学诊断的能力，包括心动周期中心肌的特征描述、癌症检测、实体瘤和淋巴结的分类、脂肪肝疾病的检测和量化，以及治疗的监测和评估。
