Department of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195, USA.
Department of Vascular Surgery, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195, USA.
Ultrasonics. 2023 Feb;128:106861. doi: 10.1016/j.ultras.2022.106861. Epub 2022 Oct 8.
Carotid atherosclerotic plaque composition may be an important indication of patient risk for future cerebrovascular events. Ultrasound spectral analysis has the potential to provide a robust measure of plaque composition in vivo if the backscatter transfer function can be sufficiently isolated from the effects of attenuation from overlying tissue, receive and transmit transfer functions from the ultrasound system and transducer, and diffraction. This study examines the usefulness of the nonlinearly generated second harmonic portion of the backscatter signal and the effects of a variety of attenuation compensation techniques for noninvasively characterizing human carotid plaque using spectral analysis and machine learning. Post-beamformed ultrasound backscatter radiofrequency (RF) data were acquired from 6 normal subjects and 119 carotid endarterectomy patients prior to surgery. Plaque obtained following surgery was histologically processed, and regions of interest (ROI) corresponding to homogenous tissue types (fibrous/fibro-lipidic, hemorrhagic and/or necrotic core and calcified) were selected from RF data. Both the harmonic and fundamental power spectra for each ROI was obtained and normalized by data from a uniform phantom (0.5 dB/cm-MHz slope of attenuation). Additional attenuation compensation approaches were compared to simply using the reference phantom: (1) optimum power spectral shift estimation, (2) one-step adventitial, or (3) two-step adventitial. Spectral parameters extracted from both the fundamental and harmonic estimates of the backscatter transfer function of 363 ROI's from 152 plaque specimens were used to train and test random forest and support vector machine classification models. The best results came from using spectral parameters derived from both the fundamental and second harmonic bands with a predictive accuracy of 65-68%, kappa statistic of 0.49-0.54, and accuracies of 84% for fibrous, 68-74% for hemorrhagic and/or necrotic core, and 78-81% for calcified ROI's. The result indicated that the nonlinearly generated second harmonic portion of backscatter is useful for carotid plaque tissue characterization and that a reference phantom approach with a 0.5 dB/cm-MHz slope of attenuation works as well as more complicated approaches.
颈动脉粥样硬化斑块的成分可能是患者未来脑血管事件风险的一个重要指标。如果能将背散射的传递函数充分地从组织衰减的影响中分离出来，从超声系统和换能器接收和传输传递函数，并克服衍射问题，超声谱分析有可能提供一种对斑块成分进行活体强有力的测量方法。本研究利用非线性产生的背散射信号二次谐波部分和各种衰减补偿技术，通过谱分析和机器学习，研究了无创性描述人颈动脉斑块的有用性。在手术前，从 6 名正常受试者和 119 名颈动脉内膜切除术患者采集了经波束形成后的超声背散射射频（RF）数据。手术获得斑块后，对其进行组织学处理，并从 RF 数据中选择对应于同质组织类型（纤维/纤维脂性、出血和/或坏死核心和钙化）的感兴趣区（ROI）。获得每个 ROI 的谐波和基波功率谱，并通过标准体模（衰减斜率为 0.5dB/cm-MHz）的数据进行归一化。与仅使用参考体模相比，比较了其他几种衰减补偿方法：（1）最佳功率谱偏移估计，（2）一步动脉壁，或（3）两步动脉壁。从 152 个斑块标本的 363 个 ROI 的背散射传递函数的基波和谐波估计中提取的光谱参数，用于训练和测试随机森林和支持向量机分类模型。最佳结果来自于使用来自基波和二次谐波带的光谱参数，其预测准确率为 65-68%，kappa 统计值为 0.49-0.54，纤维组织的准确率为 84%，出血和/或坏死核心的准确率为 68-74%，钙化 ROI 的准确率为 78-81%。结果表明，背散射的非线性产生的二次谐波部分可用于颈动脉斑块组织特征描述，并且具有 0.5dB/cm-MHz 衰减斜率的参考体模方法与更复杂的方法一样有效。
