Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Ultrason Imaging. 2024 Mar;46(2):75-89. doi: 10.1177/01617346231226224. Epub 2024 Feb 6.
Quantitative ultrasound (QUS) is an imaging technique which includes spectral-based parameterization. Typical spectral-based parameters include the backscatter coefficient (BSC) and attenuation coefficient slope (ACS). Traditionally, spectral-based QUS relies on the radio frequency (RF) signal to calculate the spectral-based parameters. Many clinical and research scanners only provide the in-phase and quadrature (IQ) signal. To acquire the RF data, the common approach is to convert IQ signal back into RF signal via mixing with a carrier frequency. In this study, we hypothesize that the performance, that is, accuracy and precision, of spectral-based parameters calculated directly from IQ data is as good as or better than using converted RF data. To test this hypothesis, estimation of the BSC and ACS using RF and IQ data from software, physical phantoms and in vivo rabbit data were analyzed and compared. The results indicated that there were only small differences in estimates of the BSC between when using the original RF, the IQ derived from the original RF and the RF reconverted from the IQ, that is, root mean square errors (RMSEs) were less than 0.04. Furthermore, the structural similarity index measure (SSIM) was calculated for ACS maps with a value greater than 0.96 for maps created using the original RF, IQ data and reconverted RF. On the other hand, the processing time using the IQ data compared to RF data were substantially less, that is, reduced by more than a factor of two. Therefore, this study confirms two things: (1) there is no need to convert IQ data back to RF data for conducting spectral-based QUS analysis, because the conversion from IQ back into RF data can introduce artifacts. (2) For the implementation of real-time QUS, there is an advantage to convert the original RF data into IQ data to conduct spectral-based QUS analysis because IQ data-based QUS can improve processing speed.
定量超声（QUS）是一种成像技术，包括基于光谱的参数化。典型的基于光谱的参数包括背散射系数（BSC）和衰减系数斜率（ACS）。传统上，基于光谱的 QUS 依赖于射频（RF）信号来计算基于光谱的参数。许多临床和研究扫描仪仅提供同相和正交（IQ）信号。为了获取 RF 数据，常用的方法是通过与载波频率混合将 IQ 信号转换回 RF 信号。在这项研究中，我们假设直接从 IQ 数据计算出的基于光谱的参数的性能（即准确性和精密度）与使用转换后的 RF 数据一样好或更好。为了验证这一假设，我们分析并比较了使用软件、物理体模和体内兔数据从 RF 和 IQ 数据估算 BSC 和 ACS 的结果。结果表明，使用原始 RF、从原始 RF 导出的 IQ 和从 IQ 重新转换的 RF 估算 BSC 之间仅存在微小差异，即均方根误差（RMSE）小于 0.04。此外，对于使用原始 RF、IQ 数据和重新转换的 RF 创建的 ACS 图，结构相似性指数度量（SSIM）的值大于 0.96。另一方面，与 RF 数据相比，使用 IQ 数据的处理时间大大减少，即减少了两倍以上。因此，本研究证实了两件事：（1）进行基于光谱的 QUS 分析时，无需将 IQ 数据转换回 RF 数据，因为从 IQ 数据转换回 RF 数据可能会引入伪影。（2）对于实时 QUS 的实现，将原始 RF 数据转换为 IQ 数据进行基于光谱的 QUS 分析具有优势，因为 IQ 数据的 QUS 可以提高处理速度。
