Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China; Sichuan Digital Economy Industry Development Research Institute, Chengdu, Sichuan 610036, China.
Ultrasonics. 2024 Apr;139:107274. doi: 10.1016/j.ultras.2024.107274. Epub 2024 Feb 27.
Numerous quantitative ultrasound imaging techniques have demonstrated superior monitoring performance for thermal ablation when compared to conventional ultrasonic B-mode imaging. However, the absence of comparative studies involving various quantitative ultrasound imaging techniques hinders further clinical exploration. In this study, we simultaneously reconstructed ultrasonic Nakagami imaging, ultrasonic horizontally normalized Shannon entropy (hNSE) imaging, and ultrasonic differential attenuation coefficient intercept (DACI) imaging from ultrasound backscattered envelope data collected during high-intensity focused ultrasound ablation treatment. We comprehensively investigated their performance differences through qualitative and quantitative analyses, including the calculation of contrast-to-noise ratios (CNR) for ultrasonic images, receiver operating characteristic (ROC) analysis with corresponding indicators, the analysis of lesion area fitting relationships, and computational time consumption comparison. The mean CNR of hNSE imaging was 10.98 ± 4.48 dB, significantly surpassing the 3.82 ± 1.40 dB (p < 0.001, statistically significant) of Nakagami imaging and the 2.45 ± 0.74 dB (p < 0.001, statistically significant) of DACI imaging. This substantial difference underscores that hNSE imaging offers the highest contrast resolution for lesion recognition. Furthermore, we evaluated the ability of multiple ultrasonic parametric imaging to detect thermal ablation lesions using ROC curves. The area under the curve (AUC) for hNSE was 0.874, exceeding the values of 0.848 for Nakagami imaging and 0.832 for DACI imaging. Additionally, hNSE imaging exhibited the strongest linear correlation coefficient (R = 0.92) in the comparison of lesion area fitting, outperforming Nakagami imaging (R = 0.87) and DACI imaging (R = 0.85). hNSE imaging also performs best in real-time monitoring with each frame taking 6.38 s among multiple ultrasonic parametric imaging. Our findings unequivocally demonstrate that hNSE imaging excels in monitoring HIFU ablation treatment and holds the greatest potential for further clinical exploration.
许多定量超声成像技术在监测热消融方面的表现优于传统超声 B 模式成像。然而,由于缺乏涉及各种定量超声成像技术的比较研究,限制了进一步的临床探索。在本研究中,我们同时从高强度聚焦超声消融治疗过程中采集的超声背散射包络数据中重建超声 Nakagami 成像、超声水平归一化 Shannon 熵(hNSE)成像和超声差分衰减系数截距(DACI)成像。我们通过定性和定量分析全面研究了它们的性能差异,包括计算超声图像的对比噪声比(CNR)、基于对应指标的接收机工作特征(ROC)分析、病变面积拟合关系的分析以及计算时间消耗的比较。hNSE 成像的平均 CNR 为 10.98±4.48dB,明显优于 Nakagami 成像的 3.82±1.40dB(p<0.001,具有统计学意义)和 DACI 成像的 2.45±0.74dB(p<0.001,具有统计学意义)。这一显著差异表明 hNSE 成像在病变识别方面具有最高的对比度分辨率。此外,我们还使用 ROC 曲线评估了多种超声参数成像检测热消融病变的能力。hNSE 的曲线下面积(AUC)为 0.874,超过了 Nakagami 成像的 0.848 和 DACI 成像的 0.832。此外,在病变面积拟合的比较中,hNSE 成像表现出最强的线性相关系数(R=0.92),优于 Nakagami 成像(R=0.87)和 DACI 成像(R=0.85)。在多种超声参数成像中,hNSE 成像的实时监测性能也最好,每个帧的处理时间为 6.38s。我们的研究结果明确表明,hNSE 成像在监测 HIFU 消融治疗方面表现出色,具有最大的临床探索潜力。