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基于高阶奇异值分解的无损超声分子成像

Nondestructive Ultrasound Molecular Imaging With Higher Order Singular Value Decomposition.

作者信息

Collado-Lara Gonzalo, Wahyulaksana Geraldi, Vos Hendrik J, Kooiman Klazina

出版信息

IEEE Trans Ultrason Ferroelectr Freq Control. 2025 Aug;72(8):1095-1107. doi: 10.1109/TUFFC.2025.3578895.

DOI:10.1109/TUFFC.2025.3578895
PMID:40498610
Abstract

Ultrasound molecular imaging (UMI) uses targeted microbubbles (MBs) to detect disease-associated biomarkers. For UMI, distinguishing the acoustic signals produced by bound MBs from those by free MBs and tissue is critical. Currently, the main approach, known as differential targeted enhancement (DTE), is time-intensive and requires MB destruction. Here, we introduce a novel, rapid, and nondestructive UMI technique utilizing higher order singular value decomposition (HOSVD). HOSVD decomposes the signals of an acoustic contrast sequence, separating them owing to their nonlinear content and temporal coherence. The nonlinear separation enables distinction between tissue and MBs, while the temporal separation enables distinction between free and bound MBs. From the HOSVD output, we defined a bound MB indicator $\chi $ , which indicates the presence of bound MBs. In our in vitro experiments, $\chi $ was lower for free MBs and tissue ( $0.04\pm ~0.03$ ) compared to bound MBs ( $0.31\pm 0.11$ without free MBs, decreasing with concentration down to $0.11\pm ~0.07$ at $20\times 10^{{3}}$ free MBs/mL). In addition, the molecular signal determined from $\chi $ correlated well with a DTE ground truth acquisition. The method was compared to other nondestructive techniques such as low-pass filtering and normalized singular spectrum area, demonstrating an average molecular signal enhancement of 12 dB. Furthermore, when used as a binary classifier, our method achieved a detection of up to $1.81\times $ more true positives while reducing false positives by up to $1.78\times $ . These findings suggest that HOSVD could pave the way to rapid, nondestructive UMI.

摘要

超声分子成像(UMI)利用靶向微泡(MBs)来检测疾病相关生物标志物。对于UMI而言,区分结合的MBs产生的声学信号与游离MBs和组织产生的信号至关重要。目前,主要方法即差分靶向增强(DTE)耗时且需要破坏MBs。在此,我们引入一种利用高阶奇异值分解(HOSVD)的新型、快速且无损的UMI技术。HOSVD对声学造影序列的信号进行分解,因其非线性内容和时间相干性将它们分离。非线性分离能够区分组织和MBs,而时间分离能够区分游离和结合的MBs。从HOSVD输出中,我们定义了一个结合MB指标$\chi$,它表明结合MBs的存在。在我们的体外实验中,与结合MBs(无游离MBs时为$0.31\pm0.11$,随着浓度降低,在$20\times10^{3}$个游离MBs/mL时降至$0.11\pm0.07$)相比,游离MBs和组织的$\chi$较低($0.04\pm0.03$)。此外,由$\chi$确定的分子信号与DTE地面真值采集结果相关性良好。该方法与其他无损技术如低通滤波和归一化奇异谱面积进行了比较,显示平均分子信号增强了12 dB。此外,当用作二元分类器时,我们的方法检测到的真阳性最多增加了$1.81\times$,同时假阳性最多减少了$1.78\times$。这些发现表明HOSVD可为快速、无损的UMI铺平道路。

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