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基于对比增强超声的呼吸运动补偿的腹部参数灌注成像:体内验证。

Abdominal parametric perfusion imaging with respiratory motion-compensation based on contrast-enhanced ultrasound: In-vivo validation.

机构信息

The 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, PR China; Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center, Montreal, QC, Canada.

The 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, PR China.

出版信息

Comput Med Imaging Graph. 2018 Apr;65:11-21. doi: 10.1016/j.compmedimag.2017.06.005. Epub 2017 Jun 22.

Abstract

Parametric perfusion imaging (PPI) based on dynamic contrast-enhanced ultrasound (DCEUS) is a multi-parametric functional method that is increasingly used to characterize the hemodynamic features of abdominal tumors. Periodic respiratory kinetics adversely affects the signal-to-clutter ratio (SCR) and accuracy of abdominal PPI. This study proposed respiratory motion-compensation (rMoCo) employing non-negative matrix factorization combined with fast block matching algorithm to effectively remove these disturbances on abdominal PPI, which was validated through in-vivo perfusion experiments. The mean calculation efficiency of rMoCo was improved by 83.6% when the algorithm was accelerated in a unique matching sequence, which was formed from dozens of DCEUS subsequences at the same respiratory phase. The horizontal and vertical displacements induced by respiratory kinetics were estimated to correct the extraction of time-intensity curves and the peak SNR remained at 22.58±2.90dB. Finally, the abdominal PPIs of four perfusion parameters were formed with non-negative rMoCo, and their SCR was improved by 3.99±0.49dB (p<0.05). Compared with the results without rMoCo, the continuity and visualization of abdominal arterioles were clearly enhanced, and their perfusion details were accurately characterized by PPIs with non-negative rMoCo. The proposed method benefits clinicians in providing accurate diagnoses and in developing appropriate therapeutic strategies for abdominal diseases.

摘要

基于动态对比增强超声(DCEUS)的参数灌注成像(PPI)是一种多参数功能方法,越来越多地用于描述腹部肿瘤的血流动力学特征。周期性呼吸运动对信号与噪声比(SCR)和腹部 PPI 的准确性有不利影响。本研究提出了一种呼吸运动补偿(rMoCo)方法,该方法采用非负矩阵分解结合快速块匹配算法,有效地去除腹部 PPI 上的这些干扰,通过体内灌注实验进行了验证。当在唯一的匹配序列中加速算法时,rMoCo 的平均计算效率提高了 83.6%,该匹配序列是由同一呼吸相位的数十个 DCEUS 子序列形成的。估计呼吸动力学引起的水平和垂直位移,以校正时间强度曲线的提取,峰值信噪比保持在 22.58±2.90dB。最后,使用非负 rMoCo 形成了四个灌注参数的腹部 PPI,其 SCR 提高了 3.99±0.49dB(p<0.05)。与没有 rMoCo 的结果相比,腹部小动脉的连续性和可视化明显增强,并且使用非负 rMoCo 的 PPI 可以准确地描述其灌注细节。该方法有助于临床医生提供准确的诊断,并为腹部疾病制定适当的治疗策略。

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