Suppr超能文献

正常脑组织的超声射频频谱分析。

Ultrasonic radio-frequency spectrum analysis of normal brain tissue.

作者信息

Strowitzki Martin, Brand Sebastian, Jenderka Klaus-Vitold

机构信息

Department of Neurosurgery, Saarland University Medical School, Homburg-Saar, Germany.

出版信息

Ultrasound Med Biol. 2007 Apr;33(4):522-9. doi: 10.1016/j.ultrasmedbio.2006.09.004.

Abstract

Acoustic tissue properties can be estimated using texture and/or spectral parameter analysis. Spectral analysis is based on the rf-signals whose frequency-content is commonly neglected in conventional B-mode imaging. Attenuation and backscatter values of normal brain tissue were analyzed. Unprocessed rf-data of 20 patients were sampled intraoperatively after craniotomy using a modified conventional ultrasonic device (Hitachi CS 9600) and analyzed off-line by a custom-made software routine. Before parameter estimation, influences of the diffraction pattern were compensated by means of a correction function obtained using a tissue-mimicking phantom. Attenuation of white matter showed a linear frequency dependence with a slope of 0.94 +/- 0.13 dB cm(-1) MHz(-1). The spectral slope was determined using 10 distinct frequencies between 2.5 and 5.75 MHz. Backscattering properties were analyzed by determining the power spectral density (PSD) and a relative backscatter coefficient (rel BSC) against the values derived from the tissue-mimicking phantom. PSD and rel BSC values were frequency-dependent, with highest PSD values at the probe's center frequency (-75.69 +/- 8.26 dB V(2) Hz(-1)). The corresponding rel BSC value at 5 MHz was determined as 15.39 +/- 8.26 dB. Finally, backscatter coefficients (BSC) of brain tissue were computed using the known BSC of the phantom. The data provided in this study are meant to serve as a base for intended future characterization of brain tissue that potentially allows intraoperative differentiation between normal and pathologic areas and therefore provides the surgeon with additional information for defining the extent of resection in brain more precisely.

摘要

声学组织特性可通过纹理和/或频谱参数分析来估计。频谱分析基于射频信号,其频率成分在传统B模式成像中通常被忽略。对正常脑组织的衰减和后向散射值进行了分析。使用改良的传统超声设备(日立CS 9600)在开颅术后对20例患者的未处理射频数据进行术中采样,并通过定制软件程序进行离线分析。在参数估计之前,利用使用组织模拟体模获得的校正函数补偿衍射图案的影响。白质的衰减呈现线性频率依赖性,斜率为0.94±0.13 dB cm(-1) MHz(-1)。频谱斜率使用2.5至5.75 MHz之间的10个不同频率确定。通过确定功率谱密度(PSD)和相对于从组织模拟体模得出的值的相对后向散射系数(rel BSC)来分析后向散射特性。PSD和rel BSC值与频率有关,在探头的中心频率处PSD值最高(-75.69±8.26 dB V(2) Hz(-1))。5 MHz时的相应rel BSC值确定为15.39±8.26 dB。最后,使用体模的已知BSC计算脑组织的后向散射系数(BSC)。本研究中提供的数据旨在作为未来对脑组织进行表征的基础,这可能允许在术中区分正常和病理区域,从而为外科医生提供更多信息,以便更精确地确定脑切除范围。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验