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Automatic image detection of Halloysite clay Nanotubes as a future ultrasound theranostic agent for tumoral cell targeting and treatment

机译:自动检测埃洛石粘土纳米管作为未来用于肿瘤细胞靶向和治疗的超声治疗剂

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Halloysite clay Nanotubes (HNTs) are nanomaterials composed of double layered aluminosilicate minerals with a hollow tubular structure in the submicron range. They are characterized by a wide range of applications in anticancer therapy as agent delivery. In this work we aim to investigate the automatic detection features of HNTs through advanced quantitative ultrasound imaging employing different concentrations (3–5 mg/mL) at clinical conventional frequency, i.e. 7 MHz. Different tissue mimicking samples of HNT containing agarose gel were imaged through a commercially available echographic system, that was opportunely combined with ultrasound signal analysis research platform for extracting the raw ultrasound radiofrequency (RF) signals. Acquired data were stored and analyzed by means of an in-house developed algorithm based on wavelet decomposition, in order to identify the specific spectrum contribution of the HNTs and generate corresponding image mapping. Sensitivity and specificity of the HNT detection were quantified. Average specificity (94.36%) was very high with reduced dependency on HNT concentration, while sensitivity showed a proportional increase with concentration with an average of 46.78%. However, automatic detection performances are currently under investigation for further improvement taking into account image enhancement and biocompatibility issues.
机译:埃洛石粘土纳米管(HNTs)是由双层铝硅酸盐矿物组成的纳米材料,其中空管状结构在亚微米范围内。它们的特点是作为药物输送剂在抗癌治疗中有广泛的应用。在这项工作中,我们旨在研究在临床常规频率(即7 MHz)下采用不同浓度(3-5 mg / mL)的高级定量超声成像技术对HNT的自动检测功能。通过可商购的回波成像系统对包含HNT的不同组织模拟样品(含HNT琼脂糖凝胶)成像,该系统适当地与超声信号分析研究平台相结合,以提取原始超声射频(RF)信号。利用内部开发的基于小波分解的算法对获取的数据进行存储和分析,以识别HNT的特定光谱贡献并生成相应的图像映射。定量检测HNT的灵敏度和特异性。平均特异性(94.36%)非常高,对HNT浓度的依赖性降低,而灵敏度显示与浓度成比例的增加,平均值为46.78%。然而,目前正在研究自动检测性能以进一步改善,并考虑到图像增强和生物相容性问题。

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