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Nanobubbles for earlier pancreatic cancer detection

Nanobubbles for earlier pancreatic cancer detection
用于早期胰腺癌检测的纳米气泡
批准号:
2886053
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
翻译
胰腺癌是英国第十大常见癌症,其发病率在过去40年中增加了30%,但5年生存率一直很低,约为8%,在同一时期没有改善。目前只有大约10%的病人适合做手术。早期发现疾病可以通过增加癌症仍然适合手术切除的患者数量,在患者预后中发挥重要作用。那些肿瘤无法触及或进展到不能手术的患者依赖于化疗或免疫疗法。然而,胰腺导管癌的特征是致密的纤维化基质和富含胶原的细胞外基质的演变,这严重限制了治疗药物的渗透。这引起了人们对开发针对这种致密基质的治疗方法的极大兴趣。迫切需要改进成像基质密度和药物渗透敏感性的方法,以更好地优化和监测治疗,以改善患者的预后。我们之前已经证明了对比增强超声(CEUS)是如何有效识别转移灶的,其中微泡可以改善图像质量并提供生理信息。然而,通常使用的造影剂微泡仅限于血液循环,限制了它们在肿瘤供血血管开始受到影响并且无法对肿瘤组织本身成像之前突出疾病的能力。在这个项目中,我们将研究纳米气泡作为早期癌症检测更合适的造影剂。它们足够小,可以逃离血管,自然地保留在肿瘤组织中。它们有可能提供不同大小的颗粒穿透肿瘤基质的信息,但要实现这一超声成像新领域的潜力,需要新的成像方法。虽然定量超声成像,特别是在乳腺成像方面,自20世纪70年代以来一直在研究,但直到最近十年,固态电子和阵列技术的发展才促进了足够的灵敏度和特异性,以与其他医学成像模式竞争。与MRI扫描相反,超声成像可以提供定量信息(如波速的空间分布),从而促进被检查的非均质结构的材料表征。此外,在无损评价(NDE)领域,近年来使用超声走时层析成像技术来绘制多晶金属[3]的各向异性晶粒结构和取向。然而,在医疗和NDE应用中,这些方法的成功高度依赖于检测孔径的范围和关于被检测对象的整体结构和特性的先验知识的可用性。为了在肿瘤表征的背景下规避这些挑战,本项目将研究使用超声造影构建癌组织定量图像的潜力。
英文摘要
Pancreatic cancer is the tenth most common cancer in the UK, with an incidence that has increased by 30% increase over the last 40 years but persistently low 5-year survival of approximately 8% that has not improved over the same time period. Currently only around 10% of patients are suited to surgery. Earlier detection of disease could play a significant role in patient outcomes by increasing the number of patients whose cancer remains suited to surgical resection. Those patients whose tumour is not accessible or too advanced for surgery are reliant on chemotherapy or immune-therapy treatments. However, pancreatic ductal carcinoma is characterised by the evolution of a dense fibrotic stroma and collagen-rich extra-cellular matrix that can severely limit the penetration of drugs available to treat it. This has led to considerable interest in the development of therapeutics that can target this dense stroma to enable treatment. Improved methods of imaging stroma density and susceptibility to drug penetration are urgently required to better optimise and monitor treatments to improve patient outcomes. We previously demonstrated how contrast enhanced ultrasound (CEUS), where microbubbles can improve image quality and provide physiological information, are effective in the identification of metastasis [1]. However, the contrast agent microbubbles commonly used are confined to the circulation, limiting their ability to highlight disease until the blood vessels supplying the tumour begin to be affected and unable to image tumour tissue itself. In this project we will investigate nanobubbles as a more suitable contrast agent for early stage cancer detection. They are small enough to escape the blood vessels and are naturally retained in tumour tissues. They have the potential to provide information on the penetration of different sized particles into the tumour stroma, but to realise the potential of this new area of ultrasound imaging novel imaging approaches are needed. Although quantitative ultrasound imaging, particularly in the context of breast imaging, has been investigated since the 1970s, it is only in the last decade that developments in solid state electronics and array technology have facilitated sufficient sensitivity and specificity to compete with alternative medical imaging modalities [2]. Contrary to MRI scans, ultrasound imaging can provide quantitative information (such as the spatial distribution of wave speed) and thus facilitate material characterisation of the heterogeneous structures under inspection. Furthermore, in the field of non-destructive evaluation (NDE), there has been a recent surge in using ultrasonic travel time tomography to map the anisotropic grain structures and orientations of polycrystalline metals [3]. However, in both medical and NDE applications, the success of these methods is highly dependent on the extent of the inspection aperture and the availability of prior knowledge about the global structure and properties of the inspected object. To circumvent these challenges in the context of tumour characterisation, this project will examine the potential of using CEUS to construct quantitative images of cancerous tissues.
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