Developing microstructural and metabolic magnetic resonance imaging to address the diagnostic and prognostic unmet needs in breast cancer

开发微观结构和代谢磁共振成像，以满足乳腺癌诊断和预后方面未满足的需求

• 批准号: MR/T024895/1
• 负责人: Oshaani Abeyakoon
• 金额: $ 33万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FT024895%2F1
• 关键词: Developing; microstructural; metabolic; magnetic; resonance

2015 saw over 55,000 new cases of breast cancer in the UK. However, not all of these breast cancers are the same. Breast cancers that look identical on standard imaging tests like x-ray mammography and ultrasound incorporate both those that are slow-growing and those that are destined to spread rapidly and claim lives. The most life-threatening tumours need aggressive treatment early but the question is how to discriminate these from those that are slower growing? Today, we do this by biopsying the tumour and examining its grade, protein expression, and if hormone receptors are present. However, a biopsy does not represent the whole tumour and current predictive methods lack precision.Hyperpolarised C13 imaging is a very novel technique that combines magnetic resonance imaging (HPMRI) with metabolic information (i.e. how the cancer cells utilise energy, for example glucose). Specifically, HPMRI allows us to measure how cells convert pyruvate to lactate, which reflects metabolic activity. Cancers have more metabolic activity than normal cells and some cancers are more metabolically active than others. For example, we know from animal studies that the most aggressive tumours convert pyruvate faster and in greater volumes than less aggressive tumours. HPMRI may therefore identify the most aggressive cancers but the test is so novel that this has not been researched to any great degree in man. Furthermore, the equipment needed for HPMRI is extremely expensive and restricted to just a few centres worldwide.There is also another problem that needs addressing, namely that almost 60% of women that have biopsy to see if there is a tumour actually have a negative result, so we really need a better way to tell if something was tumour or not. We have developed novel MRI techniques (VERDICT, T2-mapping and Fat-fraction MRI) that we are using to find tumours and avoid unnecessary biopsies in patients being investigated for prostate cancer. We think these techniques could be applied to women being investigated for breast cancer and in a similar fashion could help avoid many unnecessary breast biopsies. Our research aims to develop these new imaging techniques in women with breast cancer. We will do so in a robust, safe, validated manner by following the "Imaging Biomarker Roadmap for Cancer Studies" (Nature Reviews Clinical Oncology 2017). We will do experiments to technically validate these biomarkers, followed by biological and clinical validation, to plan for clinical implementation. We will determine if these biomarkers are reproducible and what they tell us about a breast cancer. Ultimately, if they prove sufficiently promising, we ultimately aim to add their information to existing prognostic models to detect aggressive breast cancer. A prognostic model is a collection of information known about a patient that predicts what will happen to them in the future, i.e. whether their tumour will spread. We at UCL are especially well-placed to do this work. The Medical Research Council and Cancer Research UK and other funders have already invested >£30 million to support our imaging research. For example, an MRC Clinical Research Infrastructure award funded installation and associated equipment necessary for hyperpolarised metabolic imaging and digital histopathology. We have an assembled a world-class multidisciplinary research team that is working currently in prostate cancer. A successful CARP award will allow us to turn our attention to breast cancer by funding research time for an existing NHS consultant radiologist (Dr. Abeyakoon) to join our team. She has extensive prior research experience in breast cancer imaging (having gained a PhD; unusual in radiology).The results of our research will be disseminated to the scientific community via conference proceedings and peer reviewed papers, the public via public patient engagement forums at UCL/H, and funders via grant applications to support the next phase of research

2015年，英国有超过55，000例乳腺癌新发病例。然而，并非所有这些乳腺癌都是相同的。乳腺癌在标准的成像测试中看起来相同，如x射线乳房X光检查和超声波检查，既包括那些生长缓慢的乳腺癌，也包括那些注定会迅速扩散并夺去生命的乳腺癌。最危及生命的肿瘤需要早期积极治疗，但问题是如何区分这些肿瘤和生长较慢的肿瘤？今天，我们通过对肿瘤进行活检并检查其等级，蛋白质表达以及是否存在激素受体来做到这一点。超极化C13成像是一种非常新颖的技术，它将磁共振成像（HPMRI）与代谢信息（即癌细胞如何利用能量，例如葡萄糖）相结合。具体来说，HPMRI允许我们测量细胞如何将丙酮酸转化为乳酸，这反映了代谢活性。癌症比正常细胞具有更多的代谢活性，并且一些癌症比其他癌症更具代谢活性。例如，我们从动物研究中了解到，最具侵袭性的肿瘤比侵袭性较低的肿瘤转化丙酮酸的速度更快，体积更大。因此，HPMRI可以识别最具侵袭性的癌症，但该测试是如此新颖，以至于还没有在男性中进行过任何大程度的研究。此外，HPMRI所需的设备极其昂贵，仅限于全球少数中心。还有另一个需要解决的问题，即近60%的女性进行活检以查看是否有肿瘤实际上是阴性结果，所以我们真的需要一个更好的方法来判断是否是肿瘤。我们已经开发了新的MRI技术（VERDICT，T2映射和脂肪分数MRI），我们正在使用这些技术来发现肿瘤，并避免在前列腺癌患者中进行不必要的活检。我们认为这些技术可以应用于正在接受乳腺癌检查的女性，并且以类似的方式可以帮助避免许多不必要的乳腺活检。我们的研究旨在为乳腺癌女性开发这些新的成像技术。我们将遵循“癌症研究成像生物标记物路线图”（《自然评论临床肿瘤学》2017），以稳健、安全、经过验证的方式做到这一点。我们将进行实验，从技术上验证这些生物标志物，然后进行生物学和临床验证，以计划临床实施。我们将确定这些生物标志物是否是可重复的，以及它们告诉我们关于乳腺癌的信息。最终，如果它们被证明有足够的前景，我们的最终目标是将它们的信息添加到现有的预后模型中，以检测侵袭性乳腺癌。预后模型是关于患者的已知信息的集合，其预测未来将发生在他们身上的情况，即他们的肿瘤是否会扩散。我们在UCL特别适合做这项工作。医学研究理事会和英国癌症研究和其他资助者已经投资了超过3000万英镑来支持我们的成像研究。例如，MRC临床研究基础设施奖资助了超极化代谢成像和数字组织病理学所需的安装和相关设备。我们拥有一支世界级的多学科研究团队，目前正在前列腺癌领域工作。一个成功的CARP奖将使我们能够把注意力转向乳腺癌，为现有的NHS顾问放射科医生（Abeyakoon博士）加入我们的团队提供研究时间。她在乳腺癌成像方面有着丰富的研究经验（已获得博士学位;在放射学中不常见）。我们的研究结果将通过会议记录和同行评审论文向科学界传播，通过UCL/H的公众患者参与论坛向公众传播，并通过拨款申请资助资助下一阶段的研究