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Amide Proton Transfer (APT) MRI of Brain Tumors at 3T

Amide Proton Transfer (APT) MRI of Brain Tumors at 3T
3T 脑肿瘤酰胺质子转移 (APT) MRI
批准号:
10296688
负责人:
JINYUAN ZHOU
金额:
$38.07万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-12-01 至 2024-11-30

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中文摘要
翻译
摘要 神经胶质瘤是最常见的原发性脑肿瘤,生物学上是复杂的, 分子和表型空间变异。患者日常管理的主要障碍是 神经胶质瘤,以及这些癌症的新疗法的发展,是神经影像学无法 准确定义肿瘤负荷。具体地说,钆(Gd)增强揭示了病灶区, 血脑屏障(BBB)被破坏的恶性胶质瘤,但未显示大的高风险区域 高细胞密度的浸润性肿瘤近年来,在对遗传特征的理解方面取得了突破, 神经胶质瘤,如异柠檬酸脱氢酶(IDH)突变,导致了对神经胶质瘤的迅速重新评估。 这组疾病的分子致癌作用。值得注意的是,最近的2016年WHO CNS分类 除了组织学之外,肿瘤还使用分子参数来定义肿瘤实体。2016年CNS WHO 代表未满足的放射学需求,即术前识别遗传生物标志物, 非侵入性方法,如MRI。该项目在第二个供资期(9/13- 7/17)开发了一种重要的基于蛋白质的分子MRI技术,称为酰胺质子转移- 加权(APTw)成像,成为一个敏感的,用户友好的,可重复的方法,用于常规临床使用。 大量早期临床数据表明,APTw成像为标准增加了重要价值 临床MRI序列在脑癌诊断中的应用。与对侧正常的大脑相比 组织,明显的,高度可重复的APTw高信号总是可以在高级别中可视化。 胶质瘤(包括没有Gd增强的胶质瘤)。因此,APTw成像允许准确识别 异质性胶质瘤中的高级别区域-神经外科手术中的核心需求。值得注意的是, 我最近发现APTw信号可能是一种有价值的成像生物标志物,通过它可以识别IDH 低级别胶质瘤的突变状态。这些早期发现非常令人兴奋。目前,所有使用 成像协议基本上不是定量的,并且所获得的图像通常被称为APT加权 因为有其他的贡献。本次更新申请的总体目标是高度发展 在3 T临床MRI扫描仪上使用灵敏、快速和定量的APT-MRI方法,并评估 这些方法在脑癌分子诊断中的潜力。我们设计了以下具体的 目的:(i)开发使用3 T压缩感知的定量APT-MRI方法;(ii)确定 APT-MRI预测II级胶质瘤中IDH突变状态的能力;以及(iii)确定 APT-MRI识别Gd增强肿块外肿瘤高危区域的准确性 胶质母细胞瘤患者。如果成功的话,我们的研究结果将大大推动APT-MRI达到一个全新的水平, 方法学研究和临床应用。
英文摘要
ABSTRACT Gliomas, the most common primary brain tumors, are biologically complex and exhibit substantial molecular and phenotypic spatial variation. A major obstacle in both the daily management of patients with gliomas, and in the development of new therapies for these cancers, is the inability of neuroimaging to accurately define the tumor burden. Specifically, gadolinium (Gd) enhancement reveals focal areas of malignant gliomas where the blood-brain barrier (BBB) is disrupted, but it does not show large high-risk areas of infiltrating tumor with a high cellularity. The recent breakthrough in the understanding of genetic features in gliomas, such as isocitrate dehydrogenase (IDH) mutations, has resulted in a prompt reappraisal of the molecular oncogenesis of this group of diseases. Notably, the most recent 2016 WHO classification of CNS tumors uses molecular parameters, in addition to histology, to define tumor entities. The 2016 CNS WHO represents an unmet radiographic need, namely, the identification of genetic biomarkers preoperatively, with non-invasive methods such as MRI. This project has been very successful during the 2nd funding period (9/13- 7/17) in developing an important protein-based molecular MRI technology, called amide proton transfer- weighted (APTw) imaging, into a sensitive, user-friendly, and reproducible approach for routine clinical use. Numerous early clinical data have demonstrated that APTw imaging adds important value to the standard clinical MRI sequences in brain cancer diagnosis. Compared to the contralateral normal-appearing brain tissue, the conspicuous, highly reproducible APTw hyperintensity can always be visualized in high-grade gliomas (including those without Gd enhancement). Thus, APTw imaging allowed accurate identification of high-grade regions within heterogeneous gliomas—a core need during neurosurgical procedures. Notably, we have recently found that the APTw signal could be a valuable imaging biomarker by which to identify IDH mutation status in low-grade gliomas. These early findings are very exciting. However, all currently used imaging protocols are essentially not quantitative, and the images obtained are often called APT-weighted images because of other contributions. The overall goals of this renewal application are to develop highly sensitive, fast, and quantitative APT-MRI methodologies on 3T clinical MRI scanners and to evaluate the potential of these methodologies in brain cancer molecular diagnosis. We have designed the following specific aims: (i) develop quantitative APT-MRI methodologies using compressed sensing at 3T; (ii) determine the capability of APT-MRI for the prediction of IDH mutation status in grade-II gliomas; and (iii) determine the accuracy of APT-MRI for the identification of high-risk regions of tumor outside Gd-enhancing masses in patients with glioblastomas. If successful, our results will significantly push, to a whole new level, the APT-MRI methodology research and clinical applications for brain tumors.
期刊论文(16)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/tmi.2020.3046460
发表时间: 2021-10
期刊: IEEE transactions on medical imaging
影响因子: 10.6
作者: [Guo P, Wang P, Yasarla R, Zhou J, Patel VM, Jiang S]
通讯作者: Jiang S
MoViT: Memorizing Vision Transformers for Medical Image Analysis.
MoViT:记忆用于医学图像分析的视觉变换器。
DOI: 10.1007/978-3-031-45676-3_21
发表时间: 2024
期刊: Machine learning in medical imaging. MLMI (Workshop)
影响因子: --
作者: [Shen,Yiqing, Guo,Pengfei, Wu,Jingpu, Huang,Qianqi, Le,Nhat, Zhou,Jinyuan, Jiang,Shanshan, Unberath,Mathias]
通讯作者: Unberath,Mathias
DOI: 10.1007/s11307-018-1248-1
发表时间: 2019-04
期刊: Molecular imaging and biology
影响因子: 3.1
作者: [Yu L, Li C, Luo X, Zhou J, Zhang C, Zhang Y, Chen M]
通讯作者: Chen M
DOI: 10.1002/nbm.4731
发表时间: 2023-06
期刊: NMR in biomedicine
影响因子: 2.9
作者: []
通讯作者:
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