Vascular Signature Mapping of Brain Tumor Genotypes
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 180
- 试验地点
- 2
- 主要终点
- Vessel architecture
研究概览
简要总结
A glioma is a primary brain tumor in adults that is characterized by a highly variable, but overall poor survival. The optimal timing of treatment is in part determined by the expected biological behavior of the tumor. At present the expected biological behavior, determined by the tumor genotype, can only be determined by tissue analysis, which requires brain surgery. Non-invasive and improved diagnostic methods are sought to obtain insight into the molecular profile of the tumor and the expected biological behavior to avoid surgery performed solely for diagnostic purposes. Vascularization is an important aspect of the biological behavior of a primary brain tumor. Tumor vascularization characteristics can be assessed by Magnetic Resonance Imaging (MRI), but with the currently available technology this can only be achieved with unacceptably long scan times. In this proposal, the investigators will develop and optimize a novel MRI protocol to gather a large set of quantitative vascularization parameters within an acceptable scan time. The hypothesis is that from such a 'vascular signature' the tumor genotype can be inferred by means of machine learning.
详细描述
Objective of the study:
The primary objective is to develop and clinically validate a fast multi-parametric MRI acquisition technique, for non-invasive and comprehensive characterization of the tumor's vascularization, 'vascular signature mapping', at 3 Tesla (3T) and 7 Tesla (7T) MRI.
The secondary objective is to limit difficult and time-consuming visual interpretation of the acquired vascular information by developing a computer-aided diagnostic algorithm that automatically and accurately predicts the brain tumor genotype from the vascular signature maps.
Study design:
The study 'Vascular Signature Mapping for Brain Tumor Genotypes' is a multi-center observational diagnostic study, which consists of two parts. The first part of this study aims to develop and optimize a new MRI protocol that will exploit the effect of contrast agent on the MRI signal to infer information on the vascular properties of a tumor. It combines scans during the pre-contrast injection phase, the dynamic phase during and right after contrast agent injection, as well as the quasi static post-contrast phase. This research will focus on studying the optimal way of encoding the vascular architecture into the MRI signal and the decoding approach, In addition, the image processing methodology will be optimized. The second part of this study is a proof-of-concept clinical study. This part aims to link the vascular parameters with molecular profiles of tumors by using the collected data for the development of machine learning algorithms for predicting the tumor's genotype based on its vascular signature.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients scheduled for brain MRI with contrast injection as part of the clinical diagnostic procedure (cohort 1)
- •Patients diagnosed with suspected glioma scheduled for brain MRI as part of the clinical diagnostic procedure (cohort 2)
- •Patients with (suspected) glioma referred for tumor biopsy or resection (cohort 3)
- •Age ≥ 18 years (all cohorts)
- •Signed informed consent (all cohorts)
排除标准
- •Subjects with contra-indications for an MRI exam
- •Subjects with reduced kidney function because of the risk on developing nephrogenic systemic fibrosis (NSF) under gadolinium-based contrast injection
- •Subjects with pregnancy
- •Subjects undergoing a clinical protocol that requires scanning during CA injection (cohort 1)
结局指标
主要结局
Vessel architecture
时间窗: 4 years
Structure of vessels and tortuosity
Transit time parameters
时间窗: 4 years
Timing parameters used to characterize the tumor vasculature
Vascular oxygenation level
时间窗: 4 years
Oxygen-related parameters that describe the tumor's vasculature
Cerebral blood volume
时间窗: 4 years
To characterize the tumor's vasculature
Cerebral blood flow
时间窗: 4 years
To characterize the tumor's vasculature
Optimized MR protocol
时间窗: 6 months
MR protocol optimized for SNR and the ability to obtain vascular information
次要结局
- Tumor histology(4 years)
- Tumor molecular parameters(4 years)
- Basic subject characteristics(4 years)
- Treatment information(4 years)
- Tumor progression scored on follow-up MR scan(4 years)
- Radiation necrosis evaluated on follow-up MR scan(4 years)
- Mortality(4 years)
- KPS score at follow-up of 3 and 6 months(4 years)
研究者
Matthias van Osch
Prof. Dr. Ir. Matthias van Osch
Leiden University Medical Center