Area B: Precise DCE-MRI Assessment of Brain Tumors
试验速览
- 阶段
- 不适用
- 状态
- 终止
- 入组人数
- 15
- 试验地点
- 2
- 主要终点
- Volume transfer constant (Ktrans)
研究概览
简要总结
Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) is a potentially powerful diagnostic tool for the management of brain cancer and other conditions in which the blood-brain barrier is compromised. This trial studies how well precise DCE MRI works in diagnosing participants with high grade glioma that has come back or melanoma that has spread to the brain. The specially-tailored acquisition and reconstruction (STAR) DCE MRI could provide improved assessment of brain tumor status and response to therapy.
详细描述
PRIMARY OBJECTIVES:
I. To optimize and technically validate specially-tailored acquisition and reconstruction (STAR) DCE-MRI based on the accuracy and reproducibility of whole-brain tracer-kinetic (TK) parameter maps.
SECONDARY OBJECTIVES:
I. To develop a robust clinical implementation of STAR DCE-MRI. II. To clinically evaluate STAR DCE-MRI in patients with brain tumors.
OUTLINE: Participants are assigned to 1 of 2 cohorts.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 21 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •COHORT I: Recurrent high-grade glioma (often with thin areas of enhancement) treated with bevacizumab.
- •COHORT I: We will include adult patients with histopathologically confirmed high-grade glioma with evidence of tumor progression at baseline MRI who will undergo treatment with an anti-angiogenic agent (bevacizumab) with or without concomitant chemotherapy, and Karnofsky Performance Score > 60%.
- •COHORT I: At least 30 days should have elapsed since prior therapy including surgery and temozolomide chemoradiation.
- •COHORT I: Satisfactory renal, hepatic, and hematologic function is required.
- •COHORT II: Melanoma brain metastases (often small and spread throughout the brain) treated with immunotherapy.
- •COHORT II: We will include adult patients with a tissue-proven history of melanoma who have contrast enhancing brain masses who will undergo treatment with immunotherapy with an anti-CTLA-4 or anti-PD-1 approach (e.g. ipilimumab, pembrolizumab, or nivolumab), and Karnofsky Performance Score > 60%.
- •COHORT II: At least 30 days should have elapsed since prior therapy including surgery, stereotactic brain irradiation, and corticosteroid use.
排除标准
- •COHORT I: Exclusion criteria include treatment with any other anti-cancer treatment, enzyme-inducing antiepileptic agents, anticoagulant treatment, pregnancy, other anti-angiogenesis therapy and prior thrombo-embolic disorders.
- •COHORT I: Exclusion criteria will include the standard contraindications for MRI: 1) prior work as a machinist or metal worker, or history of metal being removed from the eyes, 2) cardiac pacemaker or internal pacing wires, 3) non-MRI compatible vena cava filter, vascular aneurysm clip, heart valve, spinal or ventricular shunt, optic implant, neuro-stimulator unit, ocular implant, or intrauterine device, or 4) claustrophobia, or uncontrollable motion disorder.
- •COHORT I: Pregnant women, prisoners, and institutionalized individuals will be excluded.
- •COHORT II: Exclusion criteria include treatment with any other anti-cancer treatment, and other immunotherapy exclusion criteria.
- •COHORT II: Non-cutaneous melanomas will be excluded.
- •COHORT II: Exclusion criteria will include the standard contraindications for MRI: 1) prior work as a machinist or metal worker, or history of metal being removed from the eyes, 2) cardiac pacemaker or internal pacing wires, 3) non-MRI compatible vena cava filter, vascular aneurysm clip, heart valve, spinal or ventricular shunt, optic implant, neuro-stimulator unit, ocular implant, or intrauterine device, or 4) claustrophobia, or uncontrollable motion disorder.
- •COHORT II: Pregnant women, prisoners, and institutionalized individuals will be excluded.
结局指标
主要结局
Volume transfer constant (Ktrans)
时间窗: Up to 3 years
The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. Receiver-operating characteristic curves (ROC) will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. Classification and Regression Tree (CART) with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using area under the curve (AUC) when fitting a ROC curve using predicted outcome against the actual outcome.
Fractional extravascular-extracellular space volume (ve)
时间窗: Up to 3 years
The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. ROC will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. CART with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using AUC when fitting a ROC curve using predicted outcome against the actual outcome.
Model-free initial area under the contrast agent concentration curve (iAUC)
时间窗: Up to 3 years
The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. ROC will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. CART with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using AUC when fitting a ROC curve using predicted outcome against the actual outcome.
Fractional plasma volume (vp)
时间窗: Up to 3 years
The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. ROC will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. CART with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using AUC when fitting a ROC curve using predicted outcome against the actual outcome.
次要结局
未报告次要终点