Correction of Diffusion Gradient Bias in Quantitative Diffusivity Metrics for MultiPlatform Clinical Oncology Trials

摘要 多中心临床试验越来越多地使用定量扩散成像(DWI)来辅助患者管理 以及用于转译肿瘤学应用的治疗反应评估。系统性偏见的主要来源 在扩散中发现源自平台相关的梯度硬件。不加纠正，这些 用于描述组织病理和治疗的偏差混淆的定量扩散度量 答复导致不确定的结果，并增加了必要的受试者数量和试验费用。技术 补救措施是由密歇根大学的调查人员定义的，并促使我们的母公司AIP涉及三个人 占主导地位的核磁共振制造商。目前的AIP融合了商业科学家/工程师和 学术研究人员，并成功地设计和开发了原型校正工具 消除不同临床MRI定量DWI应用中的系统弥散加权偏差 站台。因此，两家供应商在各自的扫描仪平台上实现了原型工具 肿瘤学试验中广泛使用的平均组织扩散率测量的校正。此外，追溯的可行性 ACRIN 6698乳房的可重复性队列在所有三个供应商平台上都得到了验证 癌症成像试验。我们的AIP参与临床试验合作小组和定量成像 财团透露，在临床平台上采用开发的技术的最有效途径是 供应商实施。还指出了与高级采集协议进行灵活集成的其他需求 以及使用多个b值来准确量化超出平均扩散率的复杂指标的分析。致信地址 这些需求，续订AIP将扩展我们的合作，包括两个额外的学术癌症成像 中心还将在五个活跃的临床肿瘤学试验中整合和验证开发的实用校正工具 能够应用于先进的组织扩散率模型。这些工具将消除系统的跨平台， 交叉检查可变性，以促进纵向和多机构转译癌症研究，利用 定量扩散系数度量。该项目的成功将进一步提高癌症的精确度和精密度 检测和监控。这些目标将通过Aim1：部署DWI偏差校正工具来实现 用于多项癌症成像试验，并通过AIM2：与高级DWI的校正集成 协议和组织模型。 拟议的合作伙伴关系的学术团队由公认的定量扩散成像专家组成 标准化和转化为临床肿瘤学试验。PI机构与以下机构签订了积极的研究协议 三家占主导地位的临床MRI制造商，以前曾成功实施过 技术。项目目标的实现将消除令人困惑的重大工具偏见 目前采用定量弥散加权成像的多中心/多平台临床试验。

Abstract Multi-center clinical trials increasingly utilize quantitative diffusion imaging (DWI) to aid in patient management and treatment response assessment for translational oncology applications. A major source of systematic bias in diffusion was discovered originating from platform-dependent gradient hardware. Left uncorrected, these biases confound quantitative diffusion metrics used for characterization of tissue pathology and treatment response leading to inconclusive findings, and increasing the requisite subject numbers and trial cost. Technical remedy was defined by University of Michigan investigators and motivated our parent AIP involving the three dominant MRI manufactures. The current AIP merged expertise among commercial scientists/engineers and academic researchers, and resulted in successful design and development of prototype correction tools to eliminate systematic diffusion weighting bias in quantitative DWI applications across diverse clinical MRI platforms. As a result, two vendors have implemented prototype tools on their respective scanner platforms for correction of mean tissue diffusivity metric widely used in oncology trials. Furthermore, feasibility of retrospective correction across all three vendor platforms was demonstrated for the repeatability cohort of ACRIN 6698 breast cancer imaging trial. Our AIP participation with clinical trial cooperative groups and quantitative imaging consortia revealed that the most efficient route for adoption of developed technology on clinical platforms is by vendor implementation. Additional need was noted for flexible integration with advanced acquisition protocols and analyses using multiple b-values to accurately quantify complex metrics beyond mean diffusivity. To address these needs, the renewal AIP will extend our collaborations to include two additional academic cancer imaging centers to integrate and validate developed practical correction tools in five active clinical oncology trials, as well as enable application to advanced tissue diffusivity models. These tools will eliminate systematic cross-platform, cross-exam variability to facilitate longitudinal and multi-institutional translational cancer research that utilize quantitative diffusivity metrics. Success of this project will further enhance accuracy and precision of cancer detection and monitoring. These goals will be achieved through Aim1: deployment of DWI bias correction tools for application in multiple cancer imaging trials, and through Aim2: correction integration with advanced DWI protocols and tissue models. Academic team of the proposed partnership consists of recognized experts in quantitative diffusion imaging standardization and translation to clinical oncology trials. The PI institution has active research agreements with three dominant clinical MRI manufactures with prior record of successful implementations for the developed technologies. Accomplishment of the project goals will eliminate significant instrumental bias that confounds current multi-center/multi-platform clinical trials that employ quantitative DWI.