PDF(Pubmed)
Abstract：
Relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) perfusion MR imaging (pMRI) has been shown to be a robust marker of neuroradiological tumor burden. Recent consensus recommendations in pMRI acquisition strategies have provided a pathway for pMRI inclusion in diverse patient care centers, regardless of size or experience. However, even with proper implementation and execution of the DSC-MRI protocol, issues will arise that many centers may not easily recognize or be aware of. Furthermore, missed pMRI issues are not always apparent in the resulting rCBV images, potentiating inaccurate or missed radiological diagnoses. Therefore, we gathered from our database of DSC-MRI datasets, true-to-life examples showcasing the breakdowns in acquisition, postprocessing, and interpretation, along with appropriate mitigation strategies when possible. The pMRI issues addressed include those related to image acquisition and postprocessing with a focus on contrast agent administration, timing, and rate, signal-to-noise quality, and susceptibility artifact. The goal of this work is to provide guidance to minimize and recognize pMRI issues to ensure that only quality data is interpreted.
摘要：
从动态敏感性对比（DSC）灌注MR成像（pMRI）得出的相对脑血容量（rCBV）已被证明是神经放射学肿瘤负荷的强大标志。最近pMRI采集策略的共识建议为pMRI纳入不同患者护理中心提供了途径。无论大小或经验。然而,即使正确实施和执行DSC-MRI协议，将会出现许多中心可能不容易识别或意识到的问题。此外，在产生的rCBV图像中，错过的pMRI问题并不总是明显的，加强不准确或错过的放射学诊断。因此,我们从DSC-MRI数据集数据库中收集，真实的例子展示了收购中的故障，后处理,和解释，以及可能的适当缓解策略。解决的pMRI问题包括与图像采集和后处理相关的问题，重点是造影剂管理，定时,和率，信噪比质量，和易感性伪影。这项工作的目标是提供指导，以最大程度地减少和识别pMRI问题，以确保仅解释质量数据。
