Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Calgary Image Processing and Analysis Centre (CIPAC), Foothills Medical Centre, Calgary, Alberta, Canada.
Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada.
Neuroimage. 2022 Oct 15;260:119488. doi: 10.1016/j.neuroimage.2022.119488. Epub 2022 Jul 22.
Quantitative imaging biomarkers (QIBs) can be defined as objective measures that are sensitive and specific to changes in tissue physiology. Provided the acquired QIBs are not affected by scanner changes, they could play an important role in disease diagnosis, prognosis, management, and treatment monitoring. The precision of selected QIBs was assessed from data collected on a 3-T scanner in four healthy participants over a 5-year period. Inevitable scanner changes and acquisition protocol revisions occurred during this time. Standard and custom processing pipelines were used to calculate regional brain volume, cortical thickness, T2, T2*, quantitative susceptibility, cerebral blood flow, axial, radial and mean diffusivity, peak width of skeletonized mean diffusivity, and fractional anisotropy from the acquired images. Coefficient of variation (CoV) and intra-class correlation (ICC) indices were determined in the short-term (i.e., repeatable over three acquisitions within 4 weeks) and in the long-term (i.e., reproducible over four acquisition sessions in 5 years). Precision indices varied based on acquisition technique, processing pipeline, and anatomical region. Good repeatability (average CoV=2.40% and ICC=0.78) and reproducibility (average CoV=8.86 % and ICC=0.72) were found over all QIBs. The best performance indices were obtained for diffusion derived biomarkers (CoV∼0.96% and ICCs=0.87); conversely, the poorest indices were found for the cerebral blood flow biomarker (CoV>10% and ICC<0.5). These results demonstrate that changes in protocol, along with hardware and software upgrades, did not affect the estimates of the selected biomarkers and their precision. Further characterization of the QIB is necessary to understand meaningful changes in the biomarkers in longitudinal studies of normal brain aging and translation to clinical research.
定量影像生物标志物 (QIB) 可定义为对组织生理学变化敏感且特异的客观测量指标。如果所获得的 QIB 不受扫描仪变化的影响,它们可能在疾病诊断、预后、管理和治疗监测中发挥重要作用。在四年的时间里,从四名健康参与者在 3-T 扫描仪上采集的数据中评估了选定 QIB 的精密度。在此期间,不可避免地发生了扫描仪变化和采集方案修订。使用标准和定制处理管道从采集的图像中计算脑区容积、皮质厚度、T2、T2*、定量磁化率、脑血流、轴向、径向和平均弥散度、骨架化平均弥散度的峰值宽度和各向异性分数。在短期(即在 4 周内重复三次采集)和长期(即在 5 年内重复四次采集)确定了变化系数 (CoV) 和组内相关系数 (ICC) 指数。精密度指数基于采集技术、处理管道和解剖区域而有所不同。所有 QIB 均表现出良好的可重复性(平均 CoV=2.40%,ICC=0.78)和可再现性(平均 CoV=8.86%,ICC=0.72)。扩散衍生生物标志物的表现最佳(CoV∼0.96%,ICCs=0.87);相反,脑血流生物标志物的表现最差(CoV>10%,ICC<0.5)。这些结果表明,方案的变化以及硬件和软件升级并未影响选定生物标志物的估计及其精密度。需要进一步对 QIB 进行特征描述,以了解在正常脑老化的纵向研究和转化为临床研究中生物标志物的有意义变化。