Yang Braden, Earnest Tom, Kumar Sayantan, Kothapalli Deydeep, Benzinger Tammie, Gordon Brian, Sotiras Aristeidis
Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA 63110.
Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA 63110.
medRxiv. 2024 Oct 7:2024.06.14.24308952. doi: 10.1101/2024.06.14.24308952.
Differences in amyloid positron emission tomography (PET) radiotracer pharmacokinetics and binding properties lead to discrepancies in amyloid-β uptake estimates. Harmonization of tracer-specific biases is crucial for optimal performance of downstream tasks. Here, we investigated the efficacy of ComBat, a data-driven harmonization model, for reducing tracer-specific biases in regional amyloid PET measurements from [F]-florbetapir (FBP) and [C]-Pittsburgh Compound-B (PiB).
One-hundred-thirteen head-to-head FBP-PiB scan pairs, scanned from the same subject within ninety days, were selected from the Open Access Series of Imaging Studies 3 (OASIS-3) dataset. The Centiloid scale, ComBat with no covariates, ComBat with biological covariates, and GAM-ComBat with biological covariates were used to harmonize both global and regional amyloid standardized uptake value ratios (SUVR). Variants of ComBat, including longitudinal ComBat and PEACE, were also tested. Intraclass correlation coefficient (ICC) and mean absolute error (MAE) were computed to measure the absolute agreement between tracers. Additionally, longitudinal amyloid SUVRs from an anti-amyloid drug trial were simulated using linear mixed effects modeling. Differences in rates-of-change between simulated treatment and placebo groups were tested, and change in statistical power/Type-I error after harmonization was quantified.
In the head-to-head tracer comparison, ComBat with no covariates was the best at increasing ICC and decreasing MAE of both global summary and regional amyloid PET SUVRs between scan pairs of the same group of subjects. In the clinical trial simulation, harmonization with both Centiloid and ComBat increased statistical power of detecting true rate-of-change differences between groups and decreased false discovery rate in the absence of a treatment effect. The greatest benefit of harmonization was observed when groups exhibited differing FBP-to-PiB proportions.
ComBat outperformed the Centiloid scale in harmonizing both global and regional amyloid estimates. Additionally, ComBat improved the detection of rate-of-change differences between clinical trial groups. Our findings suggest that ComBat is a viable alternative to Centiloid for harmonizing regional amyloid PET analyses.
淀粉样蛋白正电子发射断层扫描（PET）放射性示踪剂的药代动力学和结合特性差异导致淀粉样β摄取估计值存在差异。消除示踪剂特异性偏差对于下游任务的最佳性能至关重要。在此，我们研究了数据驱动的归一化模型ComBat在减少来自[F] - 氟代贝他吡（FBP）和[C] - 匹兹堡化合物B（PiB）的区域淀粉样蛋白PET测量中示踪剂特异性偏差方面的功效。
从开放获取影像研究系列3（OASIS - 3）数据集中选择了113对在90天内对同一受试者进行扫描的FBP - PiB头对头扫描对。使用Centiloid量表、无协变量的ComBat、有生物协变量的ComBat以及有生物协变量的GAM - ComBat对全局和区域淀粉样蛋白标准化摄取值比率（SUVR）进行归一化。还测试了ComBat的变体，包括纵向ComBat和PEACE。计算组内相关系数（ICC）和平均绝对误差（MAE）以测量示踪剂之间的绝对一致性。此外，使用线性混合效应模型模拟了抗淀粉样蛋白药物试验的纵向淀粉样蛋白SUVR。测试了模拟治疗组和安慰剂组之间变化率的差异，并量化了归一化后统计功效/ I型错误的变化。
在头对头示踪剂比较中，无协变量的ComBat在提高同一组受试者扫描对之间全局汇总和区域淀粉样蛋白PET SUVR的ICC以及降低MAE方面表现最佳。在临床试验模拟中，使用Centiloid和ComBat进行归一化提高了检测组间真实变化率差异的统计功效，并在无治疗效果时降低了错误发现率。当组间FBP与PiB比例不同时，观察到归一化的最大益处。
在全局和区域淀粉样蛋白估计的归一化方面，ComBat优于Centiloid量表。此外，ComBat改善了临床试验组之间变化率差异的检测。我们的研究结果表明，ComBat是用于协调区域淀粉样蛋白PET分析的Centiloid的可行替代方法。
