Inter-scanner Aβ-PET harmonization using barrel phantom spatial resolution matching.

IF 4 Q1 CLINICAL NEUROLOGY
Gihan P Ruwanpathirana, Robert C Williams, Colin L Masters, Christopher C Rowe, Leigh A Johnston, Catherine E Davey
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引用次数: 0

Abstract

Introduction: The standardized uptake value ratio (SUVR) is used to measure amyloid beta-positron emission tomography (Aβ-PET) uptake in the brainDifferences in PET scanner technologies and image reconstruction techniques can lead to variability in PET images across scanners. This poses a challenge for Aβ-PET studies conducted in multiple centers. The aim of harmonization is to achieve consistent Aβ-PET measurements across different scanners. In this study, we propose an Aβ-PET harmonization method of matching spatial resolution, as measured via a barrel phantom, across PET scanners. Our approach was validated using paired subject data, for which patients were imaged on multiple scanners.

Methods: In this study, three different PET scanners were evaluated: the Siemens Biograph Vision 600, Siemens Biograph molecular computed tomography (mCT), and Philips Gemini TF64. A total of five, eight, and five subjects were each scanned twice with [18F]-NAV4694 across Vision-mCT, mCT-Philips, and Vision-Philips scanner pairs. The Vision and mCT scans were reconstructed using various iterations, subsets, and post-reconstruction Gaussian smoothing, whereas only one reconstruction configuration was used for the Philips scans. The full-width at half-maximum (FWHM) of each reconstruction configuration was calculated using [18F]-filled barrel phantom scans with the Society of Nuclear Medicine and Molecular Imaging (SNMMI) phantom analysis toolkit. Regional SUVRs were calculated from 72 brain regions using the automated anatomical labelling atlas 3 (AAL3) atlas for each subject and reconstruction configuration. Statistical similarity between SUVRs was assessed using paired (within subject) t-tests for each pair of reconstructions across scanners; the higher the p-value, the greater the similarity between the SUVRs.

Results: Vision-mCT harmonization: Vision reconstruction with FWHM = 4.10 mm and mCT reconstruction with FWHM = 4.30 mm gave the maximal statistical similarity (maximum p-value) between regional SUVRs. Philips-mCT harmonization: The FWHM of the Philips reconstruction was 8.2 mm and the mCT reconstruction with the FWHM of 9.35 mm, which gave the maximal statistical similarity between regional SUVRs. Philips-Vision harmonization: The Vision reconstruction with an FWHM of 9.1 mm gave the maximal statistical similarity between regional SUVRs when compared with the Philips reconstruction of 8.2 mm and were selected as the harmonized for each scanner pair.

Conclusion: Based on data obtained from three sets of participants, each scanned on a pair of PET scanners, it has been verified that using reconstruction configurations that produce matched-barrel, phantom spatial resolutions results in maximally harmonized Aβ-PET quantitation between scanner pairs. This finding is encouraging for the use of PET scanners in multi-center trials or updates during longitudinal studies.

Highlights: Question: Does the process of matching the barrel phantom-derived spatial resolution between scanners harmonize amyloid beta-standardized uptake value ratio (Aβ-SUVR) quantitation? Pertinent findings: It has been validated that reconstruction pairs with matched barrel phantom-derived spatial resolution maximize the similarity between subjects paired Aβ-PET (positron emission tomography) SUVR values recorded on two scanners. Implications for patient care: Harmonization between scanners in multi-center trials and PET camera updates in longitudinal studies can be achieved using a simple and efficient phantom measurement procedure, beneficial for the validity of Aβ-PET quantitation measurements.

利用桶状幻影空间分辨率匹配实现扫描仪间 Aβ-PET 协调。
简介:标准化摄取值比(SUVR)用于测量大脑中淀粉样β-正电子发射断层扫描(Aβ-PET)的摄取量。这给在多个中心进行的 Aβ-PET 研究带来了挑战。协调的目的是使不同扫描仪的 Aβ-PET 测量结果保持一致。在这项研究中,我们提出了一种 Aβ-PET 协调方法,通过桶状模型测量不同 PET 扫描仪的空间分辨率,使之相匹配。我们使用配对受试者数据对该方法进行了验证,患者在多台扫描仪上进行了成像:本研究评估了三种不同的 PET 扫描仪:西门子 Biograph Vision 600、西门子 Biograph 分子计算机断层扫描(mCT)和飞利浦 Gemini TF64。在 Vision-mCT、mCT-飞利浦和 Vision-Philips 扫描仪对中,分别对五名、八名和五名受试者进行了两次[18F]-NAV4694 扫描。Vision和mCT扫描使用不同的迭代、子集和重建后高斯平滑进行重建,而飞利浦扫描只使用一种重建配置。使用核医学与分子成像学会(SNMMI)幻影分析工具包,利用[18F]填充桶状幻影扫描计算每种重建配置的半最大全宽(FWHM)。使用自动解剖标记图集 3 (AAL3) 图集计算每个受试者和重建配置的 72 个脑区的区域 SUVR。使用配对(受试者内)t检验对每对扫描仪重建的SUVR之间的统计相似性进行评估;P值越高,SUVR之间的相似性越大:视觉-MCT协调:视觉重建的 FWHM = 4.10 mm 和 mCT 重建的 FWHM = 4.30 mm 在区域 SUVR 之间具有最大的统计相似性(最大 p 值)。飞利浦-mCT 协调:飞利浦重建的 FWHM 为 8.2 毫米,mCT 重建的 FWHM 为 9.35 毫米,区域 SUVR 之间的统计相似性最大。飞利浦-Vision协调:与飞利浦的 8.2 mm 重建相比,Vision 重建的 FWHM 为 9.1 mm,区域 SUVR 之间的统计相似度最高,因此被选为每对扫描仪的协调标准:根据三组参与者的数据(每组参与者都在一对 PET 扫描仪上进行扫描),已经验证了使用能产生匹配桶、幻影空间分辨率的重建配置能最大程度地协调一对扫描仪之间的 Aβ-PET 定量。这一发现对于在多中心试验中使用 PET 扫描仪或在纵向研究中进行更新是令人鼓舞的:亮点:问题:不同扫描仪之间的桶状模型空间分辨率匹配过程是否能协调淀粉样β标准化摄取值比(Aβ-SUVR)的量化?相关研究结果:经过验证,具有匹配桶状幻影衍生空间分辨率的重建对可最大程度地提高两台扫描仪记录的受试者配对 Aβ-PET(正电子发射断层扫描)SUVR 值的相似性。对患者护理的意义:多中心试验中扫描仪之间的协调和纵向研究中 PET 相机的更新可以通过简单高效的模型测量程序来实现,有利于提高 Aβ-PET 定量测量的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.80
自引率
7.50%
发文量
101
审稿时长
8 weeks
期刊介绍: Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.
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