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氟-18 氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描飞行时间高矩阵采集技术在动脉粥样硬化斑块炎症成像中的应用:体模研究。

The high matrix acquisition technique for imaging of atherosclerotic plaque inflammation in fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography with time-of-flight: Phantom study.

机构信息

Clinical Imaging Center for Healthcare, Nippon Medical School, 1-12-15, Sendagi, Bunkyo, Tokyo, 113-0022, Japan.

Department of Radiology, Nippon Medical School, Tokyo, Japan.

出版信息

J Nucl Cardiol. 2017 Aug;24(4):1161-1170. doi: 10.1007/s12350-016-0510-7. Epub 2016 May 19.

Abstract

BACKGROUND

Motion artifact and partial volume effect caused underestimation of coronary plaque inflammation. This study evaluated the high matrix acquisition technique using time-of-flight (TOF) positron emission tomography/computed tomography for imaging of atherosclerotic plaque inflammation with fluorine-18 fluorodeoxyglucose in small and moving phantoms.

METHODS AND RESULTS

All images were reconstructed using a conventional algorithm without TOF (4 × 4 × 4 mm voxel size) and a high matrix algorithm with TOF (2 × 2 × 2 mm voxel size). Microsphere phantoms of 10, 7.9, 6.2, 5.0, and 4.0 mm diameters were acquired in 3-dimensional list-mode for 30 minutes. A heart phantom mimicking cardiac motion consisted of a hot spot simulating a plaque (φ 4 mm, φ 2 mm) on the outside of the left ventricle. In the microsphere and heart phantom study, visual discrimination, maximum activity, and target-to-background ratio using the high matrix algorithm with TOF were better than those using the conventional algorithm without TOF.

CONCLUSION

The high matrix algorithm with TOF improves detection of small targets in phantoms.

摘要

背景

运动伪影和部分容积效应导致冠状动脉斑块炎症的低估。本研究评估了使用基于飞行时间(TOF)的正电子发射断层扫描/计算机断层扫描的高矩阵采集技术,用于在小的运动体模中对氟-18 氟脱氧葡萄糖成像进行动脉粥样硬化斑块炎症。

方法和结果

所有图像均使用常规算法(无 TOF,4×4×4mm 体素大小)和具有 TOF 的高矩阵算法(2×2×2mm 体素大小)进行重建。微球体体模直径为 10、7.9、6.2、5.0 和 4.0mm,以 3D 列表模式采集 30 分钟。心脏体模模拟心脏运动,在左心室外部有一个热点模拟斑块(φ 4mm、φ 2mm)。在微球体和心脏体模研究中,使用具有 TOF 的高矩阵算法的视觉辨别力、最大活性和靶与背景比均优于不使用 TOF 的常规算法。

结论

具有 TOF 的高矩阵算法可提高对小目标的检测。

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