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Automatic liver detection and standardised uptake value evaluation in whole-body Positron Emission Tomography/Computed Tomography scans

机译:全身正电子发射断层扫描/计算机断层扫描的自动肝脏检测和标准化摄取价值评估

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Background and objective: Standardised Uptake Value (SUV), in clinical research and practice, is a marker of tumour avidity in Positron Emission Tomography/Computed Tomography (PET/CT). Since many technical , physical and physiological factors affect the SUV absolute measurement, the liver uptake is often used as reference value both in quantitative and semi-quantitative evaluation. The purpose of this investigation was to automatically detect the liver position in whole-body PET/CT scans and extract its average SUV value.& para;& para;Methods: We developed an algorithm, called Liver DEtection Algorithm (LIDEA), that analyses PET/CT scans, and under the assumption that the liver is a large homogeneous volume near the centre of mass of the patient, finds its position and automatically places a region of interest (ROI) in the liver, which is used to calculate the average SUV. The algorithm was validated on a population of 630 PET/CT scans coming from more than 60 different scanners. The SUV was also calculated by manually placing a large ROI in the liver.& para;& para;Results: LIDEA identified the liver with a 97.3% sensitivity with PET/CT images only and reached a 98.9% correct detection rate when using the co-registered CT scan to avoid liver misidentification in the right lung.& para;& para;The average liver SUV obtained with LIDEA was successfully validated against its manual assessment, with no systematic difference (0.11 +/- 0.36 SUV units) and a R-2 = 0.89 correlation coefficient.& para;& para;Conclusions: LIDEA proved to be a reliable tool to automatically identify and extract the average SUV of the liver in oncological whole-body PET/CT scans. (C) 2017 Elsevier B.V. All rights reserved.
机译:背景和目的:标准化的摄取价值(SUV),在临床研究和实践中,是正电子发射断层扫描/计算断层扫描(PET / CT)的肿瘤耐酸性的标志物。由于许多技术,物理和生理因素影响SUV绝对测量,因此肝脏吸收通常用作定量和半定量评估中的参考值。本研究的目的是自动检测全体PET / CT扫描中的肝脏位置,提取其平均SUV值。¶¶方法:我们开发了一种称为肝脏检测算法(LIDEA)的算法,即分析PET / CT扫描,并且在假设肝脏是患者的质心附近的大均匀体积,发现其位置并自动地将肝脏(ROI)放置在肝脏中,用于计算平均值SUV。该算法在来自60多个不同扫描仪的630个PET / CT扫描的人口上验证。 SUV也通过在肝脏中手动放置大型投注来计算。结果:结果:LIDEA在使用CO的宠物/ CT图像时鉴定了97.3%的灵敏度97.3%的灵敏度。 - 详细说明的CT扫描,以避免右肺的肝脏错误识别。¶¶用LIIEA获得的平均肝脏SUV通过其手动评估成功验证,没有系统差异(0.11 +/- 0.36 SUV单位)和A r -2 = 0.89相关系数。¶¶结论:LIIEA被证明是一种可靠的工具,可以是自动识别和提取肿瘤内宠物/ CT扫描中肝脏平均SUV的可靠工具。 (c)2017 Elsevier B.v.保留所有权利。

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