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使用不同分割方法对异质 [F]FDG 静态(SUV)与 Patlak(Ki)全身 PET 成像进行定量分析:一项模拟研究。

Quantitative Analysis of Heterogeneous [F]FDG Static (SUV) vs. Patlak (Ki) Whole-body PET Imaging Using Different Segmentation Methods: a Simulation Study.

机构信息

Department of Nuclear Medicine and Molecular Imaging, University of Groningen, 9700 RB, Groningen, Groningen, Netherlands.

The Key Laboratory of Digital Signal and Image Processing of Guangdong Province, Shantou University, Shantou, China.

出版信息

Mol Imaging Biol. 2019 Apr;21(2):317-327. doi: 10.1007/s11307-018-1241-8.

Abstract

PURPOSE

Whole-body (WB) dynamic positron emission tomography (PET) enables imaging of highly quantitative physiological uptake parameters beyond the standardized uptake value (SUV). We present a novel dynamic WB anthropomorphic PET simulation framework to assess the potential of 2-deoxy-2-[F]fluoro-D-glucose ([F]FDG) net uptake rate constant (Ki) imaging in characterizing tumor heterogeneity.

PROCEDURES

Validated heterogeneous [F]FDG tumor kinetics were modeled within the XCAT phantom (ground truth). Thereafter, static (SUV) and dynamic PET data were simulated and reconstructed, followed by indirect WB Patlak Ki imaging. Subsequently, we compared the methods of affinity propagation (AP) and automatic segmentation with active contour (MASAC) to evaluate the impact of tumor delineation. Finally, we extracted the metabolically active tumor volume (MATV), Dice similarity coefficient (DSC), and the intratumoral heterogeneity metrics of the area under the cumulative intensity histogram curve (CIH), homogeneity, entropy, dissimilarity, high-intensity emphasis (HIE), and zone percentage (ZP), along with the target-to-background (TBR) and contrast-to-noise ratios (CNR).

RESULTS

Ki images presented higher TBR but lower CNR compared to SUV. In contrast to MASAC, AP segmentation resulted in smaller bias for MATV and DSC scores in Ki compared to SUV images. All metrics, except for ZP, were significantly different in AP segmentation between SUV and Ki images, with significant correlation observed for MATV, homogeneity, dissimilarity, and entropy. With MASAC segmentation, CIH, homogeneity, and dissimilarity were significantly different between SUV and Ki images, with all metrics, except for HIE and ZP, being significantly correlated. In ground truth images, increased heterogeneity was observed with Ki compared to SUV, with a high correlation for all metrics.

CONCLUSIONS

A novel simulation framework was developed for the assessment of the quantitative benefits of WB Patlak PET on realistic heterogeneous tumor models. Quantitative analysis showed that WB Ki imaging may provide enhanced TBR and facilitate lesion segmentation and quantification beyond the SUV capabilities.

摘要

目的

全身(WB)动态正电子发射断层扫描(PET)能够对标准化摄取值(SUV)之外的高度定量生理摄取参数进行成像。我们提出了一种新的全身动态拟人 PET 模拟框架,以评估 2-脱氧-2-[F]氟-D-葡萄糖([F]FDG)净摄取率常数(Ki)成像在表征肿瘤异质性方面的潜力。

过程

在 XCAT 体模(真实值)内对异质 [F]FDG 肿瘤动力学进行了验证建模。此后,模拟并重建了静态(SUV)和动态 PET 数据,然后进行间接的 WB 帕特拉克 Ki 成像。随后,我们比较了亲和传播(AP)和自动主动轮廓分割(MASAC)方法,以评估肿瘤描绘的影响。最后,我们提取了代谢活跃肿瘤体积(MATV)、Dice 相似系数(DSC)、累积强度直方图曲线(CIH)下面积的肿瘤内异质性指标、均匀性、熵、差异性、高强度强调(HIE)和区域百分比(ZP),以及靶与背景(TBR)和对比噪声比(CNR)。

结果

Ki 图像的 TBR 比 SUV 图像高,但 CNR 比 SUV 图像低。与 MASAC 相比,AP 分割在 Ki 图像中 MATV 和 DSC 评分的偏倚较小。除了 ZP 之外,所有指标在 SUV 和 Ki 图像之间的 AP 分割中均有显著差异,并且 MATV、均匀性、差异性和熵之间存在显著相关性。在 MASAC 分割中,SUV 和 Ki 图像之间的 CIH、均匀性和差异性有显著差异,除了 HIE 和 ZP 之外,所有指标均呈显著相关性。在真实图像中,Ki 图像的异质性比 SUV 图像高,所有指标的相关性都很高。

结论

开发了一种新的模拟框架,用于评估全身 Patlak PET 在现实异质肿瘤模型上的定量优势。定量分析表明,WB Ki 成像可能提供增强的 TBR,并有助于 SUV 功能之外的病变分割和定量。

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