18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi-Cancer Site Patient Cohort
18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi-Cancer Site Patient Cohort
复制标题
DOI：
10.2967/jnumed.114.144055
复制
发表时间：
2015-01-01
影响因子：
9.3
通讯作者：
Visvikis, Dimitris
中科院分区：
文献类型：
--
作者：
Hatt, Mathieu;Majdoub, Mohamed;Visvikis, Dimitris
在几种癌症类型中，F-18-FDG PET中肿瘤内摄取的异质性与患者的治疗结果相关。纹理特征分析是一种很有前途的量化方法。与纹理特征相关的一个悬而未决的问题是，肿瘤内异质性的量化涉及到它的额外贡献和对代谢活跃的肿瘤体积(MATV)的依赖，这已被证明是一个重要的预测和预后参数。我们的目标是使用涵盖不同癌症类型的更大的患者队列来解决这个问题。方法：建立一个包含555幅F-18-FDG PET图像(乳腺、宫颈、食道、头颈部和肺癌)的单一数据库。考虑了四个稳健且可重现的纹理特征参数。还研究了使用共生矩阵计算纹理特征的相关问题(如量化和空间方向性关系)。使用不同体积范围内的Spearman等级系数研究了这些特征与MATV之间的关系以及特征本身之间的关系。在食道癌和非小细胞肺癌(NSCLC)队列中，通过多变量COX分析评估MATV和纹理特征的互补预后价值。结果：大范围的MATV包括在考虑的人群中(3-415厘米(3)；平均，35；中位数，19；SD，50)。MATV和质地特征之间的相关性因MATV的不同而有很大差异，随着体积的增加，相关性降低。这些发现在不同的癌症类型中是可以重现的。量化和计算方法都对相关性有影响。在非小细胞肺癌中，体积和异质性是独立的预后因素(P=0.0053和0.0093)和分期(P=0.002)，但在食道肿瘤中，体积和异质性由于总体体积较小，其互补价值较小。结论：我们的结果表明，异质性量化和体积可能为大于10 cm(3)的体积提供有价值的补充信息，尽管补充信息随着体积的增大而显著增加。
Intratumoral uptake heterogeneity in F-18-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural feature analysis is a promising method for its quantification. An open issue associated with textural features for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volume (MATV), which has already been shown to be a significant predictive and prognostic parameter. Our objective was to address this question using a larger cohort of patients covering different cancer types. Methods: A single database of 555 pretreatment F-18-FDG PET images (breast, cervix, esophageal, head and neck, and lung cancer tumors) was assembled. Four robust and reproducible textural feature-derived parameters were considered. The issues associated with the calculation of textural features using co-occurrence matrices (such as the quantization and spatial directionality relationships) were also investigated. The relationship between these features and MATV, as well as among the features themselves, was investigated using Spearman rank coefficients for different volume ranges. The complementary prognostic value of MATV and textural features was assessed through multivariate Cox analysis in the esophageal and non-small cell lung cancer (NSCLC) cohorts. Results: A large range of MATVs was included in the population considered (3-415 cm(3); mean, 35; median, 19; SD, 50). The correlation between MATV and textural features varied greatly depending on the MATVs, with reduced correlation for increasing volumes. These findings were reproducible across the different cancer types. The quantization and calculation methods both had an impact on the correlation. Volume and heterogeneity were independent prognostic factors (P = 0.0053 and 0.0093, respectively) along with stage (P = 0.002) in non-small cell lung cancer, but in the esophageal tumors, volume and heterogeneity had less complementary value because of smaller overall volumes. Conclusion: Our results suggest that heterogeneity quantification and volume may provide valuable complementary information for volumes above 10 cm(3), although the complementary information increases substantially with larger volumes.