CT texture analysis in the differentiation of major renal cell carcinoma subtypes and correlation with Fuhrman grade

医学 肾细胞癌 放射科 肾肿瘤 核医学 病理 肾切除术 内科学
作者
Yu Deng,Erik Soule,Aster Samuel,Sakhi Shah,Enming Cui,Michael Asare-Sawiri,Chandru P. Sundaram,Chandana Lall,Kumaresan Sandrasegaran
出处
期刊:European Radiology [Springer Nature]
卷期号:29 (12): 6922-6929 被引量:57
标识
DOI:10.1007/s00330-019-06260-2
摘要

CT texture analysis (CTTA) using filtration-histogram–based parameters has been associated with tumor biologic correlates such as glucose metabolism, hypoxia, and tumor angiogenesis. We investigated the utility of these parameters for differentiation of clear cell from papillary renal cancers and prediction of Fuhrman grade. A retrospective study was performed by applying CTTA to pretreatment contrast-enhanced CT scans in 290 patients with 298 histopathologically confirmed renal cell cancers of clear cell and papillary types. The largest cross section of the tumor on portal venous phase axial CT was chosen to draw a region of interest. CTTA comprised of an initial filtration step to extract features of different sizes (fine, medium, coarse spatial scales) followed by texture quantification using histogram analysis. A significant increase in entropy with fine and medium spatial filters was demonstrated in clear cell RCC (p = 0.047 and 0.033, respectively). Area under the ROC curve of entropy at fine and medium spatial filters was 0.804 and 0.841, respectively. An increased entropy value at coarse filter correlated with high Fuhrman grade tumors (p = 0.01). The other texture parameters were not found to be useful. Entropy, which is a quantitative measure of heterogeneity, is increased in clear cell renal cancers. High entropy is also associated with high-grade renal cancers. This parameter may be considered as a supplementary marker when determining aggressiveness of therapy. • CT texture analysis is easy to perform on contrast-enhanced CT. • CT texture analysis may help to separate different types of renal cancers. • CT texture analysis may enhance individualized treatment of renal cancers.
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