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利用纹理分析作为预测肾细胞癌亚型、分级和分期的因素。

Using texture analysis as a predictive factor of subtype, grade and stage of renal cell carcinoma.

机构信息

Department of Radiology, Kocaeli Derince Training and Research Hospital, University of Health Sciences, İbni Sina M. Sopalı Mevki Lojman S. Derince, Kocaeli, Turkey.

Department of Urology, Kocaeli Derince Training and Research Hospital, University of Health Sciences, Kocaeli, Turkey.

出版信息

Abdom Radiol (NY). 2020 Nov;45(11):3821-3830. doi: 10.1007/s00261-020-02495-6.

Abstract

OBJECTIVE

The aim of this study was to evaluate the correlation between the tissue texture analysis and the histological subtypes, grade and stage of the disease in patients with renal cell carcinoma (RCC).

MATERIALS AND METHODS

Seventy-seven patients who underwent computed tomography due to renal mass and diagnosed with RCC as a result of pathological examination were retrospectively analyzed. In these analyses, the demographic characteristics, pathological and radiological findings of the patients were evaluated. The masses were introduced to the Radiomics extension of the software and the first- and second-order texture analysis parameters were obtained. The correlation of these parameters with histological subtype, Fuhrman grade and TNM stage was investigated.

RESULTS

In the comparison of the Radiomics values by stages, "minimum", "Long Run Low Gray-level Emphasis" values were higher in the stage 1-2 group, while "Energy", "Total energy", "Range", "Joint Average", "Sum Average", "Gray-Level Non-Uniformity", "Short-Run High Gray-level Emphasis ", "Run Length Non-Uniformity "and "High Gray-Level Run Emphasis "values were higher in the stage 3-4 group. Of these parameters, only "Gray-Level Non-Uniformity" and "Run Length Non-Uniformity'' values were significantly lower in tumors with low Fuhrman grade (1-2) and low TNM stage (1-2). There was no statistically significant correlation between the parameters found to be significant in histological subtype differentiation and Fuhrman grade and TNM stage.

CONCLUSION

This study demonstrates that "Gray-Level Non-Uniformity" and "Run Length Non-Uniformity "parameters in the texture analysis method can be used to evaluate the prognosis in patients with RCC.

摘要

目的

本研究旨在评估肾细胞癌(RCC)患者组织纹理分析与组织学亚型、分级和分期之间的相关性。

材料与方法

回顾性分析了 77 例因肾肿块而行计算机断层扫描并经病理检查诊断为 RCC 的患者。在这些分析中,评估了患者的人口统计学特征、病理和影像学发现。将这些肿块引入软件的 Radiomics 扩展模块,并获取一阶和二阶纹理分析参数。研究这些参数与组织学亚型、Fuhrman 分级和 TNM 分期的相关性。

结果

在按分期比较 Radiomics 值时,1-2 期组的“最小值”、“长行程低灰度强调”值较高,而 3-4 期组的“能量”、“总能量”、“范围”、“关节平均值”、“总和平均值”、“灰度不均匀性”、“短行程高灰度强调”、“运行长度不均匀性”和“高灰度运行强调”值较高。在这些参数中,只有“灰度不均匀性”和“运行长度不均匀性”值在低 Fuhrman 分级(1-2)和低 TNM 分期(1-2)的肿瘤中显著降低。在组织学分型分化中发现的有统计学意义的参数与 Fuhrman 分级和 TNM 分期之间没有统计学显著相关性。

结论

本研究表明,纹理分析方法中的“灰度不均匀性”和“运行长度不均匀性”参数可用于评估 RCC 患者的预后。

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