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Quantitative spectral CT evaluation of kidney tumors with the stretched-exponential nonlinear regression analysis model

机译:肾肿瘤与拉伸指数非线性回归分析模型的定量光谱CT评价

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Background: This study aimed to use the stretched-exponential nonlinear regression analysis model to explore the value of the energy spectral curve in the differential diagnosis of clear cell renal cell carcinoma (ccRCC), minimal fat renal angiomyolipoma (RAML), and hypovascular renal cell carcinoma. Methods: Sixty-five cases with renal tumors were enrolled retrospectively who had undergone a preoperative multiphase spectral CT scan of the kidney in pre-enhance and double-phase enhanced scanning. The normalized iodine concentrations (NIC) of these lesions, normal renal cortex, and psoas major were measured and calculated. The spectral curves of these lesions and normal tissues were analyzed to calculate the stretched-exponential index (α) and b value with the stretched-exponential nonlinear regression analysis model (y=–b·X α ). The differences between α, b value, and NIC of these lesions and normal tissues in pre-enhance and two enhanced phases were compared using one-way ANOVA. The correlation between α, b value, and NIC was evaluated using the Pearson coefficient test, with significance assigned at the 5% level. Results: There was no significant difference in α value between the groups in pre-enhance scanning. In the Cortical phase (CP), there were no significant differences in NIC and α value between minimal fat RAML and hypovascular renal cell carcinoma, or between ccRCC and the normal renal cortex. However, in the nephrographic phase (NP), a significant difference in α value was found between minimal fat RAML and hypovascular renal cell carcinoma, but no difference in NIC between them. In NP, there were significant differences in NIC and α values between ccRCC and the normal renal cortex. In CP and NP, there were significant differences between the psoas major and other groups in all parameters. For b value, in pre-enhance scanning, there was a significant difference between the psoas major and other groups, and between ccRCC and the normal renal cortex. There was no significant difference between other groups. After enhancement, in CP and NP, significant differences were observed between the psoas major and other groups in b value, but no significant differences were observed between all renal tumors and the normal renal cortex. A linear correlation was found between α values and NIC in CP (r=0.780, P=0.00) and NP (r=0.693, P=0.00). The b values and NIC had a low correlation in CP, with no correlation in NP. Conclusions: Quantitative spectral CT with the stretched-exponential nonlinear regression analysis model may enhance the differential diagnosis ability for renal tumors. Its clinical value remains to be further explored in other types of soft tissue lesions.
机译:背景:本研究旨在使用拉伸指数非线性回归分析模型来探讨透明细胞肾细胞癌(CCRCC),最小脂肪肾血糖素(RAM1)的差异诊断中的能谱曲线的值,以及血管肾细胞癌。方法:若干肾肿瘤患者六十五例术语,在预增强和双相增强扫描中经历了肾脏的术前多相光谱CT扫描。测量并计算出这些病变,正常肾皮层和PSOAS主要的标准化碘浓度(NIC)。分析了这些病变和正常组织的光谱曲线,以用拉伸指数非线性回归分析模型(Y = -B·xα)计算拉伸指数指数(α)和B值。使用单向ANOVA比较α,B值和NIC之间的α,B值和NIC与预增强和两种增强相的差异。使用Pearson系数测试评估α,B值和NIC之间的相关性,其意义在5%水平下分配。结果:预增强扫描中的组之间α值没有显着差异。在皮质阶段(CP)中,在最小脂肪Ram1和肿瘤肾细胞癌中或CCRCC和正常肾皮层之间没有显着差异和NIC和α值。然而,在肾脏阶段(NP)中,在最小脂肪Ram1和衰减性肾细胞癌之间发现α值的显着差异,但它们之间的NIC没有差异。在NP中,CCRCC和正常肾皮层之间的NIC和α值存在显着差异。在CP和NP中,PSOAS主要和其他参数中的其他组之间存在显着差异。对于B值,在预增强扫描中,PSOAS主要和其他组之间以及CCRCC和正常肾皮质之间存在显着差异。其他群体之间没有显着差异。在增强后,在Cp和NP中,在B值的PSOAS主要和其他组之间观察到显着差异,但在所有肾脏肿瘤和正常的肾皮层之间没有观察到显着差异。在CP(r = 0.780,p = 0.00)和np(r = 0.693,p = 0.00)之间的α值和NIC之间存在线性相关性。 B值和NIC在CP中具有低相关性,NP在NP中没有相关性。结论:具有拉伸指数非线性回归分析模型的定量光谱CT可以提高肾肿瘤的差异诊断能力。其临床价值仍有待进一步探索其他类型的软组织病变。

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