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Published on: August 2, 2018
Correlation between CT spectral quantitative parameters and expression levels of HIF-1α and ALX1 in non-small cell
Yulin Jia1, Qiulian Sun2, Yiqiao Wang3
1Radiology Department, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Abstract:
To detect the expression levels of hypoxia inducible factor-1alpha (HIF-1α) and aristaless-like homeobox 1 (ALX1) in non-small cell lung cancer and analyze the relationship between CT spectral quantitative parameters and immunohistochemical markers, in order to evaluate the biological characteristics of lung cancer by spectral CT. Spectral CT data and paraffin masses of 50 adult patients with lung cancer were collected. CT quantitative parameters including the slope of spectral curve, effective atomic number and iodine concentration in enhanced phases were acquired. Expression levels of HIF-1α and ALX1 were detected by immunohistochemical tests, and compared between different pathological types and differentiation grades of tumor cells. CT quantitative parameters at different expression levels of HIF-1α and ALX1 were compared, respectively. The relationship between CT quantitative parameters and expression levels of HIF-1α and ALX1 were analyzed. There was no significant difference of expression levels of HIF-1α and ALX1 between adenocarcinoma and squamous cell carcinoma. Expression levels of HIF-1α among different differentiation grades of tumor cells had significant difference (χ2 = 27.100, P < .001), while without significant difference in ALX1 expression. CT spectral parameters had significant difference among expression levels of HIF-1α and ALX1 (P < .01). There was a positive correlation between each CT spectral parameter and the expression level of immunohistochemical markers. CT spectral quantitative parameters are significantly different among expression levels of immunohistochemical markers. The positive correlation between CT quantitative parameter and expression level of immunohistochemical markers suggests CT spectral imaging could predict biological characteristics of tumors.

