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Correlation of ADC value and Gleason score, Ki-67, P53 proteins expression in prostate cancer / 中国医学影像技术
Chinese Journal of Medical Imaging Technology ; (12): 236-239, 2019.
Artigo em Chinês | WPRIM | ID: wpr-861464
ABSTRACT

Objective:

To explore the correlation of DWI ADC value and Gleason score, Ki-67, P53 proteins expression in prostate cancer, respectively. Methods Totally 59 patients with prostate cancer who had pathological data were enrolled and underwent DWI examination. The pathological samples were stained with Ki-67, P53 using immunohistochemistry staining. Then Gleason score was used to evaluate the degree of differentiation of tumor cells and stroma, and the patients were divided into well-differentiated group (8 scores, n=19). The differences of ADC value and the correlation with Ki-67 and P53 were analyzed.

Results:

The ADC value of prostate cancer was (0.98±0.19)×10-3 mm2/s in all 59 patients, while in well-differentiated group, moderately-differentiated group and poorly-differentiated group was (1.14±0.17)×10-3 mm2/s, (1.05±0.17)×10-3 mm2/s and (0.88±0.24)×10-3 mm2/s, respectively, and the differences were significant in total and each pairwise comparison (all P<0.05). ADC value of prostate cancer was negatively correlated with Gleason score (rs=-0.611, P=0.019), the expression of Ki-67 (rs=-0.491, P=0.016) and P53 protein (rs=-0.511, P=0.021), respectively.

Conclusion:

ADC value of prostate cancer is negatively correlated with Gleason score and Ki-67, P53 proteins expression. ADC value can be used to preliminarily and noninvasively predict the malignancy degree of tumor cells, the degree of cell differentiation and proliferation in prostate neoplasm.

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: Chinese Journal of Medical Imaging Technology Ano de publicação: 2019 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: Chinese Journal of Medical Imaging Technology Ano de publicação: 2019 Tipo de documento: Artigo