Observational analysis tracked imaging variations correlating with histopathological markers in prostate cancer, suggesting noninvasive monitoring potential.
The aim of this study was to evaluate the dynamic variations in the quantitative parameters of diffusion-weighted imaging (DWI) at different b-value combinations in a prostate cancer (PCa) mouse model for noninvasive monitoring of histopathological changes. Twenty-five male C57BL/6J mice were randomly allocated into a control group (n=5) or an experimental group (n=20). The experimental groups were used to establish the PCa model. On days 9, 12, 15, and 18 post-modeling, 5 mice were randomly selected for MRI, including T1WI, T2WI, T2WI SPIR, and DWI. The b-values were set at 0, 500, 1000, 1500, and 2000 s/mm2. Apparent diffusion coefficient (ADC) and exponential apparent diffusion coefficient (EADC) values from different b-value combinations were measured. Post-MRI, tumors were excised for histopathological analysis. DWI quantitative parameters, tumor nuclear fraction, and Ki-67 area fraction were compared on different days, along with correlation analysis. ADC values gradually decreased as tumor progressed, whereas EADC values gradually increased. Tumor nuclear fraction increased over time. Ki-67 increased first and then decreased. Tumor nuclear fraction was negatively correlated with the ADC value and positively correlated with the EADC value. The Ki-67 was positively correlated with the ADC value and negatively correlated with the EADC value. ADC values at b=1000, 1500 s/mm2 and the EADC values at b=0, 500 s/mm2 demonstrated the strongest correlations with the tumor nuclear fraction; the ADC and EADC values at b=500, 1000 s/mm2 were more strongly correlated with Ki-67, being potential noninvasive imaging biomarkers for monitoring changes in tumor histopathology.
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Zhou et al. (2025) studied this question.
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