Abstract

The propose is to study the effectiveness of multi-b-value diffusion-weighted imaging intelligent detection in the diagnosis of benign and malignant prostatic tumors infected by Escherichia coli under single exponential model, double exponential model and tensile exponential model. The patients with prostatic tumors are selected as the research objects, and the image data and interest area data are processed and analyzed through magnetic resonance diffusion weighted imaging and pathological examination of prostate biopsy. The range is divided into three groups: A, B and C. The goodness of fit of each model is compared, and the diagnostic efficacy of ADC (apparent diffusion coefficient), f (perfusion fraction), D (slow diffusion coefficient), D* (rapid diffusion coefficient), DDC (distribution diffusion coefficient) and ɑ (diffusion heterogeneity index) in differentiating benign and malignant prostate tumors is evaluated. The results show that the goodness of fit of single exponential model is low. Adjusted R2 (correction determinant coefficient) decreases with the increase of the maximum b value of fit. The goodness of fit of double exponential model and tensile exponential model is higher. In patients with prostate cancer caused by Escherichia coli, the parameters of ADC, D, DDC and ɑ value of cancer tissue and f value of group A are lower than those of benign tissue. There is no significant difference in parameters D* and f values between benign and cancerous tissues in group B and C, suggesting that the parameters ADC, D, DDC and ɑ value can be used as the basis for differentiating benign and malignant diseases of prostate, while the values of D* and f have no diagnostic efficacy. In the single index model, the ADC value is the most effective parameter to differentiate benign and malignant prostatic tumors on the premise that the b value is 0–2000 s/mm2 and <2000 s/mm2. The D, DDC and α values of double exponential model and tensile exponential model can provide more diagnostic information, and have higher diagnostic value for prostate cancer caused by Escherichia coli. However, their sensitivity and specificity are not obvious, and they can be used as a supplement to the single exponential model.

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