The anatomic zone localization based on biparametric MRI for the prediction of the risk degree of prostate cancer

Abstract

Objective: To investigate the anatomic zone localization based on biparametric magnetic resonance imaging (bpMRI) for the prediction of the risk degree in patients with prostate cancer. Methods: A total of 92 patients with prostate cancer confirmed by radical surgery in First Affiliated Hospital, Air Force Medical University, from January 2017 to December 2021 were collected. All patients underwent bpMRI (non-enhanced scan and DWI). According to ISUP grade, those patients were divided into low-risk group [≤grade 2, n=26, aged 71 (64.0, 5.2) years] and high-risk group[≥grade 3, n=66, aged 70.5 (63.0, 74.0) years]. The interobserver consistency test for ADC values was evaluated using the intraclass correlation coefficients (ICC). The differences in total prostate specific antigen (tPSA) between the two groups were compared and the χ2 test was used to compare the differences in the risk of prostate cancer in the transitional and peripheral zone. Independent correlation factors for prostate cancer risk were analyzed by logistic regression using high and low risk of prostate cancer as dependent variables, including factors such as anatomical zone, tPSA, apparent diffusion coefficient mean (ADCmean), apparent diffusion coefficient minimum (ADCmin) and age. Receiver operating characteristic (ROC) curves were plotted to assess the efficacy of the combined models of anatomical zone, tPSA, and anatomical partitioning+tPSA for diagnosing prostate cancer risk. Results: The ICC values of the ADCmean and ADCmin between the observers were 0.906 and 0.885, respectively, with good agreement. The tPSA in the low-risk group was lower than that in the high-risk group [19.64 (10.29, 35.18) ng/ml vs 72.42 (24.79, 187.98) ng/ml; P<0.001]; the risk of prostate cancer in the peripheral zone was higher than that in the transitional zone, and the difference was statistically significant (P<0.01). Multifactorial regression showed that anatomical zones (OR=0.120, 95%CI:0.029-0.501, P=0.004) and tPSA (OR=1.059, 95%CI:1.022-1.099, P=0.002) were risk factors for prostate cancer risk. The diagnostic efficacy of the combined model (AUC=0.895, 95%CI: 0.831-0.958) was better than the predictive efficacy of the single model for both anatomical partitioning (AUC=0.717, 95%CI:0.597-0.837) and tPSA (AUC=0.801, 95%CI: 0.714-0.887) (Z=3.91, 2.47; all P<0.05). Conclusions: The malignant degree of prostate cancer in peripheral zone was higher than that in transitional zone. Combination of anatomic zone located by bpMRI and tPSA can be used to predict the risk of prostate cancer before surgery, expected to provide support for patients to develop personalized treatment strategies.