Abstract: Objective To investigate the value of 3.0T magnetic resonance diffusion weighted imaging （MR-DWI） parameters combined with prostate-specific antigen density （PSAD） on predicting the differentiation degree of prostate cancer. Methods 80 patients with prostate cancer in the hospital from August 2021 to August 2024 were included in this study. According to the results of clinical and pathological examination, they were divided into 32 cases in highly differentiated group （Gleason score<7 points） and 48 cases in moderately and poorly differentiated group （Gleason score≥7 points）. The MR-DWI signs, apparent diffusion coefficient （ADC） under different b values （0 s/mm², 1000 s/mm²） and PSAD were analyzed and compared. The correlation between ADC, PSAD and Gleason score was analyzed. Receiver operating characteristic （ROC） curve was used to analyze the evaluation value of ADC and PSAD on differentiation degree of prostate cancer. Results Compared with highly differentiated group, the proportions of cases with blurred lesion boundary and lesion located in peripheral zone by MR-DWI were more in moderately and poorly differentiated group （P<0.05）. The ADCs under different b values in moderately and poorly differentiated group were smaller than those in highly differentiated group, and PSAD was higher than that in highly differentiated cancer group （P<0.05）. ADC was negatively correlated with Gleason score （P<0.05）, and PSAD was positively correlated with Gleason score （P<0.05）. The results of the ROC curve analysis for assessing the risk of low-to-intermediate-grade prostate cancer showed that the areas under the curve （AUCs） for the ADC value （b=50 s/mm²）, the ADC value （b=1200 s/mm²）, the PSAD level, and the combined model were 0.747, 0.704, 0.700, and 0.890, respectively. Statistical comparison indicated no significant difference in diagnostic performance among the three individual indicators （P>0.05）. However, the diagnostic performance of the combined model was significantly superior to that of any single indicator （Z-scores=2.662, 3.190, and 2.593, respectively; all P<0.05）. Among all assessment models, the combined model demonstrated the highest diagnostic efficacy, with a sensitivity of 66.67% and a specificity of 96.87%. Conclusion Both ADC values and PSAD levels are effective biomarkers for assessing the differentiation grade of prostate cancer. A multiparametric model, constructed by combining MR-DWI-derived ADC values with serum PSAD levels, demonstrates superior diagnostic performance in the preoperative prediction of low-to-intermediate-grade prostate cancer risk compared to each individual indicator.

Key words: magnetic resonance diffusion imaging, apparent diffusion coefficient, prostate-specific antigen density, prostate cancer, differentiation degree

摘要： 目的 探讨3.0T磁共振弥散加权成像（MR-DWI）参数联合前列腺特异性抗原密度（PSAD）预测前列腺癌分化程度的价值。方法 将我院2021年8月到2024年8月收治的前列腺腺癌患者80例纳入本次研究对象,按照临床及病理检查结果分为高分化组32例（Gleason评分<7分）和中低分化组48例（Gleason评分≥7分）。分析比较各组患者MR-DWI征象、不同b值（50 s/mm²、1200 s/mm²）下表观扩散系数（ADC）及PSAD,分析ADC值、PSAD与Gleason评分的相关性,并使用受试者工作特征（ROC）曲线分析ADC值和PSAD对前列腺癌分化程度的评估价值。结果 相较于高分化组,中低分化组患者MR-DWI显示病灶区边界模糊、病灶位于外周带的例数占比更高（P<0.05）;中低分化组患者不同b值下的ADC值均小于高分化组,PSAD高于高分化组（P<0.05）;ADC值与Gleason评分呈负相关（P<0.05）,PSAD与Gleason评分呈正相关（P<0.05）;ROC曲线分析结果显示,在评估前列腺癌中低分化风险时,ADC值（b=50 s/mm²）、ADC值（b=1200 s/mm²）、PSAD水平及三者联合模型的曲线下面积（AUC）分别为0.747、0.704、0.700和0.890。统计学比较表明,三个独立指标（两种b值下的ADC值及PSAD水平）之间的诊断效能差异无统计学意义（P>0.05）。然而,三者联合模型的诊断效能显著优于任何单一指标（Z值分别为2.662、3.190、2.593,均P<0.05）。在所有评估方案中,联合模型的诊断效能最高,其敏感度为66.67%,特异度为96.87%。结论 ADC值和PSAD水平均为评估前列腺癌分化程度的有效生物学标志物,将MR-DWI衍生的ADC值与血清PSAD水平相结合,构建的多参数联合模型在术前预测前列腺癌中低分化风险中的诊断效能优于各独立指标。

关键词: 磁共振扩散成像, 表观扩散系数, 前列腺特异性抗原密度, 前列腺癌, 分化程度