Department of Radiology, the Ninth People's Hospital Chongqing, China.
Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, China.
Clin Imaging. 2021 Apr;72:168-174. doi: 10.1016/j.clinimag.2020.10.028. Epub 2020 Oct 24.
To explore the potential value of MRI texture analysis (TA) combined with prostate-related biomarkers to predict high-grade prostate cancer (HGPCa).
Eighty-five patients who underwent MRI scanning, including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) prior to trans-rectal ultrasound (TRUS)-guided core prostate biopsy, were retrospectively enrolled. TA parameters derived from T2WI and DWI, prostate-specific antigen (PSA), and free PSA (fPSA) were compared between the HGPCa and non-high-grade prostate cancer (NHGPCa) groups using independent Student's t-test and the Mann-Whitney U test. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the predictive value for HGPCa.
Univariate analysis showed that PSA and entropy based on apparent diffusion coefficient (ADC) map differed significantly between the HGPCa and NHGPCa groups and showed higher diagnostic values for HGPCa (area under the curve (AUC) = 82.0% and 80.0%, respectively). Logistic regression and ROC curve analyses revealed that kurtosis, skewness and entropy derived from ADC maps had diagnostic power to predict HGPCa; when the three texture parameters were combined, the area under the ROC curve reached the maximum (AUC = 84.6%; 95% confidence interval (CI): 0.758, 0.935; P = 0.000).
TA parameters derived from ADC may be a valuable tool in predicting HGPCa. The combination of specific textural parameters extracted from ADC map may be additional tools to predict HGPCa.
探讨 MRI 纹理分析（TA）联合前列腺相关生物标志物预测高级别前列腺癌（HGPCa）的潜在价值。
回顾性分析 85 例经直肠超声（TRUS）引导下前列腺穿刺活检前接受 MRI 扫描（包括 T2 加权成像（T2WI）和弥散加权成像（DWI））的患者。采用独立样本 t 检验和 Mann-Whitney U 检验比较 HGPCa 组与非高级别前列腺癌（NHGPCa）组 T2WI 和 DWI 的 TA 参数、前列腺特异性抗原（PSA）和游离前列腺特异性抗原（fPSA）的差异。采用逻辑回归和受试者工作特征（ROC）曲线分析评估对 HGPCa 的预测价值。
单因素分析显示，HGPCa 组与 NHGPCa 组之间 PSA 和基于表观扩散系数（ADC）图的熵差异有统计学意义，对 HGPCa 具有较高的诊断价值（曲线下面积（AUC）分别为 82.0%和 80.0%）。逻辑回归和 ROC 曲线分析显示，ADC 图的峰度、偏度和熵的纹理参数具有预测 HGPCa 的诊断能力；当三个纹理参数联合时，ROC 曲线下面积达到最大（AUC=84.6%；95%置信区间（CI）：0.758，0.935；P=0.000）。
ADC 衍生的 TA 参数可能是预测 HGPCa 的有用工具。从 ADC 图提取的特定纹理参数的组合可能是预测 HGPCa 的附加工具。
