Department of Urology, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
Department of Urology, Gangnam Severance Hospital, Urological Science Institute, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-gu, Seoul, 06273, Republic of Korea.
BMC Urol. 2022 Oct 29;22(1):164. doi: 10.1186/s12894-022-01111-7.
To analyze grayscale values for hypoechoic lesions matched with target lesions evaluated using prebiopsy magnetic resonance imaging (MRI) according to the Prostate Imaging-Reporting and Data System (PI-RADS).
We collected data on 420 target lesions in patients who underwent MRI/transrectal ultrasound fusion-targeted biopsies between January 2017 and September 2020. Images of hypoechoic lesions that matched the target lesions on MRI were stored in a picture archiving and communication system, and their grayscale values were estimated using the red/green/blue scoring method through an embedded function. We analyzed imaging data using grayscale values.
Of the 420 lesions, 261 (62.1%) were prostate cancer lesions. There was no difference in the median grayscale values between benign and prostate cancer lesions. However, grayscale ranges (41.8-98.5 and 42.6-91.8) were significant predictors of prostate cancer and clinically significant prostate cancer (csPC) in multivariable logistic regression analyses. Area under the curve for detecting csPC using grayscale values along with conventional variables (age, prostate-specific antigen levels, prostate volume, previous prostate biopsy results, and PI-RADS scores) was 0.839, which was significantly higher than that for detecting csPC using only conventional variables (0.828; P = 0.036). Subgroup analysis revealed a significant difference for PI-RADS 3 lesions between grayscale values for benign and cancerous lesions (74.5 vs. 58.8, P = 0.008). Grayscale values were the only significant predictive factor (odds ratio = 4.46, P = 0.005) for csPC.
Distribution of grayscale values according to PI-RAD 3 scores was potentially useful, and the grayscale range (42.6-91.8) was a potential predictor for csPC diagnosis.
分析根据前列腺影像报告和数据系统（PI-RADS）评估的术前磁共振成像（MRI）匹配的低回声病变的灰度值。
我们收集了 2017 年 1 月至 2020 年 9 月期间接受 MRI/经直肠超声融合靶向活检的 420 个靶病变患者的数据。MRI 上与靶病变匹配的低回声病变的图像存储在图像存档和通信系统中，并通过嵌入式功能使用红/绿/蓝评分法估计其灰度值。我们使用灰度值分析了影像学数据。
在 420 个病变中，261 个（62.1%）为前列腺癌病变。良性和前列腺癌病变的中位灰度值无差异。然而，灰度范围（41.8-98.5 和 42.6-91.8）是多变量逻辑回归分析中前列腺癌和临床显著前列腺癌（csPC）的显著预测因子。使用灰度值结合常规变量（年龄、前列腺特异性抗原水平、前列腺体积、既往前列腺活检结果和 PI-RADS 评分）检测 csPC 的曲线下面积为 0.839，明显高于仅使用常规变量检测 csPC 的曲线下面积（0.828；P=0.036）。亚组分析显示，PI-RADS 3 病变的良性和癌性病变的灰度值有显著差异（74.5 与 58.8，P=0.008）。灰度值是 csPC 的唯一显著预测因素（优势比=4.46，P=0.005）。
根据 PI-RAD 3 评分分布的灰度值可能具有一定的应用价值，灰度范围（42.6-91.8）可能是预测 csPC 的潜在指标。
