Kim Daniel Hyeong Seok, Sonni Ida, Grogan Tristan, Sisk Anthony, Murthy Vishnu, Hsu William, Sung KyungHyun, Lu David S, Reiter Robert E, Raman Steven S
From the Departments of Radiological Sciences (D.H.S.K., I.S., V.M., W.H., K.H.S., D.S.L., S.S.R.), Medicine Statistics Core (T.G.), Pathology (A.S.), and Urology (R.E.R., S.S.R.), David Geffen School of Medicine at UCLA, 885 Tiverton Dr, Los Angeles, CA 90095.
Radiol Imaging Cancer. 2025 Jan;7(1):e240011. doi: 10.1148/rycan.240011.
Purpose To determine which quantitative 3-T multiparametric MRI (mpMRI) parameters correlate with and help predict the presence of aggressive large cribriform pattern (LCP) and intraductal carcinoma (IDC) prostate cancer (PCa) at whole-mount histopathology (WMHP). Materials and Methods This retrospective study included 130 patients (mean age ± SD, 62.6 years ± 7.2; 100% male) with 141 PCa lesions who underwent preoperative prostate 3-T mpMRI, radical prostatectomy, and WMHP between January 2019 and December 2022. Lesions at WMHP were matched to 3-T mpMRI lesions with American College of Radiology Prostate Imaging Reporting and Data System version 2.1 scores of at least 3 or higher, and the following parameters were derived: apparent diffusion coefficient (ADC), volume transfer constant, rate constant, and initial area under the curve (iAUC). Each lesion was categorized into three subcohorts with increasing aggressiveness: LCP negative and IDC negative (subcohort 1), LCP positive and IDC negative (subcohort 2), and LCP positive and IDC negative (subcohort 3). Analysis of variance was performed to assess differences, Jonckheere test was performed to establish trends, and a classification and regression tree (CART) was used to establish a prediction model. Results Of the 141 total lesions, there were 41 (29.1%), 49 (34.8%), and 51 (36.2%) lesions in subcohorts 1, 2, and 3, with mean ADCs of 892 × 10 mm/sec ± 20, 826 × 10 mm/sec ± 209, and 763 × 10 mm/sec ± 163 ( = .007) and mean iAUCs of 5.4 mmol/L/sec ± 2.5, 6.7 mmol/L/sec ± 3.0, and 6.9 mmol/L/sec ± 3.5 ( = .04), respectively. ADC was negatively correlated ( = .004), and rate constant and iAUC were positively correlated ( = .048 and = .04, respectively) with increasing histologic PCa aggressiveness. The CART model correctly allocated 39.0%, 24.5%, and 84.3% of PCa lesions to subcohorts 1, 2, and 3, respectively. Conclusion Quantitative 3-T mpMRI parameters significantly correlated with and helped predict aggressive LCP and IDC PCa at WMHP. Prostate, MRI, Pathology © RSNA, 2025.
确定哪些定量3T多参数磁共振成像（mpMRI）参数与全层组织病理学（WMHP）中侵袭性大筛状模式（LCP）和导管内癌（IDC）前列腺癌（PCa）的存在相关，并有助于预测其存在。材料与方法：这项回顾性研究纳入了130例患者（平均年龄±标准差，62.6岁±7.2岁；100%为男性），他们在2019年1月至2022年12月期间接受了术前前列腺3T mpMRI、根治性前列腺切除术和WMHP，共141个PCa病变。WMHP中的病变与美国放射学会前列腺影像报告和数据系统第2.1版评分至少为3或更高的3T mpMRI病变进行匹配，并得出以下参数：表观扩散系数（ADC）、容积转移常数、速率常数和曲线下初始面积（iAUC）。每个病变被分为三个侵袭性逐渐增加的亚组：LCP阴性和IDC阴性（亚组1）、LCP阳性和IDC阴性（亚组2）、LCP阳性和IDC阳性（亚组3）。采用方差分析评估差异，Jonckheere检验确定趋势，并使用分类与回归树（CART）建立预测模型。结果：在141个病变中，亚组1、2和3分别有41个（29.1%）、49个（34.8%）和51个（36.2%）病变，平均ADC分别为892×10⁻⁶mm²/sec±20、826×10⁻⁶mm²/sec±209和763×10⁻⁶mm²/sec±163（P = 0.007），平均iAUC分别为5.4 mmol/L/sec±2.5、6.7 mmol/L/sec±3.0和6.9 mmol/L/sec±3.5（P = 0.04）。ADC与组织学PCa侵袭性增加呈负相关（P = 0.004），速率常数和iAUC与组织学PCa侵袭性增加呈正相关（分别为P = 0.048和P = 0.04）。CART模型分别将39.0%、24.5%和84.3%的PCa病变正确分配到亚组1、2和3。结论：定量3T mpMRI参数与WMHP中侵袭性LCP和IDC PCa显著相关，并有助于预测其发生。前列腺、磁共振成像、病理学 © RSNA，2025年。
