Abdominal Imaging Section and Nuclear Radiology Department, Imaging Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH, 44195, USA.
Pathology and Laboratory Medicine Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH, 44195, USA.
Eur Radiol. 2019 Sep;29(9):4861-4870. doi: 10.1007/s00330-019-06114-x. Epub 2019 Mar 7.
We sought to evaluate the correlation between MRI phenotypes of prostate cancer as defined by PI-RADS v2 and the Decipher Genomic Classifier (used to estimate the risk of early metastases).
This single-center, retrospective study included 72 nonconsecutive men with prostate cancer who underwent MRI before radical prostatectomy performed between April 2014 and August 2017 and whose MRI registered lesions were microdissected from radical prostatectomy specimens and then profiled using Decipher (89 lesions; 23 MRI invisible [PI-RADS v2 scores ≤ 2] and 66 MRI visible [PI-RADS v2 scores ≥ 3]). Linear regression analysis was used to assess clinicopathologic and MRI predictors of Decipher results; correlation coefficients (r) were used to quantify these associations. AUC was used to determine whether PI-RADS v2 could accurately distinguish between low-risk (Decipher score < 0.45) and intermediate-/high-risk (Decipher score ≥ 0.45) lesions.
MRI-visible lesions had higher Decipher scores than MRI-invisible lesions (mean difference 0.22; 95% CI 0.13, 0.32; p < 0.0001); most MRI-invisible lesions (82.6%) were low risk. PI-RADS v2 had moderate correlation with Decipher (r = 0.54) and had higher accuracy (AUC 0.863) than prostate cancer grade groups (AUC 0.780) in peripheral zone lesions (95% CI for difference 0.01, 0.15; p = 0.018).
MRI phenotypes of prostate cancer are positively correlated with Decipher risk groups. Although PI-RADS v2 can accurately distinguish between lesions classified by Decipher as low or intermediate/high risk, some lesions classified as intermediate/high risk by Decipher are invisible on MRI.
• MRI phenotypes of prostate cancer as defined by PI-RADS v2 positively correlated with a genomic classifier that estimates the risk of early metastases. • Most but not all MRI-invisible lesions had a low risk for early metastases according to the genomic classifier. • MRI could be used in conjunction with genomic assays to identify lesions that may carry biological potential for early metastases.
我们旨在评估前列腺癌的 MRI 表型（由 PI-RADS v2 定义）与 Decipher 基因组分类器（用于估计早期转移风险）之间的相关性。
这是一项单中心、回顾性研究，纳入了 72 名连续非患者，他们于 2014 年 4 月至 2017 年 8 月期间接受了根治性前列腺切除术之前的 MRI 检查，且其 MRI 检出的病变在根治性前列腺切除标本中进行了微解剖，并使用 Decipher 进行了分析（89 个病变；23 个 MRI 不可见[PI-RADS v2 评分≤2]和 66 个 MRI 可见[PI-RADS v2 评分≥3]）。线性回归分析用于评估临床病理和 MRI 预测因素与 Decipher 结果之间的关系；相关系数（r）用于量化这些关联。AUC 用于确定 PI-RADS v2 是否可以准确区分低风险（Decipher 评分<0.45）和中/高风险（Decipher 评分≥0.45）病变。
MRI 可见病变的 Decipher 评分高于 MRI 不可见病变（平均差异 0.22；95%置信区间 0.13，0.32；p<0.0001）；大多数 MRI 不可见病变（82.6%）为低风险。PI-RADS v2 与 Decipher 具有中度相关性（r=0.54），在周围带病变中比前列腺癌分级组（AUC 0.780）具有更高的准确性（AUC 0.863）（差异的 95%置信区间为 0.01，0.15；p=0.018）。
前列腺癌的 MRI 表型与预测早期转移风险的基因组分类器呈正相关。虽然 PI-RADS v2 可以准确区分 Decipher 分类为低危或中/高危的病变，但根据基因组分类器，一些分类为中/高危的病变在 MRI 上不可见。
