Vita-Salute San Raffaele University, Milan, Italy.
Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Crit Rev Oncol Hematol. 2022 Jan;169:103544. doi: 10.1016/j.critrevonc.2021.103544. Epub 2021 Nov 18.
We present the current clinical applications of radiomics in the context of prostate cancer (PCa) management. Several online databases for original articles using a combination of the following keywords: "(radiomic or radiomics) AND (prostate cancer or prostate tumour or prostate tumor or prostate neoplasia)" have been searched. The selected papers have been pooled as focus on (i) PCa detection, (ii) assessing the clinical significance of PCa, (iii) biochemical recurrence prediction, (iv) radiation-therapy outcome prediction and treatment efficacy monitoring, (v) metastases detection, (vi) metastases prediction, (vii) prediction of extra-prostatic extension. Seventy-six studies were included for qualitative analyses. Classifiers powered with radiomic features were able to discriminate between healthy tissue and PCa and between low- and high-risk PCa. However, before radiomics can be proposed for clinical use its methods have to be standardized, and these first encouraging results need to be robustly replicated in large and independent cohorts.
我们介绍了放射组学在前列腺癌 (PCa) 管理中的当前临床应用。已经搜索了几个使用以下组合关键词的原始文章在线数据库：“(放射组学或 radiomics) AND (前列腺癌或前列腺肿瘤或前列腺肿瘤或前列腺肿瘤)”。选择的论文集中在 (i) PCa 检测，(ii) 评估 PCa 的临床意义，(iii) 生化复发预测，(iv) 放射治疗结果预测和治疗效果监测，(v) 转移检测，(vi) 转移预测，(vii) 预测前列腺外扩展。有 76 项研究进行了定性分析。基于放射组学特征的分类器能够区分健康组织和 PCa 以及低风险和高风险 PCa。然而，在放射组学能够被提议用于临床使用之前，它的方法必须标准化，并且这些令人鼓舞的初步结果需要在大的独立队列中得到稳健的复制。
