文章：

前列腺区域特异性成像生物标志物谱在风险分层与生化复发预测中的应用

Prostate Region-Wise Imaging Biomarker Profiles for Risk Stratification and Biochemical Recurrence Prediction

原文发布日期：18 August 2023

DOI: 10.3390/cancers15164163

类型: Article

开放获取: 是

英文摘要：

Background: Identifying prostate cancer (PCa) patients with a worse prognosis and a higher risk of biochemical recurrence (BCR) is essential to guide treatment choices. Here, we aimed to identify possible imaging biomarker (perfusion/diffusion + radiomic features) profiles extracted from MRIs that were able to discriminate patients according to their risk or the occurrence of BCR 10 years after diagnosis, as well as to evaluate their predictive value with or without clinical data. Methods: Patients with localized PCa receiving neoadjuvant androgen deprivation therapy and radiotherapy were retrospectively evaluated. Imaging features were extracted from MRIs for each prostate region or for the whole gland. Univariate and multivariate analyses were conducted. Results: 128 patients (mean [range] age, 71 [50–83] years) were included. Prostate region-wise imaging biomarker profiles mainly composed of radiomic features allowed discriminating risk groups and patients experiencing BCR. Heterogeneity-related radiomic features were increased in patients with worse prognosis and with BCR. Overall, imaging biomarkers profiles retained good predictive ability (AUC values superior to 0.725 in most cases), which generally improved when clinical data were included (particularly evident for the prediction of the BCR, with AUC values ranging from 0.841 to 0.877 for combined models and sensitivity values above 0.960) and when models were built per prostate region vs. the whole gland. Conclusions: Prostate region-aware imaging profiles enable identification of patients with worse prognosis and with a higher risk of BCR, retaining higher predictive values when combined with clinical variables.

摘要翻译： 

背景：识别预后较差且生化复发风险较高的前列腺癌患者对于指导治疗选择至关重要。本研究旨在从磁共振成像中提取可能的影像生物标志物（灌注/扩散+影像组学特征）图谱，以区分患者诊断后10年的风险或生化复发发生情况，并评估其在有无临床数据情况下的预测价值。方法：对接受新辅助雄激素剥夺治疗和放疗的局限性前列腺癌患者进行回顾性评估。从磁共振成像中提取各前列腺区域或全腺体的影像特征，并进行单变量和多变量分析。结果：共纳入128例患者（平均年龄71岁，范围50-83岁）。以前列腺区域为单位的影像生物标志物图谱（主要由影像组学特征构成）能够有效区分风险组别及发生生化复发的患者。预后较差及发生生化复发的患者中，与异质性相关的影像组学特征显著增加。总体而言，影像生物标志物图谱保持了良好的预测能力（多数情况下AUC值高于0.725），当纳入临床数据时预测能力普遍提升（在生化复发预测中尤为明显，组合模型的AUC值介于0.841-0.877，敏感度值超过0.960），且以前列腺区域为单位构建的模型相较于全腺体模型具有更优表现。结论：基于前列腺区域的影像特征图谱能够有效识别预后较差及生化复发高风险患者，当与临床变量结合时具有更高的预测价值。

原文链接：

Prostate Region-Wise Imaging Biomarker Profiles for Risk Stratification and Biochemical Recurrence Prediction