School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, China.
Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
J Magn Reson Imaging. 2021 Oct;54(4):1222-1230. doi: 10.1002/jmri.27678. Epub 2021 May 10.
Preoperative prediction of extracapsular extension (ECE) of prostate cancer (PCa) is important to guide clinical decision-making and improve patient prognosis.
To investigate the value of multiparametric magnetic resonance imaging (mpMRI)-based peritumoral radiomics for preoperative prediction of the presence of ECE.
Retrospective.
Two hundred eighty-four patients with PCa from two centers (center 1: 226 patients; center 2: 58 patients). Cases from center 1 were randomly divided into training (158 patients) and internal validation (68 patients) sets. Cases from center 2 were assigned to the external validation set.
FIELD STRENGTH/SEQUENCE: A 3.0 T MRI scanners (three vendors). Sequence: Pelvic T2-weighted turbo/fast spin echo sequence and diffusion weighted echo planar imaging sequence.
The peritumoral region (PTR) was obtained by 3-12 mm (half of the tumor length) 3D dilatation of the intratumoral region (ITR). Single-MRI radiomics signatures, mpMRI radiomics signatures, and integrated models, which combined clinical characteristics with the radiomics signatures were built. The discrimination ability was assessed by area under the receiver operating characteristic curve (AUC) in the internal and external validation sets.
Fisher's exact test, Mann-Whitney U-test, DeLong test.
The PTR radiomics signatures demonstrated significantly better performance than the corresponding ITR radiomics signatures (AUC: 0.674 vs. 0.554, P < 0.05 on T2-weighted, 0.652 vs. 0.546, P < 0.05 on apparent diffusion coefficient, 0.682 vs. 0.556 on mpMRI in the external validation set). The integrated models combining the PTR radiomics signature with clinical characteristics performed better than corresponding radiomics signatures in the internal validation set (eg. AUC: 0.718 vs. 0.671, P < 0.05 on mpMRI) but performed similar in the external validation set (eg. AUC: 0.684, vs. 0.682, P = 0.45 on mpMRI).
The peritumoral radiomics can better predict the presence of ECE preoperatively compared with the intratumoral radiomics and may have better generalization than clinical characteristics. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: 2.
预测前列腺癌（PCa）的囊外扩展（ECE）对于指导临床决策和改善患者预后非常重要。
研究基于多参数磁共振成像（mpMRI）的肿瘤周围放射组学在预测 ECE 存在方面的价值。
回顾性。
来自两个中心的 284 名 PCa 患者（中心 1：226 名患者；中心 2：58 名患者）。中心 1 的病例被随机分为训练集（158 名患者）和内部验证集（68 名患者）。中心 2 的病例被分配到外部验证集。
磁场强度/序列：3.0T MRI 扫描仪（三个供应商）。序列：盆腔 T2 加权涡轮/快速自旋回波序列和扩散加权回波平面成像序列。
通过对肿瘤内区域（ITR）进行 3-12mm（肿瘤长度的一半）的 3D 扩张获得肿瘤周围区域（PTR）。建立了单个 MRI 放射组学特征、mpMRI 放射组学特征和结合临床特征与放射组学特征的综合模型。在内部和外部验证集中，通过接受者操作特征曲线（ROC）下的面积（AUC）评估区分能力。
Fisher 精确检验、Mann-Whitney U 检验、DeLong 检验。
PTR 放射组学特征的性能明显优于相应的 ITR 放射组学特征（AUC：0.674 与 0.554，P<0.05 在 T2 加权图像上，0.652 与 0.546，P<0.05 在表观扩散系数上，0.682 与 0.556 在外部验证集上的 mpMRI）。在内部验证集中，将 PTR 放射组学特征与临床特征相结合的综合模型的性能优于相应的放射组学特征（例如，AUC：0.718 与 0.671，P<0.05 在 mpMRI 上），但在外部验证集中的表现相似（例如，AUC：0.684，与 0.682，P=0.45 在 mpMRI 上）。
与肿瘤内放射组学相比，肿瘤周围放射组学术前能更好地预测 ECE 的存在，且可能比临床特征具有更好的泛化能力。
4 级。
2 级。
