Department of Radiology, The Third Affiliated Hospital of Guangzhou Medical University, No. 63 Duobao Road, Guangzhou, 510000, People's Republic of China.
Guangzhou Institute of Obstetrics & Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, No. 63 Duobao Road, Guangzhou, 510000, People's Republic of China.
Eur Radiol. 2022 Nov;32(11):7532-7543. doi: 10.1007/s00330-022-08821-4. Epub 2022 May 19.
To investigate whether an MRI-radiomics-clinical-based nomogram can be used to prenatal predict the placenta accreta spectrum (PAS) disorders.
The pelvic MR images and clinical data of 156 pregnant women with pathologic-proved PAS (PAS group) and 115 pregnant women with no PAS (non-PAS group) identified by clinical and prenatal ultrasonic examination were retrospectively collected from two centers. These pregnancies were divided into a training (n = 133), an independent validation (n = 57), and an external validation (n = 81) cohort. Radiomic features were extracted from images of transverse oblique T2-weighted imaging. A radiomics signature was constructed. A nomogram, composed of MRI morphological findings, radiomic features, and prenatal clinical characteristics, was developed. The discrimination and calibration of the nomogram were conducted to assess its performance.
A radiomics signature, including three PAS-related features, was associated with the presence of PAS in the three cohorts (p < 0.001 to p = 0.001). An MRI-radiomics-clinical nomogram incorporating radiomics signature, two prenatal clinical features, and two MRI morphological findings was developed, yielding a higher area under the curve (AUC) than that of the MRI morphological-determined PAS in the training cohort (0.89 vs. 0.78; p < 0.001) and external validation cohort (0.87 vs. 0.75; p = 0.003), while a comparable AUC value in the validation cohort (0.91 vs. 0.81; p = 0.09). The calibration was good.
An MRI-radiomics-clinical nomogram had a robust performance in antenatal predicting the PAS in pregnancies.
• An MRI-radiomics-clinical-based nomogram might serve as an adjunctive approach for the treatment decision-making in pregnancies suspicious of PAS. • The radiomic score provides a mathematical formula that predicts the possibility of PAS by using the MRI data, and pregnant women with PAS had higher radiomic scores than those without PAS.
研究 MRI 放射组学-临床为基础的列线图是否可用于产前预测胎盘植入谱(PAS)疾病。
回顾性收集了来自两个中心的 156 例经病理证实的 PAS(PAS 组)和 115 例经临床和产前超声检查无 PAS(非 PAS 组)孕妇的盆腔 MRI 图像和临床资料。这些妊娠分为训练(n=133)、独立验证(n=57)和外部验证(n=81)队列。从横斜 T2 加权成像的图像中提取放射组学特征。构建放射组学特征。构建了一个由 MRI 形态学发现、放射组学特征和产前临床特征组成的列线图。对列线图进行了判别和校准,以评估其性能。
三个与 PAS 相关的放射组学特征组成的放射组学特征与三个队列中 PAS 的存在相关(p<0.001 至 p=0.001)。纳入放射组学特征、两个产前临床特征和两个 MRI 形态学发现的 MRI 放射组学-临床列线图,在训练队列(0.89 比 0.78;p<0.001)和外部验证队列(0.87 比 0.75;p=0.003)中,曲线下面积(AUC)高于 MRI 形态学确定的 PAS,而在验证队列中 AUC 值相当(0.91 比 0.81;p=0.09)。校准良好。
MRI 放射组学-临床列线图在产前预测 PAS 方面具有良好的性能。
MRI 放射组学-临床为基础的列线图可能成为疑似 PAS 妊娠治疗决策的辅助方法。
放射组评分提供了一个数学公式,通过 MRI 数据预测 PAS 的可能性,患有 PAS 的孕妇的放射组评分高于没有 PAS 的孕妇。