Suppr超能文献

基于MRI的影像组学分析用于胎盘植入谱系高危妊娠患者的术中风险评估

MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum.

作者信息

Chu Caiting, Liu Ming, Zhang Yuzhen, Zhao Shuhui, Ge Yaqiong, Li Wenhua, Gao Chengjin

机构信息

Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China.

GE Healthcare, Pudong New Town, No. 1, Huatuo Road, Shanghai 201203, China.

出版信息

Diagnostics (Basel). 2022 Feb 14;12(2):485. doi: 10.3390/diagnostics12020485.

Abstract

BACKGROUND

Gravid patients at high risk with placenta accreta spectrum (PAS) face life-threatening risk at delivery. Intraoperative risk assessment for patients is currently insufficient. We aimed to develop an assessment system of intraoperative risks through MRI-based radiomics.

METHODS

A total of 131 patients enrolled were randomly grouped according to a ratio of 7:3. Clinical data were analyzed retrospectively. Radiomic features were extracted from sagittal Fast Imaging Employing State-sate Acquisition images. Univariate and multivariate regression analyses were performed to build models using R software. A receiver operating characteristic curve and decision curve analysis (DCA) were performed to determine the predictive performance of models.

RESULTS

Six radiomic features and two clinical variables were used to construct the combined model for selection of removal protocols of the placenta, with an area under the curve (AUC) of 0.90 and 0.91 in the training and test cohorts, respectively. Nine radiomic features and two clinical variables were obtained to establish the combined model for prediction of intraoperative blood loss, with an AUC of 0.90 and 0.88 in the both cohorts, respectively. The DCA confirmed the clinical utility of the combined model.

CONCLUSION

The analysis of combined MRI-based radiomics with clinics could be clinically beneficial for patients.

摘要

背景

患有胎盘植入谱系疾病(PAS)的高危妊娠患者在分娩时面临危及生命的风险。目前对患者的术中风险评估不足。我们旨在通过基于MRI的放射组学开发一种术中风险评估系统。

方法

共纳入131例患者,按照7:3的比例随机分组。对临床资料进行回顾性分析。从矢状面稳态采集快速成像图像中提取放射组学特征。使用R软件进行单变量和多变量回归分析以建立模型。进行受试者操作特征曲线和决策曲线分析(DCA)以确定模型的预测性能。

结果

六个放射组学特征和两个临床变量用于构建胎盘切除方案选择的联合模型,在训练队列和测试队列中的曲线下面积(AUC)分别为0.90和0.91。获得九个放射组学特征和两个临床变量以建立术中失血量预测的联合模型,在两个队列中的AUC分别为0.90和0.88。DCA证实了联合模型的临床实用性。

结论

基于MRI的放射组学与临床相结合的分析对患者可能具有临床益处。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8398/8870740/cb24b62a582a/diagnostics-12-00485-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验