二叶式主动脉瓣患者左心室心肌应变参数磁共振定量研究

SHI Chunyan,ZHANG Hongkai,GAO Yifeng,ZHANG Nan,LIU Jiayi,XU Lei,FAN Zhanming

Journal of Cardiovascular and Pulmonary Diseases（2022）

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Abstract

目的:探讨二叶式主动脉瓣(BAV)患者左心室心肌应变的磁共振定量特征,为临床提供更多手术预后预测参考信息.方法:回顾性分析2015年12月至2021年4月在北京安贞医院行CMR检查的BAV患者作为病例组(BAV组),另选取同期无心血管疾病且CMR无异常表现的人群作为对照组.采用心脏磁共振组织追踪(CMR-TT)技术测量左心室心肌应变参数,包括整体径向应变峰值(GPRS)、周向应变峰值(GPCS)、纵向应变峰值(GPLS)和扭转力(Torsion).根据主动脉瓣狭窄程度将BAV组分成无或轻度狭窄组,中或重度狭窄组.比较BAV组与对照组的差异,并分析与应变参数间的相关性.结果:与对照组比较,BAV组患者GPRS、GPCS、GPLS、Torsion均较低(P均＜0.01),其中中或重度主动脉瓣狭窄组GPRS、GPCS、GPLS较无或轻度主动脉瓣狭窄组均减低(P均＜0.01),而左心室Torsion差异无统计学意义(P=0.23).相关分析结果显示,GPRS、GPCS、GPLS值与BAV患者的LVEF值呈正相关(r分别为0.907、0.784和0.745,P均＜0.0001),而与主动脉瓣狭窄程度呈负相关(r分别为-0.618、-0.602和-0.505,P均＜0.01).Torsion与BAV患者的LVEF值呈正相关(r=0.483,P＜0.05),与V/M呈负相关(r=-0.431,P＜0.05).结论:BAV患者瓣膜功能障碍会导致左心室心肌应变的改变;多参数CMR定量评估有助于BAV患者心脏功能障碍风险分层.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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