Zhang Jin, Wang Wen, Dong Jinhua, Yang Xiong, Bai Shuwei, Tian Jiaqi, Li Bo, Li Xiao, Zhang Jianjian, Wu Hangyu, Zeng Xiaoxi, Ye Yongqiang, Ding Shenghao, Wan Jieqing, Wu Ke, Mao Yufei, Li Cheng, Zhang Na, Xu Jianrong, Dai Yongming, Shi Feng, Sun Beibei, Zhou Yan, Zhao Huilin
Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
NPJ Digit Med. 2025 Jul 28;8(1):483. doi: 10.1038/s41746-025-01866-x.
Three-dimensional magnetic resonance vessel wall imaging (3D MR-VWI) is critical for characterizing cerebrovascular pathologies, yet its clinical adoption is hindered by labor-intensive postprocessing. We developed VWI Assistant, a multi-sequence integrated deep learning platform trained on multicenter data (study cohorts 1981 patients and imaging datasets) to automate artery segmentation and reconstruction. The framework demonstrated robust performance across diverse patient populations, imaging protocols, and scanner manufacturers, achieving 92.9% qualified rate comparable to expert manual delineation. VWI Assistant reduced processing time by over 90% (10-12 min per case) compared to manual methods (p < 0.001) and improved inter-/intra-reader agreement. Real-world deployment (n = 1099 patients) demonstrated rapid clinical adoption, with utilization rates increasing from 10.8% to 100.0% within 12 months. By streamlining 3D MR-VWI workflows, VWI Assistant addresses scalability challenges in vascular imaging, offering a practical tool for routine use and large-scale research, significantly improving workflow efficiency while reducing labor and time costs.
三维磁共振血管壁成像（3D MR-VWI）对于表征脑血管病变至关重要，但其临床应用受到劳动密集型后处理的阻碍。我们开发了VWI Assistant，这是一个多序列集成深度学习平台，在多中心数据（研究队列包括1981名患者和成像数据集）上进行训练，以实现动脉分割和重建的自动化。该框架在不同患者群体、成像协议和扫描仪制造商中均表现出强大的性能，合格比率达到92.9%，与专家手动描绘相当。与手动方法相比，VWI Assistant将处理时间减少了90%以上（每例10 - 12分钟）（p < 0.001），并提高了不同阅片者之间/阅片者内部的一致性。实际应用（n = 1099名患者）表明其临床应用迅速，利用率在12个月内从10.8%提高到100.0%。通过简化3D MR-VWI工作流程，VWI Assistant解决了血管成像中的可扩展性挑战，为常规使用和大规模研究提供了一个实用工具，显著提高了工作流程效率，同时降低了人力和时间成本。
