面向不完整与退化前列腺MRI的跨模态生成模型及多中心临床验证
A cross-modal generative model for incomplete and degraded prostate MRI with multicentre clinical validation
- College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）
- School of Computer Science and Technology, Tongji University（同济大学计算机科学与技术学院）
- Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院附属仁济医院）
- National University of Singapore（新加坡国立大学）
- Shanghai East Hospital, Tongji University School of Medicine（同济大学医学院附属东方医院）
- McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston (UTHealth Houston)（德克萨斯大学休斯顿健康科学中心麦克威廉姆斯生物信息学院）
- School of Transportation, Southeast University（东南大学交通学院）
- Ningbo Hangzhou Bay Hospital（宁波杭州湾医院）
- Changhai Hospital, Naval Medical University（海军军医大学长海医院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究开发MSCNet跨模态生成框架，可重建前列腺MRI缺失对比、恢复退化扫描，经多中心临床验证，其图像质量符合部分非劣效标准，诊断效能优于基线生成图像，可作为前列腺MRI的辅助技术。
AI中文摘要：
缺失或退化的序列会限制前列腺多参数MRI的应用。我们开发了MSCNet，一种序列条件跨模态生成框架，用于重建不可用对比序列并恢复退化的扫描。在10项补全任务中，任务专属MSCNet的平均结构相似性为0.818，而最强的任务匹配对比方法为0.798；匹配容量分析显示，病变保真度和边界保留度的差异更大。在一项1000例的盲法读者研究中，整体图像质量符合DWI、ADC和T2W补全的预设非劣效标准，但T1W补全不符合。在另一项200例诊断评估中，临床显著癌症的AUC分别为：采集图像0.860、MSCNet生成图像0.841、基线生成图像0.797。一项锁定的186例三医院队列支持多中心可迁移性。这些回顾性结果支持质量控制的跨模态重建作为采集前列腺MRI的辅助手段。
英文摘要：
Missing or degraded sequences can limit prostate multiparametric MRI. We developed MSCNet, a sequence-conditioned cross-modal generative framework for reconstructing unavailable contrasts and restoring degraded acquisitions. Across ten completion tasks, task-specific MSCNet achieved mean structural similarity of 0.818 versus 0.798 for the strongest task-matched comparators; matched-capacity analyses showed larger differences in lesion fidelity and boundary preservation. In a blinded 1,000-case reader study, overall image quality met the prespecified non-inferiority criterion for DWI, ADC and T2W completion, but not T1W. In a separate 200-case diagnostic assessment, AUCs for clinically significant cancer were 0.860 with acquired images, 0.841 with MSCNet and 0.797 with baseline-generated images. A locked 186-case three-hospital cohort supported multicentre transportability. These retrospective results support quality-controlled cross-modal reconstruction as an adjunct to acquired prostate MRI.
