AI辅助压缩感知用于优化内耳成像：CSAI T2-DRIVE的多评估者MRI评价
AI-Assisted Compressed Sensing for Optimized Inner Ear Imaging: a Multi-Rater MRI Evaluation of CSAI T2-DRIVE.
文献信息
| PMID | 42704461 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Enrike Rosenkranz |
| 作者单位 | Institute of Diagnostic and Interventional Neuroradiology, TUM University Hospital, Rechts der Isar Hospital, Munich, Germany. enrike.rosenkranz@tum.de. |
| 期刊 | Clinical neuroradiology |
| SCI 分区 | Q2 |
| IF | 2.9 |
| 研究类型 | AI/ML · 临床 |
| 所属专科 | 耳科 |
中文摘要
目的： 高分辨率T2加权成像对于人工耳蜗植入前的术前评估至关重要。基于AI重建的压缩感知（CSAI）可缩短采集时间，同时保持图像质量。尽管CSAI已在多种临床应用中确立，但其在内耳成像中的表现仍不明确。本研究评估了CSAI优化的T2-DRIVE序列在不同分辨率和采集时间下对内耳结构的显示效果。
方法： 在30名健康参与者中，以0.65、0.5和0.4 mm的各向同性分辨率采集CS T2-DRIVE。0.5和0.4 mm数据集还使用市售的基于AI的重建算法进行重建。三名评估者使用5点Likert量表独立评估解剖标志（耳蜗、半规管、前庭蜗神经）的成像质量、伪影和信噪比（SNR）。每名评估者在≥4周后对一部分图像重新评分。使用二次加权Cohen's kappa计算评估者间和评估者内信度，并使用累积连接混合模型（CLMM）分析序列之间的差异。
结果： 无论采用何种重建算法，0.4 mm各向同性成像的SNR均低于CSAI 0.5 mm（p < 0.001）。在所有评估者中，与0.65 mm成像相比，0.5 mm分辨率的CSAI T2显著改善了耳蜗和前庭蜗神经的显示（p < 0.001），而半规管的可评估性降低（p = 0.082）。采集时间随分辨率提高而增加（0.65/0.5/0.4 mm：4:02/4:25/4:34分钟）。
结论： AI驱动的重建算法能够在0.5 mm分辨率下，以极小的扫描时间增加，实现对关键内耳结构成像的统计学显著改善。
英文摘要
PURPOSE: High-resolution T2-weighted imaging is essential for preoperative assessment before cochlear implantation. Compressed sensing (CS) with AI-based reconstruction (CSAI) reduces acquisition times whilst preserving image quality. Although CSAI has been established in various clinical applications, its performance in inner ear imaging remains unclear. This study assesses CSAI-optimized T2-DRIVE sequences at different resolutions and acquisition times for visualizing inner ear structures.
METHODS: In 30 healthy participants, CS T2-DRIVE was acquired at isotropic resolutions of 0.65, 0.5, and 0.4 mm. 0.5 and 0.4 mm datasets were also reconstructed using a commercially available AI-based reconstruction algorithm. Three raters independently assessed the imaging quality of anatomical landmarks (cochlea, semicircular canals, vestibulocochlear nerve), artifacts, and signal-to-noise ratio (SNR) using a 5-point Likert scale. Each rater re-rated a subset of images after ≥ 4 weeks. Inter- and intra-rater reliability were calculated using quadratically weighted Cohen's kappa, and differences between sequences were analyzed using cumulative link mixed models (CLMM).
RESULTS: 0.4 mm isotropic imaging exhibited lower SNR compared to CSAI 0.5 mm, regardless of reconstruction algorithm (p < 0.001). Across all raters, CSAI T2 at 0.5 mm resolution significantly improved delineation of the cochlea and vestibulocochlear nerve compared to 0.65 mm imaging (p < 0.001), while assessability of semicircular canals was reduced (p = 0.082). Acquisition times increased with higher resolutions (0.65/0.5/0.4 mm: 4:02/4:25/4:34 min).
CONCLUSION: AI-driven reconstruction algorithms enable statistically significant improvements in imaging of key inner-ear structures with minimal increases in scan time at 0.5 mm resolution.