儿童及青年加速屏气与自由呼吸电影心脏MRI的临床评估：基于模型深度学习重建（SonicDL）
本研究回顾性纳入25例漏斗胸和15例心肌病患者，对比传统9-RR屏气电影MRI与SonicDL在4-RR屏气、1-RR屏气和1-RR自由呼吸下的表现。SonicDL显著缩短扫描时间57%-87%，4-RR屏气图像质量最高（中位4.50分，P<0.0001），各协议容积指数偏差小且与相位对比流量一致。结论认为SonicDL在保持诊断图像质量和容积准确性同时大幅降低屏气负担。
要点
- 4-RR屏气SonicDL提供加速与保真度的最佳平衡，图像质量优于其他协议。
- 自由呼吸SonicDL可作为屏气能力有限患者的实用替代方案。
- 各SonicDL协议容积指数偏差小，与相位对比流量测定的每搏量一致。
局限性
- 回顾性研究设计。
- 单中心研究。
以上解读依据论文摘要（全文未开放获取或许可不允许翻译转载）。
英文原文（摘要）· 点击展开
BACKGROUND: Balanced steady-state free-precession (bSSFP) cine imaging is the clinical standard for ventricular function assessment but requires multiple breath-holds, which can be challenging for pediatric and young adult patients. Deep learning (DL)-accelerated cine imaging offers the potential to reduce breath-hold burden, shorten scan time, and enable free-breathing acquisitions.
OBJECTIVE: To clinically evaluate a commercially available DL-accelerated cine bSSFP sequence (SonicDL) across multiple acceleration levels and breath-hold/free-breathing configurations, and to assess diagnostic image quality, ventricular volumetric accuracy, and scan time reductions.
MATERIALS AND METHODS: This retrospective study included 25 patients with pectus excavatum and 15 with cardiomyopathy who underwent conventional cine imaging with breath-hold duration of nine cardiac-cycle interval (9-RR) and SonicDL acquisitions at 4-RR breath-hold, 1-RR breath-hold, and 1-RR free breathing. Diagnostic image quality was independently scored by three expert readers using a 5-point scale. Automated DL-based segmentation provided biventricular volumetric indices, with phase-contrast flow serving as the physiological reference for stroke volume. Statistical analysis included repeated-measures ANOVA, paired tests, ICCs, and Bland-Altman analysis.
RESULTS: SonicDL significantly reduced scan time 57% (4-RR breath-hold), 79% (1-RR breath-hold), and 87% (1-RR free breathing) compared with 9-RR breath-hold imaging. Diagnostic image quality was highest for 4-RR breath-hold (median 4.50), significantly exceeding other protocols (P<0.0001). Across all SonicDL protocols, volumetric indices showed small biases (<2 mL/m2 for most parameters) with limits of agreement typically within ±6 mL/m2. Stroke volumes showed close agreement with phase-contrast flow (biases 1-5 mL/m2) across all protocols. In cardiomyopathy patients, diagnostic image quality was lower overall, but volumetric indices agreement remained within clinically acceptable ranges.
CONCLUSION: SonicDL cine bSSFP imaging substantially reduces breath-hold burden and scan time while maintaining diagnostic image quality and close agreement with conventional cine and physiologic flow measurements. The 4-RR breath-hold protocol provided the most favorable balance of acceleration and fidelity, while free-breathing acquisitions offered a practical alternative for patients with limited breath-hold capacity.
引用
- Kocaoglu M, Ta H, Lang SM, et al. Clinical evaluation of accelerated breath-held and free-breathing cine cardiac MRI using model-based deep learning reconstruction (SonicDL) in children and young adults. Pediatr Radiol. 2026. PMID: 42207257. doi:10.1007/s00247-026-06676-1
供执业医师工作参考，不替代临床判断；数值与分级以指南原文为准。