Glessgen Carl, Crowe Lindsey A, Wetzl Jens, Schmidt Michaela, Yoon Seung Su, Vallée Jean-Paul, Deux Jean-François
Department of Radiology, Geneva University Hospitals, Geneva, Switzerland.
Siemens Healthineers AG, Forchheim, Germany.
Eur Radiol. 2025 Jan 22. doi: 10.1007/s00330-025-11364-z.
Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on procedure errors and scan times compared to manual planning alone.
Consecutive patients undergoing non-stress CMR were prospectively enrolled at a single center (August 2023-February 2024) and randomized into manual, or automated scan execution using prototype software. Patients with pacemakers, targeted indications, or inability to consent were excluded. All patients underwent the same CMR protocol with contrast, in breath-hold (BH) or free breathing (FB). Supervising radiologists recorded procedure errors (plane prescription, forgotten views, incorrect propagation of cardiac planes, and field-of-view mismanagement). Scan times and idle phase (non-acquisition portion) were computed from scanner logs. Most data were non-normally distributed and compared using non-parametric tests.
Eighty-two patients (mean age, 51.6 years ± 17.5; 56 men) were included. Forty-four patients underwent automated and 38 manual CMRs. The mean rate of procedure errors was significantly (p = 0.01) lower in the automated (0.45) than in the manual group (1.13). The rate of error-free examinations was higher (p = 0.03) in the automated (31/44; 70.5%) than in the manual group (17/38; 44.7%). Automated studies were shorter than manual studies in FB (30.3 vs 36.5 min, p < 0.001) but had similar durations in BH (42.0 vs 43.5 min, p = 0.42). The idle phase was lower in automated studies for FB and BH strategies (both p < 0.001).
An AI-based automated software performed CMR at a clinical level with fewer planning errors and improved efficiency compared to manual planning.
Question What is the impact of an AI-based automated CMR planning software on procedure errors and scan times compared to manual planning alone? Findings Software-driven examinations were more reliable (71% error-free) than human-planned ones (45% error-free) and showed improved efficiency with reduced idle time. Clinical relevance CMR examinations require extensive technologist training, and continuous attention, and involve many planning steps. A fully automated software reliably acquired non-stress CMR potentially reducing mistake risk and increasing data homogeneity.
评估基于人工智能的自动心脏磁共振成像（CMR）规划软件与单独手动规划相比，对操作错误和扫描时间的影响。
在单一中心（2023年8月至2024年2月）前瞻性纳入连续接受非负荷CMR检查的患者，并随机分为手动组或使用原型软件进行自动扫描执行组。排除有起搏器、特定适应症或无法签署知情同意书的患者。所有患者均接受相同的使用对比剂的CMR检查方案，检查时采用屏气（BH）或自由呼吸（FB）方式。监督放射科医生记录操作错误（层面处方、遗漏视图、心脏层面的错误传播以及视野管理不当）。扫描时间和闲置期（非采集部分）根据扫描仪日志计算。大多数数据呈非正态分布，采用非参数检验进行比较。
纳入82例患者（平均年龄51.6岁±17.5；56例男性）。44例患者接受自动CMR检查，38例接受手动CMR检查。自动检查组的平均操作错误率（0.45）显著低于手动检查组（1.13）（p = 0.01）。自动检查组的无错误检查率（31/44；70.5%）高于手动检查组（17/38；44.7%）（p = 0.03）。在自由呼吸状态下，自动检查的时间短于手动检查（30.3分钟对36.5分钟，p < 0.001），但在屏气状态下两者持续时间相似（42.0分钟对43.5分钟，p = 0.42）。自动检查在自由呼吸和屏气策略下的闲置期均较短（均p < 0.001）。
与手动规划相比，基于人工智能的自动软件在临床水平上进行CMR检查时规划错误更少，效率更高。
问题 与单独手动规划相比，基于人工智能的自动CMR规划软件对操作错误和扫描时间有何影响？ 发现 软件驱动的检查比人工规划的检查更可靠（71%无错误），且效率更高，闲置时间减少。 临床意义 CMR检查需要技术人员进行大量培训并持续关注，且涉及许多规划步骤。全自动化软件能可靠地获取非负荷CMR，可能降低错误风险并提高数据同质性。
