IHU LIRYC, Electrophysiology and Heart Modelling Institute, Université de Bordeaux, INSERM, U1045, Avenue du Haut-Lévêque, 33604, Pessac, France.
Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604, Pessac, France.
MAGMA. 2023 Dec;36(6):877-885. doi: 10.1007/s10334-023-01101-2. Epub 2023 Jun 9.
To simplify black-blood late gadolinium enhancement (BL-LGE) cardiac imaging in clinical practice using an image-based algorithm for automated inversion time (TI) selection.
The algorithm selects from BL-LGE TI scout images, the TI corresponding to the image with the highest number of sub-threshold pixels within a region of interest (ROI) encompassing the blood-pool and myocardium. The threshold value corresponds to the most recurrent pixel intensity of all scout images within the ROI. ROI dimensions were optimized in 40 patients' scans. The algorithm was validated retrospectively (80 patients) versus two experts and tested prospectively (5 patients) on a 1.5 T clinical scanner.
Automated TI selection took ~ 40 ms per dataset (manual: ~ 17 s). Fleiss' kappa coefficient for automated-manual, intra-observer and inter-observer agreements were [Formula: see text]= 0.73, [Formula: see text] = 0.70 and [Formula: see text] = 0.63, respectively. The agreement between the algorithm and any expert was better than the agreement between the two experts or between two selections of one expert.
Thanks to its good performance and simplicity of implementation, the proposed algorithm is a good candidate for automated BL-LGE imaging in clinical practice.
通过基于图像的自动反转时间（TI）选择算法，简化临床实践中的黑血晚期钆增强（BL-LGE）心脏成像。
该算法从 BL-LGE TI 扫描图像中选择 ROI （包括血池和心肌）内具有最高数量亚阈值像素的图像对应的 TI。阈值对应 ROI 内所有扫描图像中最常见的像素强度。在 40 名患者的扫描中优化 ROI 尺寸。该算法在 1.5T 临床扫描仪上进行了回顾性验证（80 名患者）和前瞻性测试（5 名患者）。
自动 TI 选择每个数据集耗时约 40ms（手动：约 17s）。自动-手动、观察者内和观察者间的 Fleiss' kappa 系数分别为[公式：见文本]=0.73、[公式：见文本]=0.70 和 [公式：见文本]=0.63。算法与任何专家之间的一致性均优于两位专家之间或一位专家两次选择之间的一致性。
由于其良好的性能和简单的实现方式，该算法是临床实践中自动 BL-LGE 成像的良好候选方案。
