PURPOSE: To optimize imaging parameters for balanced turbo field echo (BTFE) sequence combined with motion-sensitized driven equilibrium (MSDE) preparation for endoleak detection and type classification in phantom experiments. MATERIALS AND METHODS: We prepared four phantoms: a pulsatile flow generator with an aortic aneurysm model simulating no endoleak, and a type-1, type-2, and type-3 endoleak. Throughout the experiments, MSDE-BTFE images with and without flow suppression were obtained at 1.5 T and subtraction images were used for image evaluation. The no-endoleak phantom was imaged using different MSDE-BTFE sequences to optimize the k-space trajectory and evaluate the use of electrocardiogram gating. The relative contrast between flowing saline and background was calculated. Then all phantoms were imaged to determine the optimal velocity encoding (VENC) for endoleak detection and type classification. Three independent observers performed the image evaluation. Consistencies between the interpreted and true results were analyzed using kappa statistics. RESULTS: The 3D low-high k-space trajectory with electrocardiogram gating provided the highest relative contrast. Low VENCs of 2-10 cm/s and high VENCs of 20 cm/s showed perfect consistency in endoleaks detection and type classification, respectively. CONCLUSION: MSDE-BTFE sequences of appropriate VENCs has potential for endoleak detection and type classification, without contrast material.
PURPOSE: To optimize imaging parameters for balanced turbo field echo (BTFE) sequence combined with motion-sensitized driven equilibrium (MSDE) preparation for endoleak detection and type classification in phantom experiments. MATERIALS AND METHODS: We prepared four phantoms: a pulsatile flow generator with an aortic aneurysm model simulating no endoleak, and a type-1, type-2, and type-3 endoleak. Throughout the experiments, MSDE-BTFE images with and without flow suppression were obtained at 1.5 T and subtraction images were used for image evaluation. The no-endoleak phantom was imaged using different MSDE-BTFE sequences to optimize the k-space trajectory and evaluate the use of electrocardiogram gating. The relative contrast between flowing saline and background was calculated. Then all phantoms were imaged to determine the optimal velocity encoding (VENC) for endoleak detection and type classification. Three independent observers performed the image evaluation. Consistencies between the interpreted and true results were analyzed using kappa statistics. RESULTS: The 3D low-high k-space trajectory with electrocardiogram gating provided the highest relative contrast. Low VENCs of 2-10 cm/s and high VENCs of 20 cm/s showed perfect consistency in endoleaks detection and type classification, respectively. CONCLUSION:MSDE-BTFE sequences of appropriate VENCs has potential for endoleak detection and type classification, without contrast material.