3T에서 뇌 운동피질의 기능적 자기공명영상 연구 : Gradient-Echo와 Spin-Echo EPI의 비교
Functional MR Imaging of Cerebral Motor Cortex on 3 Tesla MR Imaging : Comparison between Gradient and Spin-Echo EPI Techniques
To evaluate the accuracy and extent in the localization of cerebral motor cortex activation using a gradient- echo echo planar imaging(GE-EPI) compared to spin-echo echo planar imaging(SE-EPI) on 3T MR imaging. Functional MR imaging of cerebral motor cortex activation was examined in GE-EPI and SE-EPI in five healthy male volunteers. A right finger movement was accomplished with a paradigm of 6 task and rest periods and the cross-correlation was used for a statistical mapping algorithm. We evaluated any sorts of differences of the time series and the signal intensity changes between the rest and task periods obtained with two techniques. The qualitative analysis was distributed with activation sites of large veins and small veins by using two techniques and was found that both the techniques were clinically useful for delineating large veins and small veins in fMRI. Signal intensity change of the rest and activation periods provided similar activations in both methods(GE-EPI : 0.93±0.11, SE-EPI : 0.80±0.15) but 仕le signal intensity in GE-EPI(133.95±15.76) was larger than in SE-EPI(74.5± 18.90). The average SNRs of EPI raw data were higher at SMA in SE-EPI(48.54±12.37) than GE-EPI(41.4±12.54) and at Ml in SE-EPI(43.24±11.77) than GE_EPI(38.27±6.53). The localization of activation voxds of the GE-EPI showed a larger vein but the SE-EPI generally showed small vein. Then the analysis results of the two techniques were used for a statistical paired student t-test. SE-EPI was found clinically useful for localizing the cerebral motor cortex activation on 3.0T, but showed a little different activation patterns compared to a GE-EPI. In conclusion, SE-EPI may be feasible and can detect true cortical activation from capillaries and GE-EPI can obtain the large veins in the motor cortex activation on 3T MR imaging.
목차
Abstract I. 서론 II. 대상 및 방법 1. 대상 및 영상 획득 2. 과제 패러다임 3. 통계 및 데이터 분석 III. 결과 IV. 고찰 V. 결 론 참고문헌