Optimizations of 3D MRI Techniques in Brain by Evaluating SENSE Factors

삼차원 자기공명영상법의 뇌 구조 영상을 위한 최적화 연구: 센스인자 변화에 따른 신호변화 평가

  • Park, Myung-Hwan (Department of Radiology, East-West Neo Medical Center, Kyung Hee University) ;
  • Lee, Jin-Wan (Department of Radiology, East-West Neo Medical Center, Kyung Hee University) ;
  • Lee, Kang-Won (Department of Radiology, East-West Neo Medical Center, Kyung Hee University) ;
  • Ryu, Chang-Woo (Department of Radiology, East-West Neo Medical Center, Kyung Hee University) ;
  • Jahng, Geon-Ho (Department of Radiology, East-West Neo Medical Center, Kyung Hee University)
  • 박명환 (경희대학교 동서신의학병원 영상의학과) ;
  • 이진완 (경희대학교 동서신의학병원 영상의학과) ;
  • 이강원 (경희대학교 동서신의학병원 영상의학과) ;
  • 류창우 (경희대학교 동서신의학병원 영상의학과) ;
  • 장건호 (경희대학교 동서신의학병원 영상의학과)
  • Published : 2009.12.30

Abstract

Purpose : A parallel imaging method provides us to improve temporal resolution to obtain three-dimensional (3D) MR images. The objective of this study was to optimize three 3D MRI techniques by adjusting 2D SESNE factors of the parallel imaging method in phantom and human brain. Materials and Methods : With a 3 Tesla MRI system and an 8-channel phase-array sensitivity-encoding (SENSE) coil, three 3D MRI techniques of 3D T1-weighted imaging (3D T1WI), 3D T2-weighted imaging (3D T2WI) and 3D fluid attenuated inversion recovery (3D FLAIR) imaging were optimized with adjusting SESNE factors in a water phantom and three human brains. The 2D SENSE factor was applied on the phase-encoding and the slice-encoding directions. Signal-to-noise ratio(SNR), percent signal reduction rate(%R), and contrast-to-noise ratio(CNR) were calculated by using signal intensities obtained in specific regions-of-interest (ROI). Results : In the phantom study, SENSE factor = 3 was provided in 0.2% reduction of signals against without using SENSE with imaging within 5 minutes for 3D T1WI. SENSE factor = 2 was provided in 0.98% signal reduction against without using SENSE with imaging within 5 minutes for 3D T2WI. SENSE factor = 4 was provided in 0.2% signal reduction against without using SENSE with imaging around 6 minutes for 3D FLAIR. In the human brain study, SNR and CNR were higher with SENSE factors = 3 than 4 for all three imaging techniques. Conclusion : This study was performed to optimize 2D SENSE factors in the three 3D MRI techniques that can be scanned in clinical time limitations with minimizing SNR reductions. Without compromising SNR and CNR, the optimum 2D SENSE factors were 3 and 4, yielding the scan time of about 5 to 6 minutes. Further studies are necessary to optimize 3D MRI techniques in other areas in human body.

목적 : 평행영상(Parallel imaging)기법의 개발로 긴 촬영시간 때문에 종종 사용되지 못하던 삼차원 영상기법이 최근 들어 환자 병을 진단하는데 새로이 사용되고 있다. 이 연구의 목적은 최근에 뇌 영상에서 개발되어 이용되고 있는 삼차원 자기공명영상을 사람의 뇌에서 짧은 시간 내에 얻을 수 있도록 2차원 평행영상 기법을 사용한 최적화 방법을 연구하는데 있다. 대상 및 방법 : 검사 장비는 3.0T 자기공명영상장치를 이용하였으며 8-채널 SENSE(sensitivity encoding) 머리 코일을 이용하였다. 팬텀 및 3명의 사람 머리에서 영상을 얻었다. 세 가지의 삼차원 영상법인 3D T1WI, 3D T2WI 및 3D FLAIR 영상 방법에 대하여 평행인자(SENSE factor)의 변화에 따른 팬텀 영상을 얻었다. 각각의 영상법에서 영상획득에 적당한 SENSE 인자를 찾기 위해 Phase encoding 방향과 Slice encoding 방향을 조합한 SENSE 인자를 변화시키면서 영상을 얻었다. 영상분석을 위하여 특정영역(ROI)를 설정한 후에 신호대 잡음비 (Signal-to-noise ratio, SNR), 감소분율(Percent Signal Reduction Rate, %R), 대조도(contrast-to-noise ratio, CNR)를 계산하였다. 결과 : 팬텀을 이용한 SENSE 인자 변화에 따른 SNR 및 %R 값의 변화 결과 3D T1WI 방법에서 SENSE 인자를 사용한 것들 중에서 SENSE 인자를 총 3인 경우 약 0.2%의 신호 감소가 나타났고 영상시간은 5분 이내였다. 3D T2WI 방법의 경우 SENSE 인자를 사용한 것들 중에서 SENSE 인자를 총 3인 경우에 약 1.0% 신호 감소가 나타났고 영상 시간은 약 5분 이내였다. 3D FLAIR 방법의 경우 SENSE 인자를 사용한 것들 중에서 SENSE 인자를 4를 사용한 경우에 약 0.2% 신호 감소가 나타났고 영상시간은 약 6분이었다. 사람을 대상으로 할 경우 3D T1W 및 3D T2W영상에서 SNR 및 CNR은 SENSE 인자를 3으로 한 경우에서 SENSE 인자를 4로 한 경우 보다 높게 나타났다. 3D FALIR 영상의 경우 CNR은 SENSE 4에서는 SENSE 3에 비하여 낮았다. 결론 : 본 연구에서는 3가지 3차원 영상법을 실제 임상적용이 가능한 시간 영역에서 SENSE 인자를 변화 시키면서 치적의 영상을 얻도록 하는 연구를 실시한 결과 SNR 감소를 최소화 하면서 영상획득 시간을 약 5분에서 6분 정도 소요되는 2차원 SENSE 인자를 찾았다. 이를 뇌 영상에 적용하였을 경우 SENSE 인자를 적용하지 않은 경우와 비교하면 신호 감소는 최소화 하면서 영상의 질은 큰 영향을 주지 않은 것으로 나타났다. 3D T1W및 3D T2W는 SENSE 인자를 3으로 3D FLAIR인자는 SENSE 인자를 4로 하는 것이 환자를 대상으로 한 뇌 영상에 적합하다고 생각된다. 앞으로는 이들 영상법이 뇌 영상뿐만 아니라 다른 영역의 영상에 적용을 위한 최적화가 필요하다고 생각된다.

Keywords

References

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