딥러닝 자유호흡기법의 간 확산강조영상에서 b-value 별 여기횟수에 따른 겉보기확산계수 지도의 정확도 분석 = Analysis of Apparent Diffusion Coefficient Map Accuracy in Deep Learning Diffusion Weighted Imaging in the Liver for a Free Breathing Technique by the Number of Excitation for b-values

국문 초록 (Abstract)

본 연구에서는 호흡동조화기법의 대안으로 딥러닝 자유호흡기법에서 b-value 별 겉보기확산계수 값을 평가하고 확산강조영상과 겉보기확산계수 지도의 해부학적 일치성을 분석하여 적절한 여기횟수 값을 알아보고자 하였다. 연구방법은 2023년 7월부터 2024년 1월까지 간 자기공명영상 검사가 의뢰된 성인 남녀 35명을 대상으로 하였고 사용장비는 Magnetom Skyra 3.0T(Siemens, Germany)를 이용하였다. 자유호흡기법의 비교를 위해 b-value 50, 400, 800(s/mm2)의 여기횟수를 각각 딥러닝 호흡동조화기법에서 2,3,4으로 딥러닝을 이용하지 않은 일반 자유호흡기법에서 4,6,8으로 검사하였다. 딥러닝을 추가한 일반 자유호흡기법에서는 1,2,3 여기횟수, 2,3,4 여기횟수, 3,5,6 여기횟수, 4,6,8 여기횟수로 변화하였다. 연구 결과 딥러닝 자유호흡기법에서 간의 좌엽과 우엽, 담낭의 평균 겉보기확산계수 값은 딥러닝 호흡동조화기법과 비교하여 모두 통계적 유의성을 확인하였다. 한편 정성적 평가의 해부학적 일치성을 분석한 결과 딥러닝 자유호흡기법의 3,5,6 여기횟수와 4,6,8 여기횟수에서 가장 높은 점수를 얻었으며 검사 시간에서는 딥러닝 호흡동조화기법과 비교하여 약 51%, 40% 감소하였다. 따라서 간 진단에 있어 딥러닝 자유호흡기법에서 b-value 별 적절한 여기횟수 값을 이용한다면 겉보기확산계수 지도의 정확도 유지와 함께 검사시간을 감소시킬 수 있어 임상적으로 유용한 검사가 될 것으로 사료된다.

다국어 초록 (Multilingual Abstract)

This study evaluated the apparent diffusion coefficient value by varying the number of excitation for b-values in deep learning for a free breathing technique as an alternative to a prospective acquisition correction technique. Thirty-five patients examination from July 2023 to January 2024, using the Magnetom Skyra 3.0T. DWI was performed using FB with DL . The b-values were fixed at 50, 400, and 800 and the NEX variations were 1,2,3 NEX, 2,3,4 NEX, 3,5,6 NEX, and 4,6,8 NEX. The ADC value of the left and right lobe liver and gallbladder displayed similar result s to PACE. Misregistration of 3,5,6 and 4,6,8 NEX in the FB with DL yielded the highest scores. Respectively, the scan time was reduced by approximately 51% and 40% for PACE with DL. FB with DL using NEX for b-values effectively reduced the scan time without any deterioration in ADC Map accuracy. Therefore, this technique is a clinically feasible examination.

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