단면 영상에서 복부 근육의 최적 정량화 방법: 표준화된 근감소증 바이오 마커
- Abstract
- Abstract (English)
Purpose: The quantification of abdominal muscle mass in cross-sectional imaging has been increasingly used to diagnose sarcopenia. We aimed to determine an optimal method with a focus on the measurement area and level.
Methods: Among 50 consecutive subjects who underwent abdominal CT and MRI simultaneously for possible liver donation, the total abdominal muscle area (TAMA) and total psoas muscle area (TPA) at the L3 inferior endplate level were measured by two blinded readers. The inter-scan agreement between CT and MRI and inter-reader agreement between the two readers were evaluated by intraclass correlation coefficient (ICC) and within-subject coefficient of variation (WSCV) analyses. To evaluate the effect of measurement level, one reader measured the TAMA and TPA at six levels from the L2 to L4 vertebral bodies.
Results: Based on the ICC and WSCV values, the reliability of the TAMA was better than that of the TPA in both inter-scan agreement (ICC, 0.928 vs. 0.788 for reader 1 and 0.853 vs. 0.821 for reader 2, respectively; WSCV, 8.3% vs. 23.4% for reader 1 and 10.4% vs. 22.3% for reader 2, respectively) and inter-reader agreement (ICC, 0.986 vs. 0.886 for CT and 0.865 vs. 0.669 for MRI, respectively; WSCV, 8.2% vs. 16.0% for CT and 11.6% vs. 29.7% for MRI, respectively). These results also indicated that the inter-reader agreement of CT was better than that of MRI. In terms of the measurement level, the TAMA did not differ from the L2inf to L4inf levels, whereas the TPA was increased as measurement levels went down.
Conclusions: In terms of reliability, the TAMA is better than the TPA, and CT is better than MRI. To use these sarcopenia biomarkers in clinical practice, the standardization of measurement methods is required with large-scale evidence and the consensus of academic communities.
- Author(s)
- 박지숙
- Issued Date
- 2018
- Awarded Date
- 2018-08
- Type
- Dissertation
- Keyword
- Sarcopenia; biomarker; reliability; computed tomography; magnetic resonance imaging
- URI
- https://oak.ulsan.ac.kr/handle/2021.oak/6599
http://ulsan.dcollection.net/common/orgView/200000103071
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