Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging
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Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging. / Molwitz, I.; Leiderer, M.; McDonough, R.; Fischer, R.; Ozga, A-K; Ozden, C.; Tahir, E.; Koehler, D.; Adam, G.; Yamamura, J.
in: EUR RADIOL, Jahrgang 31, Nr. 10, 26.10.2021, S. 7529-7539.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging
AU - Molwitz, I.
AU - Leiderer, M.
AU - McDonough, R.
AU - Fischer, R.
AU - Ozga, A-K
AU - Ozden, C.
AU - Tahir, E.
AU - Koehler, D.
AU - Adam, G.
AU - Yamamura, J.
PY - 2021/10/26
Y1 - 2021/10/26
N2 - OBJECTIVES: To quantify the proportion of fat within the skeletal muscle as a measure of muscle quality using dual-energy CT (DECT) and to validate this methodology with MRI.METHODS: Twenty-one patients with abdominal contrast-enhanced DECT scans (100 kV/Sn 150 kV) underwent abdominal 3-T MRI. The fat fraction (DECT-FF), determined by material decomposition, and HU values on virtual non-contrast-enhanced (VNC) DECT images were measured in 126 regions of interest (≥ 6 cm2) within the posterior paraspinal muscle. For validation, the MR-based fat fraction (MR-FF) was assessed by chemical shift relaxometry. Patients were categorized into groups of high or low skeletal muscle mean radiation attenuation (SMRA) and classified as either sarcopenic or non-sarcopenic, according to the skeletal muscle index (SMI) and cut-off values from non-contrast-enhanced single-energy CT. Spearman's and intraclass correlation, Bland-Altman analysis, and mixed linear models were employed.RESULTS: The correlation was excellent between DECT-FF and MR-FF (r = 0.91), DECT VNC HU and MR-FF (r = - 0.90), and DECT-FF and DECT VNC HU (r = - 0.98). Intraclass correlation between DECT-FF and MR-FF was good (r = 0.83 [95% CI 0.71-0.90]), with a mean difference of - 0.15% (SD 3.32 [95% CI 6.35 to - 6.66]). Categorization using the SMRA yielded an eightfold difference in DECT VNC HU values between both groups (5 HU [95% CI 23-11], 42 HU [95% CI 33-56], p = 0.05). No significant relationship between DECT-FF and SMI-based classifications was observed.CONCLUSIONS: Fat quantification within the skeletal muscle using DECT is both feasible and reliable. DECT muscle analysis offers a new approach to determine muscle quality, which is important for the diagnosis and therapeutic monitoring of sarcopenia, as a comorbidity associated with poor clinical outcome.KEY POINTS: • Dual-energy CT (DECT) material decomposition and virtual non-contrast-enhanced DECT HU values assess muscle fat reliably. • Virtual non-contrast-enhanced dual-energy CT HU values allow to differentiate between high and low native skeletal muscle mean radiation attenuation in contrast-enhanced DECT scans. • Measuring muscle fat by dual-energy computed tomography is a new approach for the determination of muscle quality, an important parameter for the diagnostic confirmation of sarcopenia as a comorbidity associated with poor clinical outcome.
AB - OBJECTIVES: To quantify the proportion of fat within the skeletal muscle as a measure of muscle quality using dual-energy CT (DECT) and to validate this methodology with MRI.METHODS: Twenty-one patients with abdominal contrast-enhanced DECT scans (100 kV/Sn 150 kV) underwent abdominal 3-T MRI. The fat fraction (DECT-FF), determined by material decomposition, and HU values on virtual non-contrast-enhanced (VNC) DECT images were measured in 126 regions of interest (≥ 6 cm2) within the posterior paraspinal muscle. For validation, the MR-based fat fraction (MR-FF) was assessed by chemical shift relaxometry. Patients were categorized into groups of high or low skeletal muscle mean radiation attenuation (SMRA) and classified as either sarcopenic or non-sarcopenic, according to the skeletal muscle index (SMI) and cut-off values from non-contrast-enhanced single-energy CT. Spearman's and intraclass correlation, Bland-Altman analysis, and mixed linear models were employed.RESULTS: The correlation was excellent between DECT-FF and MR-FF (r = 0.91), DECT VNC HU and MR-FF (r = - 0.90), and DECT-FF and DECT VNC HU (r = - 0.98). Intraclass correlation between DECT-FF and MR-FF was good (r = 0.83 [95% CI 0.71-0.90]), with a mean difference of - 0.15% (SD 3.32 [95% CI 6.35 to - 6.66]). Categorization using the SMRA yielded an eightfold difference in DECT VNC HU values between both groups (5 HU [95% CI 23-11], 42 HU [95% CI 33-56], p = 0.05). No significant relationship between DECT-FF and SMI-based classifications was observed.CONCLUSIONS: Fat quantification within the skeletal muscle using DECT is both feasible and reliable. DECT muscle analysis offers a new approach to determine muscle quality, which is important for the diagnosis and therapeutic monitoring of sarcopenia, as a comorbidity associated with poor clinical outcome.KEY POINTS: • Dual-energy CT (DECT) material decomposition and virtual non-contrast-enhanced DECT HU values assess muscle fat reliably. • Virtual non-contrast-enhanced dual-energy CT HU values allow to differentiate between high and low native skeletal muscle mean radiation attenuation in contrast-enhanced DECT scans. • Measuring muscle fat by dual-energy computed tomography is a new approach for the determination of muscle quality, an important parameter for the diagnostic confirmation of sarcopenia as a comorbidity associated with poor clinical outcome.
UR - https://doi.org/10.1007/s00330-021-07820-1
U2 - 10.1007/s00330-021-07820-1
DO - 10.1007/s00330-021-07820-1
M3 - SCORING: Journal article
C2 - 33770247
VL - 31
SP - 7529
EP - 7539
JO - EUR RADIOL
JF - EUR RADIOL
SN - 0938-7994
IS - 10
ER -