Yanjun Chen1,2, Liang Li2,3, Nicole Le2,4, Eric Y Chang2,4, Wenhua Huang5, Ya-Jun Ma2. 1. Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China. 2. Department of Radiology, University of California, San Diego, California, USA. 3. Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China. 4. Research Service, Veterans Affairs San Diego Healthcare System, San Diego, California, USA. 5. Guangdong Provincial Key Laboratory of Medical Biomechanics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China.
Abstract
PURPOSE: To investigate the effect of fat saturation (FatSat) on quantitative UTE imaging of variable knee tissues on a 3T scanner. METHODS: Three quantitative UTE imaging techniques, including the UTE multi-echo sequence for T 2 ∗ measurement, the adiabatic T1ρ prepared UTE sequence for T1ρ measurement, and the magnetization transfer (MT)-prepared UTE sequence for MT ratio (MTR) and macromolecular proton fraction (MMF) measurements were used in this study. Twelve samples of cartilage and twelve samples of meniscus, as well as six whole knee cadaveric specimens, were imaged with the three above-mentioned UTE sequences with and without FatSat. The difference, correlation, and agreement between the UTE measurements with and without FatSat were calculated to investigate the effects of FatSat on quantification. RESULTS: Fat was well-suppressed using all three UTE sequences when FatSat was deployed. For the small sample study, the quantification difference ratio (QDR) values of all the measured biomarkers ranged from 0.7% to 12.6%, whereas for the whole knee joint specimen study, the QDR values ranged from 0.2% to 12.0%. Except for T1ρ in muscle and MMF in meniscus (p > 0.05), most of the measurements showed statistical differences for T1ρ , MTR, and MMF (p < 0.05) between FatSat and non-FatSat scans. Most of the measurements for T 2 ∗ showed no significant differences (p > 0.05). Strong correlations were found for all the biomarkers between measurements with and without FatSat. CONCLUSION: The UTE biomarkers showed good correlation and agreement with some slight differences between the scans with and without FatSat.
PURPOSE: To investigate the effect of fat saturation (FatSat) on quantitative UTE imaging of variable knee tissues on a 3T scanner. METHODS: Three quantitative UTE imaging techniques, including the UTE multi-echo sequence for T 2 ∗ measurement, the adiabatic T1ρ prepared UTE sequence for T1ρ measurement, and the magnetization transfer (MT)-prepared UTE sequence for MT ratio (MTR) and macromolecular proton fraction (MMF) measurements were used in this study. Twelve samples of cartilage and twelve samples of meniscus, as well as six whole knee cadaveric specimens, were imaged with the three above-mentioned UTE sequences with and without FatSat. The difference, correlation, and agreement between the UTE measurements with and without FatSat were calculated to investigate the effects of FatSat on quantification. RESULTS: Fat was well-suppressed using all three UTE sequences when FatSat was deployed. For the small sample study, the quantification difference ratio (QDR) values of all the measured biomarkers ranged from 0.7% to 12.6%, whereas for the whole knee joint specimen study, the QDR values ranged from 0.2% to 12.0%. Except for T1ρ in muscle and MMF in meniscus (p > 0.05), most of the measurements showed statistical differences for T1ρ , MTR, and MMF (p < 0.05) between FatSat and non-FatSat scans. Most of the measurements for T 2 ∗ showed no significant differences (p > 0.05). Strong correlations were found for all the biomarkers between measurements with and without FatSat. CONCLUSION: The UTE biomarkers showed good correlation and agreement with some slight differences between the scans with and without FatSat.
Authors: Ya-Jun Ma; Xing Lu; Michael Carl; Yanchun Zhu; Nikolaus M Szeverenyi; Graeme M Bydder; Eric Y Chang; Jiang Du Journal: Magn Reson Med Date: 2018-01-03 Impact factor: 4.668
Authors: Mohamed Jarraya; Frank W Roemer; Martin Englund; Michel D Crema; Heather I Gale; Daichi Hayashi; Jeffrey N Katz; Ali Guermazi Journal: Semin Arthritis Rheum Date: 2016-11-24 Impact factor: 5.532
Authors: Ya-Jun Ma; Wei Zhao; Lidi Wan; Tan Guo; Adam Searleman; Hyungseok Jang; Eric Y Chang; Jiang Du Journal: Magn Reson Med Date: 2018-11-16 Impact factor: 4.668
Authors: Amir Masoud Afsahi; Sam Sedaghat; Dina Moazamian; Ghazaleh Afsahi; Jiyo S Athertya; Hyungseok Jang; Ya-Jun Ma Journal: Front Endocrinol (Lausanne) Date: 2022-05-26 Impact factor: 6.055