Improved free-breathing liver fat and iron quantification using a 2D chemical shift-encoded MRI with flip angle modulation and motion-corrected averaging.
Improved free-breathing liver fat and iron quantification using a 2D chemical shift-encoded MRI with flip angle modulation and motion-corrected averaging.
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DOI:
10.1007/s00330-022-08682-x
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发表时间:
2022-08
影响因子:
5.9
通讯作者:
中科院分区:
文献类型:
--
作者:
3D chemical shift-encoded (CSE)-MRI enables accurate and precise quantification of proton density fat-fraction (PDFF) and R2*, biomarkers of hepatic fat and iron deposition. Unfortunately, 3D CSE-MRI requires reliable breath-holding. Free-breathing 2D CSE-MRI with sequential radiofrequency excitation is a motion-robust alternative but suffers from low signal-to-noise-ratio (SNR). To overcome this limitation, this work explores the combination of flip angle modulated (FAM) 2D CSE imaging with a non-local means (NLM) motion-corrected averaging technique. In this prospective study, 35 healthy subjects (27 children/8 adults) were imaged on a 3T MRI-system. Multi-echo 3D CSE (“3D”) and 2D CSE FAM (“FAM”) images were acquired during breath-hold and free-breathing, respectively, to obtain PDFF and R2* maps of the liver. Multi-repetition FAM was postprocessed with direct averaging (DA)- and NLM-based averaging and compared to 3D CSE using Bland-Altmann and regression analysis. Image quality of PDFF and R2* maps were reviewed by two radiologists using a Likert-like scale (score 1-5, 5=best). Compared to 3D CSE, multi-repetition FAM-NLM showed excellent agreement (regression slope=1.0, R2=0.996) for PDFF and good agreement (regression slope 1.08-1.15, R2≥0.899) for R2*. Further, multi-repetition FAM-NLM PDFF and R2* maps had fewer artifacts (score 3.8 vs. 3.2, p<0.0001 for PDFF; score 3.2 vs. 2.6, p<0.001 for R2*) and better overall image quality (score 4.0 vs. 3.5, p<0.0001 for PDFF; score 3.4 vs. 2.7, p<0.0001 for R2*). Free-breathing FAM-NLM provides superior image quality of the liver compared to the conventional breath-hold 3D CSE-MRI, while minimizing bias for PDFF and R2* quantification.
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影响因子:
3.3
作者:
Doneva, Mariya;Boernert, Peter;Lustig, Michael
通讯作者:
Lustig, Michael
影响因子:
3.3
作者:
Luo H;Zhu A;Wiens CN;Starekova J;Shimakawa A;Reeder SB;Johnson KM;Hernando D
通讯作者:
Hernando D
DOI:
10.1002/hep.26455
发表时间:
2013-12
期刊:
Hepatology (Baltimore, Md.)
影响因子:
--
作者:
Noureddin M;Lam J;Peterson MR;Middleton M;Hamilton G;Le TA;Bettencourt R;Changchien C;Brenner DA;Sirlin C;Loomba R
通讯作者:
Loomba R
影响因子:
3.3
作者:
Moriguchi, H;Lewin, JS;Duerk, JL
通讯作者:
Duerk, JL
DOI:
10.1002/hep.29797
发表时间:
2018-08
期刊:
Hepatology (Baltimore, Md.)
影响因子:
--
作者:
Caussy C;Reeder SB;Sirlin CB;Loomba R
通讯作者:
Loomba R