Improved quantitative myocardial T2 mapping : impact of the fitting model
Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the vox...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Akçakaya, Mehmet [verfasserIn] Weingärtner, Sebastian - 1991- [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
7 August 2014 |
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| Schlagwörter: |
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| Anmerkung: |
Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt |
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| Umfang: |
13 |
| Übergeordnetes Werk: |
Enthalten in: Magnetic resonance in medicine - New York, NY [u.a.] : Wiley-Liss, 1984, 74(2015), 1, Seite 93-105 |
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| Übergeordnetes Werk: |
volume:74 ; year:2015 ; number:1 ; pages:93-105 ; extent:13 |
| Links: |
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| DOI / URN: |
10.1002/mrm.25377 |
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| Katalog-ID: |
1567326552 |
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| 245 | 1 | 0 | |a Improved quantitative myocardial T2 mapping |b impact of the fitting model |c Mehmet Akçakaya, Tamer A. Basha, Sebastian Weingärtner, Sébastien Roujol, Sophie Berg, and Reza Nezafat |
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| 520 | |a Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. | ||
| 534 | |c 2014 | ||
| 650 | 4 | |a myocardial inflammation | |
| 650 | 4 | |a myocardial T2 mapping | |
| 650 | 4 | |a quantitative myocardial tissue characterization | |
| 650 | 4 | |a three-parameter fit | |
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10.1002/mrm.25377 doi (DE-627)1567326552 (DE-576)497326558 (DE-599)BSZ497326558 (OCoLC)1340986040 DE-627 ger DE-627 rda eng Akçakaya, Mehmet verfasserin (DE-588)1145077587 (DE-627)1005318689 (DE-576)495625507 aut Improved quantitative myocardial T2 mapping impact of the fitting model Mehmet Akçakaya, Tamer A. Basha, Sebastian Weingärtner, Sébastien Roujol, Sophie Berg, and Reza Nezafat 7 August 2014 13 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. 2014 myocardial inflammation myocardial T2 mapping quantitative myocardial tissue characterization three-parameter fit Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 74(2015), 1, Seite 93-105 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:74 year:2015 number:1 pages:93-105 extent:13 http://dx.doi.org/10.1002/mrm.25377 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25377/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 1 93-105 13 2013 01 DE-16-250 2993102907 00 --%%-- --%%-- --%%-- --%%-- l01 18-01-18 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_6 2013 01 DE-16-250 03 s s_13 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
| spelling |
10.1002/mrm.25377 doi (DE-627)1567326552 (DE-576)497326558 (DE-599)BSZ497326558 (OCoLC)1340986040 DE-627 ger DE-627 rda eng Akçakaya, Mehmet verfasserin (DE-588)1145077587 (DE-627)1005318689 (DE-576)495625507 aut Improved quantitative myocardial T2 mapping impact of the fitting model Mehmet Akçakaya, Tamer A. Basha, Sebastian Weingärtner, Sébastien Roujol, Sophie Berg, and Reza Nezafat 7 August 2014 13 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. 2014 myocardial inflammation myocardial T2 mapping quantitative myocardial tissue characterization three-parameter fit Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 74(2015), 1, Seite 93-105 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:74 year:2015 number:1 pages:93-105 extent:13 http://dx.doi.org/10.1002/mrm.25377 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25377/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 1 93-105 13 2013 01 DE-16-250 2993102907 00 --%%-- --%%-- --%%-- --%%-- l01 18-01-18 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_6 2013 01 DE-16-250 03 s s_13 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
| allfields_unstemmed |
10.1002/mrm.25377 doi (DE-627)1567326552 (DE-576)497326558 (DE-599)BSZ497326558 (OCoLC)1340986040 DE-627 ger DE-627 rda eng Akçakaya, Mehmet verfasserin (DE-588)1145077587 (DE-627)1005318689 (DE-576)495625507 aut Improved quantitative myocardial T2 mapping impact of the fitting model Mehmet Akçakaya, Tamer A. Basha, Sebastian Weingärtner, Sébastien Roujol, Sophie Berg, and Reza Nezafat 7 August 2014 13 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. 2014 myocardial inflammation myocardial T2 mapping quantitative myocardial tissue characterization three-parameter fit Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 74(2015), 1, Seite 93-105 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:74 year:2015 number:1 pages:93-105 extent:13 http://dx.doi.org/10.1002/mrm.25377 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25377/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 1 93-105 13 2013 01 DE-16-250 2993102907 00 --%%-- --%%-- --%%-- --%%-- l01 18-01-18 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_6 2013 01 DE-16-250 03 s s_13 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
| allfieldsGer |
10.1002/mrm.25377 doi (DE-627)1567326552 (DE-576)497326558 (DE-599)BSZ497326558 (OCoLC)1340986040 DE-627 ger DE-627 rda eng Akçakaya, Mehmet verfasserin (DE-588)1145077587 (DE-627)1005318689 (DE-576)495625507 aut Improved quantitative myocardial T2 mapping impact of the fitting model Mehmet Akçakaya, Tamer A. Basha, Sebastian Weingärtner, Sébastien Roujol, Sophie Berg, and Reza Nezafat 7 August 2014 13 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. 2014 myocardial inflammation myocardial T2 mapping quantitative myocardial tissue characterization three-parameter fit Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 74(2015), 1, Seite 93-105 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:74 year:2015 number:1 pages:93-105 extent:13 http://dx.doi.org/10.1002/mrm.25377 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25377/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 1 93-105 13 2013 01 DE-16-250 2993102907 00 --%%-- --%%-- --%%-- --%%-- l01 18-01-18 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_6 2013 01 DE-16-250 03 s s_13 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
| allfieldsSound |
10.1002/mrm.25377 doi (DE-627)1567326552 (DE-576)497326558 (DE-599)BSZ497326558 (OCoLC)1340986040 DE-627 ger DE-627 rda eng Akçakaya, Mehmet verfasserin (DE-588)1145077587 (DE-627)1005318689 (DE-576)495625507 aut Improved quantitative myocardial T2 mapping impact of the fitting model Mehmet Akçakaya, Tamer A. Basha, Sebastian Weingärtner, Sébastien Roujol, Sophie Berg, and Reza Nezafat 7 August 2014 13 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. 2014 myocardial inflammation myocardial T2 mapping quantitative myocardial tissue characterization three-parameter fit Weingärtner, Sebastian 1991- verfasserin (DE-588)1051891507 (DE-627)786975199 (DE-576)407522883 aut Enthalten in Magnetic resonance in medicine New York, NY [u.a.] : Wiley-Liss, 1984 74(2015), 1, Seite 93-105 Online-Ressource (DE-627)303257040 (DE-600)1493786-4 (DE-576)096290455 1522-2594 nnns volume:74 year:2015 number:1 pages:93-105 extent:13 http://dx.doi.org/10.1002/mrm.25377 Verlag Resolving-System Volltext http://onlinelibrary.wiley.com.ezproxy.medma.uni-heidelberg.de/doi/10.1002/mrm.25377/abstract Verlag Volltext GBV_USEFLAG_U GBV_ILN_2013 ISIL_DE-16-250 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 1 93-105 13 2013 01 DE-16-250 2993102907 00 --%%-- --%%-- --%%-- --%%-- l01 18-01-18 2013 01 DE-16-250 00 s hd2015 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_6 2013 01 DE-16-250 03 s s_13 2013 01 DE-16-250 04 p (DE-627)1477523898 Weingärtner, Sebastian 2013 01 DE-16-250 04 k (DE-627)1430735864 Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_3 |
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English |
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Enthalten in Magnetic resonance in medicine 74(2015), 1, Seite 93-105 volume:74 year:2015 number:1 pages:93-105 extent:13 |
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Enthalten in Magnetic resonance in medicine 74(2015), 1, Seite 93-105 volume:74 year:2015 number:1 pages:93-105 extent:13 |
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Article |
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2013:0 |
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findex.gbv.de |
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2013@01 |
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myocardial inflammation myocardial T2 mapping quantitative myocardial tissue characterization three-parameter fit |
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2013:hd2015 DE-16-250:hd2015 2013:wissenschaftlicher Artikel (Zeitschrift) DE-16-250:wissenschaftlicher Artikel (Zeitschrift) 2013:per_6 DE-16-250:per_6 2013:s_13 DE-16-250:s_13 2013:Weingärtner, Sebastian DE-16-250:Weingärtner, Sebastian 2013:Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) DE-16-250:Lehrstuhl für Computerunterstützte Klinische Medizin (CKM) 2013:Verfasser DE-16-250:Verfasser 2013:pos_3 DE-16-250:pos_3 |
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Magnetic resonance in medicine |
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Akçakaya, Mehmet @@aut@@ Weingärtner, Sebastian @@aut@@ |
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2015-01-01T00:00:00Z |
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303257040 |
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1567326552 |
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englisch |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">1567326552</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230426064453.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180118r20152014xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/mrm.25377</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)1567326552</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-576)497326558</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BSZ497326558</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1340986040</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Akçakaya, Mehmet</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1145077587</subfield><subfield code="0">(DE-627)1005318689</subfield><subfield code="0">(DE-576)495625507</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Improved quantitative myocardial T2 mapping</subfield><subfield code="b">impact of the fitting model</subfield><subfield code="c">Mehmet Akçakaya, Tamer A. Basha, Sebastian Weingärtner, Sébastien Roujol, Sophie Berg, and Reza Nezafat</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">7 August 2014</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">13</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Gesehen am 18.01.2018</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Im Titel ist „2“ tiefgestellt</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times.</subfield></datafield><datafield tag="534" ind1=" " ind2=" "><subfield code="c">2014</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">myocardial inflammation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">myocardial T2 mapping</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">quantitative myocardial tissue characterization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">three-parameter fit</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Weingärtner, Sebastian</subfield><subfield code="d">1991-</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1051891507</subfield><subfield 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Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt |
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Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt |
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Purpose: To develop an improved T2 prepared (T2prep) balanced steady-state free-precession (bSSFP) sequence and signal relaxation curve fitting method for myocardial T2 mapping. Methods: Myocardial T2 mapping is commonly performed by acquisition of multiple T2prep bSSFP images and estimating the voxel-wise T2 values using a two-parameter fit for relaxation. However, a two-parameter fit model does not take into account the effect of imaging pulses in a bSSFP sequence or other imperfections in T2prep RF pulses, which may decrease the robustness of T2 mapping. Therefore, we propose a novel T2 mapping sequence that incorporates an additional image acquired with saturation preparation, simulating a very long T2prep echo time. This enables the robust estimation of T2 maps using a 3-parameter fit model, which captures the effect of imaging pulses and other imperfections. Phantom imaging is performed to compare the T2 maps generated using the proposed 3-parameter model with the conventional two-parameter model, as well as a spin echo reference. In vivo imaging is performed on eight healthy subjects to compare the different fitting models. Results: Phantom and in vivo data show that the T2 values generated by the proposed 3-parameter model fitting do not change with different choices of the T2prep echo times, and are not statistically different than the reference values for the phantom (P = 0.10 with three T2prep echoes). The two-parameter model exhibits dependence on the choice of T2prep echo times and are significantly different than the reference values (P = 0.01 with three T2prep echoes). Conclusion: The proposed imaging sequence in combination with a three-parameter model allows accurate measurement of myocardial T2 values, which is independent of number and duration of T2prep echo times. Gesehen am 18.01.2018 Im Titel ist „2“ tiefgestellt |
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