Stelter, J.* ; Weiss, K.* ; Steinhelfer, L.* ; Spieker, V. ; Huaroc Moquillaza, E.* ; Zhang, W.* ; Makowski, M.R.* ; Schnabel, J.A. ; Kainz, B.* ; Braren, R.F.* ; Karampinos, D.C.*
     
 
    
        
Simultaneous whole-liver water T1 and T2 mapping withisotropic resolution during free-breathing.
    
    
        
    
    
        
        NMR Biomed., DOI: 10.1002/nbm.5216:e5216 (2024)
    
    
    
		
		
			
				PURPOSE: To develop and validate a data acquisition scheme combined with a motion-resolved reconstruction and dictionary-matching-based parameter estimation to enable free-breathing isotropic resolution self-navigated whole-liver simultaneous water-specific   T 1  $$ {\mathrm{T}}_1 $$  (   wT 1  $$ {\mathrm{wT}}_1 $$  ) and   T 2  $$ {\mathrm{T}}_2 $$  (   wT 2  $$ {\mathrm{wT}}_2 $$  ) mapping for the characterization of diffuse and oncological liver diseases. METHODS: The proposed data acquisition consists of a magnetization preparation pulse and a two-echo gradient echo readout with a radial stack-of-stars trajectory, repeated with different preparations to achieve different   T 1  $$ {\mathrm{T}}_1 $$  and   T 2  $$ {\mathrm{T}}_2 $$  contrasts in a fixed acquisition time of 6 min. Regularized reconstruction was performed using self-navigation to account for motion during the free-breathing acquisition, followed by water-fat separation. Bloch simulations of the sequence were applied to optimize the sequence timing for    B 1   $$ {B}_1 $$  insensitivity at 3 T, to correct for relaxation-induced blurring, and to map   T 1  $$ {\mathrm{T}}_1 $$  and   T 2  $$ {\mathrm{T}}_2 $$  using a dictionary. The proposed method was validated on a water-fat phantom with varying relaxation properties and in 10 volunteers against imaging and spectroscopy reference values. The performance and robustness of the proposed method were evaluated in five patients with abdominal pathologies. RESULTS: Simulations demonstrate good    B 1   $$ {B}_1 $$  insensitivity of the proposed method in measuring   T 1  $$ {\mathrm{T}}_1 $$  and   T 2  $$ {\mathrm{T}}_2 $$  values. The proposed method produces co-registered   wT 1  $$ {\mathrm{wT}}_1 $$  and   wT 2  $$ {\mathrm{wT}}_2 $$  maps with a good agreement with reference methods (phantom:   wT 1 = 1 . 02  wT 1,ref - 8 . 93  ms , R 2 = 0 . 991 $$ {\mathrm{wT}}_1=1.02\kern0.1em {\mathrm{wT}}_{1,\mathrm{ref}}-8.93\kern0.1em \mathrm{ms},{R}^2=0.991 $$  ;   wT 2 = 1 . 03  wT 2,ref + 0 . 73  ms , R 2 = 0 . 995 $$ {\mathrm{wT}}_2=1.03\kern0.1em {\mathrm{wT}}_{2,\mathrm{ref}}+0.73\kern0.1em \mathrm{ms},{R}^2=0.995 $$  ). The proposed   wT 1  $$ {\mathrm{wT}}_1 $$  and   wT 2  $$ {\mathrm{wT}}_2 $$  mapping exhibits good repeatability and can be robustly performed in patients with pathologies. CONCLUSIONS: The proposed method allows whole-liver   wT 1  $$ {\mathrm{wT}}_1 $$  and   wT 2  $$ {\mathrm{wT}}_2 $$  quantification with high accuracy at isotropic resolution in a fixed acquisition time during free-breathing.
			
			
				
			
		 
		
			
				
					
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
    
        Typ der Hochschulschrift
        
    
 
    
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        Schlagwörter
        Bir‐4 Preparation ; Dictionary Matching ; Radial Stack‐of‐stars ; Relaxometry ; Water–fat Separation; Multiparametric Magnetic-resonance; Inversion-recovery Molli; T2 Relaxation-times; Adipose-tissue; Gradient-echo; Fat; Mri; Disease; Quantification; Fibrosis
    
 
    
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        Sprache
        englisch
    
 
    
        Veröffentlichungsjahr
        2024
    
 
    
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        0
    
 
    
        HGF-Berichtsjahr
        2024
    
 
    
    
        ISSN (print) / ISBN
        0952-3480
    
 
    
        e-ISSN
        1099-1492
    
 
    
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	    Band: ,  
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	    Seiten: ,  
	    Artikelnummer: e5216 
	    Supplement: ,  
	
    
 
  
        
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            Verlag
            Wiley
        
 
        
            Verlagsort
            111 River St, Hoboken 07030-5774, Nj Usa
        
 
	
        
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        Begutachtungsstatus
        Peer reviewed
    
 
    
        Institut(e)
        Institute for Machine Learning in Biomed Imaging (IML)
    
 
    
        POF Topic(s)
        30205 - Bioengineering and Digital Health
    
 
    
        Forschungsfeld(er)
        Enabling and Novel Technologies
    
 
    
        PSP-Element(e)
        G-507100-001
    
 
    
        Förderungen
        TUM International Graduate School of Science and Engineering
Philips Healthcare
    
 
    
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        Erfassungsdatum
        2024-09-27