Kévin Moulin1, Eric Aliotta1,2, Daniel B Ennis1,2,3. 1. Department of Radiological Sciences, University of California, Los Angeles, California. 2. Biomedical Physics Interdepartmental Program, University of California, Los Angeles, California. 3. Department of Bioengineering, University of California, Los Angeles, California.
Abstract
PURPOSE: To study the impact of variable flow-encoding strength on intravoxel incoherent motion (IVIM) liver imaging of diffusion and perfusion. THEORY: Signal attenuation in DWI arises from (1) intravoxel microvascular blood flow, which depends on the flow-encoding strength α (first gradient moment) of the diffusion-encoding waveform, and (2) intravoxel spin diffusion, which depends on the b-value of the diffusion-encoding gradient waveforms α and b-value. Both are linked to the diffusion-encoding gradient waveform and conventionally are not independently controlled. METHODS: In this work a convex optimization framework was used to generate gradient waveforms with independent α and b-value. Thirty-six unique α and b-value sample points from 5 different gradient waveforms were used to reconstruct perfusion fraction (f), coefficient of diffusion (D), and blood velocity standard deviation (Vb ) maps using a recently proposed IVIM model. Faster acquisition strategies were evaluated with 1000 random subsampling strategies of 16, 8, and 4 α and b-value. Among the subsampled reconstructions, the sampling schemes that minimized the difference with the fully sampled reconstruction were reported. RESULTS: Healthy volunteers (N = 9) were imaged on a 3T scanner. Liver perfusion and diffusion estimates using the fully sampled IVIM method were f = 0.19 ± 0.06, D = 1.15 ± 0.15 × 10-3 mm2 /s, and Vb = 5.22 ± 3.86 mm/s. No statistical differences were found between the fully sampled and 2-times undersampled reconstruction (f = 0.2 ± 0.07, D = 1.19 ± 0.15 × 10-3 mm2 /s, Vb = 5.79 ± 3.43 mm/s); 4-times undersampled (f = 0.2 ± 0.06, D = 1.15 ± 0.17 × 10-3 mm2 /s, Vb = 4.66 ± 3.61 mm/s), or 8-times undersampled ( f = 0.2 ± 0.06, D = 1.23 ± 0.22 × 10-3 mm2 /s, Vb = 4.99 ± 3.82 mm/s) approaches. CONCLUSION: We demonstrate the IVIM signal's dependence on the b-value, the diffusion-encoding time and the flow-encoding strength and observe in vivo the ballistic regime signature of microperfusion in the liver. This work also demonstrates that using an IVIM model and sampling scheme matched to the ballistic regime, pixel-wise IVIM parameter maps are possible when sampling as few as 4 IVIM signals.
PURPOSE: To study the impact of variable flow-encoding strength on intravoxel incoherent motion (IVIM) liver imaging of diffusion and perfusion. THEORY: Signal attenuation in DWI arises from (1) intravoxel microvascular blood flow, which depends on the flow-encoding strength α (first gradient moment) of the diffusion-encoding waveform, and (2) intravoxel spin diffusion, which depends on the b-value of the diffusion-encoding gradient waveforms α and b-value. Both are linked to the diffusion-encoding gradient waveform and conventionally are not independently controlled. METHODS: In this work a convex optimization framework was used to generate gradient waveforms with independent α and b-value. Thirty-six unique α and b-value sample points from 5 different gradient waveforms were used to reconstruct perfusion fraction (f), coefficient of diffusion (D), and blood velocity standard deviation (Vb ) maps using a recently proposed IVIM model. Faster acquisition strategies were evaluated with 1000 random subsampling strategies of 16, 8, and 4 α and b-value. Among the subsampled reconstructions, the sampling schemes that minimized the difference with the fully sampled reconstruction were reported. RESULTS: Healthy volunteers (N = 9) were imaged on a 3T scanner. Liver perfusion and diffusion estimates using the fully sampled IVIM method were f = 0.19 ± 0.06, D = 1.15 ± 0.15 × 10-3 mm2 /s, and Vb = 5.22 ± 3.86 mm/s. No statistical differences were found between the fully sampled and 2-times undersampled reconstruction (f = 0.2 ± 0.07, D = 1.19 ± 0.15 × 10-3 mm2 /s, Vb = 5.79 ± 3.43 mm/s); 4-times undersampled (f = 0.2 ± 0.06, D = 1.15 ± 0.17 × 10-3 mm2 /s, Vb = 4.66 ± 3.61 mm/s), or 8-times undersampled ( f = 0.2 ± 0.06, D = 1.23 ± 0.22 × 10-3 mm2 /s, Vb = 4.99 ± 3.82 mm/s) approaches. CONCLUSION: We demonstrate the IVIM signal's dependence on the b-value, the diffusion-encoding time and the flow-encoding strength and observe in vivo the ballistic regime signature of microperfusion in the liver. This work also demonstrates that using an IVIM model and sampling scheme matched to the ballistic regime, pixel-wise IVIM parameter maps are possible when sampling as few as 4 IVIM signals.
Authors: Frederik B Laun; Tobit Führes; Hannes Seuss; Astrid Müller; Sebastian Bickelhaupt; Alto Stemmer; Thomas Benkert; Michael Uder; Marc Saake Journal: PLoS One Date: 2022-05-26 Impact factor: 3.752