Yuxin Zhang1,2, Óscar Peña-Nogales2,3, James H Holmes2, Diego Hernando1,2. 1. Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin. 2. Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin. 3. Laboratorio de Procesado de Imagen, Universidad de Valladolid, Valladolid, Spain.
Abstract
PURPOSE: To develop motion-robust, blood-suppressed diffusion-weighted imaging (DWI) of the liver with optimized diffusion encoding waveforms and evaluate the accuracy and reproducibility of quantitative apparent diffusion coefficient (ADC) measurements. METHODS: A novel approach for the design of diffusion weighting waveforms, termed M1-optimized diffusion imaging (MODI), is proposed. MODI includes an echo time-optimized motion-robust diffusion weighting gradient waveform design, with a small nonzero first-moment motion sensitivity (M1) value to enable blood signal suppression. Experiments were performed in eight healthy volunteers and five patient volunteers. In each case, DW images and ADC maps were compared between acquisitions using standard monopolar waveforms, motion moment-nulled (M1-nulled and M1-M2-nulled) waveforms, and the proposed MODI approach. RESULTS: Healthy volunteer experiments using MODI showed no significant ADC bias in the left lobe relative to the right lobe (p < .05) demonstrating robustness to cardiac motion, and no significant ADC bias with respect to monopolar-based ADC measured in the right lobe (p < .05), demonstrating blood signal suppression. In contrast, monopolar-based ADC showed significant bias in the left lobe relative to the right lobe (p < .01) due to its sensitivity to motion, and both M1-nulled and M1-M2-nulled-based ADC showed significant bias (p < .01) due to the lack of blood suppression. Preliminary patient results also suggest MODI may enable improved visualization and quantitative assessment of lesions throughout the entire liver. CONCLUSIONS: This novel method for diffusion gradient waveform design enables DWI of the liver with high robustness to motion and suppression of blood signals, overcoming the limitations of conventional monopolar waveforms and moment-nulled waveforms, respectively.
PURPOSE: To develop motion-robust, blood-suppressed diffusion-weighted imaging (DWI) of the liver with optimized diffusion encoding waveforms and evaluate the accuracy and reproducibility of quantitative apparent diffusion coefficient (ADC) measurements. METHODS: A novel approach for the design of diffusion weighting waveforms, termed M1-optimized diffusion imaging (MODI), is proposed. MODI includes an echo time-optimized motion-robust diffusion weighting gradient waveform design, with a small nonzero first-moment motion sensitivity (M1) value to enable blood signal suppression. Experiments were performed in eight healthy volunteers and five patient volunteers. In each case, DW images and ADC maps were compared between acquisitions using standard monopolar waveforms, motion moment-nulled (M1-nulled and M1-M2-nulled) waveforms, and the proposed MODI approach. RESULTS: Healthy volunteer experiments using MODI showed no significant ADC bias in the left lobe relative to the right lobe (p < .05) demonstrating robustness to cardiac motion, and no significant ADC bias with respect to monopolar-based ADC measured in the right lobe (p < .05), demonstrating blood signal suppression. In contrast, monopolar-based ADC showed significant bias in the left lobe relative to the right lobe (p < .01) due to its sensitivity to motion, and both M1-nulled and M1-M2-nulled-based ADC showed significant bias (p < .01) due to the lack of blood suppression. Preliminary patient results also suggest MODI may enable improved visualization and quantitative assessment of lesions throughout the entire liver. CONCLUSIONS: This novel method for diffusion gradient waveform design enables DWI of the liver with high robustness to motion and suppression of blood signals, overcoming the limitations of conventional monopolar waveforms and moment-nulled waveforms, respectively.
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