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Accelerated Diffusion-Weighted Imaging via Diffusion Gradient Alternation in Radial k-Space Sampling

Authors :

Fateme Hoseini Rashkani¹ Abbas Nasiraei Moghaddam²

1- دانشگاه صنعتی امیرکبیر(پلی تکنیک) 2- دانشگاه صنعتی امیرکبیر(پلی تکنیک)

Keywords :

Stroke diagnosis،Signal-to-noise ratio (SNR) enhancement،Apparent diffusion coefficient (ADC)،Non-uniform FFT (NUFFT) reconstruction،Portable MRI،Ultra-low-field MRI

Abstract :

Diffusion-weighted imaging (DWI) is essential for stroke diagnosis but remains limited by long acquisition times, particularly in portable and ultra-low-field MRI systems where reduced signal-to-noise ratio (SNR) exacerbates this challenge. Conventional DWI requires at least four full k-space acquisitions, restricting its practicality in time-critical or resource-limited settings. We propose a two-acquisition DWI framework that employs radial k-space sampling with alternating diffusion gradient directions, requiring only one non-diffusion-weighted (S₀) and one diffusion-weighted acquisition. Simulations were performed using a realistic brain phantom in MRiLab with a customized diffusion modeling pipeline and non-uniform FFT reconstruction. Results show a two-fold reduction in acquisition time while maintaining strong agreement with conventional DWI, with relative root-mean-square errors of 3.9–4.2%. Stroke-relevant tissue boundaries remained clearly visible, and error maps confirmed minimal structural distortion. Unlike cartesian undersampling, radial sampling eliminates fold-over aliasing artifacts, further supporting robust image quality. This acquisition-level acceleration is independent and can be combined with parallel imaging or compressed sensing to achieve additional gains. The method offers a practical solution for low-field and portable MRI, enabling faster and more reliable diffusion imaging in urgent clinical scenarios such as point-of-care stroke diagnosis.