Accelerated MR cell size imaging through parallel acquisition technique (PAT) and simultaneous multi-slice (SMS) with local principal component analysis (LPCA) enhancement.

Microstructural parameters are essential in tumor research, aiding in the understanding tumor pathogenesis, grading, and therapeutic efficacy. The imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) model is the most widely used MR cell size imaging technique, demonstrating success in measuring microstructural parameters of solid tumors in vivo. However, its clinical application is limited by the longer scan times required for both pulsed gradient spin-echo (PGSE) and multiple oscillating gradient spin-echo (OGSE) acquisitions across a range of b-values, which can be burdensome for patients and disrupt clinical workflows. In this work, we propose and evaluate an accelerating method that integrates parallel acquisition technique (PAT) and simultaneous multi-slice (SMS) with local principal component analysis (LPCA) denoising to reduce scan times while maintaining image quality in MR cell size imaging. PGSE and OGSE (25 Hz, 50 Hz) images were acquired using P2S2 (PAT2-SMS2), P2S3 (PAT2-SMS3), and P3S3 (PAT3-SMS3) configurations, incorporating LPCA denoising, and compared to standard P2 (PAT2-SMS1) in healthy volunteers and brain tumor patients at 3 T. Additionally, clinical feasibility was further assessed through qualitative and quantitative evaluations. Qualitative assessment, conducted by two radiologists using a 5-point Likert scale, and quantitative analysis, including noise estimation, apparent diffusion coefficient (ADC) calculation, and estimation of microstructural parameters-cell diameter (Dmean), intracellular volume fraction (Vin), and extracellular diffusivity (Dex), were performed. Overall, the integration of PAT and SMS techniques reduces acquisition time by approximately 60 % compared to standard P2 acceleration, while maintaining comparable image quality and structural fidelity with LPCA denoising.