BACKGROUND: relaxation times by minimizing echo time. Dead-time gaps and flexible temporal sampling remain challenges for dynamic applications such as functional MRI (fMRI). PURPOSE: To propose and evaluate ZTE-STAR, a dynamic ZTE framework combining paired-spoke spiral phyllotaxis sampling, algebraic dead-time infilling, and temporal total variation (TTV) reconstruction. STUDY TYPE: Prospective. SUBJECTS/PHANTOM: A numerical phantom and eight C57BL/6J mice (one for image quality assessment; seven for resting-state fMRI). FIELDSTRENGTH/SEQUENCE: 9.4 T; ZTE with a modified Spiral Phyllotaxis Golden Angle trajectory. ASSESSMENT: Reconstruction quality was assessed using peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), and temporal response using the 90%-10% fall time. In vivo assessment included temporal signal-to-noise ratio (tSNR), rigid-body motion, and exploratory group independent component analysis (ICA). STATISTICAL TEST: Descriptive statistics were used for PSNR, SSIM, motion, and tSNR. ICA was exploratory, with no inferential statistical testing. RESULTS: In trajectory-reconstruction ablation at comparable spoke counts, paired spiral phyllotaxis with TTV yielded PSNR 32.12 dB versus 29.75 dB for conventional radial sampling with TTV. ZTE-STAR at 864 spokes yielded PSNR 30.90 dB, SSIM 0.903, and 90%-10% fall time 1.8-2.1 s; at 2880 versus 2948 spokes, fall times were 5.0-5.2 versus 4.9 s. With realistic measurement noise, ZTE-STAR at 864 spokes yielded PSNR 30.12 ± 0.01 dB and SSIM 0.838 ± 0.001 versus 24.79 ± 0.01 dB and 0.604 ± 0.001 for conventional radial sampling at 2948 spokes. Whole-brain tSNR ranged from 26.6 to 30.1. Resting-state ICA yielded an exploratory default mode network-like component. DATA CONCLUSION: ZTE-STAR enabled shorter retrospective bins while maintaining reconstruction quality at lower spoke counts and supported exploratory resting-state ZTE-fMRI in mice. TECHNICAL EFFICACY: Stage 1. EVIDENCE LEVEL: 4.
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