MRI provides essential insights into tissue microstructure, and high angular resolution diffusion imaging (HARDI) enables detailed assessment of complex white matter architecture through fiber orientation distribution (FOD) analysis. However, HARDI requires high b-values and multiple diffusion directions, leading to reduced signal-to-noise ratio (SNR) and long scan times. Conventional zero-fill interpolation processing (ZIP) is widely used for super-resolution but is limited by edge blurring and artifacts. This study evaluated an AI-based reconstruction method, Precise IQ Engine (PIQE). Specifically, low-resolution diffusion data were reconstructed to standard resolution and compared with standard-resolution acquisitions. Ten healthy volunteers underwent HARDI at 3T, and FOD were estimated using constrained spherical deconvolution. Quantitative comparisons with reference data demonstrated that PIQE exhibited higher distributional similarity (lower Jensen–Shannon divergence) and directional agreement (higher angular correlation coefficient) compared with ZIP+Advanced Intelligent Clear-IQ Engine (AiCE), with statistically significant similarity observed. These findings indicate potential usefulness in advanced diffusion MRI applications.
Akihiro Kasahara, Yuichi Suzuki, Kazuki Endo et al.· Radiological Physics and Tec...· 0 citations
PURPOSE
To evaluate the clinical feasibility and quantitative performance of adaptive complex signal average (ACSA) diffusion-weighted imaging (DWI) in abdominal MRI and to compare ACSA DWI with conventional non-ACSA DWI in terms of signal intensity (SI), SNR, apparent diffusion coefficient (ADC), signal intensity difference ratio (SIDR), and lesion contrast across different numbers of excitations (NEX).
METHODS
This retrospective study included 82 patients who underwent free-breathing abdominal DWI on a 3T system between January and July 2025. ACSA DWI was reconstructed from the same raw data as non-ACSA DWI using a combination of adaptive averaging and complex-domain averaging. ROIs were placed in the liver, pancreas, left adrenal gland, and spinal muscles to measure SI, SNR, and ADC. SIDR and inter-lobar right-left (R-L) ratio in SI and ADC were calculated at NEX 2, 3, and 4. For 37 patients with non-cystic hepatic nodules, lesion SI, ADC, contrast ratio, and contrast-to-noise ratio (CNR) were assessed.
RESULTS
ACSA DWI significantly increased SI and SNR in motion-prone organs, including the lateral hepatic segment, pancreas, and left adrenal gland, at all NEX levels (P < 0.05). ADC values in abdominal parenchymal organs and hepatic nodules were lower with ACSA DWI, reflecting the noise-floor suppression and adaptive average effects. R-L SI and ADC ratios were significantly different and were closer to 1 in ACSA DWI, indicating improved hepatic signal homogeneity. Lesion SI, contrast ratio, and CNR were significantly higher with ACSA DWI, enhancing nodule conspicuity.
CONCLUSION
ACSA DWI improves signal uniformity, SNR, and lesion contrast while maintaining reasonable ADC quantification. Without prolonging scan time or modifying acquisition parameters, ACSA provides a robust, clinically feasible post-processing technique for enhancing both image quality and quantitative reliability in abdominal DWI.
Miwa Matsukuma, M. Tanabe, M. Higashi et al.· Magnetic Resonance in Medica...· 0 citations
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