Skip to content

Evaluating boost diffusion sampling for improved abdominal imaging using prototype slice-specific shimming method.

Sep 2026 · MAGMA · 0 citations · 36 references
Medicine

TL;DR

Boost iShim-DWI improves liver DWI image quality while preserving ADC comparability and may enhance differentiation of benign and malignant focal liver lesions.

View source

Similar papers

Review Open access Sep 2026

Zoom-DWI versus general-DWI in gastric cancer: a comparative evaluation of image quality, apparent diffusion coefficient, and entropy

Zoom-DWI may serve only as a complementary sequence—not a replacement—for gastric cancer MRI and is unsuitable for quantitative assessments that rely on established diagnostic ADC thresholds, demonstrating that the two DWI sequences cannot share unified quantitative diagnostic cutoffs.

Huan Xie, Han-Wei Wang, Zhi-Le Cao et al. · 0 citations
Sep 2026

Diagnostic value of diffusion-weighted imaging combined with DCE-MRI time-signal intensity curve for differentiating benign from malignant BI-RADS 4 breast lesions.

Both DWI parameters (especially ADC and D and TIC type) and TIC type help differentiate benign from malignant BI-RADS 4 lesions and the ADC combined with TIC model offers better diagnostic accuracy and is practical for clinical use.

Chao Huang, Zhi-Feng Wang, Wen-Ting Zhang et al. · 0 citations
Aug 2026

Single-shot T2-Weighted Turbo Spin-echo Imaging of the Liver Improves Lesion Characterization Compared with Free-breathing Acquisition.

SS-TSE, independent of DLR, improved T2-weighted ancillary feature assessment and LI-RADS categorization of HCC over FB-TSE via a 91.8% reduction in acquisition time; DLR did not alter these outcomes but improved image quality and lesion conspicuity.

Kumi Ozaki, Shoya Haseyama, Eri Sugioka et al. · 0 citations
Review Open access Sep 2026

The role of diffusion-weighted imaging in breast cancer: from diagnosis to treatment monitoring and follow-up.

DWI is pivotal for personalized breast cancer care, though standardized protocols and further refinement are needed for broader clinical adoption, and artificial intelligence and radiomics enhance its utility.

Yong Ye, Wen-Wen Shao, Ying Yang · 0 citations
Sep 2026

Super-Resolution Deep Learning Reconstruction for 3-Dimensional T1-Weighted Gradient-Echo Imaging in Contrast-Enhanced Liver MRI: Comparison With Conventional and Standard Deep Learning Reconstructions.

PURPOSE To evaluate the image quality of super-resolution deep learning reconstruction (SR-DLR) for 3-dimensional (3D) T1-weighted gradient-echo (GRE) imaging in contrast-enhanced MRI, compared with conventional reconstruction (Conv.) and standard deep learning reconstruction (DLR). MATERIALS AND METHODS This retrosp...

Kentaro Nishiuchi, K. Sofue, K. Tsukamoto et al. · 0 citations
Open access Sep 2026

Interobserver agreement of non-parallel transmission technology zoomed-diffusion-weighted imaging (DWI) for ordinal biparametric Vesical Imaging-Reporting and Data System (VI-RADS)-based scoring in bladder cancer lesions ≥1 cm

Background Preoperative assessment of muscle invasion in bladder cancer using the Vesical Imaging-Reporting and Data System (VI-RADS) relies heavily on diffusion-weighted imaging (DWI), but conventional single-shot echo-planar imaging diffusion-weighted imaging (ss-EPI-DWI) may be limited by image distortion and artifa...

Dian, Yu Wang, Zhen-Ming Zhang et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.