464-02-010 ISMRM Abstract

Robustness of quantitative diffusion metrics from eight models in musculoskeletal system: a phantom study

Primary: Diffusion - Diffusion Acquisition

Secondary: Musculoskeletal - Muscle

464-02-010 · Validating Diffusion MRI: Reproducibility, Simulations, and Phantoms · Tuesday, 12 May, 9:15 AM–10:10 AM · Digital Posters Row E

Keywords: Muscle Musculoskeletal MRI Quantitaitive diffusion imaging Phantom study Reproducibility of results

Accepted

Jingyu Zhong ¹, Yang Song², Yue Xing¹, Yangfan Hu¹, Wenjie Lu¹, Weiwu Yao¹

¹Department of Imaging, Tongren hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

²MR Research Collaboration Team, Siemens Healthineers Ltd. Shanghai, Shanghai, China

Presenting Author: Jingyu Zhong

Synopsis

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References

1. Mao J, Zeng W, Zhang Q, et al. Differentiation between high-grade gliomas and solitary brain metastases: a comparison of five diffusion-weighted MRI models. BMC Med Imaging 2020;20(1):124. https://doi.org/10.1186/s12880-020-00524-w [doi]

2. Mao C, Jiang W, Huang, et al. Quantitative parameters of diffusion spectrum imaging: HER2 status prediction in patients with breast cancer. Front Oncol 2022;12:817070. https://doi.org/10.3389/fonc.2022.817070 [doi]

3. She D, Huang H, Guo W, et al. Grading meningiomas with diffusion metrics: a comparison between diffusion kurtosis, mean apparent propagator, neurite orientation dispersion and density, and diffusion tensor imaging. Eur Radiol 2023;33(5):3671-3681. https://doi.org/10.1007/s00330-023-09505-3 [doi]

4. Giraudo C, Motyka S, Weber M, et al. Diffusion Tensor Imaging of Healthy Skeletal Muscles: A Comparison Between 7 T and 3 T. Invest Radiol 2019;54(1):48-54. https://doi.org/10.1097/RLI.0000000000000508 [doi]

5. Shur J, Blackledge M, D'Arcy J, et al. MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study. Eur Radiol Exp 2021;5(1):2. https://doi.org/10.1186/s41747-020-00199-6 [doi]

6. European Society of Radiology (ESR). ESR statement on the validation of imaging biomarkers. Insights Imaging 2020;11(1):76. https://doi.org/10.1186/s13244-020-00872-9 [doi]

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http://echo.ismrm.org/p/ISMRM2026/464-02-010