High Resolution 3D Magnetic Resonance Fingerprinting with Hybrid Radial-Interleaved EPI Acquisition for Knee Cartilage T<sub>1</sub>, T<sub>2</sub>Mapping

Han, Dong Woo; Hong, Taehwa; Lee, Yonghan; Kim, Dong-Hyun

doi:10.13104/imri.2021.25.3.141

Cited by 3 publications

(5 citation statements)

References 52 publications

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“…Total scan time was 4 minutes and 54 seconds. More details about the 3D MRF technique were previously described 22 . Simple dictionary matching using the inner-product was performed to acquire T1 and T2 maps.…”

Section: Methodsmentioning

confidence: 99%

“…More details about the 3D MRF technique were previously described. 22 Simple dictionary matching using the inner-product was performed to acquire T1 and T2 maps. The T1 range of the dictionary was from 150 to 3000 milliseconds with 10 milliseconds step size and 3050 to 4000 milliseconds with 50 milliseconds step size.…”

Section: Three-dimensional Magnetic Resonance Fingerprintingmentioning

confidence: 99%

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Three-Dimensional Magnetic Resonance Fingerprinting in Neonates

Kim

Han

et al. 2021

Invest Radiol

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Section: Methodsmentioning

confidence: 99%

Section: Three-dimensional Magnetic Resonance Fingerprintingmentioning

confidence: 99%

Three-Dimensional Magnetic Resonance Fingerprinting in Neonates

Kim

Han

et al. 2021

Invest Radiol

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“…A 3D MRF method was proposed for high-resolution (0.5 mm 2 ) knee cartilage PD, T 1 , and T 2 mapping. 90 Different trajectories were implemented in the k xy and k z directions followed by the singular value decomposition (SVD) compression reconstruction method to reduce reconstruction time. An algorithm was proposed to optimize the reconstruction of 3D MRF data.…”

Section: Mr Fingerprinting and Multicontrast Methodsmentioning

confidence: 99%

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications

Zibetti

Menon

Moura

et al. 2023

Magnetic Resonance Imaging

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Osteoarthritis (OA) is a widely occurring degenerative joint disease that is severely debilitating and causes significant socioeconomic burdens to society. Magnetic resonance imaging (MRI) is the preferred imaging modality for the morphological evaluation of cartilage due to its excellent soft tissue contrast and high spatial resolution. However, its utilization typically involves subjective qualitative assessment of cartilage. Compositional MRI, which refers to the quantitative characterization of cartilage using a variety of MRI methods, can provide important information regarding underlying compositional and ultrastructural changes that occur during early OA. Cartilage compositional MRI could serve as early imaging biomarkers for the objective evaluation of cartilage and help drive diagnostics, disease characterization, and response to novel therapies. This review will summarize current and ongoing state‐of‐the‐art cartilage compositional MRI techniques and highlight emerging methods for cartilage compositional MRI including MR fingerprinting, compressed sensing, multiexponential relaxometry, improved and robust radio‐frequency pulse sequences, and deep learning‐based acquisition, reconstruction, and segmentation. The review will also briefly discuss the current challenges and future directions for adopting these emerging cartilage compositional MRI techniques for use in clinical practice and translational OA research studies. Evidence Level 2 Technical Efficacy Stage 2.

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“…1) [1,4]. An iterative reconstruction method was also applied to improve image quality [2,17]. 3D MRF utilized fast imaging with steady-state precession acquisition, and it did not include radiofrequency spoilers or spoiler gradients for complete spoiling.…”

Section: Mri Acquisitions and Postprocessingmentioning

confidence: 99%

“…3D MRF utilized fast imaging with steady-state precession acquisition, and it did not include radiofrequency spoilers or spoiler gradients for complete spoiling. 3D MRF sequence detail and accuracy of T 1 and T 2 values derived from 3D MRF is described in prior studies [2,17].…”

Section: Mri Acquisitions and Postprocessingmentioning

confidence: 99%

3D MR fingerprinting-derived myelin water fraction characterizing brain development and leukodystrophy

Kim,

Han,

Kim

et al. 2023

J Transl Med

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Background Magnetic resonance fingerprinting (MRF) enables fast myelin quantification via the myelin water fraction (MWF), offering a noninvasive method to assess brain development and disease. However, MRF-derived MWF lacks histological evaluation and remains unexamined in relation to leukodystrophy. This study aimed to access MRF-derived MWF through histology in mice and establish links between myelin, development, and leukodystrophy in mice and children, demonstrating its potential applicability in animal and human studies. Methods 3D MRF was performed on normal C57BL/6 mice with different ages, megalencephalic leukoencephalopathy with subcortical cyst 1 wild type (MLC1 WT, control) mice, and MLC 1 knock-out (MLC1 KO, leukodystrophy) mice using a 3 T MRI. MWF values were analyzed from 3D MRF data, and histological myelin quantification was carried out using immunohistochemistry to anti-proteolipid protein (PLP) in the corpus callosum and cortex. The associations between ‘MWF and PLP’ and ‘MWF and age’ were evaluated in C57BL/6 mice. MWF values were compared between MLC1 WT and MLC1 KO mice. MWF of normal developing children were retrospectively collected and the association between MWF and age was assessed. Results In 35 C57BL/6 mice (age range; 3 weeks–48 weeks), MWF showed positive relations with PLP immunoreactivity in the corpus callosum (β = 0.0006, P = 0.04) and cortex (β = 0.0005, P = 0.006). In 12-week-old C57BL/6 mice MWF showed positive relations with PLP immunoreactivity (β = 0.0009, P = 0.003, R2 = 0.54). MWF in the corpus callosum (β = 0.0022, P < 0.001) and cortex (β = 0.0010, P < 0.001) showed positive relations with age. Seven MLC1 WT and 9 MLC1 KO mice showed different MWF values in the corpus callous (P < 0.001) and cortex (P < 0.001). A total of 81 children (median age, 126 months; range, 0–199 months) were evaluated and their MWF values according to age showed the best fit for the third-order regression model (adjusted R2 range, 0.44–0.94, P < 0.001). Conclusion MWF demonstrated associations with histologic myelin quantity, age, and the presence of leukodystrophy, underscoring the potential of 3D MRF-derived MWF as a rapid and noninvasive quantitative indicator of brain myelin content in both mice and humans.

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High Resolution 3D Magnetic Resonance Fingerprinting with Hybrid Radial-Interleaved EPI Acquisition for Knee Cartilage T₁, T₂Mapping

Cited by 3 publications

References 52 publications

Three-Dimensional Magnetic Resonance Fingerprinting in Neonates

Three-Dimensional Magnetic Resonance Fingerprinting in Neonates

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications

3D MR fingerprinting-derived myelin water fraction characterizing brain development and leukodystrophy

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High Resolution 3D Magnetic Resonance Fingerprinting with Hybrid Radial-Interleaved EPI Acquisition for Knee Cartilage T1, T2Mapping

Cited by 3 publications

References 52 publications

Three-Dimensional Magnetic Resonance Fingerprinting in Neonates

Three-Dimensional Magnetic Resonance Fingerprinting in Neonates

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications

3D MR fingerprinting-derived myelin water fraction characterizing brain development and leukodystrophy

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Product

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High Resolution 3D Magnetic Resonance Fingerprinting with Hybrid Radial-Interleaved EPI Acquisition for Knee Cartilage T₁, T₂Mapping