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Showing 193 to 197 of 197 entries
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Reliable Assessment of Swine Renal Fibrosis Using Quantitative Magnetization Transfer Imaging.

Investigative radiology

Jiang K, Ferguson CM, Grimm RC, Zhu X, Glockner JF, Lerman LO.
PMID: 34935650
Invest Radiol. 2021 Dec 21; doi: 10.1097/RLI.0000000000000843. Epub 2021 Dec 21.

OBJECTIVES: Quantitative magnetization transfer (qMT) is useful for measurement of murine renal fibrosis at high and ultrahigh field strengths. However, its utility at clinical field strengths and in human-like kidneys remains unknown. We tested the hypothesis that qMT would...

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Jiang K, Ferguson CM, Grimm RC, et al. Reliable Assessment of Swine Renal Fibrosis Using Quantitative Magnetization Transfer Imaging. Invest Radiol. 2021;doi: 10.1097/RLI.0000000000000843.
Jiang, K., Ferguson, C. M., Grimm, R. C., Zhu, X., Glockner, J. F., & Lerman, L. O. (2021). Reliable Assessment of Swine Renal Fibrosis Using Quantitative Magnetization Transfer Imaging. Investigative radiology, . https://doi.org/10.1097/RLI.0000000000000843
Jiang, Kai, et al. "Reliable Assessment of Swine Renal Fibrosis Using Quantitative Magnetization Transfer Imaging." Investigative radiology vol. (2021). doi: https://doi.org/10.1097/RLI.0000000000000843
Jiang K, Ferguson CM, Grimm RC, Zhu X, Glockner JF, Lerman LO. Reliable Assessment of Swine Renal Fibrosis Using Quantitative Magnetization Transfer Imaging. Invest Radiol. 2021 Dec 21; doi: 10.1097/RLI.0000000000000843. Epub 2021 Dec 21. PMID: 34935650.
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Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study.

Investigative radiology

Ammari S, Bône A, Balleyguier C, Moulton E, Chouzenoux É, Volk A, Menu Y, Bidault F, Nicolas F, Robert P, Rohé MM, Lassau N.
PMID: 34324463
Invest Radiol. 2022 Feb 01;57(2):99-107. doi: 10.1097/RLI.0000000000000811.

MATERIALS AND METHODS: This monocentric retrospective study leveraged 200 multiparametric brain MRIs acquired between November 2019 and February 2020 at Gustave Roussy Cancer Campus (Villejuif, France). A total of 145 patients were included: 107 formed the training sample (55...

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Ammari S, Bône A, Balleyguier C, et al. Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study. Invest Radiol. 2022;57(2):99-107doi: 10.1097/RLI.0000000000000811.
Ammari, S., Bône, A., Balleyguier, C., Moulton, E., Chouzenoux, �. �., Volk, A., Menu, Y., Bidault, F., Nicolas, F., Robert, P., Rohé, M. M., & Lassau, N. (2022). Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study. Investigative radiology, 57(2), 99-107. https://doi.org/10.1097/RLI.0000000000000811
Ammari, Samy, et al. "Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study." Investigative radiology vol. 57,2 (2022): 99-107. doi: https://doi.org/10.1097/RLI.0000000000000811
Ammari S, Bône A, Balleyguier C, Moulton E, Chouzenoux É, Volk A, Menu Y, Bidault F, Nicolas F, Robert P, Rohé MM, Lassau N. Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study. Invest Radiol. 2022 Feb 01;57(2):99-107. doi: 10.1097/RLI.0000000000000811. PMID: 34324463.
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Three-Dimensional Magnetic Resonance Fingerprinting in Neonates: Quantifying Regional Difference and Maturation in the Brain.

Investigative radiology

Yu N, Kim JY, Han D, Kim SY, Lee HM, Kim DH, Kim HG.
PMID: 34101674
Invest Radiol. 2022 Jan 01;57(1):44-51. doi: 10.1097/RLI.0000000000000800.

OBJECTIVES: Magnetic resonance fingerprinting (MRF) allows the simultaneous measurement of multiple tissue properties in a single acquisition. Three-dimensional (3D) MRF with high spatial resolution can be used for neonatal brain imaging. The aim of this study is to apply...

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Yu N, Kim JY, Han D, et al. Three-Dimensional Magnetic Resonance Fingerprinting in Neonates: Quantifying Regional Difference and Maturation in the Brain. Invest Radiol. 2022;57(1):44-51doi: 10.1097/RLI.0000000000000800.
Yu, N., Kim, J. Y., Han, D., Kim, S. Y., Lee, H. M., Kim, D. H., & Kim, H. G. (2022). Three-Dimensional Magnetic Resonance Fingerprinting in Neonates: Quantifying Regional Difference and Maturation in the Brain. Investigative radiology, 57(1), 44-51. https://doi.org/10.1097/RLI.0000000000000800
Yu, Nali, et al. "Three-Dimensional Magnetic Resonance Fingerprinting in Neonates: Quantifying Regional Difference and Maturation in the Brain." Investigative radiology vol. 57,1 (2022): 44-51. doi: https://doi.org/10.1097/RLI.0000000000000800
Yu N, Kim JY, Han D, Kim SY, Lee HM, Kim DH, Kim HG. Three-Dimensional Magnetic Resonance Fingerprinting in Neonates: Quantifying Regional Difference and Maturation in the Brain. Invest Radiol. 2022 Jan 01;57(1):44-51. doi: 10.1097/RLI.0000000000000800. PMID: 34101674.
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The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T.

Investigative radiology

Runge VM, Heverhagen JT.
PMID: 34510100
Invest Radiol. 2022 Jan 01;57(1):1-12. doi: 10.1097/RLI.0000000000000824.

ABSTRACT: This review provides a balanced perspective regarding the clinical utility of magnetic resonance systems across the range of field strengths for which current state-of-the-art units exist (0.55 T, 1.5 T, 3 T, and 7 T). Guidance regarding this...

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Runge VM, Heverhagen JT. The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T. Invest Radiol. 2022;57(1):1-12doi: 10.1097/RLI.0000000000000824.
Runge, V. M., & Heverhagen, J. T. (2022). The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T. Investigative radiology, 57(1), 1-12. https://doi.org/10.1097/RLI.0000000000000824
Runge, Val M, and Heverhagen, Johannes T. "The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T." Investigative radiology vol. 57,1 (2022): 1-12. doi: https://doi.org/10.1097/RLI.0000000000000824
Runge VM, Heverhagen JT. The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T. Invest Radiol. 2022 Jan 01;57(1):1-12. doi: 10.1097/RLI.0000000000000824. PMID: 34510100.
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Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study.

Investigative radiology

Ammari S, Bône A, Balleyguier C, Moulton E, Chouzenoux É, Volk A, Menu Y, Bidault F, Nicolas F, Robert P, Rohé MM, Lassau N.
PMID: 34324463
Invest Radiol. 2021 Jul 28; doi: 10.1097/RLI.0000000000000811. Epub 2021 Jul 28.

This study proposes and evaluates a deep learning method that predicts surrogate images for contrast-enhanced T1 from multiparametric magnetic resonance imaging (MRI) acquired using only a quarter of the standard 0.1 mmol/kg dose of gadolinium-based contrast agent. In particular,...

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Ammari S, Bône A, Balleyguier C, et al. Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study. Invest Radiol. 2021;doi: 10.1097/RLI.0000000000000811.
Ammari, S., Bône, A., Balleyguier, C., Moulton, E., Chouzenoux, �. �., Volk, A., Menu, Y., Bidault, F., Nicolas, F., Robert, P., Rohé, M. M., & Lassau, N. (2021). Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study. Investigative radiology, . https://doi.org/10.1097/RLI.0000000000000811
Ammari, Samy, et al. "Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study." Investigative radiology vol. (2021). doi: https://doi.org/10.1097/RLI.0000000000000811
Ammari S, Bône A, Balleyguier C, Moulton E, Chouzenoux É, Volk A, Menu Y, Bidault F, Nicolas F, Robert P, Rohé MM, Lassau N. Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study. Invest Radiol. 2021 Jul 28; doi: 10.1097/RLI.0000000000000811. Epub 2021 Jul 28. PMID: 34324463.
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Showing 193 to 197 of 197 entries