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MRI Data Analysis in Malformations of Cortical Development

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Cerebral Cortex Development

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2794))

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Abstract

Brain magnetic resonance imaging (MRI) is a noninvasive imaging modality that utilizes powerful magnets and radio waves to generate detailed images of the brain, making it a valuable tool for investigating malformations of cortical development (MCD). Various MRI techniques, including 3D T1-weighted, multiplanar thin-sliced T2-weighted, and 3D fluid-attenuated inversion recovery (FLAIR) sequences, can provide high-resolution images with excellent spatial and contrast resolution, allowing for a detailed visualization of cortical anatomy and abnormalities. Almost all MCD can be detected and characterized using MRI. Advanced techniques, such as arterial spin labeling MR perfusion, diffusion tensor imaging (DTI), and functional MRI (fMRI), may be used to improve the detection rate of these malformations and to plan surgery in case of drug-resistant epilepsy. However, there are also limitations related to high cost, relatively low availability, need for sedation or anesthesia, and limited sensitivity for detecting subtle focal cortical malformations. Despite these limitations, brain MRI plays a crucial role in the investigation of MCD, providing valuable information for diagnosis, treatment planning, and patient management.

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Acknowledgments

We thank the Unit of Neuroradiology of the Institute Giannina Gaslini for the technical support.

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Correspondence to Mariasavina Severino .

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© 2024 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Severino, M., Tortora, D., Scala, M. (2024). MRI Data Analysis in Malformations of Cortical Development. In: Nagata, Ki. (eds) Cerebral Cortex Development. Methods in Molecular Biology, vol 2794. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3810-1_23

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  • DOI: https://doi.org/10.1007/978-1-0716-3810-1_23

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3809-5

  • Online ISBN: 978-1-0716-3810-1

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