Ultrahigh-field imaging (7 Tesla) in DNET : Unmasking microstructural imaging characteristics

Article Article scientifique Rapport de cas Ultrahigh-field imaging (7 Tesla) in DNET : Unmasking microstructural imaging characteristics - A case report eng 2025-02-05 2025-03 author Calvo- Imirizaldu Marta Department of Radiology, University Clinic of Navarra, Pamplona, Spain.,Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. author Botta Daniele Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. 417457 author Seeck Margitta Division of Neurology, Geneva University Hospitals, Geneva, Switzerland. 133679 Département des neurosciences cliniques (OTONO) author Novy Jan Division of Neurology, Lausanne University Hospitals, Lausanne, Switzerland. author Ojeda Montes María José Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. 441107 author Fitsiori Aikaterini Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. 919174 Département de radiologie et informatique médicale (RADIO) author Santarosa Corrado Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. 418060 author Battistini Kevin Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. 725196 author Lövblad Karl-Olof Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. 135154 Département de radiologie et informatique médicale (RADIO) author Kurz Félix Tobias Division of Neuroradiology, Geneva University Hospitals, Geneva, Switzerland. 419472 Département de radiologie et informatique médicale (RADIO) 100749 10.1016/j.ebr.2025.100749 40017526 2589-9864 PMC11867227 https://www.sciencedirect.com/science/article/pii/S2589986425000097 Commercial ultrahigh-field 7 Tesla (T) MRI has been approved for clinical brain imaging, including applications in epilepsy and brain tumors. Increasing magnetic field strength offers significant advantages over lower-field MRI due to improved spatial resolution, signal-to-noise ratio, and contrast-to-noise ratio. These improvements provide better anatomical delineation and gray-white matter tissue-contrast differentiation. We present a case of a presumed dysembryoplastic neuroepithelial tumor (DNET) imaged at 7 T MRI of the second generation, which revealed an unprecedented level of detail of the complex and intricate tumor architecture. Insights of its different components correlate closely with its known histopathological features. These tumors are unique among low-grade neoplasms due to their distinct clinical presentation, imaging features, and histopathological architecture. DNETs are rare, typically occurring in young patients with refractory epilepsy, and are classified by their well-defined histological subtypes. We review the various MRI patterns of DNET, which have been shown to correlate with histological subtypes and the extent of the epileptogenic zone. Complete tumor resection is essential for long-term control and recurrence prevention, emphasizing the importance of precise preoperative visualization of the tumor and its surrounding tissue. In this case, 7 T images demonstrated superior lesion conspicuity and clearer boundaries, highlighting the advantages of ultrahigh-field MRI in defining the full extent of the lesion. Although 7 T MRI is not yet widely available, it has started to gain an important role in the management of epilepsy, particularly for cases requiring detailed structural analysis. 7T MRI Drug-resistant epilepsy Dysembryoplastic neuroepithelial tumor Focal cortical dysplasia Satellite lesion Dewey 616.8 Dewey 616.0757 62 Département de radiologie et informatique médicale 227 61 Département des neurosciences cliniques 226 false 470 Ischémie cérébrale et connectivité 801 119 Epilepsie et Chirurgie 149 Epilepsy & behavior reports 29 5708abe3-43e7-46cb-939c-818f5785209a Article (Published version) Public Article_scientifique_from_europePmc.pdf 3023926 application/pdf CC BY-NC-ND-4.0 918abf1b5234f7a6a0a8879722d12b186f8d30d46b9066488a90f29ee2a6467f 68f3da25-a1b6-4936-8d32-d0890bfe2362 Appendix Public mmc1.docx 19138 application/vnd.openxmlformats-officedocument.wordprocessingml.document 3ab2495246bf99d6813c8d4eb00826862f5fd00ad16011519f2b497478d01889 openAccess Faculté de médecine / Section de médecine clinique / Département de radiologie et informatique médicale Faculté de médecine / Section de médecine clinique / Département des neurosciences cliniques

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Ultrahigh-field imaging (7 Tesla) in DNET : Unmasking microstructural imaging characteristics - A case report	Epilepsy & behavior reports			2025	45	38

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Ojeda Montes, María José