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  • Meningioma Pathology and Imaging Features Associate With Genomic Profile

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    Wenya Linda Bi MD PhD; Noah Greenwald BA; Malak Abedalthagafi MD; Thibaud Coroller MSc; Sandro Santagata MD, PhD; Hugo PhD Aerts; Rameen Beroukhim MD, PhD; Raymond Huang MD, PhD; Ian F. Dunn MD

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    Meeting: Congress of Neurological Surgeons 2016 Annual Meeting

    Introduction: The genomic features of tumors are increasingly appreciated to associate with their phenotype and clinical course. Recently, our understanding of the copy number profile and mutations underlying meningiomas have expanded. We investigated the association between the genomic signature of a large series of meningiomas and its relationship to their pathologic grade and imaging features.

    Methods: We retrospectively examined 221 meningiomas (125 grade I, 83 grade II, 13 grade III) for their genomic signature and a set of defined criteria on T1-weighted gadolinium-enhanced imaging. Peritumoral edema, tumor shape, presence of cystic features, hyperostosis, invasion of adjacent venous sinuses, intratumor heterogeneity, necrosis/hemorrhage, and extent of mass effect were scored for each tumor by an experienced neuroradiologist. Chromosomal gains or losses were determined using high-resolution array CGH. Linear regression analysis and Chi squared testing were used to investigate associations, with significance defined as p value <0.05.

    Results: The extent of chromosomal copy number alterations was significantly associated with meningioma grade (p<1e-10), as well as the number of atypical features associated with grade 1 and 2 meningiomas. Intratumoral heterogeneity and cystic features associated with increasing chromosomal disruption, as defined by a more frequent copy number gains or losses. Presence of intratumoral heterogeneity and necrosis or hemorrhage within the tumor was also significantly associated with increasing meningioma grade.

    Conclusions: We demonstrate a strong association between the genomic profile, radiologic features, and pathologic classification for meningiomas. Pre-operative prediction of tumor grade and biologic signature based on imaging features offers promise for guiding personalized medicine and improving patient management.

    Patient Care: Defining an association between radiographic features of meningioma and their pathologic grade, genomic signature, and clinical outcome allows for improved peri-operative stratification of management paradigms.

    Learning Objectives: 1. Understand the progression of genomic alterations associated with meningiomas. 2. Describe the association between genomic status of meningioma and their imaging appearance and pathologic classification.


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