PURPOSE: Meningiomas are the most common extraaxial intracranial type of tumor, and their management and prognosis depend on their grade and histology. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are two new imaging techniques that have proved helpful in elucidating the microarchitecture of brain tumors. The aim of the present study was to assess the role of diffusion and diffusion tensor metrics in the identification and classification of meningioma grades and subtypes. METHODS AND MATERIALS: A total of 21 consecutive patients with meningioma were included in this retrospective study, of whom 16 had benign meningiomas (three fibroblastic, 11 transitional/mixed, two meningothelial) and five had atypical meningiomas. Tumor mean diffusivity (Dav), fractional anisotropy (FA), linear anisotropy (CL), planar anisotropy (CP), spherical anisotropy (CS) and eigenvalues (e1, e2, e3) were measured in all cases, and differences in diffusion tensor metrics between atypical, fibroblastic and other benign (transitional, meningothelial) meningiomas were statistically analyzed using the Mann-Whitney test. RESULTS: No statistically significant differences were found among the mean Dav values for atypical, fibroblastic and other benign meningiomas. Both atypical and fibroblastic meningiomas showed significantly higher mean FA values and lower mean CS values compared with other meningiomas (P<0.01), but no statistically significant difference in these values between each other. Atypical meningiomas showed higher CL values compared with fibroblastic and other benign meningiomas but, again, the difference was not statistically significant. Both atypical and fibroblastic meningiomas showed statistically significantly higher CP values and lower e3 values compared with transitional meningiomas (P<0.01). CONCLUSION: These results suggest that diffusion tensor metrics may be helpful in the differentiation of atypical, fibroblastic and other benign meningiomas.
PURPOSE:Meningiomas are the most common extraaxial intracranial type of tumor, and their management and prognosis depend on their grade and histology. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are two new imaging techniques that have proved helpful in elucidating the microarchitecture of brain tumors. The aim of the present study was to assess the role of diffusion and diffusion tensor metrics in the identification and classification of meningioma grades and subtypes. METHODS AND MATERIALS: A total of 21 consecutive patients with meningioma were included in this retrospective study, of whom 16 had benign meningiomas (three fibroblastic, 11 transitional/mixed, two meningothelial) and five had atypical meningiomas. Tumor mean diffusivity (Dav), fractional anisotropy (FA), linear anisotropy (CL), planar anisotropy (CP), spherical anisotropy (CS) and eigenvalues (e1, e2, e3) were measured in all cases, and differences in diffusion tensor metrics between atypical, fibroblastic and other benign (transitional, meningothelial) meningiomas were statistically analyzed using the Mann-Whitney test. RESULTS: No statistically significant differences were found among the mean Dav values for atypical, fibroblastic and other benign meningiomas. Both atypical and fibroblastic meningiomas showed significantly higher mean FA values and lower mean CS values compared with other meningiomas (P<0.01), but no statistically significant difference in these values between each other. Atypical meningiomas showed higher CL values compared with fibroblastic and other benign meningiomas but, again, the difference was not statistically significant. Both atypical and fibroblastic meningiomas showed statistically significantly higher CP values and lower e3 values compared with transitional meningiomas (P<0.01). CONCLUSION: These results suggest that diffusion tensor metrics may be helpful in the differentiation of atypical, fibroblastic and other benign meningiomas.
Authors: Filip Szczepankiewicz; Danielle van Westen; Elisabet Englund; Carl-Fredrik Westin; Freddy Ståhlberg; Jimmy Lätt; Pia C Sundgren; Markus Nilsson Journal: Neuroimage Date: 2016-07-20 Impact factor: 6.556
Authors: John Varlotto; John Flickinger; Martin T Pavelic; Charles S Specht; Jonas M Sheehan; Dana T Timek; Michael J Glantz; Steven Sogge; Christopher Dimaio; Richard Moser; Shakeeb Yunus; Thomas J Fitzgerald; Urvashi Upadhyay; Paul Rava; Matthew Tangel; Aaron Yao; Sangam Kanekar Journal: Oncotarget Date: 2015-11-10
Authors: Rodolfo G Gatto; Carina Weissmann; Manish Amin; Ariel Finkielsztein; Ronen Sumagin; Thomas H Mareci; Osvaldo D Uchitel; Richard L Magin Journal: Animal Model Exp Med Date: 2020-04-16