Summary

The study included 96 consecutive treatment naïve patients with intracranial meningiomas treated with surgical resection from 2010 to 2019. All patients had pre-operative T1, T1-CE, and T2-FLAIR MR images with subsequent subtotal or gross total resection of pathologically confirmed grade I or grade II meningiomas. A neuropathology team reviewed histopathology, including two subspecialty trained neuropathologists and one neuropathology fellow. The meningioma grade was confirmed based on current classification guidelines, most recently described in the 2016 WHO Bluebook. Clinical information includes grade, subtype, type of surgery, tumor location, and atypical features. Meningioma labels on T1-CE and T2-FLAIR images will also be provided in DICOM format. The hyperintense T1-contrast enhancing tumor and hyperintense T2-FLAIR and tumor were manually contoured on each MRI and reviewed by a central nervous system radiation oncologist specialist.





Data Access

Data TypeDownload all or Query/FilterLicense

Images and Radiation Therapy Structures (DICOM, 9.0 GB)







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Clinical data (CSV, 20 kB)





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Detailed Description

Image Statistics

Radiology Image Statistics

Modalities

MR, RTSTRUCT

Number of Patients

96

Number of Studies

180

Number of Series

674

Number of Images

47520

Images Size (GB)9 GB



Citations & Data Usage Policy

Vassantachart, A., Cao, Y., Shen, Z., Cheng, K., Gribble, M., Ye, J. C., Zada, G., Hurth, K., Mathew, A., Guzman, S., & Yang, W. (2023). Segmentation and Classification of Grade I and II Meningiomas from Magnetic Resonance Imaging: An Open Annotated Dataset (Meningioma-SEG-CLASS) (Version 1) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/0TKV-1A36


Vassantachart, A., Cao, Y., Gribble, M., Guzman, S., Ye, J. C., Hurth, K., Mathew, A., Zada, G., Fan, Z., Chang, E. L., & Yang, W. (2022). Automatic differentiation of Grade I and II meningiomas on magnetic resonance image using an asymmetric convolutional neural network. In Scientific Reports (Vol. 12, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1038/s41598-022-07859-0


Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7

Other Publications Using This Data

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Version 1 (Current): Updated 2023/02/13

Data TypeDownload all or Query/FilterLicense

Images, Segmentations, and Radiation Therapy Structures (DICOM, 9.0 GB)






(Download requires the NBIA Data Retriever)


Clinical data (CSV)