Summary
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. 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
Data Access
Data Type | Download all or Query/Filter | License |
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Images and Radiation Therapy Structures (DICOM, 9.0 GB) | (Download requires NBIA Data Retriever) | |
Clinical data (CSV, 20 kB) |
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Detailed Description
Image Statistics | Radiology Image Statistics |
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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
Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:
Data Citation
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
Publication Citation
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
TCIA Citation
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
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Version 1 (Current): Updated 2023/02/13
Data Type | Download all or Query/Filter | License |
---|---|---|
Images, Segmentations, and Radiation Therapy Structures (DICOM, 9.0 GB) | (Download requires the NBIA Data Retriever) | |
Clinical data (CSV) |