TCGA-LGG-Mask | ROI Masks Defining Low-Grade Glioma Tumor Regions In the TCGA-LGG Image Collection
DOI: 10.7937/K9/TCIA.2017.BD7SGWCA | Data Citation Required | 22 Views | Analysis Result
| Location | Subjects | Size | Updated | |||
|---|---|---|---|---|---|---|
| Low Grade Glioma | Brain | 188 | Software/Source Code | 2017/03/17 |
Summary
This collection contains 406 ROI masks in MATLAB format defining the low grade glioma (LGG) tumour region on T1-weighted (T1W), T2-weighted (T2W), T1-weighted post-contrast (T1CE) and T2-flair (T2F) MR images of 108 different patients from the TCGA-LGG collection. From this subset of 108 patients, 81 patients have ROI masks drawn for the four MRI sequences (T1W, T2W, T1CE and T2F), and 27 patients have ROI masks drawn for three or less of the four MRI sequences. The ROI masks were used to extract texture features in order to develop radiomic-based multivariable models for the prediction of isocitrate dehydrogenase 1 (IDH1) mutation, 1p/19q codeletion status, histological grade and tumour progression. Clinical data (188 patients in total from the TCGA-LGG collection, some incomplete depending on the clinical attribute), VASARI scores (188 patients in total from the TCGA-LGG collection, 178 complete) with feature keys, and source code used in this study are also available with this collection. Please contact Martin Vallières (mart.vallieres@gmail.com) of the Medical Physics Unit of McGill University for any scientific inquiries about this dataset.
Data Access
Some data in this collection contains images that could potentially be used to reconstruct a human face. To safeguard the privacy of participants, users must sign and submit a TCIA Restricted License Agreement to help@cancerimagingarchive.net before accessing the data.
Version 1: Updated 2017/03/17
| Title | Data Type | Format | Access Points | Subjects | License | |||
|---|---|---|---|---|---|---|---|---|
| Matlab Segmentations 2MB zip expands to 18.3MB | Segmentation | MATLAB and ZIP | 109 | 406 | CC BY 3.0 | |||
| Clinical data | Molecular Test, Follow-Up, Diagnosis | CSV | CC BY 3.0 | |||||
| VASARI information | Radiomic Feature | CSV | CC BY 3.0 | |||||
| VASARI MR feature key | Other | CC BY 3.0 |
Collections Used In This Analysis Result
| Title | Data Type | Format | Access Points | Subjects | License | |||
|---|---|---|---|---|---|---|---|---|
| Images | MR | DICOM | Requires NBIA Data Retriever |
108 | 110 | 406 | 27,301 | TCIA Restricted |
Additional Resources For This Dataset
The following external resources have been made available by the data submitters. These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.
- Source code used in this study on Github
Citations & Data Usage Policy
Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:
Data Citation |
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Su, C., Vallières, M., & Bai, H. (2017). ROI Masks Defining Low-Grade Glioma Tumor Regions In the TCGA-LGG Image Collection [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.BD7SGWCA |
Related Publications
Publications by the Dataset Authors
The authors recommended the following as the best source of additional information about this dataset:
Publication Citation |
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Zhou, H., Vallières, M., Bai, H. X., Su, C., Tang, H., Oldridge, D., Zhang, Z., Xiao, B., Liao, W., Tao, Y., Zhou, J., Zhang, P., & Yang, L. (2017). MRI features predict survival and molecular markers in diffuse lower-grade gliomas. Neuro-Oncology, 19(6), 862–870. https://doi.org/10.1093/neuonc/now256 |
Research Community Publications
TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.