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  • The Brain Resection Multimodal Imaging Database (ReMIND)

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Summary

Advanced Multimodality Image Guided Operating Suite ( AMIGO)

The standard of care for brain tumors is maximal safe surgical resection as the first step. Neuronavigation augments the surgeon’s ability to achieve this, but loses validity due to brain shift as surgery progresses. Moreover, many gliomas are difficult to distinguish from adjacent brain tissue.

Intraoperative MRI is a useful intraoperative adjunct which can be used to visualize residual tumor and brain shift. Intraoperative ultrasound is faster and easier to incorporate into the workflow, but provides lower contrast between tissue and normal brain tissue.

With the success of data-hungry AI/ML algorithms in advancing the state of the art in medical image analysis, the benefits of sharing well curated data can not be overstated.

To this end, we provide here the largest publicly-available MRI and intraoperative ultrasound imaging database of surgically treated brain tumors, including gliomas (n=92), metastases (n=11) and others (n=11). This collection contains 369 preoperative MRI series, 320 3D intraoperative ultrasound series, 300 intraoperative MRI series, and 358 segmentations collected from 114 consecutive patients at a single institution. We expect this data to be a resource for computational research in brain shift and image analysis as well as for training in interpretation of intraoperative ultrasound and MRI for neurosurgery.

To the best of our knowledge there are no other intraoperative brain tumor resection MRI and Ultrasound datasets in TCIA. Understanding brain shift, and accounting for it during brain tumor resection is an open problem, and this dataset may help computer vision researchers develop algorithms for image segmentation and registration to help understand how the brain shifts and deforms during surgery.

Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:

  • NIH grants R01EB027134, P41EB028741, and R01EB032387

Data Access

Data TypeDownload all or Query/FilterLicense

Images and Segmentations (DICOM, XX.X GB)

<< latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >>

   

(Download requires NBIA Data Retriever)

Clinical data (CSV)

Click the Versions tab for more info about data releases.

Additional Resources for this Dataset

The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.

DICOM3tools, and DCMqi software used

Third Party Analyses of this Dataset

TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:

  • <add links to TCIA Analysis Result DOIs here>


Detailed Description

Image Statistics

Radiology Image Statistics

Modalities


Number of Patients


Number of Studies


Number of Series


Number of Images


Images Size (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

DOI goes here. Create using Datacite with information from Collection Approval form

Publication Citation

We ask on the proposal form if they have ONE traditional publication they'd like users to cite.

Acknowledgement

Required acknowledgements only (ex:The CPTAC program requests that publications using data from this program...). If they just want to thank someone, that goes in the Acknowledgement section underneath the Summary.

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

Other Publications Using This Data

TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

Version 1 (Current): Updated yyyy/mm/dd

Data TypeDownload all or Query/FilterLicense

Images and Segmentations (DICOM, XX.X GB)


    (Download requires the NBIA Data Retriever)

Clinical data (CSV)



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