AI Article Synopsis
- The standard treatment for brain tumors involves surgically removing as much of the tumor as possible, but challenges like brain shift make this difficult.
- Intraoperative imaging techniques like iMRI and iUS can assist in visualizing brain tumors during surgery, with iUS being quicker but less detailed than iMRI.
- A newly released extensive database of MRI and iUS images from surgical cases aims to improve brain tumor research, enhance neurosurgical training, and facilitate AI advancements in medical imaging.
Article Abstract
The standard of care for brain tumors is maximal safe surgical resection. Neuronavigation augments the surgeon's ability to achieve this but loses validity as surgery progresses due to brain shift. Moreover, gliomas are often indistinguishable from surrounding healthy brain tissue. Intraoperative magnetic resonance imaging (iMRI) and ultrasound (iUS) help visualize the tumor and brain shift. iUS is faster and easier to incorporate into surgical workflows but offers a lower contrast between tumorous and healthy tissues than iMRI. With the success of data-hungry Artificial Intelligence algorithms in medical image analysis, the benefits of sharing well-curated data cannot be overstated. To this end, we provide the largest publicly available MRI and iUS 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 iUS series, 301 iMRI series, and 356 segmentations collected from 114 consecutive patients at a single institution. This database is expected to help brain shift and image analysis research and neurosurgical training in interpreting iUS and iMRI.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11093985 | PMC |
| http://dx.doi.org/10.1038/s41597-024-03295-z | DOI Listing |
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