ReMIND: The Brain Resection Multimodal Imaging Database

• Published in: Scientific data Vol. 11; no. 1; pp. 494 - 9
• Main Authors: Juvekar, Parikshit, Dorent, Reuben, Kögl, Fryderyk, Torio, Erickson, Barr, Colton, Rigolo, Laura, Galvin, Colin, Jowkar, Nick, Kazi, Anees, Haouchine, Nazim, Cheema, Harneet, Navab, Nassir, Pieper, Steve, Wells, William M., Bi, Wenya Linda, Golby, Alexandra, Frisken, Sarah, Kapur, Tina
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.05.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 692/308/575; 692/617/375/1922; Artificial intelligence; Brain - diagnostic imaging; Brain - surgery; Brain cancer; Brain Neoplasms - diagnostic imaging; Brain Neoplasms - surgery; Brain tumors; Data Descriptor; Databases, Factual; Glioma; Glioma - diagnostic imaging; Glioma - surgery; Humanities and Social Sciences; Humans; Image processing; Magnetic Resonance Imaging; Metastases; multidisciplinary; Multimodal Imaging; Neuroimaging; Neuronavigation - methods; Neurosurgery; Science; Science (multidisciplinary); Tumors; Ultrasonography
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-024-03295-z

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.