Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
Computer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Sci Data. 2024 May 14;11(1):494. 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.
脑肿瘤的治疗标准是最大限度地安全手术切除。神经导航增强了外科医生实现这一目标的能力，但由于脑移位，其有效性会逐渐丧失。此外，胶质瘤通常与周围健康脑组织难以区分。术中磁共振成像（iMRI）和超声（iUS）有助于观察肿瘤和脑移位。iUS 更快、更容易融入手术流程，但与 iMRI 相比，其在肿瘤和健康组织之间的对比度更低。随着数据密集型人工智能算法在医学图像分析中的成功，共享精心整理的数据的好处怎么强调都不为过。为此，我们提供了最大的公开可用于手术治疗脑肿瘤的 MRI 和 iUS 数据库，包括胶质瘤（n=92）、转移瘤（n=11）和其他肿瘤（n=11）。该数据库包含 369 个术前 MRI 系列、320 个 3D iUS 系列、301 个 iMRI 系列和 356 个从一家机构的 114 名连续患者中收集的分割。该数据库有望有助于脑移位和图像分析研究以及神经外科医生在解读 iUS 和 iMRI 方面的培训。
