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ReMIND:脑切除多模态成像数据库。

ReMIND: The Brain Resection Multimodal Imaging Database.

机构信息

Brigham and Women's Hospital, Harvard Medical School, Boston, USA.

Computer Aided Medical Procedures, Technische Universität München, Munich, Germany.

出版信息

Sci Data. 2024 May 14;11(1):494. doi: 10.1038/s41597-024-03295-z.


DOI:10.1038/s41597-024-03295-z
PMID:38744868
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11093985/
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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef0/11093985/4e8eae0a9803/41597_2024_3295_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef0/11093985/4e8eae0a9803/41597_2024_3295_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef0/11093985/4e8eae0a9803/41597_2024_3295_Fig1_HTML.jpg

相似文献

[1]
ReMIND: The Brain Resection Multimodal Imaging Database.

Sci Data. 2024-5-14

[2]
ReMIND: The Brain Resection Multimodal Imaging Database.

medRxiv. 2024-4-8

[3]
Clinical application of 3.0 T intraoperative magnetic resonance combined with multimodal neuronavigation in resection of cerebral eloquent area glioma.

Medicine (Baltimore). 2018-8

[4]
Navigated intraoperative ultrasound in pediatric brain tumors.

Childs Nerv Syst. 2024-9

[5]
Challenges and Opportunities of Intraoperative 3D Ultrasound With Neuronavigation in Relation to Intraoperative MRI.

Front Oncol. 2021-5-3

[6]
Factors triggering an additional resection and determining residual tumor volume on intraoperative MRI: analysis from a prospective single-center registry of supratentorial gliomas.

Neurosurg Focus. 2016-3

[7]
[Application of intraoperative MRI combined with neuronavigation in microsurgical resection for 
insular glioma].

Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2018-4-28

[8]
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J Neurosurg. 2017-1-6

[9]
Intraoperative Multi-Information-Guided Resection of Dominant-Sided Insular Gliomas in a 3-T Intraoperative Magnetic Resonance Imaging Integrated Neurosurgical Suite.

World Neurosurg. 2016-5

[10]
Intraoperative Integration of Multimodal Imaging to Improve Neuronavigation: A Technical Note.

World Neurosurg. 2022-8

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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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Neurooncol Adv. 2025-1-28

[9]
Deep Learning-Based Glioma Segmentation of 2D Intraoperative Ultrasound Images: A Multicenter Study Using the Brain Tumor Intraoperative Ultrasound Database (BraTioUS).

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[10]
DNA palette code for time-series archival data storage.

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本文引用的文献

[1]
Unified Brain MR-Ultrasound Synthesis using Multi-Modal Hierarchical Representations.

Med Image Comput Comput Assist Interv. 2023-10-13

[2]
Challenges and Opportunities of Intraoperative 3D Ultrasound With Neuronavigation in Relation to Intraoperative MRI.

Front Oncol. 2021-5-3

[3]
Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets.

Med Image Anal. 2021-1

[4]
cIMPACT-NOW update 7: advancing the molecular classification of ependymal tumors.

Brain Pathol. 2020-9

[5]
cIMPACT-NOW update 6: new entity and diagnostic principle recommendations of the cIMPACT-Utrecht meeting on future CNS tumor classification and grading.

Brain Pathol. 2020-7

[6]
Evaluation of MRI to Ultrasound Registration Methods for Brain Shift Correction: The CuRIOUS2018 Challenge.

IEEE Trans Med Imaging. 2020-3

[7]
cIMPACT-NOW update 4: diffuse gliomas characterized by MYB, MYBL1, or FGFR1 alterations or BRAF mutation.

Acta Neuropathol. 2019-4

[8]
SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research.

J Digit Imaging. 2018-6

[9]
: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM.

Cancer Res. 2017-11-1

[10]
WHO 2016 Classification of gliomas.

Neuropathol Appl Neurobiol. 2018-2

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