梳理28个胶质瘤MRI公开数据集，助研究者高效选型。
Exploring Adult Glioma through MRI: A Review of Publicly Available Datasets to Guide Efficient Image Analysis
- 系统检索3大平台，汇总2005至2024年28个胶质瘤MRI数据集。
- 覆盖5515名患者、62019张图像，分析标注与分类分布情况。
- 揭示仅2个数据集符合最新WHO分类标准，提示更新方向。
公开数据对医学影像分析发展至关重要，尤其在构建机器学习模型方面。胶质瘤是最常见的原发性脑肿瘤，磁共振成像（MRI）是其诊断与治疗中的常用手段。然而，当前胶质瘤MRI公开数据的可用性与质量尚不明确。本综述通过Google Dataset Search、The Cancer Imaging Archive（TCIA）和Synapse平台检索，共发现2005年至2024年5月期间发布的28个公开数据集，涵盖5515名患者、62019张图像。我们分析了这些数据集的来源、规模、格式、标注方式及可访问性，并考察了其中肿瘤类型、分级与分期的分布情况。特别讨论了世界卫生组织（WHO）脑肿瘤分类的演变，尤其是2021年更新对胶质母细胞瘤定义的重大调整。同时指出可利用这些数据集开展的研究方向，如肿瘤恶性转化过程、MRI标准化及肿瘤分割等。值得注意的是，28个数据集中仅有2个反映当前的WHO分类标准。本综述全面梳理了当前可获取的胶质瘤MRI公开数据资源，为医学影像分析研究者提供高效的数据选择参考。
原文摘要 · Abstract (English)
Publicly available data is essential for the progress of medical image analysis, in particular for crafting machine learning models. Glioma is the most common group of primary brain tumors, and magnetic resonance imaging (MRI) is a widely used modality in their diagnosis and treatment. However, the availability and quality of public datasets for glioma MRI are not well known. In this review, we searched for public datasets for glioma MRI using Google Dataset Search, The Cancer Imaging Archive (TCIA), and Synapse. A total of 28 datasets published between 2005 and May 2024 were found, containing 62019 images from 5515 patients. We analyzed the characteristics of these datasets, such as the origin, size, format, annotation, and accessibility. Additionally, we examined the distribution of tumor types, grades, and stages among the datasets. The implications of the evolution of the WHO classification on tumors of the brain are discussed, in particular the 2021 update that significantly changed the definition of glioblastoma. Additionally, potential research questions that could be explored using these datasets were highlighted, such as tumor evolution through malignant transformation, MRI normalization, and tumor segmentation. Interestingly, only two datasets among the 28 studied reflect the current WHO classification. This review provides a comprehensive overview of the publicly available datasets for glioma MRI currently at our disposal, providing aid to medical image analysis researchers in their decision-making on efficient dataset choice.
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