里奥·奥尔特加大学医院胶质母细胞瘤数据集：术前、术后早期及复发MRI扫描的综合集合（RHUH-GBM）
The Rio Hortega University Hospital Glioblastoma dataset: a comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM)
AI总结：
本文发布RHUH-GBM胶质母细胞瘤多参数MRI数据集，涵盖术前、术后早期及复发影像，并提供专家校正分割、分子与生存数据，以支持复发模式研究及诊断预后模型开发。
摘要：
胶质母细胞瘤是一种高度侵袭性的原发性脑肿瘤，与患者不良预后相关。尽管磁共振成像（MRI）在诊断、表征和预测胶质母细胞瘤进展方面发挥着关键作用，但公共MRI库存在显著缺陷，包括术后和随访研究不足，以及缺乏专家肿瘤分割。为解决这些问题，我们提出了“里奥·奥尔特加大学医院胶质母细胞瘤数据集（RHUH-GBM）”，该集合包含多参数MRI图像、体积评估、分子数据和生存详情，对象为接受了强化肿瘤全切除或近全切除的胶质母细胞瘤患者。该数据集具有经专家校正的肿瘤子区域分割，为开发术后和随访MRI扫描算法提供了宝贵的真值数据。RHUH-GBM数据集的公开发布显著促进了胶质母细胞瘤研究，使科学界能够研究复发模式并开发新的诊断和预后模型。这可能带来更个性化、更有效的治疗，并最终改善患者预后。
英文摘要：
Glioblastoma, a highly aggressive primary brain tumor, is associated with poor patient outcomes. Although magnetic resonance imaging (MRI) plays a critical role in diagnosing, characterizing, and forecasting glioblastoma progression, public MRI repositories present significant drawbacks, including insufficient postoperative and follow-up studies as well as expert tumor segmentations. To address these issues, we present the "Río Hortega University Hospital Glioblastoma Dataset (RHUH-GBM)," a collection of multiparametric MRI images, volumetric assessments, molecular data, and survival details for glioblastoma patients who underwent total or near-total enhancing tumor resection. The dataset features expert-corrected segmentations of tumor subregions, offering valuable ground truth data for developing algorithms for postoperative and follow-up MRI scans. The public release of the RHUH-GBM dataset significantly contributes to glioblastoma research, enabling the scientific community to study recurrence patterns and develop new diagnostic and prognostic models. This may result in more personalized, effective treatments and ultimately improved patient outcomes.
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