ISLES'24 - A Real-World Longitudinal Multimodal Stroke Dataset

This multi-center dataset consists of 149 acute ischemic stroke cases, representing the training set of the ISLES'24 challenge. All data are provided in NIfTI format (.nii.gz) and organized according to the BIDS standard. For each case, the following data are included: Admission imaging: non-contrast CT (NCCT), CT angiography (CTA), 4D CT perfusion (CTP) time series, and perfusion maps (Tmax, CBF, CBV, MTT). Follow-up imaging: post-treatment MRI (DWI and ADC). Clinical data: demographics, patient history, admission NIHSS, 3‑month functional outcome (mRS), etc. Annotations: binary infarct masks derived from follow-up MRI (lesion-msk.nii.gz), large vessel occlusion binary masks derived from CTA (lvo-msk.nii.gz), and the multi-labeled Circle of Willis anatomy generated with an automatic algorithm over CTA (cow-msk.nii.gz) This dataset combines multimodal imaging, longitudinal follow-up, and structured clinical variables to support benchmarking of stroke infarct prediction methods. Data structure 'Raw_data' refers to the 'raw' acquired scans, which are released in their original space, just defaced. 'Derivatives' include all modalities linearly co-registered to the NCCT space. Ses-0001 points to the acute imaging data, while Ses-0002 refers to the follow-up imaging data (sub-acute stroke phase). A single case-sample is structured as follows. raw_data/├── sub-strokecase0001/│ └── ses-0001/│ ├── perfusion-maps/│ │ ├── sub-strokecase0001_ses-0001_tmax.nii.gz│ │ ├── sub-strokecase0001_ses-0001_mtt.nii.gz│ │ ├── sub-strokecase0001_ses-0001_cbf.nii.gz│ │ └── sub-strokecase0001_ses-0001_cbv.nii.gz│ ├── sub-strokecase0001_ses-0001_ncct.nii.gz│ ├── sub-strokecase0001_ses-0001_cta.nii.gz│ └── sub-strokecase0001_ses-0001_ctp.nii.gz derivatives/├── sub-strokecase0001/│ ├── ses-0001/│ │ ├── perfusion-maps/│ │ │ ├── sub-strokecase0001_ses-0001_space-ncct_tmax.nii.gz│ │ │ ├── sub-strokecase0001_ses-0001_space-ncct_mtt.nii.gz│ │ │ ├── sub-strokecase0001_ses-0001_space-ncct_cbf.nii.gz│ │ │ └── sub-strokecase0001_ses-0001_space-ncct_cbv.nii.gz│ │ ├── sub-strokecase0001_ses-0001_space-ncct_cta.nii.gz│ │ ├── sub-strokecase0001_ses-0001_space-ncct_ctp.nii.gz│ │ ├── sub-stroke0086_ses-01_space-ncct_cow-msk.nii.gz│ │ └── sub-stroke0086_ses-01_space-ncct_lvo-msk.nii.gz│ └── ses-0002/│ ├── sub-strokecase0001_ses-02_space-ncct_dwi.nii.gz│ ├── sub-strokecase0001_ses-02_space-ncct_adc.nii.gz│ └── sub-strokecase0001_ses-02_space-ncct_lesion-msk.nii.gz phenotype/├── ses-0001/│ └── sub-strokecase0001_ses-0001_demographic_baseline.csv└── ses-0002/ └── sub-strokecase0001_ses-0001_outcome.csv Please cite the following two works when using this dataset: Riedel, O. E., de la Rosa, E., Hernandez Petzsche, M., Baazaoui, H., Yang, K., Musio, F. A., … & Kirschke, J. S. (2024). ISLES’24 – A Real-World Longitudinal Multimodal Stroke Dataset. arXiv e-prints, arXiv:2408.09259. de la Rosa, E., Su, R., Reyes, M., Wiest, R., Riedel, E. O., Kofler, F., … & Menze, B. (2024). ISLES’24: Final Infarct Prediction with Multimodal Imaging and Clinical Data. Where Do We Stand? arXiv preprint, arXiv:2408.10966. If you use the Circle of Willis masks, please ALSO cite: Yang, K., Musio, F., Ma, Y., Juchler, N., Paetzold, J. C., Al-Maskari, R., ... & Menze, B. (2024). Benchmarking the cow with the topcow challenge: Topology-aware anatomical segmentation of the circle of willis for cta and mra. ArXiv, arXiv-2312.本多中心数据集包含149例急性缺血性脑卒中病例，为ISLES'24挑战赛的训练集。 所有数据均以NIfTI格式（.nii.gz）提供，并按照BIDS（Brain Imaging Data Structure，脑成像数据结构）标准进行组织。每例病例包含以下数据： - 入院影像学：非增强CT（NCCT）、CT血管造影（CTA）、4D CT灌注（CTP）时间序列以及灌注参数图（Tmax、CBF、CBV、MTT）。 - 随访影像学：治疗后磁共振成像（MRI），包含扩散加权成像（DWI）与表观扩散系数成像（ADC）。 - 临床数据：人口统计学信息、患者病史、入院时美国国立卫生研究院卒中量表（NIHSS）评分、3个月功能预后（改良Rankin量表，mRS）等。 - 标注信息：基于随访MRI生成的二进制梗死掩码（lesion-msk.nii.gz）、基于CTA生成的大血管闭塞二进制掩码（lvo-msk.nii.gz），以及通过自动算法在CTA影像上生成的多标签大脑动脉环（Willis环）解剖结构掩码（cow-msk.nii.gz）。 本数据集整合了多模态影像学、纵向随访数据与结构化临床变量，可用于脑卒中梗死预测方法的基准测试。 ### 数据结构 「原始数据（Raw_data）」指采集得到的原始扫描影像，已按照原始空间发布，仅完成了去面部标识处理。「衍生数据（Derivatives）」包含所有与NCCT空间线性配准后的模态数据。Ses-0001对应急性期影像学数据，Ses-0002则对应随访影像学数据（亚急性脑卒中阶段）。单例样本的结构如下所示： raw_data/├── sub-strokecase0001/│ └── ses-0001/│ ├── perfusion-maps/│ │ ├── sub-strokecase0001_ses-0001_tmax.nii.gz│ │ ├── sub-strokecase0001_ses-0001_mtt.nii.gz│ │ ├── sub-strokecase0001_ses-0001_cbf.nii.gz│ │ └── sub-strokecase0001_ses-0001_cbv.nii.gz│ ├── sub-strokecase0001_ses-0001_ncct.nii.gz│ ├── sub-strokecase0001_ses-0001_cta.nii.gz│ └── sub-strokecase0001_ses-0001_ctp.nii.gz derivatives/├── sub-strokecase0001/│ ├── ses-0001/│ │ ├── perfusion-maps/│ │ │ ├── sub-strokecase0001_ses-0001_space-ncct_tmax.nii.gz│ │ │ ├── sub-strokecase0001_ses-0001_space-ncct_mtt.nii.gz│ │ │ ├── sub-strokecase0001_ses-0001_space-ncct_cbf.nii.gz│ │ │ └── sub-strokecase0001_ses-0001_space-ncct_cbv.nii.gz│ │ ├── sub-strokecase0001_ses-0001_space-ncct_cta.nii.gz│ │ ├── sub-strokecase0001_ses-0001_space-ncct_ctp.nii.gz│ │ ├── sub-stroke0086_ses-01_space-ncct_cow-msk.nii.gz│ │ └── sub-stroke0086_ses-01_space-ncct_lvo-msk.nii.gz│ └── ses-0002/│ ├── sub-strokecase0001_ses-02_space-ncct_dwi.nii.gz│ ├── sub-strokecase0001_ses-02_space-ncct_adc.nii.gz│ └── sub-strokecase0001_ses-02_space-ncct_lesion-msk.nii.gz phenotype/├── ses-0001/│ └── sub-strokecase0001_ses-0001_demographic_baseline.csv└── ses-0002/ └── sub-strokecase0001_ses-0001_outcome.csv 使用本数据集时，请引用以下两篇文献： Riedel, O. E., de la Rosa, E., Hernandez Petzsche, M., Baazaoui, H., Yang, K., Musio, F. A., … & Kirschke, J. S. (2024). ISLES’24 – A Real-World Longitudinal Multimodal Stroke Dataset. arXiv e-prints, arXiv:2408.09259. de la Rosa, E., Su, R., Reyes, M., Wiest, R., Riedel, E. O., Kofler, F., … & Menze, B. (2024). ISLES’24: Final Infarct Prediction with Multimodal Imaging and Clinical Data. Where Do We Stand? arXiv preprint, arXiv:2408.10966. 若使用大脑动脉环（Willis环）掩码，请额外引用： Yang, K., Musio, F., Ma, Y., Juchler, N., Paetzold, J. C., Al-Maskari, R., ... & Menze, B. (2024). Benchmarking the cow with the topcow challenge: Topology-aware anatomical segmentation of the circle of willis for cta and mra. ArXiv, arXiv-2312.