HyKid: An Open MRI Dataset with Expert-Annotated Multi-Structure and Choroid Plexus in Pediatric Hydrocephalus

Evaluation of hydrocephalus in children is challenging, and the related research is limited by a lack of publicly available, expert-annotated datasets, particularly those with segmentation of the choroid plexus. To address this, we present HyKid, an open-source dataset from 48 pediatric patients with hydrocephalus. 3D MRIs were provided with 1mm isotropic resolution, which was reconstructed from routine low-resolution images using a slice-to-volume algorithm. Manually corrected segmentations of brain tissues, including white matter, grey matter, lateral ventricle, external CSF, and the choroid plexus, were provided by an experienced neurologist. Additionally, structured data was extracted from clinical radiology reports using a Retrieval-Augmented Generation framework. The strong correlation between choroid plexus volume and total CSF volume provided a potential biomarker for hydrocephalus evaluation, achieving excellent performance in a predictive model (AUC=0.87). The proposed HyKid dataset provided a high-quality benchmark for neuroimaging algorithms development, and it revealed the choroid plexus related features in hydrocephalus assessments.<br>Our datasets are publicly available at <a href='https://www.synapse.org/Synapse:syn68544889'>https://www.synapse.org/Synapse:syn68544889</a> and <a href='https://github.com/yunzxu/HyKid'>https://github.com/yunzxu/HyKid</a>

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Publication Details

Journal
The Journal of Machine Learning for Biomedical Imaging
Published
2025-12-31
DOI
https://doi.org/10.59275/j.melba.2025-f184
Primary Topic
Cerebrospinal fluid and hydrocephalus
Type
article
Field-Weighted Citation Impact
0.00

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article

HyKid: An Open MRI Dataset with Expert-Annotated Multi-Structure and Choroid Plexus in Pediatric Hydrocephalus

Yushuang Ding, Yunzhi Xu, Li Zhao, Hongxi Zhang et al.
The Journal of Machine Learning for Biomedical Imaging
Cerebrospinal fluid and hydrocephalus
article

HyKid: An Open MRI Dataset with Expert-Annotated Multi-Structure and Choroid Plexus in Pediatric Hydrocephalus

Yushuang Ding, Yunzhi Xu, Li Zhao, Hongxi Zhang, Hu Sun
article en

Abstract

Evaluation of hydrocephalus in children is challenging, and the related research is limited by a lack of publicly available, expert-annotated datasets, particularly those with segmentation of the choroid plexus. To address this, we present HyKid, an open-source dataset from 48 pediatric patients with hydrocephalus. 3D MRIs were provided with 1mm isotropic resolution, which was reconstructed from routine low-resolution images using a slice-to-volume algorithm. Manually corrected segmentations of brain tissues, including white matter, grey matter, lateral ventricle, external CSF, and the choroid plexus, were provided by an experienced neurologist. Additionally, structured data was extracted from clinical radiology reports using a Retrieval-Augmented Generation framework. The strong correlation between choroid plexus volume and total CSF volume provided a potential biomarker for hydrocephalus evaluation, achieving excellent performance in a predictive model (AUC=0.87). The proposed HyKid dataset provided a high-quality benchmark for neuroimaging algorithms development, and it revealed the choroid plexus related features in hydrocephalus assessments.<br>Our datasets are publicly available at <a href='https://www.synapse.org/Synapse:syn68544889'>https://www.synapse.org/Synapse:syn68544889</a> and <a href='https://github.com/yunzxu/HyKid'>https://github.com/yunzxu/HyKid</a>

The Journal of Machine Learning for Biomedical ImagingVol. 3(MICCAI Open Data 2024-2025)
Children's Hospital of Zhejiang University (CN), Zhejiang Hospital (CN), Zhejiang University (CN)
Ministry of Education, India, Zhejiang University
Openalex Percentile: Top 35%
Cerebrospinal fluid and hydrocephalus
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