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Purpose <p>Linear two-dimensional indices such as the Evans index, callosal angle, and fronto-occipital horn ratio remain the clinical standard for hydrocephalus assessment, yet are limited by measurement variability, insensitivity to spatial CSF redistribution, and reduced sensitivity to volumetric change over time. This narrative review aims to summarize established two-dimensional indices, their structural limitations, and describe how automated segmentation and radiomic feature extraction enable three-dimensional assessment across four clinical domains.</p> Methods <p>A narrative literature review was conducted using PubMed. Studies addressing hydrocephalus imaging biomarkers, ventricular volumetry, automated segmentation, radiomics, and machine learning applications were reviewed. Reference lists of relevant articles were hand-searched for additional sources. The literature was synthesized across four clinical domains: pediatric hydrocephalus monitoring, differential diagnosis of ventriculomegaly, preoperative prediction of response to cerebrospinal fluid diversion, and longitudinal post-treatment follow-up.</p> Results <p>Across pediatric hydrocephalus monitoring, differential diagnosis of ventriculomegaly, preoperative prediction of response to CSF diversion, and post-shunt longitudinal follow-up, three-dimensional volumetric and radiomic approaches consistently outperform linear indices. Machine learning models report AUCs exceeding 0.9 for differential diagnosis and shunt response prediction. Automated segmentation has reached excellent performance for detection tasks, and volumetry is more sensitive to postoperative change than the Evans index.</p> Conclusions <p>Despite strong metric performance, clinical translation remains limited by small single-centre datasets, missing external validation, and undefined thresholds for clinically meaningful volumetric change. Embedding validated tools into radiological workflows and clinical guidelines will be essential before three-dimensional biomarkers can improve routine hydrocephalus care.</p>

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Moving on in hydrocephalus imaging: from 2D to 3D biomarkers

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月21日

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  • Raffaele Da Mutten,
  • Rafael Turczynski Holmgren,
  • Erik Edström,
  • Adrian Elmi-Terander,
  • Victor Egon Staartjes

摘要

Purpose

Linear two-dimensional indices such as the Evans index, callosal angle, and fronto-occipital horn ratio remain the clinical standard for hydrocephalus assessment, yet are limited by measurement variability, insensitivity to spatial CSF redistribution, and reduced sensitivity to volumetric change over time. This narrative review aims to summarize established two-dimensional indices, their structural limitations, and describe how automated segmentation and radiomic feature extraction enable three-dimensional assessment across four clinical domains.

Methods

A narrative literature review was conducted using PubMed. Studies addressing hydrocephalus imaging biomarkers, ventricular volumetry, automated segmentation, radiomics, and machine learning applications were reviewed. Reference lists of relevant articles were hand-searched for additional sources. The literature was synthesized across four clinical domains: pediatric hydrocephalus monitoring, differential diagnosis of ventriculomegaly, preoperative prediction of response to cerebrospinal fluid diversion, and longitudinal post-treatment follow-up.

Results

Across pediatric hydrocephalus monitoring, differential diagnosis of ventriculomegaly, preoperative prediction of response to CSF diversion, and post-shunt longitudinal follow-up, three-dimensional volumetric and radiomic approaches consistently outperform linear indices. Machine learning models report AUCs exceeding 0.9 for differential diagnosis and shunt response prediction. Automated segmentation has reached excellent performance for detection tasks, and volumetry is more sensitive to postoperative change than the Evans index.

Conclusions

Despite strong metric performance, clinical translation remains limited by small single-centre datasets, missing external validation, and undefined thresholds for clinically meaningful volumetric change. Embedding validated tools into radiological workflows and clinical guidelines will be essential before three-dimensional biomarkers can improve routine hydrocephalus care.