Comprehensive Morphometric Analysis to Identify Key Neuroimaging Biomarkers for the Diagnosis of Adult Hydrocephalus Using Artificial Intelligence

Neurosurgery 96:1386–1396, 2025

This study used AI and SHAP analysis to identify five key, easily measurable 1-D neuroimaging biomarkers—FTHR, MEI, MCMI, SMLH, and CPCA—for accurately diagnosing adult non-normal pressure hydrocephalus, offering a practical, standardized, and interpretable approach to improve early detection and clinical decision-making.

• Hydrocephalus diagnosis is often inconsistent due to reliance on clinical and qualitative radiological assessments.

• This study used artificial intelligence (AI) and SHAP analysis to identify key, easily measurable neuroimaging biomarkers for adult non-normal pressure hydrocephalus (non-NPH).

• A comprehensive set of 21 morphometric features was analyzed from MRI images of 42 adult non-NPH patients and 40 healthy controls.

• Gradient Boosting was the best-performing AI classifier, achieving 0.94 accuracy and 0.97 AUC.

• Ventricular volume is the most important biomarker, but measurement is complex for clinicians.

• Five key 1-D biomarkers identified are: frontal-temporal horn ratio (FTHR), modified Evans index (MEI), modified cella media index (MCMI), sagittal maximum lateral ventricle height (SMLH), and coronal posterior callosal angle (CPCA).

• These five markers are easily measurable and provide high diagnostic accuracy, supporting practical clinical use.

• The approach addresses multicollinearity and improves diagnostic standardization, but further validation with larger datasets is needed.