Comprehensive Morphometric Analysis to Identify Key Neuroimaging Biomarkers for the Diagnosis of Adult Hydrocephalus Using Artificial Intelligence
This study highlights the importance of a multifaceted diagnostic approach incorporating 5 easily measurable 1-D neuroimaging biomarkers for neurosurgeons to differentiate non-normal pressure hydrocephalus from healthy subjects. Incorporating our artificial intelligence model, interpreted through SHAP analysis, into routine clinical workflows may transform the diagnostic landscape for hydrocephalus by standardizing diagnosis and overcoming the limitations of visual evaluations, particularly in early stages and challenging cases.
Authors
- Michelangelo Pagan
- Sonja Chen (ORCID: https://orcid.org/0000-0001-6174-8723)
- Jacob Rosen
- Seifollah Gholampour (ORCID: https://orcid.org/0000-0002-4924-4239)
- Ibrahim Gomaa (ORCID: https://orcid.org/0000-0003-1221-1318)
- Mark Graham Waterstraat
- Arshia Dehghan
Institutions
- University of Illinois Chicago (US)
- University of Chicago (US)
- Neurological Surgery (US)
Publication Details
- Journal
- Neurosurgery
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1227/neu.0000000000003248
- Citations
- 2
- Primary Topic
- Cerebrospinal fluid and hydrocephalus
- Type
- article
- Field-Weighted Citation Impact
- 0.54