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Updated: Jun 26, 2026

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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Screening for Normal Pressure Hydrocephalus on Head CT Using Automated Callosal Angle Assessment.

Sennett Yang1, Jazza Jamil2, Diep Nguyen3

  • 1School of Medicine, Creighton University, Phoenix Campus, Phoenix, AZ 85004, USA.

Tomography (Ann Arbor, Mich.)
|June 25, 2026
PubMed
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This summary is machine-generated.

Automated callosal angle measurement on head CT reliably detects normal pressure hydrocephalus (NPH). This tool aids in early diagnosis and treatment of NPH, a reversible cause of dementia and gait issues in older adults.

Area of Science:

  • Neurology
  • Radiology
  • Medical Imaging

Background:

  • Normal pressure hydrocephalus (NPH) is an underdiagnosed condition in older adults, causing gait impairment and fall risk.
  • The callosal angle is a known imaging biomarker for NPH, but its application on routine head CT needs validation.
  • Early diagnosis of NPH is crucial for timely intervention and management.

Purpose of the Study:

  • To validate an automated measurement of the callosal angle on routine head CT scans for NPH detection.
  • To compare automated measurements with manual assessments performed by radiologists.
  • To evaluate the diagnostic performance of the automated callosal angle measurement as a screening tool for NPH.

Main Methods:

  • Retrospective analysis of 198 patients with probable NPH and 198 matched controls.
Keywords:
automated image analysiscallosal anglecomputed tomographydementia screeningnormal pressure hydrocephalus

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  • Manual callosal angle measurements by residents and neuroradiologists.
  • Comparison of automated and manual measurements using intraclass correlation (ICC) and diagnostic accuracy metrics.

    • Main Results:

    • Automated callosal angle measurements showed strong agreement with manual measurements (ICC = 0.90).
    • An automated threshold of <90° yielded 84.1% accuracy, 90.4% sensitivity, and 77.8% specificity.
    • An optimized threshold of 95° achieved 85.9% accuracy, sensitivity, and specificity, with an AUC of 0.915.

    Conclusions:

    • Automated callosal angle assessment on routine head CT is a reliable and scalable method for NPH detection.
    • This automated tool can facilitate earlier diagnosis and treatment of NPH, a reversible cause of dementia.
    • The validated automated measurement supports its use as a screening tool for NPH.