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Related Concept Videos

Increased Intracranial Pressure l: Introduction01:14

Increased Intracranial Pressure l: Introduction

Intracranial hypertension is a sustained elevation of intracranial pressure (ICP) above 22 mm Hg. In supine adults, normal ICP is ~7–15 mm Hg.The rigid, nonexpandable cranium contains three components—brain tissue, blood, and cerebrospinal fluid (CSF)—that total ~1,700 mL in a typical adult: 1,400 mL brain (~80%), 150 mL blood (~10%), and 150 mL CSF (~10%). According to the Monro–Kellie doctrine, total intracranial volume is effectively fixed. When one component expands, CSF and venous blood...
Increased Intracranial Pressure ll: Pathophysiology01:29

Increased Intracranial Pressure ll: Pathophysiology

Increased intracranial pressure (ICP) refers to a potentially life-threatening rise in pressure inside the skull. This usually happens when there is a major change in the volume of brain tissue, blood, or cerebrospinal fluid (CSF) — the three components inside the skull. According to the Monro-Kellie doctrine, if the volume of one component increases, the volumes of the other components must decrease to maintain normal pressure. If this does not happen, ICP rises.The process often begins with...
Cerebral Edema ll: Pathophysiology01:22

Cerebral Edema ll: Pathophysiology

Vasogenic edema is a major form of cerebral edema characterized by abnormal accumulation of fluid in the brain’s extracellular space due to disruption of the blood–brain barrier (BBB). The BBB is a specialized structure composed of endothelial cells connected by tight junctions, supported by astrocytic endfeet and a basement membrane. Under normal conditions, it tightly regulates the movement of ions, proteins, and solutes between the bloodstream and brain parenchyma. When this barrier loses...

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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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Redefining Idiopathic Normal Pressure Hydrocephalus Using AI-Driven Brain Volumetry.

Juan Sahuquillo1,2,3, Murad Al-Nusaif2,4, Aasma Sahuquillo-Muxi2

  • 1Department of Neurosurgery, Vall d'Hebron University Hospital (VHUH), Vall d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035 Barcelona, Spain.

Biomedicines
|March 28, 2026
PubMed
Summary
This summary is machine-generated.

Idiopathic normal pressure hydrocephalus (iNPH) diagnosis is improved by artificial intelligence-based brain volumetry (AI-BrV). AI-BrV offers precise 3D quantification, overcoming limitations of traditional methods for better patient stratification and treatment decisions.

Keywords:
MRI volumetryartificial intelligencebrain atrophyidiopathic normal pressure hydrocephalusneurodegenerationventriculomegaly

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Area of Science:

  • Neuroimaging
  • Artificial Intelligence
  • Neurology

Background:

  • Idiopathic normal pressure hydrocephalus (iNPH) presents diagnostic challenges, often mimicking cerebral atrophy or neurodegenerative diseases.
  • Distinguishing iNPH from other conditions is complex due to a continuum of ventricular enlargement and mixed pathologies.
  • Conventional neuroradiological markers have limitations including subjectivity and poor predictive value.

Purpose of the Study:

  • To introduce artificial intelligence-based brain volumetry (AI-BrV) as a novel quantitative approach for iNPH assessment.
  • To highlight AI-BrV's potential to overcome limitations of traditional 2D imaging markers.
  • To explore AI-BrV's utility in improving differential diagnosis and predicting outcomes in iNPH.

Main Methods:

  • AI-BrV enables automated, precise, and reproducible 3D quantification of brain structures, including CSF spaces and brain matter volumes.
  • AI-BrV facilitates the derivation of composite indices and ratios for disease phenotyping.
  • Pipelines allow retrospective analysis of large datasets and integration with clinical and machine-learning frameworks.

Main Results:

  • AI-BrV addresses limitations of traditional methods like the Evans Index and DESH pattern.
  • Quantitative structural assessment via AI-BrV offers improved precision and reproducibility.
  • AI-BrV facilitates normative modeling and validation of volumetric biomarkers.

Conclusions:

  • AI-BrV represents a paradigm shift in the quantitative structural assessment of iNPH.
  • This technology promises enhanced patient selection, refined disease categorization, and informed treatment decisions for iNPH.
  • AI-BrV offers a framework for a more precise, reproducible, and evidence-based approach to iNPH diagnosis and management.