Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Increased Intracranial Pressure l: Introduction

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Predictors of hospital length of stay, discharge disposition, and readmission after craniopharyngioma surgery: a multicenter study from the RAPID database.

Neurosurgical focus·2026

Same author

Frailty and postoperative outcomes following craniopharyngioma resection: a multicenter Registry for Adenomas of the Pituitary and Related Disorders analysis.

Neurosurgical focus·2026

Same author

Risk factors for postoperative cerebrospinal fluid leak following endoscopic transsphenoidal surgery for craniopharyngioma: a multicenter cohort study with a contemporary surgeon practice survey.

Journal of neuro-oncology·2026

Same author

Benchmarking Surgical Outcomes for Endoscopic Transnasal Craniopharyngioma Resection: Implications for Clinical Practice From the RAPID Consortium.

Operative neurosurgery (Hagerstown, Md.)·2026

Same author

Acute Toxicity From Short-Course Radiation Therapy for Rectal Cancer: A Single-Institution Experience.

Advances in radiation oncology·2026

Same author

Adamantinomatous craniopharyngioma: outcomes from a US multicenter registry cohort (RAPID consortium study).

Journal of neurosurgery·2026

Same journal

Enhancing Volumetric Imaging in Linear-Array Photoacoustic Tomography: multiview fusion with deep learning.

IEEE transactions on bio-medical engineering·2026

Same journal

Robust Rule-based Heuristic Assistance Strategy for a Semi-Active Shoulder Exoskeleton Used in Overhead Work.

IEEE transactions on bio-medical engineering·2026

Same journal

Highly Accelerated 1-mm Isotropic 3D Chemical Exchange Saturation Transfer MRI Using Wave-Co-CAIPI at 5 Tesla.

IEEE transactions on bio-medical engineering·2026

Same journal

Systematic Evaluation of Hip Exoskeleton Assistance Parameters for Enhancing Gait Stability During Ground Slip Perturbations.

IEEE transactions on bio-medical engineering·2026

Same journal

SleepConFormer: A Single-Channel EEG Framework for Sleep Staging and Consciousness Assessment in Patients with Disorders of Consciousness.

IEEE transactions on bio-medical engineering·2026

Same journal

Modeling Partial and Total Support of Left Ventricular Assist Device for Discrete Hemodynamic Control Framework.

IEEE transactions on bio-medical engineering·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 6, 2026

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Noninvasive intracranial pressure assessment based on a data-mining approach using a nonlinear mapping function.

Sunghan Kim¹, Fabien Scalzo, Marvin Bergsneider

¹Department of Neurosurgery, David Geffen School of Medicine at University of California, Los Angeles, CA 90095-7065, USA. visionsk@gmail.com

IEEE Transactions on Bio-Medical Engineering

|November 25, 2010

Summary

This summary is machine-generated.

This study enhances noninvasive intracranial pressure (ICP) assessment using a novel data-mining framework. Kernel spectral regression, a nonlinear mapping function, significantly improved accuracy compared to linear methods for noninvasive ICP monitoring.

More Related Videos

A Bedside, Single Burr Hole Approach to Multimodality Monitoring in Severe Brain Injury

A Bedside, Single Burr Hole Approach to Multimodality Monitoring in Severe Brain Injury

Published on: March 26, 2019

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Published on: December 10, 2014

Related Experiment Videos

Last Updated: Jun 6, 2026

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

A Bedside, Single Burr Hole Approach to Multimodality Monitoring in Severe Brain Injury

A Bedside, Single Burr Hole Approach to Multimodality Monitoring in Severe Brain Injury

Published on: March 26, 2019

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Published on: December 10, 2014

Area of Science:

Biomedical Engineering
Medical Informatics
Neuroscience

Background:

Intracranial pressure (ICP) monitoring is crucial for managing neurological conditions.
Current ICP measurement methods are invasive, carrying risks like hemorrhage and infection.
Developing noninvasive ICP (NICP) assessment is a significant clinical need.

Purpose of the Study:

To improve the performance of a previously proposed data-mining framework for noninvasive ICP assessment.
To evaluate the efficacy of various linear and nonlinear mapping functions for NICP.
To identify the optimal mapping function for enhanced NICP accuracy.

Main Methods:

Utilized a data-mining framework for noninvasive ICP (NICP) assessment.
Implemented and compared multiple linear and nonlinear mapping functions.
Focused on kernel spectral regression as a nonlinear mapping technique.
Evaluated framework performance based on NICP accuracy.

Main Results:

Nonlinear mapping functions generally outperformed linear ones.
Kernel spectral regression demonstrated a significant performance improvement for NICP assessment.
The proposed data-mining framework with kernel spectral regression achieved superior NICP accuracy.

Conclusions:

Kernel spectral regression is a highly effective nonlinear mapping function for data-mining-based NICP assessment.
This approach offers a promising noninvasive alternative to traditional ICP monitoring.
Further research can refine this method for clinical application.