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Quantitative Analysis

Quantitative Analysis

Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...

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Related Experiment Video

Updated: Nov 26, 2025

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

Pediatric Head CT: Automated Quantitative Analysis with Quantile Regression.

K A Cauley¹, Y Hu², S W Fielden³

¹From the Departments of Radiology (K.A.C.) keithcauley@hotmail.com.

AJNR. American Journal of Neuroradiology

|December 11, 2020

Summary

This summary is machine-generated.

This study developed an automated method using head CT scans to model brain development in children and adolescents. The findings provide a quantitative reference for comparing individual brain metrics to age- and sex-matched peers.

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Area of Science:

Radiology
Medical Imaging
Pediatric Imaging

Background:

Age-related changes in pediatric and adolescent brain development are complex.
Quantitative analysis of brain development using clinical head CT data is crucial for clinical utility.
Automated processing of medical imaging data can aid in developing such models.

Purpose of the Study:

To demonstrate automated processing of digital clinical head CT data.
To develop a clinically useful model of age-related brain changes in the first two decades of life.
To enable quantitative comparison of individual cases to age- and sex-matched peer groups.

Main Methods:

Retrospective selection of 415 pediatric head CT scans (birth to 20 years) with normal findings.
Automated image segmentation to assess brain volume, parenchymal fraction, radiodensity, and radiomass.
Statistical modeling and quantile regression to analyze age- and sex-related brain metrics.

Main Results:

Brain volume increased over threefold from birth to 20 years, with males showing a slightly steeper trajectory.
Brain parenchymal fraction stabilized between 2-3 years, while brain radiodensity increased and then stabilized by age 3.
Brain radiomass showed a 5.6-fold increase, with minor sex differences at 20 years.

Conclusions:

Automated segmentation of head CT images enables the creation of a reference database for pediatric and adolescent brain quantitative analysis.
Quantile regression provides a method for interpreting individual brain metrics relative to normative data.
This approach facilitates clinical application for assessing brain development in children and adolescents.