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Related Concept Videos

Assessment of Ventilation I: Respiratory Rate

Assessment of Ventilation I: Respiratory Rate

Assessment of Ventilation
A Ventilation assessment is critical for monitoring a patient's health status. Respiration, one of the most accessible vital signs, provides insights into the function of numerous body systems and can indicate serious health issues, such as brainstem injuries from head trauma.
Critical Guidelines for Assessing Ventilation:

Assessment of Ventilation II: Respiratory Depth and Rhythm

Assessment of Ventilation II: Respiratory Depth and Rhythm

Respiratory Depth
Respiratory depth measures the volume of air inhaled or exhaled during a breath. It can vary from shallow to deep and typically remains consistent when a person is at rest or asleep. Occasionally, individuals will automatically inhale deeply, known as sighing, which inflates the lungs with more air than normal breathing.
To assess respiratory depth, observe the degree of chest excursion or movement:

Margin of Error

Margin of Error

The margin of error is also called the maximum error of an estimate. The margin of error is the maximum possible or expected difference between the observed sample parameter value and the actual population parameter value. For proportion, it is the maximum difference between the value of sample proportion obtained from the data and the true value of population proportion. As the true value of the population parameter is not known, the margin of error is calculated using the sample statistic.

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Related Experiment Video

Updated: Apr 14, 2026

Evaluation of Respiratory System Mechanics in Mice using the Forced Oscillation Technique

Evaluation of Respiratory System Mechanics in Mice using the Forced Oscillation Technique

Published on: May 15, 2013

Prediction error and required internal margin provided for irregular respiratory movements: a phantom study.

Nobuyoshi Fukumitsu¹, Haruko Numajiri, Kayoko Ohnishi

¹Proton Medical Research Center, University of Tsukuba, 1-1-1, Tennoudai, Tsukuba, 305-8575, Japan, fukumitsun@yahoo.co.jp.

Japanese Journal of Radiology

|April 17, 2015

Summary

Irregular breathing movements, especially complex amplitude variations, increase prediction errors and require larger internal margins in 4D CT imaging. This impacts treatment planning accuracy for radiation therapy.

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Related Experiment Videos

Last Updated: Apr 14, 2026

Evaluation of Respiratory System Mechanics in Mice using the Forced Oscillation Technique

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Published on: May 15, 2013

Combining Volumetric Capnography And Barometric Plethysmography To Measure The Lung Structure-function Relationship

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Published on: January 8, 2019

Employing the Forced Oscillation Technique for the Assessment of Respiratory Mechanics in Adults

Employing the Forced Oscillation Technique for the Assessment of Respiratory Mechanics in Adults

Published on: February 9, 2022

Area of Science:

Medical Imaging
Radiation Oncology
Respiratory Motion Management

Background:

Accurate tumor targeting in radiation therapy requires precise compensation for respiratory motion.
Irregular breathing patterns pose challenges for real-time motion tracking and prediction systems.

Purpose of the Study:

To quantify prediction errors associated with irregular respiratory movements.
To determine the internal margin needed to account for these movements in four-dimensional CT (4DCT).

Main Methods:

Simulated irregular respiratory movements (cycle and amplitude variations) using a moving phantom.
Acquired images with a real-time position management (RPM) and 4DCT system.
Calculated target displacement and required margins for irregular motion compensation.

Main Results:

Amplitude irregularity led to reduced image reproducibility and necessitated larger margins compared to cycle irregularity.
More complex amplitude irregularities resulted in significant displacement and increased margin requirements.
Cycle irregularity also impacted stable placement and required margins.

Conclusions:

Real-time position management (RPM) and 4DCT systems are susceptible to prediction errors.
Complicated amplitude irregularity in respiratory motion is a key factor contributing to these prediction errors.
Findings highlight the need for advanced motion management strategies to address complex breathing patterns.