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Computed Tomography

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...

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Related Experiment Video

Updated: May 28, 2025

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

A Retrospective Analysis of the First Clinical 5DCT Workflow.

Michael Lauria¹, Minji Kim¹, Dylan O'Connell¹

¹Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.

|February 13, 2025

Summary

Five-dimensional computed tomography (5DCT) improves radiotherapy planning by creating motion-compensated images. Quality assurance reports show DIR quality is key to 5DCT success, encouraging workflow improvements.

Keywords:

4DCT image-guided radiotherapy lung radiotherapy model-based CT motion management

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Area of Science:

Radiotherapy Physics
Medical Imaging
Computational Anatomy

Background:

Five-dimensional computed tomography (5DCT) was developed to address artifacts in four-dimensional computed tomography (4DCT) caused by irregular patient breathing during radiotherapy planning.
Clinical implementation of 5DCT since March 2019 allows for motion-compensated CT simulation, enhancing treatment planning accuracy.

Purpose of the Study:

To evaluate the challenges and quality of a clinical 5DCT workflow using quality assurance (QA) reports.
To assess the impact of breathing patterns, image quality, and deformable image registration (DIR) on the suitability for treatment planning (STP) of 5DCT datasets.

Main Methods:

Analysis of 169 thoracic 5DCT datasets acquired between March 2019 and December 2022.
Utilized motion models from fast-helical free-breathing CT scans with respiratory bellows monitoring to generate 5DCT phase images.
QA reports assessed breathing pattern, image quality, DIR quality, and model fitting, with a validation process determining the STP grade.

Main Results:

The STP grade showed moderate correlations with breathing irregularity (Spearman's ρ=0.26), image quality (ρ=0.30), and DIR quality (ρ=0.50).
Regular breathing patterns, superior image quality, and better DIR quality were significantly correlated with higher STP grades (p < 0.001).
5DCT datasets were used for treatment planning in 82% of cases, with 6% deemed unusable due to factors unrelated to 5DCT quality.

Conclusions:

Deformable image registration (DIR) quality demonstrated the strongest association with STP, indicating that improving DIR accuracy is crucial for enhancing 5DCT.
The high utilization rate of 5DCT phase images confirms the workflow's reliability and supports continued development.