A perfusion phantom for dynamic micro-CT imaging

This study presents the development, implementation, and testing of a 3D printed phantom with two compartments designed for dynamic micro-CT imaging using low molecular weight contrast agents. The phantom was evaluated through both optical and micro-CT imaging to assess its ability to generate and repeat various time attenuation curves (TACs). The optical tests demonstrated the phantom’s capability to produce a wide variety of time contrast curves by adjusting valve positions, while maintaining a repeatable input curve. Micro-CT tests confirmed the generation of diverse time attenuation curves, although repeatability was affected by the increased viscosity of the ISOVUE contrast agent. Using a gamma variate function to model the generated TAC shapes, the phantom was able to generate attenuation starting times ranging from ~12-25 seconds and peak times ranging from ~25-60 seconds. Having patterned our design after a fully tested clinical CT perfusion phantom, this preclinical phantom promises to be a valuable tool for validating and quantifying perfusion micro-CT measurements. This work represents one of the first adaptations and implementations of a dynamic perfusion phantom for CT at the preclinical level, providing a standardized method for quality assurance in preclinical and research settings. Future research should focus on addressing the observed inconsistencies and exploring the phantom’s potential in various preclinical applications.

Authors

Institutions

Publication Details

Published
2025-04-08
DOI
https://doi.org/10.1117/12.3047282
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A perfusion phantom for dynamic micro-CT imaging

Cristian T. Badea, Darin P. Clark, Alexandra Badea, Alex J. Allphin
Advanced MRI Techniques and Applications
article

A perfusion phantom for dynamic micro-CT imaging

Cristian T. Badea, Darin P. Clark, Alexandra Badea, Alex J. Allphin
article en

Abstract

This study presents the development, implementation, and testing of a 3D printed phantom with two compartments designed for dynamic micro-CT imaging using low molecular weight contrast agents. The phantom was evaluated through both optical and micro-CT imaging to assess its ability to generate and repeat various time attenuation curves (TACs). The optical tests demonstrated the phantom’s capability to produce a wide variety of time contrast curves by adjusting valve positions, while maintaining a repeatable input curve. Micro-CT tests confirmed the generation of diverse time attenuation curves, although repeatability was affected by the increased viscosity of the ISOVUE contrast agent. Using a gamma variate function to model the generated TAC shapes, the phantom was able to generate attenuation starting times ranging from ~12-25 seconds and peak times ranging from ~25-60 seconds. Having patterned our design after a fully tested clinical CT perfusion phantom, this preclinical phantom promises to be a valuable tool for validating and quantifying perfusion micro-CT measurements. This work represents one of the first adaptations and implementations of a dynamic perfusion phantom for CT at the preclinical level, providing a standardized method for quality assurance in preclinical and research settings. Future research should focus on addressing the observed inconsistencies and exploring the phantom’s potential in various preclinical applications.

Duke University (US)
Affordable and clean energy
Openalex Percentile: Top 89%
Advanced MRI Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.