Fast dual-energy micro-CT with reliable detection of iodine in thin vessels

X-ray micro-computed tomography (μCT) is a widely used imaging modality in preclinical research, with a range of specific applications. Minimising the dose both from x-rays and of administered contrast agents such as iodine is desirable for the improvement of research and subject outcomes. Here, we introduce a new data processing scheme that enables accurate localisation and quantification of iodine concentrations resulting from fast, low dose μCT scans. The technique makes use of characteristic shape detection to selectively decompose dual-energy x-ray μCT data in iodine-containing regions only, thus removing any background iodine signal in the decomposed basis. We demonstrate the technique's effectiveness using scan data acquired over 3.6 s and a dose to water of 8.7 mGy where the weakest concentration of iodine successfully isolated was 21 mgI ml<sup>-1</sup>in a 500 μm diameter vessel, and note that this scan speed could be further improved with a detector with a faster framerate. The technique is extended to complex vessel shapes in three dimensions and remains robust. It is expected to be useful in the context of small animal imaging as the low dose requirements increase the repeatability of scans per subject.

Authors

Institutions

Publication Details

Journal
Biomedical Physics & Engineering Express
Published
2025-05-27
DOI
https://doi.org/10.1088/2057-1976/addd26
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fast dual-energy micro-CT with reliable detection of iodine in thin vessels

Charlotte K. Hagen, Alberto Astolfo, Ian Buchanan, David Bate et al.
Biomedical Physics & Engineering Express
Advanced X-ray and CT Imaging
article

Fast dual-energy micro-CT with reliable detection of iodine in thin vessels

Charlotte K. Hagen, Alberto Astolfo, Ian Buchanan, David Bate, G. Lioliou, Michela Esposito, Marco Endrizzi, Alessandro Olivo, Tom Partridge
article en

Abstract

X-ray micro-computed tomography (μCT) is a widely used imaging modality in preclinical research, with a range of specific applications. Minimising the dose both from x-rays and of administered contrast agents such as iodine is desirable for the improvement of research and subject outcomes. Here, we introduce a new data processing scheme that enables accurate localisation and quantification of iodine concentrations resulting from fast, low dose μCT scans. The technique makes use of characteristic shape detection to selectively decompose dual-energy x-ray μCT data in iodine-containing regions only, thus removing any background iodine signal in the decomposed basis. We demonstrate the technique's effectiveness using scan data acquired over 3.6 s and a dose to water of 8.7 mGy where the weakest concentration of iodine successfully isolated was 21 mgI ml<sup>-1</sup>in a 500 μm diameter vessel, and note that this scan speed could be further improved with a detector with a faster framerate. The technique is extended to complex vessel shapes in three dimensions and remains robust. It is expected to be useful in the context of small animal imaging as the low dose requirements increase the repeatability of scans per subject.

Biomedical Physics & Engineering ExpressVol. 11(4)
Transport Research Laboratory (United Kingdom) (GB), University College London (GB)
EPSRC Centre for Doctoral Training in Medical Imaging
Affordable and clean energy
Openalex Percentile: Top 89%
Advanced X-ray and CT Imaging
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.