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Evaluation of Different Registration Algorithms to Reduce Motion Artifacts in CT-Thermography (CTT)

Authors :
Bogdan Kostyrko
Kerstin Rubarth
Christian Althoff
Miriam Zibell
Christina Ann Neizert
Franz Poch
Giovanni Federico Torsello
Bernhard Gebauer
Kai Lehmann
Stefan Markus Niehues
Jürgen Mews
Torsten Diekhoff
Julian Pohlan
Source :
Diagnostics, Vol 13, Iss 12, p 2076 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Computed tomography (CT)-based Thermography (CTT) is currently being investigated as a non-invasive temperature monitoring method during ablation procedures. Since multiple CT scans with defined time intervals were acquired during this procedure, interscan motion artifacts can occur between the images, so registration is required. The aim of this study was to investigate different registration algorithms and their combinations for minimizing inter-scan motion artifacts during thermal ablation. Four CTT datasets were acquired using microwave ablation (MWA) of normal liver tissue performed in an in vivo porcine model. During each ablation, spectral CT volume scans were sequentially acquired. Based on initial reconstructions, rigid or elastic registration, or a combination of these, were carried out and rated by 15 radiologists. Friedman’s test was used to compare rating results in reader assessments and revealed significant differences for the ablation probe movement rating only (p = 0.006; range, 5.3–6.6 points). Regarding this parameter, readers assessed rigid registration as inferior to other registrations. Quantitative analysis of ablation probe movement yielded a significantly decreased distance for combined registration as compared with unregistered data. In this study, registration was found to have the greatest influence on ablation probe movement, with connected registration being superior to only one registration process.

Details

Language :
English
ISSN :
20754418
Volume :
13
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.6aebbaf98f8747e18a56fbe0ba231ee7
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics13122076