Effectuality study of a 3D motion correction algorithm in C-arm CTs of severely impaired image quality during transarterial chemoembolization

• Published in: Cancer imaging 2022-07, Vol.22 (1), p.1-37, Article 37
• Main Authors: Becker, Lena S, Dewald, Cornelia L. A, von Falck, Christian, Werncke, Thomas, Maschke, Sabine K, Kloeckner, Roman, Wacker, Frank K, Meyer, Bernhard C, Hinrichs, Jan B
• Format: Article
• Language: English
• Subjects: Algorithms; C-Arm CT; Catheters; Chemoembolization; Comparative analysis; Datasets; Image acquisition; Image quality; Image segmentation; Interventional Radiology; Liver; Medical imaging; Motion correction algorithm; Patients; Sensors; Software; Statistical analysis; Three dimensional motion; Transarterial chemoembolization; Veins & arteries; Visualization; Work stations
• ISSN: 1470-7330; 1740-5025; 1470-7330
• DOI: 10.1186/s40644-022-00473-3

Background To evaluate effectivity of a 3D-motion correction algorithm in C-Arm CTs (CACT) with limited image quality (IQ) during transarterial chemoembolization (TACE). Methods From 1/2015-5/2021, 644 CACTs were performed in patients during TACE. Of these, 27 CACTs in 26 patients (18 m, 8f; 69.7 years [+ or -] 10.7 SD) of limited IQ were included. Post-processing of the original raw-data sets (CACT.sub.Org) included application of a 3D-motion correction algorithm and bone segmentation (CACT.sub.MC_no_bone). Four radiologists (R1-4) compared the images by choosing their preferred dataset and recommending repeat acquisition in case of severe IQ-impairment. R1,2 performed additional grading of intrahepatic vessel visualization, presence/extent of movement artifacts, and overall IQ. Results R1,2 demonstrated excellent interobserver agreement for overall IQ (ICC 0.79,p < 0.01) and the five-point vessel visualization scale before and after post-processing of the datasets (ICC 0.78,p < 0.01). Post-processing caused significant improvement, with overall IQ improving from 2.63 (CACT.sub.Org) to 1.39 (CACT.sub.MC_no_bone;p < 0.01) and a decrease in the mean distance of identifiable, subcapsular vessels to the liver capsule by 4 mm (p < 0.01). This proved especially true for datasets with low parenchymal and high hepatic artery contrast. A good interobserver agreement (ICC = 0.73) was recorded concerning the presence of motion artifacts, with significantly less discernible motion after post-processing (CACT.sub.Org:1.31 [+ or -] 1.67, CACT.sub.MC_no_bone:1.00 [+ or -] 1.34, p < 0.01). Of the 27 datasets, [greater than or equal to] 23 CACT.sub.MC_no_bone were preferred, with identical datasets chosen by the readers to show benefit from the algorithm. Conclusion Application of a 3D-motion correction algorithm significantly improved IQ in diagnostically limited CACTs during TACE, with the potential to decrease repeat acquisitions. Keywords: C-Arm CT, Transarterial chemoembolization, Motion correction algorithm, Interventional Radiology