Utility of Cone-Beam CT for Bronchial Artery Embolization and Chemoinfusion: A Single-Institution Retrospective Case Series

Enhancing procedural decision making with cone beam CT in renal artery embolization

Cone-beam computed tomography (CBCT) has proven to be a safe and effective adjunctive imaging tool for interventional radiology. Nevertheless, limited studies have examined the application of CBCT in renal artery embolization (RAE). The objective of this study is to evaluate the role of CBCT in intra-procedural decision-making for RAE. This multicenter retrospective study included 40 consecutive patients (age: 55.9 ± 16.5 years; male, 55%) who underwent CBCT during RAE from January 2019 to January 2023. The additional information provided by CBCT was classified into Category 1 (no additional information), Category 2 (more information without changing the treatment plan), and Category 3 (valuable information that led to a change in the treatment plan). CBCT did not add unique information for four patients (10%) classified as Category 1. CBCT clarified ambiguous angiographic findings and confirmed the existing treatment plan for 19 patients (47.5%) graded as Category 2; complex vascular anatomy was explained (n = 13), and a correlation between vascular territory and target lesion was established (n = 6). CBCT offered valuable information that was not visible on digital subtraction angiography and changed the treatment plan for 17 patients categorized as Category 3; a mismatch between the vascular territory and the target lesion led to the identification of alternative (n = 3) and additional feeders (n = 8); and the extent of embolization was reduced by using automatic feeder detection software (n = 6). CBCT is an efficient tool that aids in the decision-making process during the embolization procedure by providing supplementary imaging information. This additional information enables the confident identification of target vessels, facilitates superselective embolization, prevents non-target embolization, and helps locate missing feeders.

Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT

OBJECTIVES

In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a trade-off exists between 6-second runs (high radiation dose and motion artifacts, but low noise) and 3-second runs (vice versa). This study aimed to determine the efficacy of an advanced deep learning denoising (DLD) technique in mitigating the trade-offs related to radiation dose and image quality during interventional BAE CBCT.

MATERIALS AND METHODS

This study included BMI-matched patients undergoing 6-second and 3-second BAE CBCT scans. The dose-area product values (DAP) were obtained. All datasets were reconstructed using standard weighted filtered back projection (OR) and a novel DLD software. Objective image metrics were derived from place-consistent regions of interest, including CT numbers of the Aorta and lung, noise, and contrast-to-noise ratio. Three blinded radiologists performed subjective assessments regarding image quality, sharpness, contrast, and motion artifacts on all dataset combinations in a forced-choice setup (-1 = inferior, 0 = equal; 1 = superior). The points were averaged per item for a total score. Statistical analysis ensued using a properly corrected mixed-effects model with post hoc pairwise comparisons.

RESULTS

Sixty patients were assessed in 30 matched pairs (age 64 ± 15 years; 10 female). The mean DAP for the 6 s and 3 s runs was 2199 ± 185 µGym² and 1227 ± 90 µGym², respectively. Neither low-dose imaging nor the reconstruction method introduced a significant HU shift (p ≥ 0.127). The 3 s-DLD presented the least noise and superior contrast-to-noise ratio (CNR) (p < 0.001). While subjective evaluation revealed no noticeable distinction between 6 s-DLD and 3 s-DLD in terms of quality (p ≥ 0.996), both outperformed the OR variants (p < 0.001). The 3 s datasets exhibited fewer motion artifacts than the 6 s datasets (p < 0.001).

CONCLUSIONS

DLD effectively mitigates the trade-off between radiation dose, image noise, and motion artifact burden in regular reconstructed BAE CBCT by enabling diagnostic scans with low radiation exposure and inherently low motion artifact burden at short examination times.

Perspectives of Cone-beam Computed Tomography in Interventional Radiology: Techniques for Planning, Guidance, and Monitoring

Cone-beam computed tomography (CBCT) has emerged as a prominent imaging modality in interventional radiology that offers real-time visualization and precise guidance in various procedures. This article aims to provide an overview of the techniques used to guide and monitor interventions that use CBCT. It discusses the advantages of CBCT, its current applications, and potential future CBCT-related developments in the field of interventional radiology.