Optimal CT scanning parameters for commonly used tumor ablation applicators

Eltorai, Adam E.M.; Baird, Grayson L.; Monu, Nicholas; Wolf, Farrah J.; Seidler, Michael; Collins, Scott; Kim, Jeom-Soon; Dupuy, Damian E.

doi:10.1016/j.ejrad.2017.01.005

Cited by 1 publication

(2 citation statements)

References 18 publications

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“…In the second study, the results of the first study could be confirmed with the overall interaction of the different acquisition and image reconstruction parameters [33]. In both studies, the rationale for choosing the provided CT parameters was operator experience with the intention to optimize image quality and reduce metal artifacts.…”

Section: Discussionmentioning

confidence: 82%

“…To the best of our knowledge, there are no instances in the literature regarding artifact reduction for other CT-guided thermal ablation procedures such as RFA or cryoablation (CRYO). Two studies have addressed the optimal CT technique for different and commonly used tumor ablation applicators [32,33]. In the first study, 11 different MWA, RFA and CRYO applicators were positioned in bovine livers, followed by CT scans with fixed tube current (440 mAs) but different tube potentials (80-140 kV p ), different scan times (0.5-2.0 s), different pitch factors (0.5-1.75) and different acquisition types (spiral or incremental) [32].…”

Section: Discussionmentioning

confidence: 99%

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The value of iterative metal artifact reduction algorithms during antenna positioning for CT-guided microwave ablation

Duong

Melzig

Vollherbst

et al. 2019

International Journal of Hyperthermia

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Objectives: To compare image quality between filtered back projection (FBP) and iterative reconstruction algorithm and dedicated metal artifact reduction (iMAR) algorithms during antenna positioning for computed tomography-guided microwave ablation (MWA). Materials and methods: An MWA antenna was positioned in the liver of five pigs under CT guidance. Different exposure settings (120kV p /200mAs-120kV p /50mAs) and image reconstruction techniques (FBP, iterative reconstruction with and without iMAR) were applied. Quantitative image analysis included density measurements in six positions (e.g., liver in extension of the antenna [ANTENNA] and liver >3 cm away from the antenna [LIVER-1]). Qualitative image analysis included assessment of overall quality, image noise, artifacts at the antenna tip, artifacts in liver parenchyma bordering antenna tip and newly generated artifacts. Two independent observers performed the analyses twice and interreader agreement was compared with Bland-Altman analysis. Results: For all exposure and reconstruction settings, density measurements for ANTENNA were significantly higher for the I30-1 iMAR compared with FBP and I30-1 (e.g., 8.3À17.2HU vs. À104.5 to 155.1HU; p 0.01, respectively). In contrast, for all exposure settings, density measurements for LIVER-1 were comparable between FBP and I30-1 iMAR (e.g., 49.4À50.4HU vs. 50.1À52.5U, respectively). For all exposure and reconstruction settings, subjective image quality for LIVER-1 was better for the I30-1 iMAR algorithm compared with FBP and I30-1. Bland-Altman interobserver agreement was from À0.2 to 0.2 for FBP and iMAR, and Cohen's kappa was 0.74. Conclusion: Iterative algorithms I30-1 with iMAR algorithm improves image quality during antenna positioning and placement for CT-guided MWA and is applicable over a range of exposure settings.

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Section: Discussionmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%