Presentation + Paper
15 February 2021 A framework of metal object insertion in the projection domain for interventional CT image quality optimization
Author Affiliations +
Abstract
Numerous advances in CT imaging have led to improved image guidance for interventional oncology procedures. However, image artifacts stemming from metal devices used during procedures have remained a persistent problem. Severe artifacts introduced by metallic treatment devices significantly degrade image quality in anatomical regions of interest and can substantially reduce the confidence of the interventional radiologist in accurate probe placement. The purpose of this work is to develop a framework to accurately simulate the presence of metal objects in CT images, which could be used for image quality assessment and development of artifact mitigation strategies. The projection domain insertion framework was developed based on an existing lesion insertion tool. New noise and beam hardening models were developed and incorporated into the insertion algorithm to better replicate the artifactual signal produced by the metal objects. These models were validated by comparing images of real and artificially inserted metallic rods with known material composition and dimensions in head and body CT phantoms. The validated model was applied to a single cryoablation probe, which was imaged with routine clinical acquisition parameters and reconstructed with three different sets of reconstruction settings to evaluate their effects on probe segmentation and eventual insertion performance. To determine the optimal digital probe model derived from CT images, the segmented probes were inserted into the projection data from a water phantom and compared to the corresponding water images with the real probe. Additional phantom studies were conducted with two probes positioned such that they were coplanar with the imaging plane, to fully evaluate the severity of the simulated metal artifacts. Finally, a comprehensive library of metallic probes used in our clinical practice during cryoablation and microwave ablation procedures was generated, and an intuitive graphical user interface was built to facilitate efficient insertion of any number of different probes at arbitrary positions in patient CT data. Results from the metallic rod experiments demonstrated that quantum noise, electronic noise, and beam hardening were properly modeled. Further, digital probe models derived from probe images from high resolution reconstructions with an extended HU scale yielded simulated image artifacts consistent with presentation of real artifacts; whereas, using probe models derived from segmentations of clinical reconstructions or high resolution reconstruction without the extended HU scale did not. Extension of the insertion model to two coplanar probes demonstrated production of realistic artifacts with similar magnitude and texture to real probes. Lastly, the model was successfully applied to patient data and generated convincing artifacts as compared to patient images with real probes.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Liqiang Ren, Andrea Ferrero, and Christopher Favazza "A framework of metal object insertion in the projection domain for interventional CT image quality optimization", Proc. SPIE 11598, Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling, 115981F (15 February 2021); https://doi.org/10.1117/12.2582305
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CITATIONS
Cited by 1 patent.
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KEYWORDS
Image segmentation

Computed tomography

Data modeling

Metals

Data acquisition

Image quality

Image resolution

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