Development of A Ct Metal Artifact Management Algorithm For Proton Therapy Planning (Ampp) For Head and Neck Cancer Patients

<p><strong>Purpose</strong>: Dental amalgams (high Z materials) are common sources of artifacts in Head and Neck (HN) images. Commercial artifact reduction techniques have been offered, but many are impractical, produce inaccurate CT images or are not clinically available, thus not widely implemented. The goal of this work is to use CT gantry tilts to develop and evaluate a stereoscopic HN metal artifact management algorithm and investigate its improvement in proton treatment planning.</p> <p><strong>Methods:</strong> The in-house CT metal artifact management method for proton planning (AMPP) uses two angled CT scans to generate a single image set with no metal artifacts posterior to the dental metal implants. The algorithm was evaluated (geometrical distortion and HU accuracy) using a geometrical phantom simulating a HN patient with dental fillings. A HN anthropomorphic phantom composed of proton tissue equivalent materials, human skull, air cavities was used to perform a quantitative image quality comparison between AMPP and four major CT vendors’ commercial metal artifact reduction (MAR) solutions (OMAR from Philips, iMAR from Siemens, SEMAR from Canon, SmartMAR from GE), along with their implications on proton dose distributions.</p> <p><strong>Results:</strong> The in-house algorithm designed produced geometrically and HU accurate images free of metal artifacts posterior to the oral cavity. AMPP outperformed all vendors’ solutions in terms of image quality, showing lower HU differences and fewer bad pixels (4.2% compared to 25.5-65.5%). Dose distributions were negatively impacted by the presence of metal artifacts; the vendor solutions provided varying, but suboptimal, mitigation of this effect. Our in-house algorithm (AMPP) outperformed the vendor’s solutions on all treatment plans and showed the most comparable DVHs to the baseline (no metal).</p> <p><strong>Conclusion:</strong> A novel in-house algorithm was designed that produces geometrically and HU accurate images free of CT metal artifacts posterior to the HN region. Commercial MAR algorithms were ineffective at reducing artifacts in a HN geometrical and anthropomorphic phantom scenario. Correspondingly, they were not successful at mitigating the impact of artifacts on proton dose distributions. Our in-house algorithm outperformed all four commercial vendor solutions in both imaging and dose distributions, and is ready to be implemented on patients.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation (PhD)

Year dc:date.available

2020

Authors dc:creator

• Branco, Daniela
• <p><a href="https://www.orcid.org/0000-0002-1194-2234" target="_blank" title="https://www.orcid.org/0000-0002-1194-2234 ">0000-0002-1194-2234</a></p>

Contributors dc:contributor

• David Followill
• Stephen Kry
• Paige Taylor

• CT
• Tilted angle
• Algorithm
• metal artifact reduction
• MAR
• image quality
• treatment planning
• proton dosimetry
• dose calculation
• stereoscopic
• Diagnosis
• Medicine and Health Sciences
• Oncology
• Other Analytical, Diagnostic and Therapeutic Techniques and Equipment
• Radiology

Repository record dc:identifier

https://digitalcommons.library.tmc.edu/utgsbs_dissertations/1017

OAI identifier oai:identifier

oai:digitalcommons.library.tmc.edu:utgsbs_dissertations-2066