Treatment planning dose accuracy improvement in the presence of dental implants

Holly M. Parenica, John R. Ford, Panayiotis Mavroidis, Ying Li, Nikos Papanikolaou, Sotirios Stathakis

Research output: Contribution to journalArticle

Abstract

Streaking artifacts in computed tomography (CT) scans caused by metallic dental implants (MDIs) can lead to inaccuracies in dose calculations. This study quantifies and compares the effect of MDIs on dose distributions using the collapsed cone convolution superposition (CCCS) and Monte Carlo (MC) algorithms, with and without correcting for the density of the MDIs. Ion chamber measurements were taken to test the ability of the algorithms in Pinnacle3 and Monaco to calculate dose near high-Z materials. Nine previously treated patients with head and neck cancer were included in this study. The MDI and the streaking artifacts on the CT images were carefully contoured. For each patient, a plan was optimized and calculated using the Pinnacle3 treatment planning system (TPS). Two dose calculations were performed for each patient: one with overridden densities of the MDI and CT artifacts and one without overridden densities of the MDI and CT artifacts. The plans were then exported to the Monaco TPS and recalculated for the same number of monitor units (MUs) using its MC dose calculation algorithm. The changes in dose to the planning target volume (PTV) and surrounding healthy tissues were examined between all the plans using VelocityAI. For the ion chamber measurements, when correct density information was used, Monaco was within 3% of the measured values, whereas the doses calculated in Pinnacle3 varied up to 7%. The CCCS algorithm in Pinnacle3 calculated only a significant decrease in PTV coverage for 1 patient when the densities were overridden. The MC algorithm in Monaco was able to calculate a significant change in PTV coverage for five of the patients when the density was overridden. Additionally, when healthy tissues affected by streaking artifacts were assigned the correct density, cumulative (from all the fractions) point doses increased up to 46.2 Gy. Not properly accounting for MDIs can impact both the high-dose regions (PTVs) and surrounding healthy tissues. This study demonstrates that if MDIs and the artifacts are not appropriately accounted for by contouring and assigning to them the correct density, there is a potential risk of compromising the quality of the plan regarding PTV coverage and dose to healthy tissues.

Original languageEnglish (US)
JournalMedical Dosimetry
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Dental Implants
Monaco
Artifacts
Tomography
Therapeutics
Ions
Head and Neck Neoplasms

Keywords

  • Collapsed cone convolution superposition
  • Dose calculation algorithms
  • Metal implants
  • Monte Carlo

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Oncology
  • Radiology Nuclear Medicine and imaging

Cite this

Treatment planning dose accuracy improvement in the presence of dental implants. / Parenica, Holly M.; Ford, John R.; Mavroidis, Panayiotis; Li, Ying; Papanikolaou, Nikos; Stathakis, Sotirios.

In: Medical Dosimetry, 01.01.2018.

Research output: Contribution to journalArticle

Parenica, Holly M. ; Ford, John R. ; Mavroidis, Panayiotis ; Li, Ying ; Papanikolaou, Nikos ; Stathakis, Sotirios. / Treatment planning dose accuracy improvement in the presence of dental implants. In: Medical Dosimetry. 2018.
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abstract = "Streaking artifacts in computed tomography (CT) scans caused by metallic dental implants (MDIs) can lead to inaccuracies in dose calculations. This study quantifies and compares the effect of MDIs on dose distributions using the collapsed cone convolution superposition (CCCS) and Monte Carlo (MC) algorithms, with and without correcting for the density of the MDIs. Ion chamber measurements were taken to test the ability of the algorithms in Pinnacle3 and Monaco to calculate dose near high-Z materials. Nine previously treated patients with head and neck cancer were included in this study. The MDI and the streaking artifacts on the CT images were carefully contoured. For each patient, a plan was optimized and calculated using the Pinnacle3 treatment planning system (TPS). Two dose calculations were performed for each patient: one with overridden densities of the MDI and CT artifacts and one without overridden densities of the MDI and CT artifacts. The plans were then exported to the Monaco TPS and recalculated for the same number of monitor units (MUs) using its MC dose calculation algorithm. The changes in dose to the planning target volume (PTV) and surrounding healthy tissues were examined between all the plans using VelocityAI. For the ion chamber measurements, when correct density information was used, Monaco was within 3{\%} of the measured values, whereas the doses calculated in Pinnacle3 varied up to 7{\%}. The CCCS algorithm in Pinnacle3 calculated only a significant decrease in PTV coverage for 1 patient when the densities were overridden. The MC algorithm in Monaco was able to calculate a significant change in PTV coverage for five of the patients when the density was overridden. Additionally, when healthy tissues affected by streaking artifacts were assigned the correct density, cumulative (from all the fractions) point doses increased up to 46.2 Gy. Not properly accounting for MDIs can impact both the high-dose regions (PTVs) and surrounding healthy tissues. This study demonstrates that if MDIs and the artifacts are not appropriately accounted for by contouring and assigning to them the correct density, there is a potential risk of compromising the quality of the plan regarding PTV coverage and dose to healthy tissues.",
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