Erica Manduzzi B S Grand Valley State University

Erica Manduzzi, B. S. Grand Valley State University manduzze@mail. gvsu. edu Dosimetric Impact of Radiotherapy Plans with the Use of a Metal Artifact Reduction Algorithm Applied during CT Simulation Results Introduction Methods to overcome metal artifacts in computed tomography (CT) have been researched and developed for nearly 40 years. When x-rays pass through metal, physical effects are created that hinder the diagnostic quality of the image. Specifically for radiotherapy treatment plans, these physical effects (metal artifacts) in the CT images have the ability to lead to dose distribution calculation errors, potentially affecting patient treatment outcome. Multiple methods and algorithms have been proposed and developed to eliminate metal artifacts by correcting the underlying image data and improving image quality. Conclusion Figure 1. Axial slice of a sample patient containing metallic hardware with the Smart MAR applied (left) and without any MAR correction (right). The GE Healthcare Smart MAR algorithm uses an automated, three-stage projection based process to improve CT image data. The purpose of this study is to assess the dosimetric impact that the GE Healthcare Smart MAR algorithm has on radiotherapy plans when applied during CT simulation. Methods • External beam radiation therapy (EBRT) plans of fifteen (n=15) patients containing metallic hardware in their treatment area were retrospectively analyzed. • 9 (60%) Head and neck plans • 4 (27%) Pelvis plans • 2 (13%) Spine plans • Additionally, 80% RT plans utilized VMAT and 20% utilized 3 DCRT. • Two additional treatment plans (without any form of correction and with manual correction) were also constructed for each patient. • Plan settings (Isocenter placement, MUs, normalization, and plan geometry) were equivalent for each of the three plans within each patient. • Dosimetric impact was assessed by analyzing multiple metrics between the three plans per patient including: • PTV maximum dose, PTV minimum dose, PTV mean dose, conformity index, and gradient measure Figure 2. Plan evaluation assessing isodose distribution with respected DVH of a sample patient with metallic hardware. Plan evaluation displays a plan with the GE Healthcare Smart MAR applied (left top and bottom) and one without any form of MAR correction (right top and bottom) with their respective isodose lines. DVH includes dose to volume comparisons of the left parotid gland (brown), spinal cord (blue), oral cavity (magenta), and PTV (red), for a 3 DCRT plan with MAR applied (square) and without MAR applied (diamond). Variable Test Statistic (F) p value Max PTV Dose 1. 226 0. 309 Min PTV Dose 0. 239 0. 687 Mean PTV Dose 1. 054 0. 343 Conformity Index 0. 864 0. 433 Gradient Measure 0. 090 0. 914 Table 1. Multiple, independent repeated ANOVA tests were performed. The significance level was set at 0. 05. The Smart MAR algorithm did not have a significant dosimetric impact on any of the five variables when applied to the radiotherapy plans (GE MAR correction vs. no correction vs. manual correction). The results of this study indicate that the GE Healthcare Smart MAR algorithm does not have a significant impact on dose to the PTV, nor on the conformity index or gradient measure value compared to plans without a form of MAR applied or with manual correction. Although the algorithm did not have a significant impact to these five measured values, visual change was seen in a few patients between plans with MAR applied and plans without, therefore, change is still possible in overall isodose distribution throughout the patient, as indicated in Figure 2. Although a statistically significant dosimetric impact was not found between the three plans constructed for each patient, previous studies have shown that the GE Healthcare Smart MAR algorithm accurately reduces metal artifact, improves CT accuracy, and decreases image noise; therefore, this product can be implemented within the clinic to increase confidence in contouring near metal artifact, as well as reduce time required to manually correct HU values. References Bedos, L. , Aillères, N. , Azria, D. , & Fenoglietto, P. (2014). CT Number Accuracy Assessment of a New Metal Artifact Reduction Algorithm for CT Simulations in Radiation Therapy. International Journal of Radiation Oncology • Biology • Physics, 90(1), S 865 -S 866. Boas, F. , & Fleischmann, D. (2012). CT artifacts: Causes and reduction techniques. London: Future Medicine Ltd. Huang, J. Y. , Followill, D. S. , Howell, R. M. , Liu, X. , Mirkovic, D. , Stingo, F. C. , & Kry, S. F. (2016). Approaches to reducing photon dose calculation errors near metal implants. Medical Physics, 43(9), 5117 -5130. Karimi, S. , Cosman, P. , Wald, C. , & Martz, H. (2012). Segmentation of artifacts and anatomy in CT metal artifact reduction. Medical physics, 39(10), 5857 -5868. Kataoka, M. , Hochman, M. , Rodriguez, E. , Lin, P. , Kubo, S. , & Raptopolous, V. (2010). A review of factors that affect artifact from metallic hardware on multi-row detector computed tomography. Current Problems in Diagnostic Radiology, 39(4), 125 -136. Rechner, L. , Kovacs, D. , Bangsgaard, A. , Berthelsen, A. , & Aznar, M. (2016). PO-0915: Evaluation of a metal artifact reduction algorithm for radiotherapy CT scans. Radiotherapy and Oncology, 119, S 442 -S 443. Reft, C. , Alecu, R. , Das, I. , Gerbi, B. , Keall, P. , Lief, E. , . . AAPM Radiation Therapy Committee Task Group 63. (2003). Dosimetric considerations for patients with HIP prostheses undergoing pelvic irradiation. report of the AAPM radiation therapy committee task group 63. Medical Physics, 30(6), 1162 -1182. Yazdia, M. , Gingras, L. , & Beaulieu, L. (2005). An adaptive approach to metal artifact reduction in helical computed tomography for radiation therapy treatment planning: experimental and clinical studies. International Journal of Radiation Oncology* Biology* Physics, 62(4), 1224 -1231. Acknowledgements Scott Green & Kristen Vu, Research Advisors Maggie Kurp-Dilan, Ina Sala, & Ahpa Plypoo, Clinical Preceptors GVSU Statistical Consulting Center Dr. B. Sango Otieno, Associate Professor