A component method to delineate surgical spine implants for proton Monte Carlo dose calculation

• Type of Material: Article
• Authors: Chih-Wei Chang, Emory University; Serdar Charyyev, Emory University; Joseph Harms, University of Alabama Birmingham; Roelf Slopsema, Emory University; Jonathan Wolf, Emory University; Daniel Refai, Emory University; Tim Yoon, Emory University; Mark McDonald, Emory University; Jeffrey Bradley, Emory University; Shuai Leng, Mayo Clinic; Jun Zhou, Emory University; Xiaofeng Yang, Emory University; Liyong Lin, Emory University
• Language: English
• Date: 2022-10-09
• Publisher: WILEY
• Publication Version: Final Published Version
• Copyright Statement: © 2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1002/acm2.13800
• Title of Journal or Parent Work: JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS
• Volume: 24
• Issue: 1
• Start Page: e13800
• End Page: e13800
• Keywords: METAL ARTIFACT REDUCTION; Science & Technology; OUTCOMES; CHONDROSARCOMAS; Life Sciences & Biomedicine; RADIATION-THERAPY; CT HOUNSFIELD UNITS; OPTIMIZATION; proton therapy; surgical implant delineation; Monte Carlo dose calculation; Radiology, Nuclear Medicine & Medical Imaging; RADIOTHERAPY; CALIBRATION; CHORDOMAS; MANAGEMENT
• Research Categories: Health Sciences, Oncology

Abstract

Purpose: Metallic implants have been correlated to local control failure for spinal sarcoma and chordoma patients due to the uncertainty of implant delineation from computed tomography (CT). Such uncertainty can compromise the proton Monte Carlo dose calculation (MCDC) accuracy. A component method is proposed to determine the dimension and volume of the implants from CT images. Methods: The proposed component method leverages the knowledge of surgical implants from medical supply vendors to predefine accurate contours for each implant component, including tulips, screw bodies, lockers, and rods. A retrospective patient study was conducted to demonstrate the feasibility of the method. The reference implant materials and samples were collected from patient medical records and vendors, Medtronic and NuVasive. Additional CT images with extensive features, such as extended Hounsfield units and various reconstruction diameters, were used to quantify the uncertainty of implant contours. Results: For in vivo patient implant estimation, the reference and the component method differences were 0.35, 0.17, and 0.04 cm3 for tulips, screw bodies, and rods, respectively. The discrepancies by a conventional threshold method were 5.46, 0.76, and 0.05 cm3, respectively. The mischaracterization of implant materials and dimensions can underdose the clinical target volume coverage by 20 cm3 for a patient with eight lumbar implants. The tulip dominates the dosimetry uncertainty as it can be made from titanium or cobalt–chromium alloys by different vendors. Conclusions: A component method was developed and demonstrated using phantom and patient studies with implants. The proposed method provides more accurate implant characterization for proton MCDC and can potentially enhance the treatment quality for proton therapy. The current proof-of-concept study is limited to the implant characterization for lumbar spine. Future investigations could be extended to cervical spine and dental implants for head-and-neck patients where tight margins are required to spare organs at risk.