Monte Carlo modeling for dose assessment in cone beam CT for oral and maxillofacial applications. Issue 7 (18th June 2013)

• Record Type: Journal Article
• Authors: Zhang, G.; Marshall, N.; Bogaerts, R.; Jacobs, R.; Bosmans, H.
• Is Part Of: Medical physics. Volume 40:Issue 7(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-06-18
• Subjects: Dose‐volume analysis -- Monte Carlo methods -- Computed tomography -- Algebraic structures and number theory -- Geometry, differential geometry, and topology; biological organs -- computerised tomography -- dosimetry -- geometry -- Monte Carlo methods -- phantoms -- polynomials; cone beam CT -- oral imaging -- Monte Carlo -- dose calculation -- anatomical phantoms; Computerised tomographs; Dosimetry -- Anatomy -- Cone beam computed tomography -- Medical imaging -- Monte Carlo methods -- Tissues -- Computed tomography -- Calibration -- Photons -- Ionization chambers; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4810967
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : To adjust Monte Carlo modeling for dose assessment in dedicated cone beam computed tomography (CBCT) of the oral and maxillofacial region. Methods: : Two different CBCT systems with different fields of view (FOVs), beam qualities, and scan geometries were modeled using Monte Carlo simulation. Dose calculations for typical CBCT examinations were performed with the head and neck part of four computational anatomical phantoms. Results: : Simulation results compared favorably to values acquired experimentally using physical phantoms (in the literature). For a given phantom scanned with 90 kV and 60 × 60 mm FOV, effective dose per mAs was on average the same for the two different systems. Exposing the four phantoms under identical settings for the same CBCT system resulted in variations in organ doses of greater than 100%, leading to differences in effective dose of 30%. For one system, the dose dependence on the operating tube potential can be described with a quadratic polynomial function. Dose distributions over the axial plane were presented as contour plots. Conclusions: : Monte Carlo modeling is an efficient and accurate means of evaluating dose distributions for dedicated cone beam oral and maxillofacial CT. Results suggest large dose differences among patients undergoing the same examination on a given system, supporting approaches toward patient specific dosimetry. A dedicated and standardized computational phantom for head and neck dosimetry should be established.