Characterization and validation of the thorax phantom Lungman for dose assessment in chest radiography optimization studies

Abstract. This work concerns the validation of the Kyoto-Kagaku thorax anthropomorphic phantom Lungman for use in chest radiography optimization. The equivalence in terms of polymethyl methacrylate (PMMA) was established for the lung and mediastinum regions of the phantom. Patient chest examination data acquired under automatic exposure control were collated over a 2-year period for a standard x-ray room. Parameters surveyed included exposure index, air kerma area product, and exposure time, which were compared with Lungman values. Finally, a voxel model was developed by segmenting computed tomography images of the phantom and implemented in PENELOPE/penEasy Monte Carlo code to compare phantom tissue-equivalent materials with materials from ICRP Publication 89 in terms of organ dose. PMMA equivalence varied depending on tube voltage, from 9.5 to 10.0 cm and from 13.5 to 13.7 cm, for the lungs and mediastinum regions, respectively. For the survey, close agreement was found between the phantom and the patients’ median values (deviations lay between 8% and 14%). Differences in lung doses, an important organ for optimization in chest radiography, were below 13% when comparing the use of phantom tissue-equivalent materials versus ICRP materials. The study confirms the value of the Lungman for chest optimization studies.

[1]  Ehsan Samei,et al.  Chest radiography: optimization of X-ray spectrum for cesium iodide-amorphous silicon flat-panel detector. , 2003, Radiology.

[2]  Icru.,et al.  Phantoms and Computational Models in Therapy, Diagnosis and Protection , 1992 .

[3]  Anders Tingberg,et al.  Method of simulating dose reduction for digital radiographic systems. , 2005, Radiation protection dosimetry.

[4]  Walter Heindel,et al.  Experimental evaluation of a portable indirect flat-panel detector for the pediatric chest: comparison with storage phosphor radiography at different exposures by using a chest phantom. , 2005, Radiology.

[5]  J. Sempau,et al.  PENELOPE-2006: A Code System for Monte Carlo Simulation of Electron and Photon Transport , 2009 .

[6]  Karl Ludwig,et al.  Low-voltage digital selenium radiography: detection of simulated interstitial lung disease, nodules, and catheters--a phantom study. , 2004, Radiology.

[7]  Michael Sandborg,et al.  A Monte Carlo-based model for simulation of digital chest tomosynthesis. , 2010, Radiation protection dosimetry.

[8]  C E Ravin,et al.  Digital chest radiography with photostimulable storage phosphors: signal-to-noise ratio as a function of kilovoltage with matched exposure risk. , 1993, Radiology.

[9]  J Yorkston,et al.  Optimal kvp selection for dual-energy imaging of the chest: evaluation by task-specific observer preference tests. , 2007, Medical physics.

[10]  David E. Hintenlang,et al.  Physical Phantoms for Experimental Radiation Dosimetry , 2009 .

[11]  Kazuki Takeda,et al.  Evaluation of the effects of subject thickness on the exposure index in digital radiography , 2015, Radiological Physics and Technology.

[12]  J. Sempau,et al.  A PENELOPE-based system for the automated Monte Carlo simulation of clinacs and voxelized geometries-application to far-from-axis fields. , 2011, Medical physics.

[13]  Walter J. Riker A Review of J , 2010 .

[14]  A. Bardy,et al.  [On reference values]. , 2008, Duodecim; laaketieteellinen aikakauskirja.

[15]  E. Pedroni,et al.  The calibration of CT Hounsfield units for radiotherapy treatment planning. , 1996, Physics in medicine and biology.

[16]  Hilde Bosmans,et al.  Experimental investigation on the choice of the tungsten/rhodium anode/filter combination for an amorphous selenium-based digital mammography system , 2006, European Radiology.

[17]  Ehsan Samei,et al.  Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE. , 2014, Medical physics.

[18]  C S Moore,et al.  Correlation of the clinical and physical image quality in chest radiography for average adults with a computed radiography imaging system. , 2013, The British journal of radiology.

[19]  Ernst J Rummeny,et al.  EVALUATION OF DOSE REDUCTION POTENTIALS OF A NOVEL SCATTER CORRECTION SOFTWARE FOR BEDSIDE CHEST X-RAY IMAGING. , 2016, Radiation protection dosimetry.

[20]  Patrick C Brennan,et al.  Digital radiography exposure indices: A review , 2014, Journal of medical radiation sciences.

[21]  Michael Sandborg,et al.  Towards optimization in digital chest radiography using Monte Carlo modelling , 2006, Physics in medicine and biology.

[22]  D R Pina,et al.  Optimization of standard patient radiographic images for chest, skull and pelvis exams in conventional x-ray equipment. , 2004, Physics in medicine and biology.

[23]  C J Martin,et al.  Dose-image quality optimisation in digital chest radiography. , 2005, Radiation protection dosimetry.

[24]  T. R. Fewell,et al.  Beam quality independent attenuation phantom for estimating patient exposure from x-ray automatic exposure controlled chest examinations. , 1984, Medical physics.

[25]  Ehsan Samei,et al.  An exposure indicator for digital radiography: AAPM Task Group 116 (executive summary). , 2009, Medical physics.

[26]  D. Dance,et al.  Design and application of a structured phantom for detection performance comparison between breast tomosynthesis and digital mammography , 2017, Physics in medicine and biology.

[27]  Andrew Tootell,et al.  Anthropomorphic chest phantom imaging – The potential for dose creep in computed radiography , 2013 .

[28]  Milan Sonka,et al.  3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.

[29]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[30]  J Vassileva,et al.  A phantom for dose-image quality optimization in chest radiography. , 2002, The British journal of radiology.

[31]  Michael Sandborg,et al.  Comparison of clinical and physical measures of image quality in chest and pelvis computed radiography at different tube voltages. , 2006, Medical physics.

[32]  C E Ravin,et al.  Threshold perception performance with computed and screen-film radiography: implications for chest radiography. , 1992, Radiology.

[33]  J. Boone,et al.  An accurate method for computer-generating tungsten anode x-ray spectra from 30 to 140 kV. , 1997, Medical physics.