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Quantifying Image Quality in Diagnostic Radiology Using Simulation of the Imaging System and Model Observers

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Quantifying Image Quality in Diagnostic Radiology Using Simulation of the Imaging System and Model Observers Linköping University Medical Dissertations No. 1050 Quantifying image quality in diagnostic radiology using simulation of the imaging system and model observers Gustaf Ullman Radiation Physics, Department of Medicine and Health Faculty of Health Sciences Linköping University, Sweden Linköping 2008 ©Gustaf Ullman, 2008 Cover picture/illustration: An oil painting by Gustaf Ullman representing a chest radiograph Published articles and figures have been reprinted with the permission of the copyright holder. Printed in Sweden by LiU‐Tryck, Linköping, Sweden, 2008 ISBN 978‐91‐7393‐952‐2 ISSN 0345‐0082 ii Don’t worry about saving these songs! And if one of our instruments breaks, it doesn’t matter We have fallen into the place where everything is Music. The strumming and the flute notes rise into the atmosphere, and even if the whole world’s harp should burn up, there would still be hidden instruments playing. So the candle flickers and goes out. We have a piece of flint and a spark. This singing art is sea foam. The graceful movements come from a pearl somewhere on the ocean floor. Poems reach up like spindrift and the edge of driftwood along the beach, wanting! They derive from a slow and powerful root that we can’t see Stop the words now. Open the window in the center of your chest, and let the spirits fly in and out. Jalal al‐Din Rumi iii iv CONTENTS 1. INTRODUCTION................................................................................................ 1 1.1. Radiation protection in diagnostic radiology..................................... 1 1.2. Optimisation of diagnostic radiology .................................................. 2 1.3. Optimisation using a Monte Carlo based computational model ... 2 2. OBJECTIVE ........................................................................................................... 5 3. MONTE CARLO BASED COMPUTATIONAL MODEL OF THE IMAGING SYSTEM................................................................................................... 7 3.1. Introduction............................................................................................... 7 3.2. Computational model of the x‐ray imaging systems ........................ 9 3.2.1. Model of the imaging system........................................................... 9 3.2.2. Monte Carlo simulation of photon transport............................... 14 3.2.3. Scoring quantities............................................................................. 18 3.2.4. Calculated quantities....................................................................... 19 3.3. Calculation of images from the high‐resolution phantom ............ 20 3.4. Uncertainties............................................................................................ 22 3.4.1. Stochastic uncertainties ................................................................... 22 3.4.2. Systematic uncertainties.................................................................. 22 4. ASSESSMENT OF IMAGE QUALITY .......................................................... 25 4.1. Introduction............................................................................................. 25 4.2. Image quality assessment as developed in this work..................... 26 4.2.1. The task.............................................................................................. 26 4.2.2. Model of the imaging system and patient.................................... 27 4.2.3. Observers........................................................................................... 29 4.2.4. Figures of merit ................................................................................ 30 5. RESULTS AND DISCUSSION ....................................................................... 41 5.1. Ideal observer with a simplified patient‐model .............................. 41 v Contents 5.2. Low resolution voxel phantom ............................................................ 43 5.3. High resolution voxel phantom........................................................... 44 5.4. Ideal observer with simple anatomical background....................... 46 5.5. Correlation to human observers .......................................................... 49 5.6. Model observers with complex anatomical background ............... 52 6. SUMMARY AND CONCLUSIONS............................................................... 59 7. FUTURE WORK ................................................................................................. 61 8. ACKNOWLEDGEMENTS ............................................................................... 63 9. REFERENCES...................................................................................................... 65 vi Abstract ABSTRACT Accurate measures of both clinical image quality and patient radiation risk are needed for successful optimisation of medical imaging with ionising radiation. Optimisation in diagnostic radiology means finding the image acquisition technique that maximises the perceived information content and minimises the radiation risk or keeps it at a reasonably low level. The assessment of image quality depends on the diagnostic task and may in addition to system and quantum noise also be hampered by overlying projected anatomy. The main objective of this thesis is to develop methods for assessment of image quality in simulations of projection radiography. In this thesis, image quality is quantified by modelling the whole x‐ray imaging system including the x‐ray tube, patient, anti‐scatter device, image detector and the observer. This is accomplished by using Monte Carlo (MC) simulation methods that allow simultaneous estimates of measures of image quality and patient dose. Measures of image quality include the signal‐to‐noise‐ratio, SNR, of pathologic lesions and radiation risk is estimated by using organ doses to calculate the effective dose. Based on high‐resolution anthropomorphic phantoms, synthetic radiographs were calculated and used for assessing image quality with model‐observers (Laguerre‐Gauss (LG) Hotelling observer) that mimic real, human observers. Breast and particularly chest imaging were selected as study cases as these are particularly challenging for the radiologists. In chest imaging the optimal tube voltage in detecting lung lesions was investigated in terms of their SNR and the contrast of the lesions relative to the ribs. It was found that the choice of tube voltage depends on whether SNR of the lesion or the interfering projected anatomy (i.e. the ribs) is most important for detection. The Laguerre‐Gauss (LG) Hotelling observer is influenced by the projected anatomical background and includes this into its figure‐of‐merit, SNRhot,LG. The LG‐observer was found to be a better model of the radiologist than the ideal observer that only includes the quantum noise in its analysis. The measures of image quality derived from our model are found to correlate relatively well with the radiologist’s assessment of image quality. Therefore MC simulations can be a valuable and an efficient tool in the search for dose‐ efficient imaging systems and image acquisition schemes. vii List of papers LIST OF PAPERS This thesis is based on the following papers I. Gustaf Ullman, Michael Sandborg, David R Dance, Martin Yaffe, Gudrun Alm Carlsson. A search for optimal x‐ray spectra in iodine contrast media mammography. Phys. Med. Biol. 50, 3143–3152 (2005)* II. Gustaf Ullman, Michael Sandborg, David R Dance, Roger Hunt, and Gudrun Alm Carlsson. Distributions of scatter to primary ratios and signal to noise ratios per pixel in digital chest imaging. Radiat Prot Dosim, 114, no 1‐3, 355‐358 (2005)* III. Gustaf Ullman, Michael Sandborg, David R Dance, Roger A Hunt and Gudrun Alm Carlsson. Towards optimization in digital chest radiography using Monte Carlo modelling. Phys Med Biol 51, 2729‐ 2743 (2006)* IV. Michael Sandborg, Anders Tingberg, Gustaf Ullman, David R Dance and Gudrun Alm Carlsson. Comparison of clinical and physical measures of image quality in chest and pelvis computed radiography at different tube voltages. Med. Phys. 33(11) 4169‐4175 (2006)* V. Gustaf Ullman, Alexandr Malusek, Michael Sandborg, David R. Dance and Gudrun Alm Carlsson. Calculation of images from an anthropomorphic chest phantom using Monte Carlo methods. Proc of SPIE 6142, (2006)* VI. Gustaf Ullman, Magnus Båth, Gudrun Alm Carlsson, David R Dance, Markku Tapiovaara, and Michael Sandborg. Development of a Monte Carlo based model for optimization using the Laguerre‐Gauss Hotelling observer. (To be submitted to Med Phys) *Reprints have been included with the permission from the publisher ix List of papers Other peer reviewed papers by the author not included in the thesis 1. Gustaf Ullman, Michael Sandborg, David R Dance, Roger Hunt, and Gudrun Alm Carlsson. The influence of patient thickness, tube voltage and image detector on patient dose and detail signal to noise ratio in digital chest imaging. Radiat Prot Dosim, 114, no 1‐3, 294‐297, 2005 2. Markus Håkansson, Magnus Båth, Sara Börjesson, Susanne Kheddache, Gustaf Ullman, Lars Gunnar Månsson. Nodule detection in digital chest radiography: effect of nodule location. Radiat Prot Dosim 114, no 1‐3, 92‐96, 2005 3. R A Hunt, D R Dance, P R Bakic, A D A Maidment, M Sandborg, G Ullman and G Alm Carlsson. Calculation of the properties of digital mammograms using a computer simulation. Radiat Prot Dosim 114, no 1‐3, 395‐398, 2005 4. D R Dance, R A Hunt, P R Bakic, A D A Maidment, M Sandborg, G Ullman
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