Quantifying image quality in diagnostic radiology using simulation of the imaging system and model observers

University dissertation from Institutionen för medicin och hälsa

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.