The quality of an image is a function of the imaging dose received by the patient. The dotted line indicates the minimum image quality required to detect a given feature of interest. Without overt image planning, it is probable that most clinical images are acquired using suboptimal techniques. Insufficient exposure can leave potentially detectable features masked by image noise, while excessive exposure yields unnecessary patient dose.
The response curve of the imaging detector is shown. These data were integrated into the image planning system algorithm to predict absolute values of tissue contrast.
The absolute values of the pixel intensity across the lung nodule embedded in lung tissue are shown. The edges of the nodule can be appreciated in both the simulated and measured images. Noise becomes appreciable at low mAs levels and begins to obscure the nodule in the measured image.
The geometric appearance of the lung nodule in the respiratory phantom is a function of the exposure level and image detector saturation. The vertical dimension of the visible nodule is predicted by the image planning system.
As the image approaches saturation at high mAs values, the nodule gradually becomes less visible and its geometric dimensions vary. The top row compares measured (left) and simulated (right) images acquired at 4 mAs and 80 kVp. The bottom row compares measured (left) and simulated (right) images acquired at 100 mAs.
The variation in image detector response is plotted across the mammography step wedge. Comparison between simulated and measured images shows good agreement over a wide range of exposure levels and beam qualities.
The measured image (left) and simulated image (right) of the mammography step wedge phantom is shown. Data were acquired at 10 mAs exposure level and 80 kVp beam quality. There is good geometric and visual agreement between the two images.
The contrast between the vertebral body and surrounding soft tissue is shown for the two abdominal phantom models studied. The image simulation algorithm predicts the input exposure level (i.e., mAs setting) at which image saturation and subsequent loss of contrast occurs.
Measured (left) and simulated (right) images are compared for two abdominal phantoms. Images presented in the top row are from the 057 phantom and those in the bottom row are from the 071 phantom. Boxes indicate the regions of interest used to assess the contrast.
(a) Clinical image acquired with our OBI system at 80 kVp and 32 mAs. (b) The corresponding simulated image is shown. Note the boney anatomy is readily appreciable in both images. Spatial resolution in the simulated image is limited due to reconstruction resolution; however, the contrast of the bone and airways is notable in both measured and simulated images.
An example of the use of the IPS in selecting an imaging goal is shown. Top row: simulated images assessing differences in contrast using different kVp and mAs settings. Bottom row: measured images. Selection of the imaging goal could include soft tissue differentiation, e.g., ROI 3 which is likely to be reliably visible versus ROI 1 which is not likely to be clinically visible. Reduction in dose is achieved by declaring the fiducial marker to be the imaging goal (right column). The low contrast lines are the tennis raquet on the Linac table.
Differences in the use of imaging procedures in the context of radiotherapy are compared to those in diagnostic imaging.
The transmitted intensity is calculated for equally weighted spectral components of a hypothetical x-ray beam. The “full bone” calculations consider photoelectric interactions, whereas the “water equivalent bone” calculations only consider Compton processes. The lack of transmission of the 30 and 50 keV components results in image contrast that is dominated by the 100 keV spectral component and Compton processes. The two calculation methods yield similar contrast at the exit of the hypothetical phantom.
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