Automatic exposure control calibration and optimisation for abdomen, pelvis and lumbar spine imaging with an Agfa...

The use of three physical image quality metrics, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and mean effective noise equivalent quanta (eNEQ_m) have recently been examined by our group for their appropriateness in the calibration of an automatic exposure control (AEC) device for chest radiography with an Agfa computed radiography (CR) imaging system. This study uses the same methodology but investigates AEC calibration for abdomen, pelvis and spine CR imaging. AEC calibration curves were derived using a simple uniform phantom (equivalent to 20 cm water) to ensure each metric was held constant across the tube voltage range. Each curve was assessed for its clinical appropriateness by generating computer simulated abdomen, pelvis and spine images (created from real patient CT datasets) with appropriate detector air kermas for each tube voltage, and grading these against reference images which were reconstructed at detector air kermas correct for the constant detector dose indicator (DDI) curve currently programmed into the AEC device. All simulated images contained clinically realistic projected anatomy and were scored by experienced image evaluators. Constant DDI and CNR curves did not provide optimized performance but constant eNEQ_m and SNR did, with the latter being the preferred calibration metric given that it is easier to measure in practice. This result was consistent with the previous investigation for chest imaging with AEC devices. Medical physicists may therefore use a simple and easily accessible uniform water equivalent phantom to measure the SNR image quality metric described here when calibrating AEC devices for abdomen, pelvis and spine imaging with Agfa CR systems, in the confidence that clinical image quality will be sufficient for the required clinical task. However, to ensure appropriate levels of detector air kerma the advice of expert image evaluators must be sought.