An Adaptive Deadtime Model for Better Quantification in PET

Abstract

It is essential to have a proper deadtime correction method prior to scatter correction and the reconstruction process. Imperfections in the deadtime model might potentially affect the scatter correction and hence provide inaccurate quantification in the reconstructed images. Even though deadtime is ideally a function of singles rates, correction methods for count losses in PET systems might become more complicated mainly due to processing detector signals especially for the piled-up and scattered piled-up events, changes in scatter distribution for detector pairs at different energy levels and multiplexing the detector readout to minimize the number of electronics channels both in singles and coincidence event processors. PET scanners with long axial long field-of-view (LAFOV) introduce an additional complexity due to increased sensitivity in detection of scatter.In this investigation, a new deadtime correction model based on singles rates is discussed with an additional adaptive coefficient. The new model has the flexibility of using two energy windows to accommodate the change in scatter and piled-up scatter events due to various patient/phantom sizes and activity distribution as well. Proposed deadtime model was tested on three phantoms with various shapes and sizes. Two different scanner models were used to test the performance of the new deadtime model. Quantitative accuracy within 2% was achieved up to 150kcps average energy qualified (EQ) block rate for Siemens Biograph Vision Quadra PET/CT scanner with long axial field of views. Quantitative accuracy within 5% was achieved up to 400kcps average energy qualified block rate for Siemens Biograph Vision 600 PET/CT clinical scanner.