Accounting for Breathing Pattern Variability in Event-by-Event Respiratory Motion Correction in PET Using Dynamic Internal-External Motion Correlation

For respiratory motion correction (MC), we previously proposed a listmode-based non-rigid event-by-event (EBE) approach based on internal-external motion correlation (INTEX). This approach assumes the INTEX relationship is valid for the entire PET data acquisition. However, irregular respiratory patterns (RP) with varying amplitudes may change the INTEX correlation during the scan. In addition, baseline shift may change the reference location of MC, thus introducing additional errors. In this work, we first investigated the impact of motion amplitude change and baseline shift on the INTEX correlation. We proposed a new model of Dynamic-INTEX (DINTEX), which dynamically modulates the INTEX correlation in response to varying motion amplitudes and baseline shifts. Two methods to define the D-INTEX were presented. We evaluated DINTEX using three human datasets with 18F-FPDTBZ (pancreas tracer) and compared it with the conventional INTEX, which utilizes a single correlation throughout the scan. The initial results showed that the INTEX correlation varies when RP changes and baseline shifts. D-INTEX outperformed conventional INTEX in terms of organ resolution and contrast recovery (SUV increase: 32.9%±14.7% vs. 20.8%±13.9%). In sum, respiratory pattern change and baseline shift could cause INTEX correlation variation. The proposed D-INTEX method dynamically adjusts INTEX to account for such variabilities. Although the initial results are very promising, substantial additional evaluation is required in order to confirm the findings.