Erroneous cardiac ECG-gated PET list-mode trigger events can be retrospectively identified and replaced by an offline reprocessing approach: first results in rodents

Abstract

The assessment of left ventricular function, wall motion and myocardial viability using electrocardiogram (ECG)-gated [(18)F]-FDG positron emission tomography (PET) is widely accepted in human and in preclinical small animal studies. The nonterminal and noninvasive approach permits repeated in vivo evaluations of the same animal, facilitating the assessment of temporal changes in disease or therapy response. Although well established, gated small animal PET studies can contain erroneous gating information, which may yield to blurred images and false estimation of functional parameters. In this work, we present quantitative and visual quality control (QC) methods to evaluate the accuracy of trigger events in PET list-mode and physiological data. Left ventricular functional analysis is performed to quantify the effect of gating errors on the end-systolic and end-diastolic volumes, and on the ejection fraction (EF). We aim to recover the cardiac functional parameters by the application of the commonly established heart rate filter approach using fixed ranges based on a standardized population. In addition, we propose a fully reprocessing approach which retrospectively replaces the gating information of the PET list-mode file with appropriate list-mode decoding and encoding software. The signal of a simultaneously acquired ECG is processed using standard MATLAB vector functions, which can be individually adapted to reliably detect the R-peaks. Finally, the new trigger events are inserted into the PET list-mode file. A population of 30 mice with various health statuses was analyzed and standard cardiac parameters such as mean heart rate (119 ms ± 11.8 ms) and mean heart rate variability (1.7 ms ± 3.4 ms) derived. These standard parameter ranges were taken into account in the QC methods to select a group of nine optimal gated and a group of eight sub-optimal gated [(18)F]-FDG PET scans of mice from our archive. From the list-mode files of the optimal gated group, we randomly deleted various fractions (5% to 60%) of contained trigger events to generate a corrupted group. The filter approach was capable to correct the corrupted group and yield functional parameters with no significant difference to the optimal gated group. We successfully demonstrated the potential of the fully reprocessing approach by applying it to the sub-optimal group, where the functional parameters were significantly improved after reprocessing (mean EF from 41% ± 16% to 60% ± 13%). When applied to the optimal gated group the fully reprocessing approach did not alter the functional parameters significantly (mean EF from 64% ± 8% to 64 ± 7%). This work presents methods to determine and quantify erroneous gating in small animal gated [(18)F]-FDG PET scans. We demonstrate the importance of a quality check for cardiac triggering contained in PET list-mode data and the benefit of optionally reprocessing the fully recorded physiological information to retrospectively modify or fully replace the cardiac triggering in PET list-mode data. We aim to provide ...

Automatic Cardiac Self-Gating of Small-Animal PET Data

“…A recent work [7] has shown that the ECG-based CGS in small animals is not perfect, and some errors may be expected. In our case, about 5 % of the heartbeats are missed by the ECG.…”

“…In some preclinical settings, this additional equipment may not be available, or it may not work properly during an acquisition, and furthermore, it is usually rather cumbersome to use in small animals. Moreover, the use of these systems requires the integration of software, hardware, and user input, which could be problematic [7]. Recently, it has been shown that the CGS derived from an ECG may have a significant amount of errors, such as missing heartbeats, which may worsen the quality of the gated images [7].…”

“…Moreover, the use of these systems requires the integration of software, hardware, and user input, which could be problematic [7]. Recently, it has been shown that the CGS derived from an ECG may have a significant amount of errors, such as missing heartbeats, which may worsen the quality of the gated images [7]. Therefore, it would be desirable to be able to reconstruct an adequate CGS directly from the measured PET data without any additional equipment or input from the user.…”

“…At this step, the standard scanner's software rejects coincidences that belong to heartbeats 10 % larger or shorter than the average, as obtained from the CGS. This avoids potential artifacts in the reconstructed images caused by missing beats or errors in the processing of the ECG signal [7] and typically affects to 5 % of the data.…”

Editorial: Derivation of respiratory gating signals from ECG signals

“…In the work of Todica et al, ECG data were processed off-line to embed the triggers into the list-mode data prior to image reconstruction, recognizing that accurate temporal synchronization between the ECG and the PET scanner is essential. 12 Their implementation is vendor specific due to the unique list-mode file format; utilization of a Figure 1. Simulation of a phantom image (left) and with an image acquisition, reconstruction, and cardiac motion mimicking blur, both without (center) and with (right) the presence of sinusoidal horizontal motion.…”