A method to synchronize signals from multiple patient monitoring devices through a single input channel for inclusion in list‐mode acquisitions

Abstract

Purpose: This technical note documents a method that the authors developed for combining a signal to synchronize a patient-monitoring device with a second physiological signal for inclusion into listmode acquisition. Our specific application requires synchronizing an external patient motion-tracking system with a medical imaging system by multiplexing the tracking input with the ECG input. The authors believe that their methodology can be adapted for use in a variety of medical imaging modalities including single photon emission computed tomography (SPECT) and positron emission tomography (PET). Methods: The authors insert a unique pulse sequence into a single physiological input channel. This sequence is then recorded in the list-mode acquisition along with the R-wave pulse used for ECG gating. The specific form of our pulse sequence allows for recognition of the time point being synchronized even when portions of the pulse sequence are lost due to collisions with R-wave pulses. This was achieved by altering our software used in binning the list-mode data to recognize even a portion of our pulse sequence. Limitations on heart rates at which our pulse sequence could be reliably detected were investigated by simulating the mixing of the two signals as a function of heart rate and time point during the cardiac cycle at which our pulse sequence is mixed with the cardiac signal. Results: The authors have successfully achieved accurate temporal synchronization of our motiontracking system with acquisition of SPECT projections used in 17 recent clinical research cases. In our simulation analysis the authors determined that synchronization to enable compensation for body and respiratory motion could be achieved for heart rates up to 125 beats-per-minute (bpm). Conclusions: Synchronization of list-mode acquisition with external patient monitoring devices such as those employed in motion-tracking can reliably be achieved using a simple method that can be implemented using minimal external hardware and software modification through a single input channel, while still recording cardiac gating signals.

Evaluation of Rigid-Body Motion Compensation in Cardiac Perfusion SPECT Employing Polar-Map Quantification

“…During the time period over which these 64 volunteer studies were acquired various methods were developed and used to synchronize visual tracking information with list-mode acquired perfusion SPECT data. These included: 1) a second physiological input channel [19] activated by Philips service and deactivated when power was cycled, 2) the same physiological input channel as used for the ECG signal and a novel input channel combiner (ICC) [24] developed for this specific purpose, or 3) knowledge embedded in the list-mode and VTS data of the bed motion between the low-dose cone-beam CT and gated cardiac SPECT acquisition. Detected photon events as well as other control events in the list-mode data file were temporally interspersed by 1 ms timing events that made it easy to accurately determine the time the physiological signals arrived.…”

“…We have developed an integrated motion tracking and acquisition strategy [17–24], which enables rigid-body and respiratory motion compensation, either separately [19–22] or in some combination [17,18]. These corrections run with minimal initial user interaction employing a visual tracking system (VTS) from Vicon Motion Systems, Inc. (Lake Forest, CA) for motion tracking during SPECT acquisition.…”

“…These corrections run with minimal initial user interaction employing a visual tracking system (VTS) from Vicon Motion Systems, Inc. (Lake Forest, CA) for motion tracking during SPECT acquisition. In preliminary investigations with patients who volunteered to undergo a second session of imaging where they were instructed to move our methods have shown good visual agreement when compared to the initial no motion induced baseline acquisitions [23–24]. In this study we report on the next phase of our investigations by evaluating the effectiveness of our rigid-body motion compensation methodology in 64 patient volunteers employing polar-map quantification [25].…”

Multi-scale event synchronization analysis for unravelling climate processes: A wavelet-based approach

“…Various methods for studying synchronization are available, based on recurrences (Marwan et al, 2007;Donner et al, 2010;Arnhold et al, 1999;Le Van Quyen et al, 1999;Quiroga et al, 2000Quiroga et al, , 2002Schiff et al, 1996), phase differences (Schiff et al, 1996;Rosenblum et al, 1997), or the quasi-simultaneous appearance of events (Tass et al, 1998;Stolbova et al, 2014;Malik et al, 2012;Rheinwalt et al, 2016). For the latter, the method of event synchronization (ES) has received popularity owing to its simplicity, in particular within the fields of brain (Pfurtscheller and Silva 1999;Krause et al, 1996) and cardiovascular research (O'Connor et al, 2013), non-linear chaotic systems (Callahan et al, 1990), and climate sciences (Tass et al, 1998;Stolbova et al, 2014;Malik et al, 2012;Rheinwalt et al, 2016). ES Published by Copernicus Publications on behalf of the European Geosciences Union & the American Geophysical Union.…”

Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach

“…For the latter, the method of event synchronization (ES) has received popularity owing to its simplicity, in particular within the fields of brain (Pfurtscheller and Silva 1999;Krause et al, 1996) and cardiovascular research (O'Connor et al, 2013), non-linear chaotic systems (Callahan et al, 1990), and climate sciences (Tass et al, 1998;Stolbova et al, 2014;Malik et al, 2012;Rheinwalt et al, 2016)…”