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Impact of irregular waveforms on data-driven respiratory gated PET/CT images processed using MotionFree algorithm

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MotionFree® (AMF) is a data-driven respiratory gating (DDG) algorithm for image processing that has recently been introduced into clinical practice. The present study aimed to verify the accuracy of respiratory waveform and the effects of normal and irregular respiratory motions using AMF with the DDG algorithm.


We used a NEMA IEC body phantom comprising six spheres (37-, 28-, 22-, 17-, 13-, and 10 mm diameter) containing 18F. The sphere-to-background ratio was 4:1 (21.2 and 5.3 kBq/mL). We acquired PET/CT images from a stationary or moving phantom placed on a custom-designed motion platform. Respiratory motions were reproduced based on normal (sinusoidal or expiratory-paused waveforms) and irregular (changed amplitude or shifted baseline waveforms) movements. The “width” parameters in AMF were set at 10–60% and extracted data during the expiratory phases of each waveform. We verified the accuracy of the derived waveforms by comparing those input from the motion platform and output determined using AMF. Quantitative accuracy was evaluated as recovery coefficients (RCs), improvement rate, and %change that were calculated based on sphere diameter or width. We evaluated statistical differences in activity concentrations of each sphere between normal and irregular waveforms.


Respiratory waveforms derived from AMF were almost identical to the input waveforms on the motion platform. Although the RCs in each sphere for expiratory-paused and ideal stationary waveforms were almost identical, RCs except the expiratory-paused waveform were lower than those for the stationary waveform. The improvement rate decreased more for the irregular, than the normal waveforms with AMF in smaller spheres. The %change was improved by decreasing the width of waveforms with a shifted baseline. Activity concentrations significantly differed between normal waveforms and those with a shifted baseline in spheres < 28 mm.


The PET images using AMF with the DDG algorithm provided the precise waveform of respiratory motions and the improvement of quantitative accuracy in the four types of respiratory waveforms. The improvement rate was the most obvious in expiratory-paused waveforms, and the most subtle in those with a shifted baseline. Optimizing the width parameter in irregular waveform will benefit patients who breathe like the waveform with the shifted baseline.

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Data availability

The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.


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We thank the staff at the Diagnostic Imaging Center at Cancer Institute Hospital of JFCR which contributed to the study design and phantom data acquisition. We are also grateful to Mr. Miyachi (GE Healthcare Co., Ltd.) and Mr. Saito for technical support with the AMF. This study was supported in part by the National Cancer Center Research and Development Fund (2020-J-3) and by a KAKENHI Grant-in-Aid for Young Scientists (No. 22K18234) and from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), the Japanese Government.


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Correspondence to Noriaki Miyaji.

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Miyaji, N., Miwa, K., Yamashita, K. et al. Impact of irregular waveforms on data-driven respiratory gated PET/CT images processed using MotionFree algorithm. Ann Nucl Med 37, 665–674 (2023).

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