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

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Abstract

Objectives

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.

Methods

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.

Results

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.

Conclusions

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.

References

  1. van der Vos CS, Koopman D, Rijnsdorp S, Arends AJ, Boellaard R, van Dalen JA, et al. Quantification, improvement, and harmonization of small lesion detection with state-of-the-art PET. Eur J Nucl Med Mol Imaging. 2017;44:4–16.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Pepin A, Daouk J, Bailly P, Hapdey S, Meyer ME. Management of respiratory motion in PET/computed tomography: the state of the art. Nucl Med Commun. 2014;35:113–22.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Aide N, Lasnon C, Kesner A, Levin CS, Buvat I, Iagaru A, et al. New PET technologies - embracing progress and pushing the limits. Eur J Nucl Med Mol Imaging. 2021;48:2711–26.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kesner AL, Schleyer PJ, Büther F, Walter MA, Schäfers KP, Koo PJ. On transcending the impasse of respiratory motion correction applications in routine clinical imaging—a consideration of a fully automated data driven motion control framework. EJNMMI Phys. 2014;1:8.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Thielemans K, Rathore S, Engbrant F, Razifar P. Device-less gating for PET/CT using PCA. In: 2011 IEEE Nuclear Science Symposium Conference Record; 2011. p. 3904–10.

  6. Thielemans K, Schleyer P, Marsden PK, Manjeshwar RM, Wollenweber SD, Ganin A. Comparison of different methods for data-driven respiratory gating of PET data. In: 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC); 2013. p. 1–4.

  7. Schleyer P, Hong I, Jones J, Hamill J, Panin V, Fuerst S. Data-driven respiratory gating whole body PET using continuous bed motion. In: 2018 IEEE nuclear science symposium and medical imaging conference proceedings (NSS/MIC); 2018. p. 1–5.

  8. Schleyer PJ, O’Doherty MJ, Barrington SF, Marsden PK. Retrospective data-driven respiratory gating for PET/CT. Phys Med Biol. 2009;54:1935–50.

    Article  PubMed  Google Scholar 

  9. Bundschuh RA, Martinez-Moeller A, Essler M, Martinez MJ, Nekolla SG, Ziegler SI, et al. Postacquisition detection of tumor motion in the lung and upper abdomen using list-mode PET data: a feasibility study. J Nucl Med. 2007;48:758–63.

    Article  PubMed  Google Scholar 

  10. Feng T, Wang J, Sun Y, Zhu W, Dong Y, Li H. Self-gating: an adaptive center-of-mass approach for respiratory gating in PET. IEEE Trans Med Imaging. 2018;37:1140–8.

    Article  PubMed  Google Scholar 

  11. KhamisH WS. MotionFree:Device-less digital respiratory gating technique, seamlessly integrated in PET imaging routine. In: Co. GE, editor.

  12. Sebastian Fuerst JH, Inki Hong, Judson Jones, Paul Schleyer. OncoFreeze: Deviceless motion management for PET imaging. In: Siemens Medical Solutions USA I, editor.

  13. Feng T, Yang G, Liu H, Ding Y, Lv Y, Li H, et al. Data-driven phase-matched PET/CT: a solution for axial location-dependent respiratory phase in CT. J Nucl Med. 2021;62:1420.

    Google Scholar 

  14. Morley NC, McGowan DR, Gleeson FV, Bradley KM. Software respiratory gating of positron emission tomography-computed tomography improves pulmonary nodule detection. Am J Respir Crit Care Med. 2017;195:261–2.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Liberini V, Kotasidis F, Treyer V, Messerli M, Orita E, Engel-Bicik I, et al. Impact of PET data driven respiratory motion correction and BSREM reconstruction of (68)Ga-DOTATATE PET/CT for differentiating neuroendocrine tumors (NET) and intrapancreatic accessory spleens (IPAS). Sci Rep. 2021;11:2273.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Buther F, Jones J, Seifert R, Stegger L, Schleyer P, Schafers M. Clinical evaluation of a data-driven respiratory gating algorithm for whole-body PET with continuous bed motion. J Nucl Med. 2020;61:1520–7.

    Article  PubMed  Google Scholar 

  17. Kang SY, Moon BS, Kim HO, Yoon HJ, Kim BS. The impact of data-driven respiratory gating in clinical F-18 FDG PET/CT: comparison of free breathing and deep-expiration breath-hold CT protocol. Ann Nucl Med. 2021;35:328–37.

    Article  CAS  PubMed  Google Scholar 

  18. Kesner AL, Chung JH, Lind KE, Kwak JJ, Lynch D, Burckhardt D, et al. Validation of software gating: a practical technology for respiratory motion correction in PET. Radiology. 2016;281:239–48.

    Article  PubMed  Google Scholar 

  19. Walker MD, Morgan AJ, Bradley KM, McGowan DR. Evaluation of data-driven respiratory gating waveforms for clinical PET imaging. EJNMMI Res. 2019;9:1.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Walker MD, Morgan AJ, Bradley KM, McGowan DR. Data-driven respiratory gating outperforms device-based gating for clinical (18)F-FDG PET/CT. J Nucl Med. 2020;61:1678–83.

    Article  CAS  PubMed  Google Scholar 

  21. Walker MD, Bradley KM, McGowan DR. Evaluation of principal component analysis-based data-driven respiratory gating for positron emission tomography. Br J Radiol. 2018;91:20170793.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Buther F, Ernst I, Frohwein LJ, Pouw J, Schafers KP, Stegger L. Data-driven gating in PET: Influence of respiratory signal noise on motion resolution. Med Phys. 2018;45:3205–13.

    Article  PubMed  Google Scholar 

  23. Reynes-Llompart G, Gamez-Cenzano C, Romero-Zayas I, Rodriguez-Bel L, Vercher-Conejero JL, Marti-Climent JM. Performance characteristics of the whole-body discovery IQ PET/CT System. J Nucl Med. 2017;58:1155–61.

    Article  PubMed  Google Scholar 

  24. Tachibana H, Kitamura N, Ito Y, Kawai D, Nakajima M, Tsuda A, et al. Management of the baseline shift using a new and simple method for respiratory-gated radiation therapy: detectability and effectiveness of a flexible monitoring system. Med Phys. 2011;38:3971–80.

    Article  PubMed  Google Scholar 

  25. Seppenwoolde Y, Shirato H, Kitamura K, Shimizu S, van Herk M, Lebesque JV, et al. Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys. 2002;53:822–34.

    Article  PubMed  Google Scholar 

  26. Liu C, Alessio A, Pierce L, Thielemans K, Wollenweber S, Ganin A, et al. Quiescent period respiratory gating for PET/CT. Med Phys. 2010;37:5037–43.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Shirato H, Seppenwoolde Y, Kitamura K, Onimura R, Shimizu S. Intrafractional tumor motion: lung and liver. Semin Radiat Oncol. 2004;14:10–8.

    Article  PubMed  Google Scholar 

  28. Sigfridsson J, Lindstrom E, Iyer V, Holstensson M, Velikyan I, Sundin A, et al. Prospective data-driven respiratory gating of [(68)Ga]Ga-DOTATOC PET/CT. EJNMMI Res. 2021;11:33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Kim DH, Yoo EH, Hong US, Kim JH, Ko YH, Moon SC, et al. Image Registration of (18)F-FDG PET/CT Using the MotionFree Algorithm and CT Protocols through Phantom Study and Clinical Evaluation. Healthcare (Basel). 2021;9.

  30. Yamashita K, Miyaji N, Motegi K, Ito S. Terauchi T [Effects of CT-based attenuation correction on pet images using data-driven respiratory gating]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2021;77:1317–24.

    Article  PubMed  Google Scholar 

  31. Soret M, Bacharach SL, Buvat I. Partial-volume effect in PET tumor imaging. J Nucl Med. 2007;48(6):932–45.

    Article  PubMed  Google Scholar 

  32. Daou D. Respiratory motion handling is mandatory to accomplish the high-resolution PET destiny. Eur J Nucl Med Mol Imaging. 2008;35:1961–70.

    Article  PubMed  Google Scholar 

  33. Okubo M, Nishimura Y, Nakamatsu K, Okumura M, Shibata T, Kanamori S, et al. Static and moving phantom studies for radiation treatment planning in a positron emission tomography and computed tomography (PET/CT) system. Ann Nucl Med. 2008;22:579–86.

    Article  PubMed  Google Scholar 

  34. Teo BK, Saboury B, Munbodh R, Scheuermann J, Torigian DA, Zaidi H, et al. The effect of breathing irregularities on quantitative accuracy of respiratory gated PET/CT. Med Phys. 2012;39:7390–7.

    Article  PubMed  Google Scholar 

  35. Alessio AM, Kinahan PE. Improved quantitation for PET/CT image reconstruction with system modeling and anatomical priors. Med Phys. 2006;33:4095–103.

    Article  PubMed  Google Scholar 

  36. Frood R, McDermott G, Scarsbrook A. Respiratory-gated PET/CT for pulmonary lesion characterisation-promises and problems. Br J Radiol. 2018;91:20170640.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Tsutsui Y, Kidera D, Taniguchi T, Akamatsu G, Komiya I, Umezu Y, et al. Accuracy of amplitude-based respiratory gating for PET/CT in irregular respirations. Ann Nucl Med. 2014;28:770–9.

    Article  CAS  PubMed  Google Scholar 

  38. van Elmpt W, Hamill J, Jones J, De Ruysscher D, Lambin P, Ollers M. Optimal gating compared to 3D and 4D PET reconstruction for characterization of lung tumours. Eur J Nucl Med Mol Imaging. 2011;38:843–55.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Kim JS, Park CR, Yoon SH, Lee JA, Kim TY, Yang HJ. Improvement of image quality using amplitude-based respiratory gating in PET-computed tomography scanning. Nucl Med Commun. 2021;42:553–65.

    Article  PubMed  Google Scholar 

  40. Kesner AL, Meier JG, Burckhardt DD, Schwartz J, Lynch DA. Data-driven optimal binning for respiratory motion management in PET. Med Phys. 2018;45:277–86.

    Article  PubMed  Google Scholar 

  41. Chen S, Hu P, Gu Y, Yu H, Shi H. Performance characteristics of the digital uMI550 PET/CT system according to the NEMA NU2-2018 standard. EJNMMI Phys. 2020;7:43.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

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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Authors and Affiliations

  1. Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, 10-6 Sakaemachi, Fukushima-Shi, Fukushima, 960-8516, Japan

    Noriaki Miyaji, Kenta Miwa & Tensho Yamao

  2. Department of Nuclear Medicine, Cancer Institute Hospital of Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-Ku, Tokyo, 135-8550, Japan

    Kosuke Yamashita, Kazuki Motegi & Takashi Terauchi

  3. School of Allied Health Sciences, Kitasato University, 1-15-1 Kitazato, Minami-Ku Sagamihara, Kanagawa, 252-0373, Japan

    Kei Wagatsuma

  4. Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakae-Cho, Itabashi-Ku, Tokyo, 173-0015, Japan

    Yuto Kamitaka

  5. Department of Radiology, Virginia Mason Medical Center, 1100 9Th Ave, Seattle, Washington, 98101, USA

    Mitsutomi Ishiyama

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  1. Noriaki Miyaji
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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). https://doi.org/10.1007/s12149-023-01870-9

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