PET/MR quality assurance and evaluation of degradation factors due to respiratory motion using experimental phantoms
DOI:
https://doi.org/10.37004/sefm/2024.25.1.004Keywords:
PET/MR, quality assurance, experimental phantoms, respiratory movement, attenuation correctionAbstract
This study aims to create a phantom-based quality control (QC) test for hybrid PET/MR systems. A method that minimises error in attenuation maps (AM) for PET/MR phantom measurements has been validated and implemented in the QC to assess the impact of different respiratory motion degradation factors.
The MRI-QUASAR-Motion phantom with 3D-printing inserts was employed as well as the Duetto tool to generate AMs from computed tomography (AM-CT) scans. Using recovery coefficients (RC), the impact of motion compensation on AMs, discrimination of irregular cycles and averaging for co-registered respiratory phases on PET images was quantified. No significant improvements were observed with motion compensation in the AMs (p = 0.31) or when discriminating irregular cycles (p = 0.16). There was also no significant difference between estimating the concentration in each respiratory phase and averaging its value (RCconcentración = 0.982 ± 0.013) or estimating it in the average image of the respiratory phases (RCconcentración = 0.978 ± 0.009).
Our QC test for PET/MR systems allows us to recommend avoiding the post-processing involved by the respiratory motion compensation in AMs, the discrimination of irregular respiratory cycles and the co-registration of respiratory phases.
References
Meikle SR, et al. Quantitative PET in the 2020s: a roadmap. Phys Med Biol. 2021;66(6). https://doi.org/10.1088/1361-6560/abd4f7
Zhu T, Das S, Wong TZ. Integration of PET/MR Hybrid Imaging into Radiation Therapy Treatment. Magn Reson Imaging Clin N Am. 2017; 25(2):377-430. https://doi.org/10.1016/j.mric.2017.01.001
Currie GM, Kamvosoulis P, Bushong S. PET/MRI, Part 2: Technologic Principles. J Nucl Med Technol. 2021; 49(3):217-225. https://doi.org/10.2967/jnmt.120.261862
Balyasnikova S, et al. PET/MR in oncology: an introduction with focus on MR and future perspectives for hybrid imaging. Am J Nucl Med Mol Imaging. 2012; 2(4):458–474.
Lennie E, Tsoumpas C, Sourbron S. Multimodal phantoms for clinical PET/MRI. EJNMMI Physics. 2021; 8(62). https://doi.org/10.1186/s40658-021-00408-0
Akamatsu G, et al. A review of harmonization strategies for quantitative PET. Ann Nucl Med. 2023; 37(2):71-88. https://doi.org/10.1007/s12149-022-01820-x
Ehman EC, et al. PET/MRI: Where might it replace PET/CT? J Magn Reson. 2017; 46(5):1247-1262. https://doi.org/10.1002/jmri.25711
Dutta J, et al. Pulmonary imaging using respiratory motion compensated simultaneous PET/MR. Med Phys. 2015; 42(7):4227-4240. https://doi.org/10.1118/1.4921616
Soret M, Bacharach SL, Buvat I. Partial-Volume Effect in PET Tumor Imaging. J Nucl Med. 2007; 48(6):932–945. https://doi.org/10.2967/jnumed.106.035774
Carles M, et al. Evaluation of PET texture features with heterogeneous phantoms: complementarity and effect of motion and segmentation method. Phys Med Biol. 2017; 62(2):652.
Ionascu D, et al. Internal-external correlation investigations of respiratory induced motion of lung tumors. Med. Phys. 2007; 34(10):3893-3903. https://doi.org/10.1118/1.2779941
Carles M, et al. Significance of the impact of motion compensation on the variability of PET image features. Phys Med Biol. 2018; 63(6):065013. https://doi.org/10.1088/1361-6560/aab180
Mancosu P, et al. 4D-PET data sorting into different number of phases: a NEMA IQ phantom study. J Appl Clin Med Phys. 2009; 10(4):220-231. https://doi.org/10.1120/jacmp.v10i4.2917
Dawood M, et al. Respiratory gating in positron emission tomography: A quantitative comparison of different gating schemes. Med Phys. 2007; 34(7):3067-3076. https://doi.org/10.1118/1.2748104
Kesner AL, et al. Validation of Software Gating: A Practical Technology for Respiratory Motion Correction in PET. Radiology. 2016; 281(1):239-248. https://doi.org/10.1148/radiol.2016152105
Chang G, et al. Joint correction of respiratory motion artifact and partial volume effect in lung/thoracic PET/CT imaging. Med Phys. 2010; 37(12):6221-6232. https://doi.org/10.1118/1.3512780
Frood R, McDermott G, Scarsbrook A. Respiratory-gated PET/CT for pulmonary lesion characterisation-promises and problems. Br J Radiol. 2018; 91(1086):20170640. https://doi.org/10.1259/bjr.20170640
Martinez-Movilla A, et al. Comparison of protocols with respiratory-gated (4D) motion compensation in PET/CT: open-source package for quantification of phantom image quality. EJNMMI Phys. 2022; 9(80). https://doi.org/10.1186/s40658-022-00509-4
Modus Medical Devices. QUASAR MRI Motion Phantom. [Consultado 30 jul 2023]. Disponible en: https://modusqa.com/products/quasar-mri4d-motion-phantom/
Park SJ, et al. Evaluation of the combined effects of target size, respiratory motion and background activity on 3D and 4D PET/CT images. Phys Med Biol. 2008; 53(13):3661–3679.
Carles M, et al. 4D FDG-PET quantification in thoracic anatomical structures for anthropomorphic phantom measurements. IEEE Nucl Sci Symp Medical Imaging Conf. 2014:1-4. https://doi.org/10.1109/NSSMIC.2014.7430816
Grant AM, et al. NEMA NU 2-2012 performance studies for the SiPM-based ToF-PET component of the GE SIGNA PET/MR system. Med Phys. 2016; 43(5):2334-2343. https://doi.org/10.1118/1.4945416
Surti S, et al. Performance of Philips Gemini TF PET/CT Scanner with Special Consideration for Its Time-of-Flight Imaging Capabilities. J Nucl Med. 2007; 48(3):471-480.
Saborido-Moral JD, et al. Free automatic software for the quality assurance of CT metrics reproducibility: calibration, edges and radiomics. Phys Med. 2023; 114:103153. https://doi.org/10.1016/j.ejmp.2023.103153
Ziegler S, et al. NEMA image quality phantom measurements and attenuation correction in integrated PET/MR hybrid imaging. EJNMMI Physics. 2015; 2(18). https://doi.org/10.1186/s40658-015-0122-3
Aide N, et al. EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies. Eur J Nucl Med Mol Imaging. 2017; 44(1):17-31. https://doi.org/10.1007/s00259-017-3740-2
Nyflot MJ. et al. Impact of CT attenuation correction method on quantitative respiratory-correlated (4D) PET/CT imaging. Med Phys. 2015; 42(1):110–120. https://doi.org/10.1118/1.4903282
Cui Y, Bowsher J, Cai J. Impact of moving target on measurement accuracy in 3D and 4D PET imaging—a phantom study. Adv Radiat Oncol. 2017; 2(1):94-100. https://doi.org/10.1016/j.adro.2016.12.002
Pönisch F, et al. Attenuation correction of four dimensional (4D) PET using phase-correlated 4D-computed tomography. Phys Med Biol. 2008; 53(13):N259–N268. https://doi.org/10.1088/0031-9155/53/13/N03
Nagel CC, et al. Phased attenuation correction in respiration correlated computed tomography/positron emitted tomography. Med Phys. 2006; 33(6):1840–1847. https://doi.org/10.1118/1.2198170
Lu Y, et al. Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data. J Nucl Med. 2018; 59(9):1480–1486. https://doi.org/10.2967/jnumed.117.203000
Nii T, et al. Evaluation of Data-Driven Respiration Gating in Continuous Bed Motion in Lung Lesions. J Nucl Med Technol. 2023; 51(1):32-37. https://doi.org/10.2967/jnmt.122.264909
