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Development of an adjustable dynamic phantom for testing deviceless motion correction algorithm in PET.

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Τίτλος: Development of an adjustable dynamic phantom for testing deviceless motion correction algorithm in PET.
Συγγραφείς: Kühnel C; Clinic for Nuclear Medicine, University Hospital Jena, Jena, Thuringia, Germany., Schmidt TN; Clinic for Nuclear Medicine, University Hospital Jena, Jena, Thuringia, Germany., Schreiber L; Clinic for Nuclear Medicine, University Hospital Jena, Jena, Thuringia, Germany., Ginter H; Central Research Facilities, University Hospital Jena, Jena, Thuringia, Deutschland., Händel M; Central Research Facilities, University Hospital Jena, Jena, Thuringia, Deutschland., Freesmeyer M; Clinic for Nuclear Medicine, University Hospital Jena, Jena, Thuringia, Germany., Gühne F; Clinic for Nuclear Medicine, University Hospital Jena, Jena, Thuringia, Germany.
Πηγή: Medical physics [Med Phys] 2026 Aug; Vol. 53 (8), pp. e70577.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: John Wiley and Sons, Inc Country of Publication: United States NLM ID: 0425746 Publication Model: Print Cited Medium: Internet ISSN: 2473-4209 (Electronic) Linking ISSN: 00942405 NLM ISO Abbreviation: Med Phys Subsets: MEDLINE
Imprint Name(s): Publication: 2017- : Hoboken, NJ : John Wiley and Sons, Inc.
Original Publication: Lancaster, Pa., Published for the American Assn. of Physicists in Medicine by the American Institute of Physics.
Ιατρικοί όροι (MeSH): Image Processing, Computer-Assisted*/methods , Image Processing, Computer-Assisted*/instrumentation , Positron-Emission Tomography*/instrumentation , Phantoms, Imaging* , Algorithms*, Movement ; Polymethyl Methacrylate
Περίληψη: Background: Respiratory motion during PET Imaging leads to blurring, volumetric overestimation, and reduced quantitative accuracy. Deviceless motion correction algorithms (MCA) such as OncoFreeze (OF) by Siemens Healthineers (Forchheim, Germany) extract respiratory waveforms from list-mode data but require validation that cannot be obtained in vivo.
Purpose: To develop and validate an adjustable dynamic phantom with fillable spheres for quantitative assessment of deviceless PET motion correction.
Methods: A microprocessor-controlled two-axis phantom was constructed to generate linear craniocaudal (cc), ventrodorsal (vd), and diagonal (diag) motion with amplitudes of 0-40 mm and frequencies of 10-40 min- 1. Polymethylmethacrylate (PMMA) spheres (4, 1, and 0.25 mL) filled with 1 8F-fluorodeoxyglucose (FDG) were placed in a water-filled PMMA tank and imaged on a Biograph Vision 600 PET/CT (Siemens Healthineers AG, Forchheim, Germany). For each sphere and direction, 2-min PET scans were acquired with and without MCA, yielding 288 datasets. Volumes, activities, and recovery coefficients (RCs) were extracted using two different isocontours.
Results: Without correction, motion produced substantial overestimation of apparent volume: +15%-55% (4 mL), +81%-166% (1 mL) and +276%-509% (0.25 mL), depending on trajectory and IC37. MCA reduced these distortions: For the 1 mL sphere from +87% to -8% (vd) and +166% to +82% (diag). IC0.1-based activity remained within ≈1%-2% of the nominal value and was minimally affected by MCA, while IC37 underestimated activity (∼45%) and was direction-dependently altered by correction. RCs increased with sphere size and were partially improved by MCA but not restored to static levels.
Conclusions: The phantom provides a reproducible ground-truth framework for evaluating deviceless PET motion correction. MCA reduces motion-induced blurring and volumetric inflation, though correction remains size- and direction-dependent. The system enables systematic benchmarking and further optimization of motion-correction algorithms.
(© 2026 The Author(s). Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)
References: Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394‐424. doi:10.3322/caac.21492.
Owens C, Hindocha S, Lee R, Millard T, Sharma B. The lung cancers: staging and response, CT, (18)F‐FDG PET/CT, MRI, DWI: review and new perspectives. Br J Radiol. 2023;96(1148):20220339. doi:10.1259/bjr.20220339.
Qu X, Huang X, Yan W, Wu L, Dai K. A meta‐analysis of 18FDG‐PET‐CT, 18FDG‐PET, MRI and bone scintigraphy for diagnosis of bone metastases in patients with lung cancer. Eur J Radiol. 2012;81(5):1007‐1015. doi:10.1016/j.ejrad.2011.01.126.
Krause BJ. Einführung gesundheitspolitische Sicht. In: Mohnike W, Mohnike K, Lampe M, eds. PET/CT‐Atlas: Interdisziplinäre PET/CT‐ und PET/MR‐Diagnostik und Therapie. Springer; 2024:3‐6. doi:10.1007/978‐3‐662‐67192‐4.
Korreman SS. Motion in radiotherapy: photon therapy. Phys Med Biol. 2012;57(23):R161‐91. doi:10.1088/0031‐9155/57/23/R161.
Liu C, Pierce LA, 2nd, Alessio AM, Kinahan PE. The impact of respiratory motion on tumor quantification and delineation in static PET/CT imaging. Phys Med Biol. 2009;54(24):7345‐7362. doi:10.1088/0031‐9155/54/24/007.
GmbH SH, OncoFreeze AI. Deviceless motion management for PET imaging. 2501 North Barrington Road. Siemens Medical Solutions USA, Inc. Molcular Imaging; 2021:6.
Meier JG, Wu CC, Betancourt Cuellar SL, et al. Evaluation of a novel elastic respiratory motion correction algorithm on quantification and image quality in abdomino‐thoracic PET/CT. J Nucl Med. 2018;60(2):279‐284. doi:10.2967/jnumed.118.213884.
Lappchen T, Meier LP, Furstner M, et al. 3D printing of radioactive phantoms for nuclear medicine imaging. EJNMMI Phys. 2020;7(1):22. doi:10.1186/s40658‐020‐00292‐0.
Gear JI, Cummings C, Craig AJ, et al. Abdo‐Man: a 3D‐printed anthropomorphic phantom for validating quantitative SIRT. EJNMMI Phys. 2016;3(1):17. doi:10.1186/s40658‐016‐0151‐6.
Ahmad E, Semenov D, Bubnov A, et al. Phantoms for nuclear medicine. Med Radiol Radiat Safety. 2020;65(2):62‐67. doi:10.12737/1024‐6177‐2020‐65‐2‐62‐67.
Green S, Grice J. Technical note: 3D‐printed phantom for dedicated cardiac protocols and geometries in nuclear medicine. Med Phys. 2022;49(2):943‐951. doi:10.1002/mp.15406.
Kallos‐Balogh P, Vas NF, Toth Z, et al. Multicentric study on the reproducibility and robustness of PET‐based radiomics features with a realistic activity painting phantom. PLoS ONE. 2024;19(10):e0309540. doi:10.1371/journal.pone.0309540.
Gregg KW, Ruff C, Koenig G, et al. Development and first implementation of a novel multi‐modality cardiac motion and dosimetry phantom for radiotherapy applications. Med Phys. 2024;51(10):7479‐7491. doi:10.1002/mp.17315.
SabbirAhmed AS, Demir M, Kabasakal L, Uslu I. A dynamic renal phantom for nuclear medicine studies. Med Phys. 2005;32(2):530‐538. doi:10.1118/1.1851923.
Seppenwoolde Y, Shirato H, Kitamura K, 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(4):822‐834. doi:10.1016/s0360‐3016(02)02803‐1.
Westphal JG, Winkens T, Kuhnel C, Freesmeyer M. Low‐activity (124)I‐PET/low‐dose CT versus (131)I probe measurements in pretherapy assessment of radioiodine uptake in benign thyroid diseases. J Clin Endocrinol Metab. 2014;99(6):2138‐2145. doi:10.1210/jc.2013‐4390.
Alvarez P, Molineu A, Hernandez N, et al. Anthropomorphic phantoms for quality assurance in radiation therapy. presented at: Proceedings of the 46th Annual Meeting of the American Association of Physicists in Medicine (AAPM); 2004; Pittsburgh, Pennsylvania, USA.
Arshad MA, Gitau S, Tam H, et al. Optimal method for metabolic tumour volume assessment of cervical cancers with inter‐observer agreement on [18F]‐fluoro‐deoxy‐glucose positron emission tomography with computed tomography. Eur J Nucl Med Mol Imaging. 2021;48(6):2009‐2023. doi:10.1007/s00259‐020‐05136‐8.
Bailey DL, Townsend DW, Valk PE, Maisey MN. Positron Emission Tomography: Basic Sciences. Springer; 2006.
Moses WW. Fundamental limits of spatial resolution in PET. Nucl Instrum Methods Phys Res A. 2011;648 Supplement (1):S236‐S240. doi:10.1016/j.nima.2010.11.092.
Boellaard R. Need for standardization of 18F‐FDG PET/CT for treatment response assessments. J Nucl Med. 2011;52 Suppl (2):93S‐100S. doi:10.2967/jnumed.110.085662.
Boellaard R, Delgado‐Bolton R, Oyen WJ, et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging. 2015;42(2):328‐354. doi:10.1007/s00259‐014‐2961‐x.
Cherry SR, Sorenson JA, Phelps ME. Physics in Nuclear Medicine E‐Book. Physics in Nuclear Medicine E‐Book; 2012.
Gillman A, Smith J, Thomas P, Rose S, Dowson N. PET motion correction in context of integrated PET/MR: current techniques, limitations, and future projections. Med Phys. 2017;44(12):e430‐e445. doi:10.1002/mp.12577.
Meier JG, Einstein SA, Diab RH, Erasmus LJ, Xu G, Mawlawi OR. Impact of free‐breathing CT on quantitative measurements of static and quiescent period‐gated PET Images. Phys Med Biol. 2019;64(10):105013. doi:10.1088/1361‐6560/ab1cdd.
Substance Nomenclature: 9011-14-7 (Polymethyl Methacrylate)
Entry Date(s): Date Created: 20260722 Date Completed: 20260722 Latest Revision: 20260726
Update Code: 20260726
PubMed Central ID: PMC13389335
DOI: 10.1002/mp.70577
PMID: 42482411
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:2473-4209
DOI:10.1002/mp.70577