Ryu H, Meikle SR, Willowson KP, Eslick EM, Bailey DL. Performance evaluation of quantitative SPECT/CT using NEMA NU 2 PET methodology. Phys Med Biol. 2019;64:145017.
Attarwala AA, Hardiansyah D, Romanó C, Jiménez-Franco LD, Roscher M, Wängler B, et al. Performance assessment of the ALBIRA II pre-clinical SPECT S102 system for 99mTc imaging. Ann Nucl Med. 2021;35:111–20. https://doi.org/10.1007/s12149-020-01547-7.
CAS Article PubMed Google Scholar
Khorshidi A. Assessment of SPECT images using UHRFB and other low-energy collimators in brain study by Hoffman phantom and manufactured defects. Eur Phys J Plus. 2020;135:1–19. https://doi.org/10.1140/epjp/s13360-020-00238-6.
Blaire T, Bailliez A, Ben Bouallegue F, Bellevre D, Agostini D, Manrique A. First assessment of simultaneous dual isotope (123I/99mTc) cardiac SPECT on two different CZT cameras: a phantom study. J Nucl Cardiol. 2018;25:1692–704.
Timmins R, Ruddy TD, Wells RG. Patient position alters attenuation effects in multipinhole cardiac SPECT. Med Phys. 2015;42:1233–40.
Zhang D, Ghaly M, Mok GSP. Interpolated CT for attenuation correction on respiratory gating cardiac SPECT/CT—a simulation study. Med Phys. 2019;46:2621–8.
Veress AI, Fung GSK, Lee TS, Tsui BMW, Kicska GA, Segars WP, et al. The direct incorporation of perfusion defect information to define ischemia and infarction in a finite element model of the left ventricle. J Biomech Eng. 2015;137:1–10.
Visser JJN, Sokole EB, Verberne HJ, Habraken JBA, Van De Stadt HJF, Jaspers JEN, et al. A realistic 3-D gated cardiac phantom for quality control of gated myocardial perfusion SPET: the Amsterdam gated (AGATE) cardiac phantom. Eur J Nucl Med Mol Imaging. 2004;31:222–8.
Kim S, Oh J, Jeong D, Park W, Bae J. Consistent and reproducible direct ink writing of eutectic gallium-indium for high-quality soft sensors. Soft Robot. 2018;5:601–12.
Abdullah KA, McEntee MF, Reed W, Kench PL. Development of an organ-specific insert phantom generated using a 3D printer for investigations of cardiac computed tomography protocols. J Med Radiat Sci. 2018;65:175–83.
Okkalidis N, Chatzigeorgiou C, Okkalides D. Assessment of 11 available materials with custom three-dimensional-printing patterns for the simulation of muscle, fat, and lung hounsfield units in patient-specific phantoms. J Eng Sci Med Diagn Ther. 2018;1:1–7.
Vyavahare S, Teraiya S, Panghal D, Kumar S. Fused deposition modelling: a review. Rapid Prototyp J. 2020;26:176–201.
Hong D, Lee S, Kim GB, Lee SM, Kim N, Seo JB. Development of a CT imaging phantom of anthromorphic lung using fused deposition modeling 3D printing. Medicine (United States). 2020;99:e18617.
Zhang J, Hu Q, Wang S, Tao J, Gou M. Digital light processing based three-dimensional printing for medical applications. Int J Bioprinting. 2020;6:12–27.
Robinson SS, Aubin CA, Wallin TJ, Gharaie S, Xu PA, Wang K, et al. Stereolithography for personalized left atrial appendage occluders. Adv Mater Technol. 2018;3:1–9.
Ramírez-Nava GJ, Santos-Cuevas CL, Chairez-Oria I, Rioja-Guerrero E, Oroz-Duarte J. Tomographic 99mTc radioactivity quantification in three-dimensional printed polymeric phantoms with bioinspired geometries. Radiat Phys Chem. 2020;177:109130. https://doi.org/10.1016/j.radphyschem.2020.109130.
Gear JI, Cummings C, Craig AJ, Divoli A, Long CDC, Tapner M, et al. Abdo-Man: a 3D-printed anthropomorphic phantom for validating quantitative SIRT. EJNMMI Phys. 2016. https://doi.org/10.1186/s40658-016-0151-6.
Article PubMed PubMed Central Google Scholar
Anwari V, Lai A, Ursani A, Rego K, Karasfi B, Sajja S, et al. 3D printed CT-based abdominal structure mannequin for enabling research. 3D Print Med. 2020. https://doi.org/10.1186/s41205-020-0056-9.
Article PubMed PubMed Central Google Scholar
Alqahtani MS, Lees JE, Bugby SL, Samara-Ratna P, Ng AH, Perkins AC. Design and implementation of a prototype head and neck phantom for the performance evaluation of gamma imaging systems. EJNMMI Phys. 2017. https://doi.org/10.1186/s40658-017-0186-3.
Article PubMed PubMed Central Google Scholar
Woliner-van der Weg W, Deden LN, Meeuwis APW, Koenrades M, Peeters LHC, Kuipers H, et al. A 3D-printed anatomical pancreas and kidney phantom for optimizing SPECT/CT reconstruction settings in beta cell imaging using 111In-exendin. EJNMMI Phys. 2016. https://doi.org/10.1186/s40658-016-0165-0.
Article PubMed PubMed Central Google Scholar
Gear JI, Cummings C, Sullivan J, Cooper-Rayner N, Downs P, Murray I. Radioactive 3D printing for the production of molecular imaging phantoms. Phys Med Biol. 2020. https://doi.org/10.1088/1361-6560/aba40e.
Läppchen T, Meier LP, Fürstner M, Prenosil GA, Krause T, Rominger A, et al. 3D printing of radioactive phantoms for nuclear medicine imaging. EJNMMI Phys. 2020. https://doi.org/10.1186/s40658-020-00292-0.
Article PubMed PubMed Central Google Scholar
Robinson AP, Tipping J, Cullen DM, Hamilton D, Brown R, Flynn A, et al. Organ-specific spect activity calibration using 3d printed phantoms for molecular radiotherapy dosimetry. EJNMMI Phys. 2016;3:1–11. https://doi.org/10.1186/s40658-016-0148-1.
Filippou V, Tsoumpas C. Recent advances on the development of phantoms using 3D printing for imaging with CT, MRI, PET, SPECT, and ultrasound. Med Phys. 2018;45:e740–60.
Gear JI, Long C, Rushforth D, Chittenden SJ, Cummings C, Flux GD. Development of patient-specific molecular imaging phantoms using a 3D printer. Med Phys. 2014;41:1–4.
Tran-Gia J, Lassmann M. Optimizing image quantification for 177Lu SPECT/CT based on a 3D printed 2-compartment kidney phantom. J Nucl Med. 2018;59:616–24.
Pfaehler E, Beukinga RJ, de Jong JR, Slart RHJA, Slump CH, Dierckx RAJO, et al. Repeatability of 18F-FDG PET radiomic features: a phantom study to explore sensitivity to image reconstruction settings, noise, and delineation method. Med Phys. 2019;46:665–78.
Matsutomo N, Seki H, Hishikawa M, Motegi K, Yamamoto T. Technical Note: development of an ischemic defect model insert attachable to a commercially available myocardial phantom. Med Phys. 2020;47:4340–7.
Green S, Grice J. Technical note: 3D-printed phantom for dedicated cardiac protocols and geometries in nuclear medicine. Med Phys. 2021. https://doi.org/10.1002/mp.15406.
Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin JC, Pujol S, et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012;30:1323–41. https://doi.org/10.1016/j.mri.2012.05.001.
Article PubMed PubMed Central Google Scholar
Liu D, Yu J. Otsu method and K-means. In: Proceedings of 2009 9th Int Conf Hybrid Intell Syst HIS 2009, vol. 1. 2009. p. 344–9.
Paraskevoudis K, Karayannis P, Koumoulos EP. Real-time 3D printing remote defect detection (stringing) with computer vision and artificial intelligence. Processes. 2020;8:1464.
Imbert L, Poussier S, Franken PR, Songy B, Verger A, Morel O, et al. Compared performance of high-sensitivity cameras dedicated to myocardial perfusion SPECT: a comprehensive analysis of phantom and human images. J Nucl Med. 2012;53:1897–903.
Liu CJ, Cheng JS, Chen YC, Huang YH, Yen RF. A performance comparison of novel cadmium–zinc–telluride camera and conventional SPECT/CT using anthropomorphic torso phantom and water bags to simulate soft tissue and breast attenuation. Ann Nucl Med. 2015;29:342–50. https://doi.org/10.1007/s12149-015-0952-z.
Kobayashi H, Momose M, Kanaya S, Kondo C, Kusakabe K, Mitsuhashi N. Scatter correction by two-window method standardizes cardiac I-123 MIBG uptake in various gamma camera systems. Ann Nucl Med. 2003;17:309–13.
Okuda K, Nakajima K, Yoneyama H, Shibutani T, Onoguchi M, Matsuo S, et al. Impact of iterative reconstruction with resolution recovery in myocardial perfusion SPECT: phantom and clinical studies. Sci Rep. 2019;9:1–9. https://doi.org/10.1038/s41598-019-56097-4.
Purser NJ, Armstrong IS, Williams HA, Tonge CM, Lawson RS. Apical thinning: real or artefact? Nucl Med Commun. 2008;29:382–9.
Steffen DA, Giannopoulos AA, Grossmann M, Messerli M, Schwyzer M, Gräni C, et al. “Apical thinning”: relations between myocardial wall thickness and apical left ventricular tracer uptake as assessed with positron emission tomography myocardial perfusion imaging. J Nucl Cardiol. 2020;27:452–60.
Denisova NV, Ansheles AA. A study of false apical defects in myocardial perfusion imaging with SPECT/CT. Biomed Phys Eng Express. 2018. https://doi.org/10.1088/2057-1976/aae414.
Okuda K, Nakajima K, Matsuo S, Kondo C, Sarai M, Horiguchi Y, et al. Creation and characterization of normal myocardial perfusion imaging databases using the IQ·SPECT system. J Nucl Cardiol. 2018;25:1328–37.
Johnson KM, Johnson HE, Dowe DA. Left ventricular apical thinning as normal anatomy. J Comput Assist Tomogr. 2009;33:334–7.
Yoneyama H, Nakajima K, Okuda K, Matsuo S, Onoguchi M, Kinuya S, et al. Reducing the small-heart effect in pediatric gated myocardial perfusion single-photon emission computed tomography. J Nucl Cardiol. 2017;24:1378–88.
Germano G, Kavanagh PB. Ready, shoot, aim? Summary justice for small hearts in nuclear cardiology. J Nucl Cardiol. 2017;24:1389–92.
Germano G, Kavanagh PB, Waechter P, Areeda J, Van Kriekinge S, Sharir T, et al. A new algorithm for the quantitation of myocardial perfusion. SPECT I: technical principles and reproducibility. J Nucl Med. 2000;41:712–9.
Johansson L, Lomsky M, Marving J, Ohlsson M, Svensson SE, Edenbrandt L. Diagnostic evaluation of three cardiac software packages using a consecutive group of patients. EJNMMI Res. 2011;1:1–7.
留言 (0)