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Introduction: Positron emission tomography (PET) has undergone transformative advancements, evolving from a research tool into a cornerstone of precision medicine. Objective: This review highlights key developments in PET imaging, including the introduction of specialized systems such as brain and breast-dedicated scanners, total-body PET, and hybrid PET/CT and PET/MRI technologies. Methods: These innovations have significantly enhanced diagnostic accuracy and patient management across oncology, neurology and cardiology. The emergence of novel radiotracers beyond fluorodeoxyglucose (FDG) has expanded PET's clinical applications by targeting specific molecular pathways, improving sensitivity and specificity in disease characterization. Notable tracers include those for tumor proliferation, hypoxia and receptor-specific imaging, which facilitate personalized treatment strategies. The integration of artificial intelligence (AI) has revolutionized PET imaging by improving image reconstruction, noise reduction, motion correction and lesion segmentation. AI-driven tools enhance diagnostic precision while reducing scan times and radiation exposure, making PET safer and more efficient. Furthermore, AI accelerates radiotracer development by optimizing molecular design and enabling personalized dosimetry planning for theranostic applications. Total-body PET scanners represent a technological milestone, offering unparalleled sensitivity, reduced radiation doses, faster scans, the ability to track systemic diseases comprehensively and to enhance diagnosis by novel imaging biomarkers. These advancements enable earlier disease detection, precise monitoring of treatment efficacy and deeper insights into disease mechanisms. Results: Collectively, these innovations underscore PET's transformative role in advancing precision medicine through early diagnosis, disease monitoring and tailored therapeutic interventions. Conclusions: This review concludes that ongoing technological progress will continue to redefine the capabilities of PET imaging in clinical practice and research.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
40--57
Opis fizyczny
Bibliogr. 286 poz., rys.
Twórcy
- Department of Electrical and Computer Engineering, Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, United States
autor
- Department of Electrical and Computer Engineering, Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, United States
autor
- Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland
- Center for Theranostics, Jagiellonian University, Krakow, Poland
autor
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
Bibliografia
- 1. Ter-Pogossian MM. The origins of positron emission tomography. Semin Nucl Med. 1992;22(3):140-9. doi: https://doi.org/10.1016/s0001-2998(05)80142-4.
- 2. Muehllehner G, Karp JS. Positron emission tomography. Phys Med Biol. 2006;51(13):R117. doi: https://doi.org/10.1088/0031-9155/51/13/R08.
- 3. Ollinger JM, Fessler JA. Positron-emission tomography. IEEE Signal Process Mag. 1997;14(1):43-55.
- 4. Ell PJ. The contribution of medical physics to nuclear medicine: a physician’s perspective. EJNMMI Phys. 2014;1:1-7.
- 5. Moskal P, Stępień E, Werner T, Alavi A: Unparalleled and revolutionary impact of PET imaging on research and day to day practice of medicine. Bio-Algorithms and Med-Systems. 2021;17(4):203-12. doi: https://doi. org/10.1515/bams-2021-0186.
- 6. Ter-Pogossian MM, Phelps ME, Hoffman EJ, Mullani NA. A positron- -emission transaxial tomograph for nuclear imaging (PETT). Radiol. 1975;114(1):89-98.
- 7. Vaquero JJ, Kinahan P. Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems. Annu Rev Biomed Eng. 2015;17:385-414. doi: https://doi.org/10.1146/annurev-bioeng-071114-040723.
- 8. Yu S. Review of F-FDG Synthesis and Quality Control. Biomed Imaging Interv J. 2006;2(4):e57. doi: https://doi.org/10.2349/biij.2.4.e57.
- 9. Fletcher JW, Djulbegovic B, Soares HP, Siegel BA, Lowe VJ, Lyman GH, et al. Recommendations on the use of 18F-FDG PET in oncology. J Nucl Med. 2008;49(3):480–508. doi: https://doi.org/10.2967/jnumed.107.047787.
- 10. Fowler JS. 18F-FDG Radiosynthesis: A Landmark in the History of PET. J Nucl Med. 2020;61(Suppl 2):105S-6S. doi: https://doi.org/10.2967/jnumed.120.250191.
- 11. Salas JR, Clark PM. Signaling Pathways That Drive 18F-FDG Accumulation in Cancer. J Nucl Med. 2022;63(5):659-63. doi: https://doi. org/10.2967/jnumed.121.262609.
- 12. Rudroff T, Kindred JH, Kalliokoski KK. [18F]-FDG positron emission tomography-an established clinical tool opening a new window into exercise physiology. J Appl Physiol. 2015;118(10):1181-90. doi: https://doi. org/10.1152/japplphysiol.01070.2014.
- 13. Otsuka M, Ichiya Y, Kuwabara Y, Miyake Y, Tahara T, Masuda K, et al. Cerebral blood flow, oxygen and glucose metabolism with PET in progressive supranuclear palsy. Ann Nucl Med. 1989;3:111-18. doi: https://doi.org/10.1007/BF03178296.
- 14. Parodi K, Yamaya T, Moskal P. Experience and new prospects of PET imaging for ion beam therapy monitoring. Z Med Phys. 2023;33(1):22-34.
- 15. Ayesa SL, Murphy A. Positron emission tomography: Evolving modalities, radiopharmaceuticals and professional collaboration. J Med Radiat Sci. 2022;69(4):415-8.
- 16. Kjaer A. Hybrid imaging with PET/CT and PET/MR. Cancer Imaging. 2014;14(Suppl 1):O32. doi: https://doi.org/10.1186/1470-7330-14-S1-O32.
- 17. de Galiza Barbosa F, Delso G, Ter Voert EE, Huellner MW, Herrmann K, Veit-Haibach P. Multi-technique hybrid imaging in PET/CT and PET/MR: what does the future hold? Clin Radiol. 2016;71(7):660-72. doi: https://doi.org/10.1016/j.crad.2016.03.013.
- 18. Takahashi M, Nishikido F, Akamatsu G, Tashima H, Iwao Y, Suga M, et al. The first human study of add-on PET: A PET-integrated RF coil for 3 T MRI. EJNMMI Phys. 2025;12(1):19. doi: https://doi.org/10.1186/ s40658-025-00731-w.
- 19. Hussain D, Abbas N, Khan J. Recent Breakthroughs in PET-CT Multimodality Imaging: Innovations and Clinical Impact. Bioengineering (Basel). 2024;11(12):1213. doi: https://doi.org/10.3390/bioengineering11121213.
- 20. Trotter J, Pantel AR, Teo BK, Escorcia FE, Li T, Pryma DA, et al. Positron Emission Tomography (PET)/Computed Tomography (CT) Imaging in Radiation Therapy Treatment Planning: A Review of PET Imaging Tracers and Methods to Incorporate PET/CT. Adv Radiat Oncol. 2023;8(5):101212. doi: https://doi.org/10.1016/j.adro.2023.101212.
- 21. Mason C, Gimblet GR, Lapi SE, Lewis JS. Novel Tracers and Radionuclides in PET Imaging. Radiol Clin North Am. 2021;59(5):887-918. doi: https://doi.org/10.1016/j.rcl.2021.05.012.
- 22. Surti S. Update on time-of-flight PET imaging. J Nucl Med. 2015;56(1):98-105. doi: https://doi.org/10.2967/jnumed.114.145029.
- 23. Surti S, Karp JS. Update on latest advances in time-of-flight PET. Phys Med. 2020;80:251-8. doi: https://doi.org/10.1016/j.ejmp.2020.10.031.
- 24. Lois C, Jakoby BW, Long MJ, Hubner KF, Barker DW, Casey ME, et al. An assessment of the impact of incorporating time-of-flight information into clinical PET/CT imaging. J Nucl Med. 2010;51(2):237-45. doi: https://doi.org/10.2967/jnumed.109.068098.
- 25. Ullah MN, Pratiwi E, Cheon J, Choi H, Yeom JY. Instrumentation for time-of-flight positron emission tomography. Nucl Med Mol Imaging. 2016;50:112-22.
- 26. Lecoq P, Gundacker S. SiPM applications in positron emission tomography: toward ultimate PET time-of-flight resolution. Eur Phys J Plus. 2021;136(3):292. doi: https://doi.org/10.1140/epjp/s13360-021-01183-8.
- 27. Schaart DR, Schramm G, Nuyts J, Surti S. Time of Flight in Perspective: Instrumental and Computational Aspects of Time Resolution in Positron Emission Tomography. IEEE Trans Radiat Plasma Med Sci. 2021;5(5):598-618. doi: https://doi.org/10.1109/trpms.2021.3084539.
- 28. Del Guerra A, Belcari N, Bisogni MG, LLosa G, Marcatili S, Ambrosi G, et al. Advantages and pitfalls of the silicon photomultiplier (SiPM) as photodetector for the next generation of PET scanners. Nucl Instrum Methods Phys Res A. 2010;617(1-3):223-6. doi: https://doi.org/10.1016/j.nima.2009.09.121.
- 29. Cherry SR, Jones T, Karp JS, Qi J, Moses WW, Badawi RD. Total-Body PET: Maximizing Sensitivity to Create New Opportunities for Clinical Research and Patient Care. J Nucl Med. 2018;59(1):3-12. doi: https://doi. org/10.2967/jnumed.116.184028.
- 30. Nadig V, Herrmann K, Mottaghy FM, Schulz V. Hybrid total-body pet scanners-current status and future perspectives. Eur J Nucl Med Mol Imaging. 2022;49(2):445-59. doi: https://doi.org/10.1007/s00259-021-05536-4.
- 31. Vandenberghe S, Moskal P, Karp JS. State of the art in total body PET. EJNMMI Phys. 2020;7(1):35. doi: https://doi.org/10.1186/s40658-020-00290-2.
- 32. Rathod N, Jutidamrongphan W, Bosbach WA, Chen Y, Penner JL, Sari H, et al. Total Body PET/CT: Clinical Value and Future Aspects of Quantification in Static and Dynamic Imaging. Semin Nucl Med. 2025;55(1):98-106. doi: https://doi.org/10.1053/j.semnuclmed.2024.11.004.
- 33. Wang G, Rahmim A, Gunn RN. PET Parametric Imaging: Past, Present, and Future. IEEE Trans Radiat Plasma Med Sci. 2020;4(6):663-75. doi: https://doi.org/10.1109/trpms.2020.3025086.
- 34. Wang G, Nardo L, Parikh M, Abdelhafez YG, Li E, Spencer BA, et al. Total-Body PET Multiparametric Imaging of Cancer Using a Voxelwise Strategy of Compartmental Modeling. J Nucl Med. 2022;63(8):1274-81. doi: https://doi.org/10.2967/jnumed.121.262668.
- 35. Moskal P. Positronium imaging. In: 2019 IEEE nuclear science symposium and medical imaging conference (NSS/MIC): 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2019); 2019 Oct 26-2 Nov; Manchester, United Kingdom. New York: IEEE; 2019. p. 1-3.
- 36. Moskal P, Dulski K, Chug N, Curceanu C, Czerwiński E, Dadgar M, et al. Positronium imaging with the novel multiphoton PET scanner. Sci Adv. 2021;7(42):eabh4394. doi: https://doi.org/10.1126/sciadv.abh4394.
- 37. Moskal P, Baran J, Bass S, Choiński J, Chug N, Curceanu C, et al. Positronium image of the human brain in vivo. Sci Adv. 2024;10(37):eadp2840. doi: https://doi.org/10.1126/sciadv.adp2840.
- 38. Moskal P, Jasińska B, Stępień EŁ, Bass SD. Positronium in medicine and biology. Nat Rev Phys. 2019;1(9):527-29.
- 39. Steinberger WM, Mercolli L, Breuer J, Sari H, Parzych S, Niedzwiecki S, et al. Positronium lifetime validation measurements using a long-axial field-of-view positron emission tomography scanner. EJNMMI Phys. 2024;11(1):76. doi: https://doi.org/10.1186/s40658-024-00678-4.
- 40. Qi J, Huang B. Positronium Lifetime Image Reconstruction for TOF PET. IEEE Trans Med Imaging. 2022;41(10):2848-55. https://doi.org/10.1109/TMI.2022.3174561.
- 41. Berens L, Hsu I, Chen C, Halpern H, Kao C. An analytic, moment-based method to estimate orthopositronium lifetimes in positron annihilation lifetime spectroscopy measurements. Bioalgorithms Medsyst. 2024;20(Special Issue):40-8. doi: https://doi.org/10.5604/01.3001.0054.9141.
- 42. Chen Z, Kao CM, Huang HH, An L. Enhanced positronium lifetime imaging through two-component reconstruction in time-of-flight positron emission tomography. Front Phys. 2024;12:1429344.
- 43. Moskal P. Positron emission tomography could be aided by entanglement. Physics. 2024;17:138.
- 44. Moskal P, Kumar D, Sharma S, Beyene EY, Chug N, Coussat A, et al. Non-maximal entanglement of photons from positron-electron annihilation demonstrated using a novel plastic PET scanner. Sci Adv. 2025;11(18):eads3046.
- 45. Romanchek G, Shoop G, Abbaszadeh S. Application of quantum entanglement induced polarization for dual-positron and prompt gamma imaging. Bio-Algorithms and Med-Systems. 2023;19(1):9-16. doi: https://doi.org/10.5604/01.3001.0054.1817.
- 46. Kim D, Rachman AN, Taisei U, Uenomachi M, Shimazoe K, Takahashi H. Background reduction in PET by double Compton scattering of quantum entangled annihilation photons. J Instrum. 2023;18(7):P07007.
- 47. Watts DP, Bordes J, Brown JR, Cherlin A, Newton R, Allison J, et al. Photon quantum entanglement in the MeV regime and its application in PET imaging. Nat Commun. 2021;12(1):2646. doi: https://doi.org/10.1038/ s41467-021-22907-5.
- 48. Parashari S, Makek M, Bokulić T, Bosnar D, Kožuljević AM, Kuncic Z, et al. Optimization of detector modules for measuring gamma-ray polarization in Positron Emission Tomography. Nucl Instrum Methods Phys Res A. 2022;1040:167186.
- 49. Beyene E, Das M, Durak-Kozica M, Korcyl G, Mryka W, Niedźwiecki S, et al. Exploration of simultaneous dual-isotope imaging with multiphoton modular J-PET scanner. Bio-Algorithms and Med-Systems. 2023;19(1):101-8. doi: https://doi.org/10.5604/01.3001.0054.1940.
- 50. Pratt EC, Lopez-Montes A, Volpe A, Crowley MJ, Carter LM, Mittal V, et al. Simultaneous quantitative imaging of two PET radiotracers via the detection of positron-electron annihilation and prompt gamma emissions. Nat Biomed Eng. 2023;7(8):1028-39. doi: https://doi.org/10.1038/ s41551-023-01060-y.
- 51. Moskal P, Gajos A, Mohammed M, Chhokar J, Chug N, Curceanu C, et al. Testing CPT symmetry in ortho-positronium decays with positronium annihilation tomography. Nat Commun. 2021;12(1):5658. doi: https://doi.org/10.1038/s41467-021-25905-9.
- 52. Tashima H, Yamaya T. Three-Gamma Imaging in Nuclear Medicine: A Review. IEEE Trans Radiat Plasma Med Sci. 2024; 8(8):853-66.
- 53. Pedersen C, Aboian M, McConathy JE, Daldrup-Link H, Franceschi AM. PET/MRI in Pediatric Neuroimaging: Primer for Clinical Practice. AJNR Am J Neuroradiol. 2022;43(7):938-43. doi: https://doi.org/10.3174/ajnr.A7464.
- 54. Catana C, Drzezga A, Heiss WD, Rosen BR. PET/MRI for neurologic applications. J Nucl Med. 2012;53(12):1916-25. doi: https://doi.org/10.2967/jnumed.112.105346.
- 55. Pedersen C, Aboian M, Messina SA, Daldrup-Link H, Franceschi AM. PET/MRI Applications in Pediatric Epilepsy. World J Nucl Med. 2023;22(2):078-86.
- 56. Baratto L, Hawk KE, States L, Qi J, Gatidis S, Kiru L, et al. PET/MRI Improves Management of Children with Cancer. J Nucl Med. 2021;62(10):1334-40. doi: https://doi.org/10.2967/jnumed.120.259747.
- 57. González-Montoro A, Freire M, Barberá J, de Alfonso C, Alamo J, Cañizareset G, et al. MR compatibility assesment of the edgeless preclinical PET insert: ScintoTube. In: 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room- -Temperature Semiconductor Detectors (NSS MIC RTSD), IEEE 2023; 2023 Nov 4-11; Vancouver, Canada. New York: IEEE; 2023. p. 1-2.
- 58. Currie GM, Kamvosoulis P, Bushong S. PET/MRI, Part 2: Technologic Principles. J Nucl Med Technol. 2021;49(3):217-25. doi: https://doi.org/10.2967/jnmt.120.261862.
- 59. Cal-Gonzalez J, Rausch I, Shiyam Sundar LK, Lassen M, Muzik O, Moser E, et al. Hybrid imaging: instrumentation and data processing. Front Phys. 2018;6:47.
- 60. Mankoff DA, Pantel AR, Viswanath V, Karp JS. Advances in PET Diagnostics for Guiding Targeted Cancer Therapy and Studying In Vivo Cancer Biology. Curr Pathobiol Rep. 2019;7(3):97-108. doi: https://doi. org/10.1007/s40139-019-00202-9.
- 61. Bar-Shalom R, Valdivia AY, Blaufox MD. PET imaging in oncology. Semin Nucl Med. 2000;30(3):150-85. doi: https://doi.org/10.1053/snuc.2000.7439.
- 62. Strauss LG, Conti PS. The applications of PET in clinical oncology. J Nucl Med. 1991;32(4): 623-48.
- 63. Rohren EM, Turkington TG, Coleman RE. Clinical applications of PET in oncology. Radiology. 2004;231(2):305-32. doi: https://doi.org/10.1148/radiol.2312021185.
- 64. Hoh CK, Schiepers C, Seltzer MA, Gambhir SS, Silverman DH, Czernin J, et al. PET in oncology: will it replace the other modalities? Semin Nucl Med. 1997;27(2):94-106. doi: https://doi.org/10.1016/s0001-2998(97)80042-6.
- 65. Gallamini A, Zwarthoed C, Borra A. Positron Emission Tomography (PET) in Oncology. Cancers (Basel). 2014;6(4):1821-89. doi: https://doi.org/10.3390/cancers6041821.
- 66. Dresel S. PET in Oncology. vol. 170. Berlin, Springer Science & Business Media; 2009.
- 67. Zaidi H, Karakatsanis N. Towards enhanced PET quantification in clinical oncology. Br J Radiol. 2018;91(1081):20170508. doi: https://doi.org/10.1259/bjr.20170508.
- 68. Delbeke D. Oncological applications of FDG PET imaging. J Nucl Med. 1999;40(10):1706-15.
- 69. Kreisl WC, Kim MJ, Coughlin JM, Henter ID, Owen DR, Innis RB. PET imaging of neuroinflammation in neurological disorders. Lancet Neurol. 2020;19(11):940-50. doi: https://doi.org/10.1016/S1474-4422(20)30346-X.
- 70. Brooks D. PET: its clinical role in neurology. J Neurol Neurosurg Psychiatry. 1991;54(1):1-5. doi: https://doi.org/10.1136/jnnp.54.1.1.
- 71. Sarikaya I. PET imaging in neurology: Alzheimer’s and Parkinson’s diseases. Nucl Med Commun. 2015;36(8):775-81.
- 72. Hubner KF. PET imaging in neurology. J Nucl Med Technol. 1990;18(4):229-34.
- 73. Barrington S. Clinical uses of PET in neurology. Nucl Med Commun. 2000; 21(3):237-40.
- 74. Takalkar A, Mavi A, Alavi A, Araujo L. PET in cardiology. Radiol Clin. 2005;43(1):107-19.
- 75. Maisey M. Clinical PET in cardiology and cardiac surgery. Nucl Med Commun. 2000;21(3):234-6.
- 76. Plein S., Sivananthan M. The role of positron emission tomography in cardiology. Radiography. 2001;7(1):11-20.
- 77. Nienaber C. PET in cardiology: current status and clinical expectations. Clin Phys. 1994;14(3): 337-48.
- 78. Lee WW. Recent Advances in Nuclear Cardiology. Nucl Med Mol Imaging. 2016;50(3):196-206. doi: https://doi.org/10.1007/s13139-016-0433-x.
- 79. Heinke W, Schwarzbauer C. In vivo imaging of anaesthetic action in humans: approaches with positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). Br J Anaesth. 2002;89(1):112-22. doi: https://doi.org/10.1093/bja/aef155.
- 80. Ametamey SM, Honer M, Schubiger PA. Molecular imaging with PET. Chem Rev. 2008;108(5):1501-16.
- 81. Delgado-Bolton RC, Fernández-Pérez C, González-Maté A, Carreras JL. Meta-analysis of the performance of 18F-FDG PET in primary tumor detection in unknown primary tumors. J Nucl Med. 2003;44(8):1301-14.
- 82. Younes-Mhenni S, Janier MF, Cinotti L, Antoine JC, Tronc F, Cottin V, et al. FDG-PET improves tumour detection in patients with paraneoplastic neurological syndromes. Brain. 2004;127(Pt 10):2331-8. doi: https://doi. org/10.1093/brain/awh247.
- 83. Kubota K, Itoh M, Ozaki K, Ono S, Tashiro M, Yamaguchi K, et al. Advantage of delayed whole-body FDG-PET imaging for tumour detection. Eur J Nucl Med. 2001;28:696-703.
- 84. Hoh CK, Hawkins RA, Glaspy JA, Dahlbom M, Tse NY, Hoffman EJ, et al. Cancer detection with whole-body PET using 2-[18F]fluoro-2-deoxy-D-glucose. J Comput Assist Tomogr. 1993;17(4):582-9. doi: https://doi.org/10.1097/00004728-199307000-00012.
- 85. Apostolova I, Wedel F, Brenner W. Imaging of Tumor Metabolism Using Positron Emission Tomography (PET). Recent Results Cancer Res. 2016;207:177-205. doi: https://doi.org/10.1007/978-3-319-42118-6_8.
- 86. de Geus-Oei LF, Ruers TJ, Punt CJ, Leer JW, Corstens FH, Oyen WJ. FDG-PET in colorectal cancer. Cancer Imaging. 2006;6(Spec No A):S71.
- 87. Kostakoglu L, Agress H Jr, Goldsmith SJ. Clinical role of FDG PET in evaluation of cancer patients. Radiographics. 2003;23(2):315-40. doi: https://doi.org/10.1148/rg.232025705.
- 88. Jadvar H, Alavi A, Gambhir SS. 18F-FDG uptake in lung, breast, and colon cancers: molecular biology correlates and disease characterization. J Nucl Med. 2009;50(11):1820-7. doi: https://doi.org/10.2967/jnumed.108.054098.
- 89. Guo R, Yan W, Wang F, Su H, Meng X, Xie Q, et al. The utility of 18F-FDG PET/CT for predicting the pathological response and prognosis to neoadjuvant immunochemotherapy in resectable non-small-cell lung cancer. Cancer Imaging. 2024;24(1):120. doi: https://doi.org/10.1186/s40644-024-00772-x.
- 90. Al-Ibraheem A, Abdlkadir AS, Juweid ME, Al-Rabi K, Ma’koseh M, Abdel-Razeq H, et al. FDG-PET/CT in the Monitoring of Lymphoma Immunotherapy Response: Current Status and Future Prospects. Cancers (Basel). 2023;15(4):1063. doi: https://doi.org/10.3390/cancers15041063.
- 91. Yen C, Lin CL, Chiang MC. Exploring the Frontiers of Neuroimaging: A Review of Recent Advances in Understanding Brain Functioning and Disorders. Life (Basel). 2023;13(7):1472. doi: https://doi.org/10.3390/life13071472.
- 92. Saulin A, Savli M, Lanzenberger R. Serotonin and molecular neuroimaging in humans using PET. Amino Acids. 2012;42:2039-57.
- 93. Schwenck J, Sonanini D, Cotton JM, Rammensee HG, la Fougère C, Zender L, et al. Advances in PET imaging of cancer. Nat Rev Cancer. 2023;23(7):474-90. doi: https://doi.org/10.1038/s41568-023-00576-4.
- 94. Nordberg A, Rinne JO, Kadir A, Långström B. The use of PET in Alzheimer disease. Nat Rev Neurol. 2010;6(2):78-87. doi: https://doi.org/10.1038/nrneurol.2009.217.
- 95. Rice L, Bisdas S. The diagnostic value of FDG and amyloid PET in Alzheimer’s disease – A systematic review. Eur J Radiol. 2017;94:16-24.
- 96. Marcus C, Mena E, Subramaniam RM. Brain PET in the diagnosis of Alzheimer’s disease. Clin Nucl Med. 2014;39(10):e413-26. doi: https://doi.org/10.1097/RLU.0000000000000547.
- 97. Sioka C, Fotopoulos A, Kyritsis AP. Recent advances in PET imaging for evaluation of Parkinson’s disease. Eur J Nucl Med Mol Imaging. 2010;37:1594-603. doi: https://doi.org/10.1007/s00259-009-1357-9.
- 98. Morrish P, Sawle G, Brooks D. An [18F] dopa-PET and clinical study of the rate of progression in Parkinson’s disease. Brain. 1996;119(2):585-91.
- 99. Volkow ND, Fowler JS, Gatley SJ, Logan J, Wang GJ, Ding YS, et al. PET evaluation of the dopamine system of the human brain. J Nucl Med. 1996;37(7):1242-56.
- 100. la Fougère C, Rominger A, Förster S, Geisler J, Bartenstein P. PET and SPECT in epilepsy: a critical review. Epilepsy Behav. 2009;15(1):50-5. doi: https://doi.org/10.1016/j.yebeh.2009.02.025.
- 101. Engel J Jr. The use of positron emission tomographic scanning in epilepsy. Ann Neurol. 1984;15(S1):180-91.
- 102. Talbot PS, Laruelle M. The role of in vivo molecular imaging with PET and SPECT in the elucidation of psychiatric drug action and new drug development. Eur Neuropsychopharmacol. 2002;12(6):503-11. doi: https://doi.org/10.1016/s0924-977x(02)00099-8.
- 103. Mayberg HS. Positron emission tomography imaging in depression: a neural systems perspective. Neuroimaging Clin N Am. 2003;13(4):805-15. doi: https://doi.org/10.1016/s1052-5149(03)00104-7.
- 104. Brooks DJ. Imaging approaches to Parkinson disease. J Nucl Med. 2010;51(4):596-609. doi: https://doi.org/10.2967/jnumed.108.059998.
- 105. Dobrucki LW, Sinusas AJ. PET and SPECT in cardiovascular molecular imaging. Nat Rev Cardiol. 2010;7(1):38-47. doi: https://doi.org/10.1038/nrcardio.2009.201.
- 106. Jaffer FA, Libby P, Weissleder R. Molecular imaging of cardiovascular disease. Circulation. 2007;116(9):1052-61.
- 107. Schindler TH, Schelbert HR, Quercioli A, Dilsizian V. Cardiac PET imaging for the detection and monitoring of coronary artery disease and microvascular health. JACC Cardiovasc Imaging. 2010;3(6):623-40. doi: https://doi.org/10.1016/j.jcmg.2010.04.007.
- 108. Kazakauskaitė E, Žaliaduonytė-Pekšienė D, Rumbinaitė E, Keršulis J, Kulakienė I, Jurkevičius R. Positron Emission Tomography in the Diagnosis and Management of Coronary Artery Disease. Medicina (Kaunas). 2018;54(3):47. doi: https://doi.org/10.3390/medicina54030047.
- 109. Khalaf S, Al-Mallah MH. Fluorodeoxyglucose Applications in Cardiac PET: Viability, Inflammation, Infection, and Beyond. Methodist Debakey Cardiovasc J. 2020;16(2):122-129. doi: https://doi.org/10.14797/mdcj-16-2-122.
- 110. Slomka P, Berman DS, Alexanderson E, Germano G. The role of PET quantification in cardiovascular imaging. Clin Transl Imaging. 2014;2(4):343-58. doi: https://doi.org/10.1007/s40336-014-0070-2.
- 111. Netala VR, Teertam SK, Li H, Zhang Z. A Comprehensive Review of Cardiovascular Disease Management: Cardiac Biomarkers, Imaging Modalities, Pharmacotherapy, Surgical Interventions, and Herbal Remedies. Cells. 2024;13(17):1471.
- 112. Campbell BA, Brown R, Lambertini A, Hofman MS, Bressel M, Seymour JF, et al. Are dynamic or fixed FDG-PET measures of disease of greater prognostic value in patients with relapsed/refractory diffuse large B-cell lymphoma undergoing autologous haematopoietic stem cell transplantation? Br J Haematol. 2023;201(3):502-9. doi: https://doi.org/10.1111/bjh.18644.
- 113. Wang J, Jin C, Cen P, Zhou R, Zhong Y, Tian M, et al. Future direction: molecular imaging-based stem cell research. Eur J Nucl Med Mol Imaging. 2025;52(5):1614-7. doi: https://doi.org/10.1007/s00259-025-07067-8.
- 114. Moskal P, Stępień EŁ. Prospects and Clinical Perspectives of Total-Body PET Imaging Using Plastic Scintillators. PET Clin. 2020;15(4):439-52. doi: https://doi.org/10.1016/j.cpet.2020.06.009.
- 115. Bockisch A, Freudenberg LS, Schmidt D, Kuwert T. Hybrid imaging by SPECT/CT and PET/CT: proven outcomes in cancer imaging. Semin Nucl Med. 2009;39(4):276-89. doi: https://doi.org/10.1053/j.semnuclmed.2009.03.003.
- 116. Hernot S, van Manen L, Debie P, Mieog JSD, Vahrmeijer AL. Latest developments in molecular tracers for fluorescence image-guided cancer surgery. Lancet Oncol. 2019;20(7):e354-67. doi: https://doi.org/10.1016/S1470-2045(19)30317-1.
- 117. Lheureux S, Denoyelle C, Ohashi PS, De Bono JS, Mottaghy FM. Molecularly targeted therapies in cancer: a guide for the nuclear medicine physician. Eur J Nucl Med Mol Imaging. 2017;44(Suppl 1):41-54. doi: https://doi.org/10.1007/s00259-017-3695-3.
- 118. Artesani A, Bruno A, Gelardi F, Chiti A. Empowering PET: harnessing deep learning for improved clinical insight. Eur Radiol Exp. 2024;8(1):17. doi: https://doi.org/10.1186/s41747-023-00413-1.
- 119. 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(9):2711-26. doi: https://doi.org/10.1007/s00259-021-05390-4.
- 120. Badawi RD, Shi H, Hu P, Chen S, Xu T, Price PM, et al. First Human Imaging Studies with the EXPLORER Total-Body PET Scanner. J Nucl Med. 2019;60(3):299-303. doi: https://doi.org/10.2967/jnumed.119.226498.
- 121. Lin KJ, Hsu WC, Hsiao IT, Wey SP, Jin LW, Skovronsky D, et al. Whole- -body biodistribution and brain PET imaging with [18F]AV-45, a novel amyloid imaging agent-a pilot study. Nucl Med Biol. 2010;37(4):497-508. doi: https://doi.org/10.1016/j.nucmedbio.2010.02.003.
- 122. Wildburger NC, Gyngard F, Guillermier C, Patterson BW, Elbert D, Mawuenyega KG, et al. Amyloid-Plaques in Clinical Alzheimer’s Disease Brain Incorporate Stable Isotope Tracer In Vivo and Exhibit Nanoscale Heterogeneity. Front Neurol. 2018;9:169. doi: https://doi.org/10.3389/fneur.2018.00169.
- 123. Bidesi NSR, Vang Andersen I, Windhorst AD, Shalgunov V, Herth MM. The role of neuroimaging in Parkinson’s disease. J Neurochem. 2021;159(4):660-89. doi: https://doi.org/10.1111/jnc.15516.
- 124. Hampel H, Toschi N, Babiloni C, Baldacci F, Black KL, Bokde ALW, et al. Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology. J Alzheimers Dis. 2018;64(s1):S47-105. doi: https://doi.org/10.3233/JAD-179932.
- 125. Bayer AJ. The role of biomarkers and imaging in the clinical diagnosis of dementia. Age Ageing. 2018;47(5): 641-3.
- 126. Di Meco A, Vassar R. Early detection and personalized medicine: Future strategies against Alzheimer’s disease. Prog Mol Biol Transl Sci. 2021;177:157-73. doi: https://doi.org/10.1016/bs.pmbts.2020.10.002.
- 127. Okamura N, Harada R, Furumoto S, Arai H, Yanai K, Kudo Y. Tau PET imaging in Alzheimer’s disease. Curr Neurol Neurosci Rep. 2014;14:1-7.
- 128. Leuzy A, Chiotis K, Lemoine L, Gillberg PG, Almkvist O, Rodriguez-Vieitez E, et al. Tau PET imaging in neurodegenerative tauopathies- -still a challenge. Mol Psychiatry. 2019;24(8):1112-34. doi: https://doi.org/10.1038/s41380-018-0342-8.
- 129. Saint-Aubert L, Lemoine L, Chiotis K, Leuzy A, Rodriguez-Vieitez E, Nordberg A. Tau PET imaging: present and future directions. Mol Neurodegener. 2017;12(1):1-21.
- 130. Fleisher AS, Pontecorvo MJ, Devous MD Sr, Lu M, Arora AK, Truocchio SP, et al. Positron Emission Tomography Imaging With [18F]flortaucipir and Postmortem Assessment of Alzheimer Disease Neuropathologic Changes. JAMA Neurol. 2020;77(7):829-39. doi: https://doi.org/10.1001/jamaneurol.2020.0528.
- 131. Rowe CC, Doré V, Krishnadas N, Burnham S, Lamb F, Mulligan R, et al. Tau imaging with 18F-MK6240 across the Alzheimer’s disease spectrum. medRxiv. 2022;2022-02.
- 132. Shah M, Catafau AM. Molecular imaging insights into neurodegeneration: focus on tau PET radiotracers. J Nucl Med. 2014;55(6):871-4.
- 133. Ossenkoppele R, Hansson O. Towards clinical application of tau PET tracers for diagnosing dementia due to Alzheimer’s disease. Alzheimers Dement. 2021;17(12):1998-2008. doi: https://doi.org/10.1002/alz.12356.
- 134. Petersen GC, Roytman M, Chiang GC, Li Y, Gordon ML, Franceschi AM. Overview of tau PET molecular imaging. Curr Opin Neurol. 2022;35(2):230-9. doi: https://doi.org/10.1097/WCO.0000000000001035.
- 135. Gibbons GS, Kim SJ, Robinson JL, Changolkar L, Irwin DJ, Shaw LM, et al. Detection of Alzheimer’s disease (AD) specific tau pathology with conformation-selective anti-tau monoclonal antibody in co-morbid frontotemporal lobar degeneration-tau (FTLD-tau). Acta Neuropathol Commun. 2019;7:1-12.
- 136. Armstrong MJ, Litvan I, Lang AE, Bak TH, Bhatia KP, Borroni B, et al. Criteria for the diagnosis of corticobasal degeneration. Neurology. 2013;80(5):496-503. doi: https://doi.org/10.1212/WNL.0b013 e31827f0fd1.
- 137. Williams DR, Lees AJ. Progressive supranuclear palsy: clinicopathological concepts and diagnostic challenges. Lancet Neurol. 2009;8(3):270-9. doi: https://doi.org/10.1016/S1474-4422(09)70042-0.
- 138. Groot C, Villeneuve S, Smith R, Hansson O, Ossenkoppele R. Tau PET Imaging in Neurodegenerative Disorders. J Nucl Med. 2022;63(Suppl 1):20S-6S. doi: https://doi.org/10.2967/jnumed.121.263196.
- 139. Wang YT, Edison P. Tau Imaging in Neurodegenerative Diseases Using Positron Emission Tomography. Curr Neurol Neurosci Rep. 2019;19(7):45. doi: https://doi.org/10.1007/s11910-019-0962-7.
- 140. Yoshida E, Tashima H, Akamatsu G, Iwao Y, Takahashi M, Yamashita T, et al. 245 ps-TOF brain-dedicated PET prototype with a hemispherical detector arrangement. Phys Med Biol. 2020;65(14):145008. doi: https://doi.org/10.1088/1361-6560/ab8c91.
- 141. González-Montoro A, Barberá J, Lucero A, Diaz K, Jiménez Serrano S, Sanchez D, et al. First results of the 4D-PET brain system. IEEE Trans Radiat Plasma Med Sci. 2024;8(7): 839-49.
- 142. Eubank WB, Mankoff DA. Evolving role of positron emission tomography in breast cancer imaging. Semin Nucl Med. 2005;35(2):84-99. doi: https://doi.org/10.1053/j.semnuclmed.2004.11.001.
- 143. Thompson C, Murthy K, Picard Y, Weinberg I, Mako R. Positron emission mammography (PEM): a promising technique for detecting breast cancer. IEEE Trans Nucl Sci. 1995;42(4):1012-7.
- 144. Moliner L, Gonzalez AJ, Soriano A, Sanchez F, Correcher C, Orero A, et al. Design and evaluation of the MAMMI dedicated breast PET. Med Phys. 2012;39(9):5393-404. doi: https://doi.org/10.1118/1.4742850.
- 145. Ming Y, Wu N, Qian T, Li X, Wan DQ, Li C, et al. Progress and Future Trends in PET/CT and PET/MRI Molecular Imaging Approaches for Breast Cancer. Front Oncol. 2020;10:1301. doi: https://doi.org/10.3389/fonc.2020.01301.
- 146. Hashimoto R, Akashi-Tanaka S, Watanabe C, Masuda H, Taruno K, Takamaru T, et al. Diagnostic performance of dedicated breast positron emission tomography. Breast Cancer. 2022;29(6):1013-21. doi: https://doi.org/10.1007/s12282-022-01381-x.
- 147. Karellas A, Vedantham S. Breast cancer imaging: a perspective for the next decade. Med Phys. 2008;35(11):4878-97. doi: https://doi.org/10.1118/1.2986144.
- 148. Han S, Choi JY. Impact of 18F-FDG PET, PET/CT, and PET/MRI on Staging and Management as an Initial Staging Modality in Breast Cancer: A Systematic Review and Meta-analysis. Clin Nucl Med. 2021;46(4):271-82. doi: https://doi.org/10.1097/RLU.0000000000003502.
- 149. Hadebe B, Harry L, Ebrahim T, Pillay V, Vorster M. The Role of PET/CT in Breast Cancer. Diagnostics (Basel). 2023;13(4):597. doi: https://doi.org/10.3390/diagnostics13040597.
- 150. Miyake KK, Nakamoto Y, Togashi K. Current status of dedicated breast PET imaging. Curr Radiol Rep. 2016;4:1-11.
- 151. Berg WA. Nuclear Breast Imaging: Clinical Results and Future Directions. J Nucl Med. 2016;57 Suppl 1:46S-52S. doi: https://doi.org/10.2967/jnumed.115.157891.
- 152. Narayanan D, Berg WA. Use of breast-specific PET scanners and comparison with MR imaging. Magn Reson Imaging Clin. 2018;26(2):265-72.
- 153. Narayanan D, Berg WA. Dedicated breast gamma camera imaging and breast PET: current status and future directions. PET Clinics; 2018;13(3):363-81.
- 154. Chen L, Yang Q, Bao J, Liu D, Huang X, Wang J. Direct comparison of PET/ CT and MRI to predict the pathological response to neoadjuvant chemotherapy in breast cancer: a meta-analysis. Sci Rep. 2017;7(1):8479. doi: https://doi.org/10.1038/s41598-017-08852-8.
- 155. Jones T, Townsend D. History and future technical innovation in positron emission tomography. J Med Imaging (Bellingham). 2017;4(1):011013. doi: https://doi.org/10.1117/1.JMI.4.1.011013.
- 156. Katal S, Eibschutz LS, Saboury B, Gholamrezanezhad A, Alavi A. Advantages and Applications of Total-Body PET Scanning. Diagnostics (Basel). 2022;12(2):426. doi: https://doi.org/10.3390/diagnostics12020426.
- 157. Spencer BA, Berg E, Schmall JP, Omidvari N, Leung EK, Abdelhafez YG, et al. Performance Evaluation of the uEXPLORER Total-Body PET/CT Scanner Based on NEMA NU 2-2018 with Additional Tests to Characterize PET Scanners with a Long Axial Field of View. J Nucl Med. 2021;62(6):861-70. doi: https://doi.org/10.2967/jnumed.120.250597.
- 158. Roncali E, Cherry SR. Application of silicon photomultipliers to positron emission tomography. Ann Biomed Eng. 2011;39(4):1358-77. doi: https://doi.org/10.1007/s10439-011-0266-9.
- 159. Lewellen TK. Recent developments in PET detector technology. Phys Med Biol. 2008;53(17):R287-317. doi: https://doi.org/10.1088/0031-9155/53/17/R01.
- 160. Badawi R, Liu W, Berg E, Lv Y, Xu T, An S, et al. Progress on the EXPLORER project: towards a total body PET scanner for human imaging. J Nuclear Med. 2018;59(supplement 1):223.
- 161. Rahmim A, Lodge MA, Karakatsanis NA, Panin VY, Zhou Y, McMillan A, et al. Dynamic whole-body PET imaging: principles, potentials and applications. Eur J Nucl Med Mol Imaging. 201;46(2):501-18. doi: https://doi.org/10.1007/s00259-018-4153-6.
- 162. Surti S, Pantel AR, Karp JS. Total Body PET: Why, How, What for? IEEE Trans Radiat Plasma Med Sci. 2020;4(3):283-92. doi: https://doi.org/10.1109/trpms.2020.2985403.
- 163. Meng X, Kong X, Xia L, Wu R, Zhu H, Yang Z. The Role of Total-Body PET in Drug Development and Evaluation: Status and Outlook. J Nucl Med. 2024;65(Suppl 1):46S-53S. doi: https://doi.org/10.2967/jnumed.123.266978.
- 164. Sun Y, Cheng Z, Qiu J, Lu W. Performance and application of the total-body PET/CT scanner: a literature review. EJNMMI Res. 2024;14(1):38. doi: https://doi.org/10.1186/s13550-023-01059-1.
- 165. Peruzzotti-Jametti L, Willis CM, Hamel R, Krzak G, Pluchino S. Metabolic Control of Smoldering Neuroinflammation. Front Immunol. 2021;12:705920. doi: https://doi.org/10.3389/fimmu.2021.705920.
- 166. Seifert R, Weber M, Kocakavuk E, Rischpler C, Kersting D. Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives. Semin Nucl Med. 2021;51(2):170-7. doi: https://doi.org/10.1053/j.semnuclmed.2020.08.003.
- 167. Reader AJ, Pan B. AI for PET image reconstruction. Br J Radiol. 2023;96(1150):20230292. doi: https://doi.org/10.1259/bjr.20230292.
- 168. Reader AJ, Corda G, Mehranian A, da Costa-Luis C, Ellis S, Schnabel JA. Deep learning for PET image reconstruction. IEEE Trans Radiat Plasma Med Sci. 2020;5(1): 1-25.
- 169. Reader AJ, Schramm G. Artificial Intelligence for PET Image Reconstruction. J Nucl Med. 2021;62(10):133-3. doi: https://doi.org/10.2967/jnumed.121.262303.
- 170. Keshavarz A, Rostami H, Jafari E, Assadi M. Artificial intelligence-based PET image acquisition and reconstruction. Clin Transl Imaging. 2022;10(4):343-53.
- 171. Lindgren Belal S, Larsson M, Holm J, Buch-Olsen KM, Sörensen J, Bjartell A, et al. Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index. Eur J Nucl Med Mol Imaging. 2023;50(5):1510-20. doi: https://doi.org/10.1007/s00259-023-06108-4.
- 172. Ng ACT, van Rosendael AR, Bax JJ. Automated artificial intelligence quantification of aortic atherosclerotic calcifications by 18F-sodium fluoride PET/CT. J Nucl Cardiol. 2022;29(4):2011-2. doi: https://doi.org/10.1007/s12350-021-02700-z.
- 173. Gålne A, Enqvist O, Sundlöv A, Valind K, Minarik D, Trägårdh E. AI-based quantification of whole-body tumour burden on somatostatin receptor PET/CT. Eur J Hybrid Imaging. 2023;7(1):14. doi: https://doi.org/10.1186/s41824-023-00172-7.
- 174. Gong K, Guan J, Kim K, Zhang X, Yang J, Seo Y, et al. Iterative PET Image Reconstruction Using Convolutional Neural Network Representation. IEEE Trans Med Imaging. 2019;38(3):675-85. doi: https://doi.org/10.1109/ TMI.2018.2869871.
- 175. Herraiz JL, España S, Vaquero JJ, Desco M, Udías JM. FIRST: Fast Iterative Reconstruction Software for (PET) tomography. Phys Med Biol. 2006;51(18):4547-65. doi: https://doi.org/10.1088/0031-9155/51/18/007.
- 176. Hutton B, Nuyts J, Zaidi H. Iterative reconstruction methods. In: Zaidi H, editor. Quantitative Analysis in Nuclear Medicine Imaging. Boston, MA: Springer; 2006.
- 177. Riddell C, Carson RE, Carrasquillo JA, Libutti SK, Danforth DN, Whatley M et al. Noise reduction in oncology FDG PET images by iterative reconstruction: a quantitative assessment. J Nucl Med. 2001;42(9):1316-23.
- 178. Gong K, Cherry SR, Qi J. On the assessment of spatial resolution of PET systems with iterative image reconstruction. Phys Med Biol. 2016;61(5):N193-202. doi: https://doi.org/10.1088/0031-9155/61/5/N193.
- 179. Hamill J, Bruckbauer T. Iterative reconstruction methods for high-throughput PET tomographs. Phys Med Biol. 2002;47(15):2627-36. doi: https://doi.org/10.1088/0031-9155/47/15/305.
- 180. Cui J, Gong K, Guo N, Wu C, Meng X, Kim K, et al. PET image denoising using unsupervised deep learning. Eur J Nucl Med Mol Imaging. 2019;46(13):2780-9. doi: https://doi.org/10.1007/s00259-019-04468-4.
- 181. Liu J, Malekzadeh M, Mirian N, Song TA, Liu C, Dutta J. Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement. PET Clin. 2021;16(4):553-76. doi: https://doi.org/10.1016/j.cpet.2021.06.005.
- 182. De Summa M, Ruggiero MR, Spinosa S, Iachetti G, Esposito S, Annunziata S, et al. Denoising approaches by SubtlePET™ artificial intelligence in positron emission tomography (PET) for clinical routine application. Clin Transl Imaging. 2024;1-10. doi: https://doi.org/10.1007/s40336-024-00625-4.
- 183. Shiri I, Salimi Y, Hervier E, Pezzoni A, Sanaat A, Mostafaei S, et al. Artificial Intelligence-Driven Single-Shot PET Image Artifact Detection and Disentanglement: Toward Routine Clinical Image Quality Assurance. Clin Nucl Med. 2023;48(12):1035–46. doi: https://doi.org/10.1097/RLU.0000000000004912.
- 184. Jo YH, Yoo SJ, Bae SH, Seon JR, Kim SH, Lee WJ. The Correction Effect of Motion Artifacts in PET/CT Image using System. J Korean Radiol Soc. 2024;18(1):45-52.
- 185. Song TA, Chowdhury SR, Yang F, Dutta J. PET image super-resolution using generative adversarial networks. Neural Netw. 2020;125:83-91. doi: https://doi.org/10.1016/j.neunet.2020.01.029.
- 186. Yang G, Li C, Yao Y, Wang G, Teng Y. Quasi-supervised learning for super-resolution PET. Comput Med Imaging Graph. 2024;113:102351. doi: https://doi.org/10.1016/j.compmedimag.2024.102351.
- 187. Yoshimura T, Hasegawa A, Kogame S, Magota K, Kimura R, Watanabe S, et al. Medical Radiation Exposure Reduction in PET via Super-Resolution Deep Learning Model. Diagnostics (Basel). 2022;12(4):872. doi: https://doi.org/10.3390/diagnostics12040872.
- 188. Kruzhilov I, Kudin S, Vetoshkin L, Sokolova E, Kokh V. Whole-body PET image denoising for reduced acquisition time. Front Med (Lausanne). 2024;11:1415058. doi: https://doi.org/10.3389/fmed.2024.1415058.
- 189. Moskal P, Kowalski P, Shopa RY, Raczyński L, Baran J, Chug N, et al. Simulating NEMA characteristics of the modular total-body J-PET scanner-an economic total-body PET from plastic scintillators. Phys Med Biol. 2021;66(17): 175015. doi: https://doi.org/10.1088/1361-6560/ac16bd.
- 190. Moskal P, Stepien E, Khreptak A. A vision to increase the availability of PET diagnostics in low- and medium-income countries by combining a low-cost modular J-PET tomograph with the 44Ti/44Sc generator. Bio-Algorithms and Med-Systems. 2024;20(special issue):55-62. doi: https://doi.org/10.5604/01.3001.0054.9273.
- 191. Hellwig D, Hellwig NC, Boehner S, Fuchs T, Fischer R, Schmidt D. Artificial Intelligence and Deep Learning for Advancing PET Image Reconstruction: State-of-the-Art and Future Directions. Nuklearmedizin. 2023;62(6):334-42. doi: https://doi.org/10.1055/a-2198-0358.
- 192. Mehranian A, Wollenweber SD, Walker MD, Bradley KM, Fielding PA, Su KH, et al. Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise. Eur J Nucl Med Mol Imaging. 2022;49(2):539-49. doi: https://doi.org/10.1007/s00259- 021-05478-x.
- 193. Chan C, Zhou J, Yang L, Qi W, Asma E. Noise to noise ensemble learning for PET image denoising. In: 2019 IEEE nuclear science symposium and medical imaging conference (NSS/MIC): 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2019); 2019 Oct 26-2 Nov; Manchester, United Kingdom. New York: IEEE; 2019. p. 1-3.
- 194. Rahmim A, Rousset O, Zaidi H. Strategies for Motion Tracking and Correction in PET. PET Clin. 2007;2(2):251-66. doi: https://doi.org/10.1016/j.cpet.2007.08.002.
- 195. Hagiwara A, Fujita S, Ohno Y, Aoki S. Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence. Invest Radiol. 2020;55(9):601-16. doi: https://doi.org/10.1097/RLI.0000000000000666.
- 196. Mali SA, Ibrahim A, Woodruff HC, Andrearczyk V, Müller H, Primakov S, et al. Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods. J Pers Med. 2021;11(9):842. doi: https://doi.org/10.3390/jpm11090842.
- 197. Papadimitroulas P, Brocki L, Christopher Chung N, Marchadour W, Vermet F, Gaubert L, et al. Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization. Phys Med. 2021;83:108-21. doi: https://doi.org/10.1016/j.ejmp.2021.03.009.
- 198. Li T, Sahu AK, Talwalkar A, Smith V. Federated learning: Challenges, methods, and future directions. IEEE Signal Process Mag. 2020;37(3):50-60.
- 199. Li L, Fan Y, Tse M, Lin KY. A review of applications in federated learning. Comput Ind Eng. 2020;149:106854. doi: https://doi.org/10.1016/j.cie.2020.106854.
- 200. Kairouz P, McMahan HB, Avent B, Bellet A, Bennis M, Bhagoji AN, et al. Advances and open problems in federated learning. Found Trends Mach Learn. 2021;14(1-2):1-210.
- 201. Zhang C, Xie Y, Bai H, Yu B, Li W, Gao Y. A survey on federated learning. Knowl.-Based Syst. 2021;216:106775.
- 202. Mammen PM. Federated learning: Opportunities and challenges. arXiv preprint. 2021;arXiv:2101.05428. doi: https://doi.org/10.48550/arXiv.2101.05428.
- 203. Gunning D, Stefik M, Choi J, Miller T, Stumpf S, Yang GZ. XAI-Explainable artificial intelligence. Sci Robot. 2019;4(37):eaay7120. doi: https://doi.org/10.1126/scirobotics.aay7120.
- 204. Samek W, Müller KR. Towards explainable artificial intelligence. In: Samek W, Montavon G, Vedaldi A, Hansen LK, Muller K-R, editors. Explainable AI: interpreting, explaining and visualizing deep learning. Cham: Springer; 2019. p. 5-22.
- 205. Xu F, Uszkoreit H, Du Y, Fan W, Zhao D, Zhu J. Explainable AI: A brief survey on history, research areas, approaches and challenges. In: Tang J, Kan MY, Zhao D, Li S, Zan H, editors. Natural language processing and Chinese computing: 8th cCF international conference, NLPCC; 2019 Oct 9-14; Dunhuang, China. Berlin: Springer; 2019, p. 563–574.
- 206. Dwivedi R, Dave D, Naik H, Singhal S, Rana O, Patel P, et al. Explainable AI (XAI): Core ideas, techniques, and solutions. ACM Comput Surv. 2023;55(9):1-33.
- 207. Borrelli P, Ly J, Kaboteh R, Ulén J, Enqvist O, Trägårdh E, et al. AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients. EJNMMI Phys. 2021;8(1):32. doi: https://doi.org/10.1186/s40658-021-00376-5.
- 208. Leal JP, Rowe SP, Stearns V, Connolly RM, Vaklavas C, Liu MC, et al. Automated lesion detection of breast cancer in [18F] FDG PET/CT using a novel AI-Based workflow. Front Oncol. 2022;12:1007874. doi: https://doi.org/10.3389/fonc.2022.1007874.
- 209. Hein SP, Schultheiss M, Gafita A, Zaum R, Yagubbayli F, Tauber R, et al. Towards AI Lesion Tracking in PET/CT Imaging: A Siamese-based CNN Pipeline applied on PSMA PET/CT Scans. arXiv preprint. 2024; arXiv:2406.09327.
- 210. Pfaehler E, Mesotten L, Kramer G, Thomeer M, Vanhove K, de Jong J, et al. Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET. EJNMMI Res. 2021;11(1):4. doi: https://doi.org/10.1186/s13550-020-00744-9.
- 211. Yousefirizi F, Jha AK, Brosch-Lenz J, Saboury B, Rahmim A. Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging. PET Clin. 2021;16(4):577-96. doi: https://doi.org/10.1016/j.cpet.2021.06.001.
- 212. Carlsen EA, Lindholm K, Hindsholm A, Gæde M, Ladefoged CN, Loft M, et al. A convolutional neural network for total tumor segmentation in [64Cu]Cu-DOTATATE PET/CT of patients with neuroendocrine neoplasms. EJNMMI Res. 2022;12(1):30. doi: https://doi.org/10.1186/s13550-022-00901-2.
- 213. Shiyam Sundar LK, Yu J, Muzik O, Kulterer OC, Fueger B, Kifjak D, et al. Fully Automated, Semantic Segmentation of Whole-Body 18F-FDG PET/CT Images Based on Data-Centric Artificial Intelligence. J Nucl Med. 2022;63(12):1941-8. doi: https://doi.org/10.2967/jnumed.122.264063.
- 214. Polymeri E, Kjölhede H, Enqvist O, Ulén J, Poulsen MH, Simonsen JA, et al. Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients. Scand J Urol. 2021;55(6):427-33. doi: https://doi.org/10.1080/21681805.2021.1977845.
- 215. Katsari K, Penna D, Arena V, Polverari G, Ianniello A, Italiano D, et al. Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment. EJNMMI Phys. 2021;8(1):25. doi: https://doi.org/10.1186/s40658-021-00374-7.
- 216. Lin A, Kolossváry M, Motwani M, Išgum I, Maurovich-Horvat P, Slomka PJ, et al. Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease. Radiol Cardiothorac Imaging. 2021;3(1):e200512. doi: https://doi.org/10.1148/ryct.2021200512.
- 217. Lee JW, Lee SM. Radiomics in Oncological PET/CT: Clinical Applications. Nucl Med Mol Imaging. 2018;52(3):170-89. doi:https://doi.org/10.1007/ s13139-017-0500-y.
- 218. Krajnc D, Papp L, Nakuz TS, Magometschnigg HF, Grahovac M, Spielvogel CP, et al. Breast Tumor Characterization Using [18F]FDG-PET/CT Imaging Combined with Data Preprocessing and Radiomics. Cancers (Basel). 2021;13(6):1249. doi: https://doi.org/10.3390/cancers13061249.
- 219. Oikonomou A, Khalvati F, Tyrrell PN, Haider MA, Tarique U, Jimenez-Juan L, et al. Radiomics analysis at PET/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy. Sci Rep. 2018;8(1):4003. doi: https://doi.org/10.1038/ s41598-018-22357-y.
- 220. Manafi-Farid R, Askari E, Shiri I, Pirich C, Asadi M, Khateri M, et al. [18F]FDG-PET/CT Radiomics and Artificial Intelligence in Lung Cancer: Technical Aspects and Potential Clinical Applications. Semin Nucl Med. 2022;52(6):759-80. doi: https://doi.org/10.1053/j.semnuclmed.2022.04.004.
- 221. Ghezzo S, Bharathi PG, Duan H, Mapelli P, Sorgo P, Davidzon GA, et al. The Challenge of External Generalisability: Insights from the Bicentric Validation of a [68Ga]Ga-PSMA-11 PET Based Radiomics Signature for Primary Prostate Cancer Characterisation Using Histopathology as Reference. Cancers (Basel). 2024;16(23):4103. doi: https://doi.org/10.3390/cancers16234103.
- 222. Mu W, Qi J, Lu H, Schabath M, Balagurunathan Y, Tunali I, et al. Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients. Medical Imaging 2018: Computer-Aided Diagnosis, SPIE. 2018:854-860.
- 223. Mawlawi O, Townsend DW. Multimodality imaging: an update on PET/CT technology. Eur J Nucl Med Mol Imaging. 2009;36 Suppl 1:S15-29. doi: https://doi.org/10.1007/s00259-008-1016-6.
- 224. Eze C, Schmidt-Hegemann NS, Sawicki LM, Kirchner J, Roengvoraphoj O, Käsmann L, et al. PET/CT imaging for evaluation of multimodal treatment efficacy and toxicity in advanced NSCLC-current state and future directions. Eur J Nucl Med Mol Imaging. 2021;48(12):3975-89. doi: https://doi.org/10.1007/s00259-021-05211-8.
- 225. Guo H, Xu K, Duan G, Wen L, He Y. Progress and future prospective of FDG-PET/CT imaging combined with optimized procedures in lung cancer: toward precision medicine. Ann Nucl Med. 2022;36(1):1-14. doi: https://doi.org/10.1007/s12149-021-01683-8.
- 226. Kretschmer J, Pellico J, Prytula-Kurkunova A, De Rosales RTM, Martins AF. Advances in PET/MRI and Probe Development for Biomedical Precision Imaging Applications. In: CFGC, editor. Lanthanide and Other Transition Metal Ion Complexes and Nanoparticles in Magnetic Resonance Imaging. Boca Raton: CRC Press; 2024, p. 367-98.
- 227. Huo E, Wilson DM, Eisenmenger L, Hope TA. The Role of PET/MR Imaging in Precision Medicine. PET Clin. 2017;12(4):489-501. doi: https://doi.org/10.1016/j.cpet.2017.05.006.
- 228. Lamb J, Holland JP. Advanced Methods for Radiolabeling Multimodality Nanomedicines for SPECT/MRI and PET/MRI. J Nucl Med. 2018;59(3):382-9. doi: https://doi.org/10.2967/jnumed.116.187419.
- 229. Yang CT, Ghosh KK, Padmanabhan P, Langer O, Liu J, Eng DNC, et al. PET-MR and SPECT-MR multimodality probes: Development and challenges. Theranostics. 2018;8(22):6210-32. doi: https://doi.org/10.7150/ thno.26610.
- 230. Long NM, Smith CS. Causes and imaging features of false positives and false negatives on 18 F-PET/CT in oncologic imaging. Insights Imaging. 2011;2(6):67998. doi: https://doi.org/10.1007/s13244-010-0062-3.
- 231. Carter KR, Kotlyarov E. Common causes of false positive F18 FDG PET/CT scans in oncology. Braz Arch Biol Technol. 2007;50:29-35.
- 232. Lakhani A, Khan SR, Bharwani N, Stewart V, Rockall AG, Khan S, et al. FDG PET/CT Pitfalls in Gynecologic and Genitourinary Oncologic Imaging. Radiographics. 2017;37(2):577-94. doi: https://doi.org/10.1148/ rg.2017160059.
- 233. Chang JM, Lee HJ, Goo JM, Lee HY, Lee JJ, Chung JK, et al. False positive and false negative FDG-PET scans in various thoracic diseases. Korean J Radiol. 2006;7(1):57-69. doi: https://doi.org/10.3348/kjr.2006.7.1.57.
- 234. Bai JW, Qiu SQ, Zhang GJ. Molecular and functional imaging in cancer-targeted therapy: current applications and future directions. Signal Transduct Target Ther. 2023;8(1):89. doi: https://doi.org/10.1038/s41392-023-01366-y.
- 235. Peterson TE, Manning HC. Molecular imaging: 18F-FDG PET and a whole lot more. J Nucl Med Technol. 2009;37(3):151-61. doi: https://doi.org/10.2967/jnmt.109.062729.
- 236. Buck AK, Halter G, Schirrmeister H, Kotzerke J, Wurziger I, Glatting G, et al. Imaging proliferation in lung tumors with PET: 18F-FLT versus 18F-FDG. J Nucl Med. 2003;44(9):1426-31.
- 237. Barthel H, Cleij MC, Collingridge DR, Hutchinson OC, Osman S, He Q, et al. 3’-deoxy-3’-[18F]fluorothymidine as a new marker for monitoring tumor response to antiproliferative therapy in vivo with positron emission tomography. Cancer Res. 2003;63(13):3791-8.
- 238. Deppen SA, Blume JD, Kensinger CD, Morgan AM, Aldrich MC, Massion PP, et al. Accuracy of FDG-PET to diagnose lung cancer in areas with infectious lung disease: a meta-analysis. JAMA. 2014;312(12):1227-36. doi: https://doi.org/10.1001/jama.2014.11488.
- 239. Bag AK, Wing MN, Sabin ND, Hwang SN, Armstrong GT, Han Y, et al. 11C-Methionine PET for Identification of Pediatric High-Grade Glioma Recurrence. J Nucl Med. 2022;63(5):664-71. doi: https://doi.org/10.2967/jnumed.120.261891.
- 240. Dunet V, Pomoni A, Hottinger A, Nicod-Lalonde M, Prior JO. Performance of 18F-FET versus 18F-FDG-PET for the diagnosis and grading of brain tumors: systematic review and meta-analysis. Neuro Oncol. 2016;18(3):426-34. doi: https://doi.org/10.1093/neuonc/nov148.
- 241. Hutterer M, Nowosielski M, Putzer D, Jansen NL, Seiz M, Schocke M, et al. [18F]-fluoro-ethyl-L-tyrosine PET: a valuable diagnostic tool in neuro-oncology, but not all that glitters is glioma. Neuro Oncol. 2013;15(3):341-51. doi: https://doi.org/10.1093/neuonc/nos300.
- 242. Moerlein SM, Schwarz SW, Dehdashti F. Beyond FDG: Novel radiotracers for PET imaging of melanoma and sarcoma. PET/CT and PET/MR in Melanoma and Sarcoma. 2021;201-31. doi: https://doi.org/10.1007/978-3-030-60429-5_10.
- 243. Mach RH, Dehdashti F, Wheeler KT. PET Radiotracers for Imaging the Proliferative Status of Solid Tumors. PET Clin. 2009;4(1):1-15. doi: https://doi.org/10.1016/j.cpet.2009.04.012.
- 244. Pantel AR, Ackerman D, Lee SC, Mankoff DA, Gade TP. Imaging Cancer Metabolism: Underlying Biology and Emerging Strategies. J Nucl Med. 2018;59(9):1340-9. doi: https://doi.org/10.2967/jnumed.117.199869.
- 245. Kwee SA, Wong L, Chan OTM, Kalathil S, Tsai N. PET/CT with 18F Fluorocholine as an Imaging Biomarker for Chronic Liver Disease: A Preliminary Radiopathologic Correspondence Study in Patients with Liver Cancer. Radiology. 2018;287(1):294-302. doi: https://doi.org/10.1148/radiol.2018171333.
- 246. Kwee SA, Lim J, Watanabe A, Kromer-Baker K, Coel MN. Prognosis Related to Metastatic Burden Measured by ¹⁸F-Fluorocholine PET/CT in Castration-Resistant Prostate Cancer. J Nucl Med. 2014;55(6):905–10. doi: https://doi.org/10.2967/jnumed.113.135194.
- 247. Xu Z, Li XF, Zou H, Sun X, Shen B. 18F-Fluoromisonidazole in tumor hypoxia imaging. Oncotarget. 2017;8(55):94969-79. doi: https://doi.org/10.18632/oncotarget.21662.
- 248. Muzi M, Peterson LM, O’Sullivan JN, Fink JR, Rajendran JG, McLaughlin LJ, et al. 18F-Fluoromisonidazole Quantification of Hypoxia in Human Cancer Patients Using Image-Derived Blood Surrogate Tissue Reference Regions. J Nucl Med. 2015;56(8):1223-8. doi: https://doi.org/10.2967/jnumed.115.158717.
- 249. Adnan A, Basu S. Somatostatin Receptor Targeted PET-CT and Its Role in the Management and Theranostics of Gastroenteropancreatic Neuroendocrine Neoplasms. Diagnostics (Basel). 2023;13(13):2154. doi: https://doi.org/10.3390/diagnostics13132154.
- 250. Uemura M, Watabe T, Hoshi S, Tanji R, Yaginuma K, Kojima Y. The current status of prostate cancer treatment and PSMA theranostics. Ther Adv Med Oncol. 2023;15:17588359231182293. doi: https://doi.org/10.1177/17588359231182293.
- 251. Fortunati E, Argalia G, Zanoni L, Fanti S, Ambrosini V. New PET Radiotracers for the Imaging of Neuroendocrine Neoplasms. Curr Treat Options Oncol. 2022;23(5):703-20. doi: https://doi.org/10.1007/s11864-022-00967-z.
- 252. Weiner AB, Agrawal R, Valle LF, Sonni I, Kishan AU, Rettig MB, et al. Impact of PSMA PET on Prostate Cancer Management. Curr Treat Options Oncol. 2024;25(2):191-205. doi: https://doi.org/10.1007/s11864-024-01181-9.
- 253. Dhoundiyal S, Srivastava S, Kumar S, Singh G, Ashique S, Pal R, et al. Radiopharmaceuticals: navigating the frontier of precision medicine and therapeutic innovation. Eur J Med Res. 2024;29(1):26. doi: https://doi.org/10.1186/s40001-023-01627-0.
- 254. White Al-Habeeb N, Kulasingam V, Diamandis EP, Yousef GM, Tsongalis GJ, Vermeulen L, et al. The Use of Targeted Therapies for Precision Medicine in Oncology. Clin Chem. 2016;62(12):1556-64. https://doi.org/doi:10.1373/clinchem.2015.247882.
- 255. Weber WA, Barthel H, Bengel F, Eiber M, Herrmann K, Schäfers M. What Is Theranostics? J Nucl Med. 2023;64(5):669-70. doi: https://doi.org/10.2967/jnumed.123.265670.
- 256. Gomes Marin JF, Nunes RF, Coutinho AM, Zaniboni EC, Costa LB, Barbosa FG, et al. Theranostics in Nuclear Medicine: Emerging and Re-emerging Integrated Imaging and Therapies in the Era of Precision Oncology. Radiographics. 2020;40(6):1715-40. doi: https://doi.org/10.1148/rg.2020200021.
- 257. Burkett BJ, Bartlett DJ, McGarrah PW, Lewis AR, Johnson DR, Berberoğlu K, et al. A Review of Theranostics: Perspectives on Emerging Approaches and Clinical Advancements. Radiol Imaging Cancer. 2023;5(4):e220157. doi: https://doi.org/10.1148/rycan.220157.
- 258. Anderson RC, Velez EM, Desai B, Jadvar H. Management Impact of 68Ga-DOTATATE PET/CT in Neuroendocrine Tumors. Nucl Med Mol Imaging. 2021;55(1):31-7. doi: https://doi.org/10.1007/s13139-020-00677-0.
- 259. Deppen SA, Liu E, Blume JD, Clanton J, Shi C, Jones-Jackson LB, et al. Safety and Efficacy of 68Ga-DOTATATE PET/CT for Diagnosis, Staging, and Treatment Management of Neuroendocrine Tumors. J Nucl Med. 2016;57(5):708-14. doi: https://doi.org/10.2967/jnumed.115.163865.
- 260. Mitjavila M, Jimenez-Fonseca P, Belló P, Pubul V, Percovich JC, Garcia-Burillo A, et al. Efficacy of [177Lu]Lu-DOTATATE in metastatic neuroendocrine neoplasms of different locations: data from the SEPTRALU study. Eur J Nucl Med Mol Imaging. 2023;50(8):2486-500. doi: https://doi.org/10.1007/s00259-023-06166-8.
- 261. Fendler WP, Calais J, Eiber M, Flavell RR, Mishoe A, Feng FY, et al. Assessment of 68Ga-PSMA-11 PET Accuracy in Localizing Recurrent Prostate Cancer: A Prospective Single-Arm Clinical Trial. JAMA Oncol. 2019;5(6):856-63. doi: https://doi.org/10.1001/jamaoncol.2019.0096.
- 262. Bois F, Noirot C, Dietemann S, Mainta IC, Zilli T, Garibotto V, et al. [68Ga] Ga-PSMA-11 in prostate cancer: a comprehensive review. Am J Nucl Med Mol Imaging. 2020;10(6):349-74.
- 263. Rahbar K, Schmidt M, Heinzel A, Eppard E, Bode A, Yordanova A, et al. Response and Tolerability of a Single Dose of 177Lu-PSMA-617 in Patients with Metastatic Castration-Resistant Prostate Cancer: A Multicenter Retrospective Analysis. J Nucl Med. 2016;57(9):1334-8. doi: https://doi.org/10.2967/jnumed.116.173757.
- 264. Cattaneo M, Froio A, Gallino A. Cardiovascular Imaging and Theranostics in Cardiovascular Pharmacotherapy. Eur Cardiol. 2019;14(1):62-4. doi: https://doi.org/10.15420/ecr.2019.6.1.
- 265. Huang R, Hu Q, Ko CN, Tang FK, Xuan S, Wong HM, et al. Nano-based theranostic approaches for infection control: current status and perspectives. Mater Chem Front. 2024;8(1):9-40.
- 266. Rong J, Haider A, Jeppesen TE, Josephson L, Liang SH. Radiochemistry for positron emission tomography. Nat Commun. 2023;14(1):3257. doi: https://doi.org/10.1038/s41467-023-36377-4.
- 267. Scheinberg DA, McDevitt MR. Actinium-225 in targeted alpha-particle therapeutic applications. Curr Radiopharm. 2011;4(4):306-20. doi: https://doi.org/10.2174/1874471011104040306.
- 268. Jeelani S, Reddy RJ, Maheswaran T, Asokan G, Dany A, Anand B. Theranostics: A treasured tailor for tomorrow. J Pharm Bioallied Sci. 2014;6(Suppl 1):S6-8.
- 269. Ataeinia B, Heidari P. Artificial Intelligence and the Future of Diagnostic and Therapeutic Radiopharmaceutical Development: In Silico Smart Molecular Design. PET Clin. 2021;16(4):513-23. doi: https://doi.org/10.1016/j.cpet.2021.06.008.
- 270. McGale JP, Howell HJ, Beddok A, Tordjman M, Sun R, Chen D, et al. Integrating Artificial Intelligence and PET Imaging for Drug Discovery: A Paradigm Shift in Immunotherapy. Pharmaceuticals (Basel). 2024;17(2):210. doi: https://doi.org/10.3390/ph17020210.
- 271. Kang SK, Choi H, Lee JS. Alzheimer’s Disease Neuroimaging Initiative. Translating amyloid PET of different radiotracers by a deep generative model for interchangeability. Neuroimage. 2021;232:117890. doi: https://doi.org/10.1016/j.neuroimage.2021.117890.
- 272. Webb EW, Scott PJ. Potential applications of artificial intelligence and machine learning in radiochemistry and radiochemical engineering. PET Clin. 2021;16(4):525.
- 273. Rokuss M, Kovacs B, Kirchhoff Y, Xiao S, Ulrich C, Klaus H, et al. From FDG to PSMA: A Hitchhiker’s Guide to Multitracer, Multicenter Lesion Segmentation in PET/CT Imaging. arXiv preprint. 2024;arXiv:2409.09478.
- 274. Siegel JA, Thomas SR, Stubbs JB, Stabin MG, Hays MT, Koral KF, et al. MIRD pamphlet no. 16: Techniques for quantitative radiopharmaceutical biodistribution data acquisition and analysis for use in human radiation dose estimates. J Nucl Med. 1999;40(2):37S-61S.
- 275. Bednarz B. Theranostics and Patient-Specific Dosimetry. Semin Radiat Oncol. 2023;33(3):317-26. doi: https://doi.org/10.1016/j.semradonc.2023.03.011.
- 276. Kesner AL, Brosch-Lenz J, Gear J, Lassmann M. Dosimetry Software for Theranostic Applications: Current Capabilities and Future Prospects. J Nucl Med. 2025;66(2):166-72. doi: https://doi.org/10.2967/jnumed.124.268998.
- 277. Berman DS, Maddahi J, Tamarappoo BK, Czernin J, Taillefer R, Udelson JE, et al. Phase II safety and clinical comparison with single-photon emission computed tomography myocardial perfusion imaging for detection of coronary artery disease: flurpiridaz F 18 positron emission tomography. J Am Coll Cardiol. 2013;61(4):469-77. doi: https://doi.org/10.1016/j.jacc.2012.11.022.
- 278. Builoff V, Lemley M, Fujito H, Miller R, Ramirez G, Kavanagh P, et al. Automated quantitation of 18F-flurpiridaz PET MPI and its diagnostic performance of coronary artery disease. Eur Heart J Cardiovasc Imaging. 2024;25(Suppl 1):jeae142-086.
- 279. Maddahi J, Agostini D, Bateman TM, Bax JJ, Beanlands RSB, Berman DS, et al. Flurpiridaz F-18 PET Myocardial Perfusion Imaging in Patients With Suspected Coronary Artery Disease. J Am Coll Cardiol. 2023;82(16):1598-1610. doi: https://doi.org/10.1016/j.jacc.2023.08.016.
- 280. Radaram B, Glazer SE, Yang P, Li CW, Hung MC, Gammon ST, et al. Evaluation of 89Zr-Labeled Anti-PD-L1 Monoclonal Antibodies Using DFO and Novel HOPO Analogues as Chelating Agents for Immuno-PET. ACS Omega. 2023;8(19):17181-94. doi: https://doi.org/10.1021/acsomega.3c01547.
- 281. Tinianow JN, Gill HS, Ogasawara A, Flores JE, Vanderbilt AN, Luis E, Vandlen R, et al. Site-specifically 89Zr-labeled monoclonal antibodies for ImmunoPET. Nucl Med Biol. 2010;37(3):289-97. doi: https://doi.org/10.1016/j.nucmedbio.2009.11.010.
- 282. Tarkin JM, Joshi FR, Evans NR, Chowdhury MM, Figg NL, Shah AV, et al. Detection of Atherosclerotic Inflammation by 68Ga-DOTATATE PET Compared to [18F]FDG PET Imaging. J Am Coll Cardiol. 2017;69(14):1774-91. doi: https://doi.org/10.1016/j.jacc.2017.01.060.
- 283. Blasi F, Oliveira BL, Rietz TA, Rotile NJ, Day H, Naha PC, et al. Radiation Dosimetry of the Fibrin-Binding Probe ⁶⁴Cu-FBP8 and Its Feasibility for PET Imaging of Deep Vein Thrombosis and Pulmonary Embolism in Rats. J Nucl Med. 2015;56(7):1088–93. doi: https://doi.org/10.2967/jnumed.115.157982.
- 284. Vilche M, Reyes AL, Vasilskis E, Oliver P, Balter H, Engler H. ⁶⁸Ga-NOTA-UBI-29-41 as a PET Tracer for Detection of Bacterial Infection. J Nucl Med. 2016;57(4):622-7. doi: https://doi.org/10.2967/jnumed.115.161265.
- 285. Boddeti DK, Kumar V. Evaluation of 68Ga-DOTA-Ubiquicidin (29-41) for imaging Staphylococcus aureus (Staph A) infection and turpentine-induced inflammation in a preclinical setting. World J Nucl Med. 2021;20(3):266-72. doi: https://doi.org/10.4103/wjnm.WJNM_103_20.
- 286. Ebenhan T, Mokaleng BB, Venter JD, Kruger HG, Zeevaart JR, Sathekge M. Preclinical Assessment of a 68Ga-DOTA-Functionalized Depsipeptide as a Radiodiagnostic Infection Imaging Agent. Molecules. 2017;22(9):1403. doi: https://doi.org/10.3390/molecules22091403.
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