Amani Shyaa Jebur (1)
Nuclear physics has fundamentally transformed medical diagnostics through Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET), which provide functional and physiological information beyond conventional imaging modalities. This study conducts a comprehensive comparative analysis of SPECT and PET by examining their nuclear physics principles, technical instrumentation, image quality parameters, and clinical applications. Employing systematic literature review methodology, the research synthesizes peer-reviewed articles from major scientific databases published between 2015 and 2025. The analysis reveals that PET demonstrates superior spatial resolution (4-7 mm versus 8-12 mm), enhanced sensitivity (1-2% compared to 0.01-0.03%), and greater quantitative accuracy due to coincidence detection and higher photon energy (511 keV). Conversely, SPECT maintains advantages in cost-effectiveness, radiotracer accessibility through on-site synthesis, and longer half-lives suitable for extended protocols. This research integrates physical, instrumental, and patient-dependent factors influencing image quality while exploring emerging developments including hybrid imaging and artificial intelligence applications. The findings establish evidence-based criteria for modality selection, emphasizing the complementary nature of these techniques in advancing precision diagnostics across oncology, cardiology, and neurology.Keywords : Nuclear Medicine Imaging, SPECT Modality, PET Technology, Radiotracer Applications, Gamma Photon Detection, Medical DiagnosticsHighlight :
M. N. Wernick and J. N. Aarsvold, Emission Tomography: The Fundamentals of PET and SPECT. San Diego, CA, USA: Elsevier Academic Press, 2004.
H. N. Wagner and J. W. Buchanan, Principles of Nuclear Medicine, 2nd ed. Philadelphia, PA, USA: W.B. Saunders Company, 1995.
N. P. Van der Meulen, C. Müller, and S.Konijnenberg, "New Radionuclides and Technological Advances in SPECT and PET Scanners," Cancers, vol. 13, no. 23, art. 6183, Dec. 2021, doi: 10.3390/cancers13236183.
G. Segall, "Assessment of Myocardial Viability by Positron Emission Tomography," Nuclear Medicine Communications, vol. 23, no. 4, pp. 323-330, Apr. 2002, doi: 10.1097/00006231-200204000-00003.
Y. Bouchareb and A. Al-Jebur, "Technological Advances in SPECT and SPECT/CT Imaging," Diagnostics, vol. 14, no. 13, art. 1431, Jul. 2024, doi: 10.3390/diagnostics14131431.
H. Alva-Sánchez, C. Quintana-Bautista, D. Martínez-Dávalos, M. Rodríguez-Villafuerte, and A. E. Martínez-Dávalos, "Positron Range in Tissue-Equivalent Materials: Experimental microPET Studies," Physics in Medicine and Biology, vol. 61, no. 17, pp. 6307-6318, Sep. 2016, doi: 10.1088/0031-9155/61/17/6307.
A. Cuocolo and P. Monteiro, "PET and SPECT Specialty Grand Challenge: When Knowledge Travels at the Speed of Light, Photons Take to the Field," Frontiers in Nuclear Medicine, vol. 1, art. 671914, Jun. 2021, doi: 10.3389/fnume.2021.671914.
L. M. Carter, A. J. Kesner, and J. A. Pratt, "The Impact of Positron Range on PET Resolution, Evaluated with Phantoms and PHITS Monte Carlo Simulations for Conventional and Non-conventional Radionuclides," Molecular Imaging and Biology, vol. 22, no. 1, pp. 73-84, Feb. 2020, doi: 10.1007/s11307-019-01337-2.
A. Gonzalez-Montoro, J. J. Vaquero, M. Desco, M. J. Hsu, K. Thielemans, and P. Hutton, "Advances in Detector Instrumentation for PET," Journal of Nuclear Medicine, vol. 63, no. 8, pp. 1138-1144, Aug. 2022, doi: 10.2967/jnumed.121.262509.
Q. Yin, H. Hung, S. Wang, and X. Hu, "Diagnostic Performance of MRI, SPECT, and PET in Detecting Renal Cell Carcinoma: A Systematic Review and Meta-analysis," BMC Cancer, vol. 22, no. 1, art. 163, Feb. 2022, doi: 10.1186/s12885-022-09745-6.
F. F. Alqahtani, T. A. Aleanizy, E. El Tahir, R. Alhabib, and R. Alsaif, "SPECT/CT and PET/CT, Related Radiopharmaceuticals, and Areas of Application and Comparison," Saudi Pharmaceutical Journal, vol. 31, no. 3, pp. 312-328, Mar. 2023, doi: 10.1016/j.jsps.2023.01.003.
D. Hussain and A. Ngaile, "Recent Breakthroughs in PET-CT Multimodality Imaging: Innovations and Clinical Impact," Bioengineering, vol. 11, no. 12, art. 1213, Dec. 2024, doi: 10.3390/bioengineering11121213.
C. Nappi, A. Cuocolo, V. Cantoni, and W. Acampa, "The Machine Learning Approach: Artificial Intelligence is Coming to Support Critical Clinical Thinking," Journal of Nuclear Cardiology, vol. 27, no. 1, pp. 156-158, Feb. 2020, doi: 10.1007/s12350-018-1372-8.
D. Han, J. Lee, J. M. Miller, M. Y. Andreini, J. K. Min, and L. J. Shaw, "Incremental Role of Resting Myocardial Computed Tomography Perfusion for Predicting Physiologically Significant Coronary Artery Disease: A Machine Learning Approach," Journal of Nuclear Cardiology, vol. 25, no. 1, pp. 223-233, Feb. 2018, doi: 10.1007/s12350-017-0834-y.
A. Sánchez-Crespo, P. Andreo, and S. A. Larsson, "Positron Flight in Human Tissues and Its Influence on PET Image Spatial Resolution," European Journal of Nuclear Medicine and Molecular Imaging, vol. 31, no. 1, pp. 44-51, Jan. 2004, doi: 10.1007/s00259-003-1330-y.