سامانه مدیریت نشریات علمی دانشگاه علوم پزشکی مشهد

Sugiura, Akie, Shibutani, Takayuki, Onoguchi, Masahisa, Nagaki, Akio, Tsuboi, Kotatsu, Ito, Toshimune, Ichikawa, Hajime. (1403). Relationship between physical parameters and visual analysis for assessment of image quality: a multi-center and multi-vendor phantom study in brain SPECT. , 13(1), 42-52. doi: 10.22038/aojnmb.2024.75204.1524
Akie Sugiura; Takayuki Shibutani; Masahisa Onoguchi; Akio Nagaki; Kotatsu Tsuboi; Toshimune Ito; Hajime Ichikawa. "Relationship between physical parameters and visual analysis for assessment of image quality: a multi-center and multi-vendor phantom study in brain SPECT". , 13, 1, 1403, 42-52. doi: 10.22038/aojnmb.2024.75204.1524
Sugiura, Akie, Shibutani, Takayuki, Onoguchi, Masahisa, Nagaki, Akio, Tsuboi, Kotatsu, Ito, Toshimune, Ichikawa, Hajime. (1403). 'Relationship between physical parameters and visual analysis for assessment of image quality: a multi-center and multi-vendor phantom study in brain SPECT', , 13(1), pp. 42-52. doi: 10.22038/aojnmb.2024.75204.1524
Sugiura, Akie, Shibutani, Takayuki, Onoguchi, Masahisa, Nagaki, Akio, Tsuboi, Kotatsu, Ito, Toshimune, Ichikawa, Hajime. Relationship between physical parameters and visual analysis for assessment of image quality: a multi-center and multi-vendor phantom study in brain SPECT. , 1403; 13(1): 42-52. doi: 10.22038/aojnmb.2024.75204.1524

Relationship between physical parameters and visual analysis for assessment of image quality: a multi-center and multi-vendor phantom study in brain SPECT

Asia Oceania Journal of Nuclear Medicine and Biology
مقاله 5، دوره 13، شماره 1، فروردین 2025، صفحه 42-52    اصل مقاله (1.42 M)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22038/aojnmb.2024.75204.1524
نویسندگان
Akie Sugiura* 1؛ Takayuki Shibutani1؛ Masahisa Onoguchi1؛ Akio Nagaki2؛ Kotatsu Tsuboi3؛ Toshimune Ito4؛ Hajime Ichikawa5
1Department of Quantum Medical Technology, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Ishikawa, Japan
2Department of Radiological Technology, Kurashiki Central Hospital, Okayama, Japan
3Department of Radiological Technology, Hamamatsu Red Cross Hospital, Shizuoka, Japan
4Department of Radiological Technology, Faculty of Medical Technology, Tokyo, Japan
5Department of Radiology, Toyohashi Municipal Hospital, Aichi, Japan
چکیده
Objective(s): Brain perfusion single-photon emission computed tomography (SPECT) image quality varies depending on SPECT systems. This study aimed to evaluate the relationship between physical parameters and visual analysis for assessment of the brain SPECT image quality. We conducted our phantom study under various conditions in a multi-center and multi-vendor study.
Methods: SPECT images of the brain phantom were acquired from eight devices in five institutions. The phantom was filled with 28 kBq/ml of 99mTc solution at the start of scanning. We obtained various data with different acquisition times under clinical reconstruction and acquisition conditions at each institution. Four physical parameters (percent contrast, contrast noise ratio (CNR), asymmetry index (AI), and sharpness index (SI)) were measured with the phantom. Seven observers blindly evaluated all image series and scored them on a scale of 1–3 using four checkpoints: contrast, image noise, symmetry, and sharpness. The average score for all observers was calculated.
Results: CNR increased with increasing visual analysis scores for contrast and image noise, both of which were significantly different between the group with scores “<2” and the group with scores “≥2 and <3”. AI decreased as the visual analysis score for symmetry increased, and the AI of both groups with scores “≥2 and <3” and “3” were significantly lower than that of the group with scores “<2”. Conversely, no relationship with visual analysis was found for percent contrast and SI.
Conclusion: We clarified the relationship between physical parameters and visual analysis of a brain phantom in a multi-center and multi-vendor study. CNR and AI showed agreement with visual analysis.
کلیدواژه‌ها
Brain perfusion SPECT؛ Multi-center؛ Multi-vendor؛ Physical parameter؛ Visual analysis
مراجع
  1. McArthur C, Jampana R, Patterson J, Hadley D. Applications of cerebral SPECT. Clinical radiology. 2011; 66(7): 651-61.
  2. Camargo EE. Brain SPECT in neurology and psychiatry. J Nucl Med. 2001; 42: 611-623.
  3. Catafau AM. Brain SPECT in clinical practice. Part I: Perfusion. J Nucl Med. 2001; 42: 259-271.
  4. Heikkinen J, Kuikka JT, Ahonen A, Rautio A. Quality of brain perfusion single-photon emission tomography images: multicentre evaluation using an anatomically accurate three-dimensional phantom. Eur J Nucl Med. 1998; 25: 1415-1422.
  5. Ritt P, Sanders J, Kuwert T. SPECT/CT technology. Clin Transl Imaging. 2014; 2: 445-457.
  6. Ljungberg M, Pretorius PH. SPECT/CT: an update on technological developments and clinical applications. Br J Radiol. 2018; 91(1081):20160402.
  7. Van den Wyngaert T, Elvas F, De Schepper S, Kennedy JA, Israel O. SPECT/CT: standing on the shoulders of giants, it is time to reach for the sky! J Nucl Med. 2020; 61: 1284-1291.
  8. Bordonne M, Chawki MB, Marie P, Zaragori T, Roch V, Grignon R, et al. High-quality brain perfusion SPECT images may be achieved with a high-speed recording using 360° CZT camera. EJNMMI physics. 2020; 7: 1-12.
  9. Sakaguchi K, Kaida H, Yoshida S, Ishii K. Attenuation correction using deep learning for brain perfusion SPECT images. Ann Nucl Med. 2021; 35:589-599.
  10. Yamanaga T, Hasegawa S, Imoto A, Kikuchi A, Shimada H, Narita A, et al. Guidelines for standardization of brain perfusion SPECT imaging 1.0. Kakuigaku gijutsu. 2017; 37: 505–516.
  11. Minoshima S, Maruno H, Yui N, Togawa T, Kinoshita F, Kubota M, et al. Optimization of Butterworth filter for brain SPECT imaging. Ann Nucl Med. 1993; 7:71-77.
  12. Sugibayashi K, Suga Y, Hyashi M. Investigation of the Optimal Cut-off Frequency of Pre-processing Filter in Cerebral Perfusion SPECT Images. Jpn J Nucl Med Technol. 2002; 22: 137-143 (in Japanese).
  13. Sugiura A, Onoguchi M, Shibutani T, Kouno Y. Influence of minimum counts in brain perfusion SPECT: phantom and clinical studies. J Nucl Med Technol. 2022; 50: 342-347.
  14. Ikari Y, Akamatsu G, Nishino T, Ishii K, Ito K, Iwatsubo T, et al. Phantom criteria for qualification of brain FDG and amyloid PET across different cameras. EJNMMI phys. 2016; 3:1-18.
  15. Hoffman EJ, Cutler PD, Digby WM, Mazziotta JC. Three-dimensional phantom to simulate cerebral blood flow and metabolic images for PET. IEEE Trans Nucl Sci. 1990; 37: 616–620.
  16. Vallabhajosula S, Zimmerman RE, Picard M, Stritzke P, Mena I, Hellman RS, et al. Technetium-99m ECD: a new brain imaging agent: in vivo kinetics and biodistribution studies in normal human subjects. J Nucl Med. 1989; 30: 599-604.
  17. Lim JS, Ryu YH, Kim BM, Lee JD. Crossed cerebellar diaschisis due to intracranial hematoma in basal ganglia or thalamus. J Nucl Med. 1998; 39:2044-2047.
  18. Salvadori J, Imbert L, Perrin M, Karcher G, Lamiral Z, Marie PY, et al. Head-to-head comparison of image quality between brain 18F-FDG images recorded with a fully digital versus a last-generation analog PET camera. EJNMMI Res. 2019; 9: 1-8.
  19. Verwer EE, Golla SSV, Kaalep A, Lubberink M, van Velden FHP, Bettinardi V, et al. Harmonization of PET/CT contrast recovery performance for brain studies. Eur J Nucl Med Mol Imag. 2021; 48: 2856-2870.
  20. PET phantom test procedures for brain PET imaging with 18F-FDG and amyloid imaging agent. Japanese Society of Nuclear Medicine website. http://jsnm.org/ wp_jsnm/wp-content/uploads/2021/02/ Dementia_Phantom Test_20210208.pdf. Accessed 24 July 2022.
  21. Takeuchi R, Yonekura Y, Matsuda H, Konishi J. Usefulness of a three-dimensional stereotaxic ROI template on anatomically standardised 99mTc-ECD SPET. Eur J Nucl Med Mol Imag. 2002; 29: 331-341.
  22. 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: 1897–1903.
  23. Kanda Y. Investigation of the freely available easy-to-use software ‘EZR’for medical statistics. Bone Marrow Transplant. 2013; 48: 452-458.
  24. Shibutani T, Onoguchi M, Miyamoto N, Yamamoto Y, Kinuya S. Influence of Attenuation Correction by Brain Perfusion SPECT/CT Using a Simulated Abnormal Bone Structure: Comparison Between Chang and CT Methods. J Nucl Med Technol. 2017; 45: 208-213.
  25. Ichikawa K, Hara T, Niwa S, Yamaguchi I, Ohashi K. Evaluation of low contrast detectability using signal-to-noise ratio in computed tomography. Med Imaging Inf Sci. 2007; 24:106-11.
  26. Song TA, Chowdhury SR, Yang F, Dutta J. PET image super-resolution using generative adversarial networks. Neural Netw. 2020; 125: 83-91.
آمار
تعداد مشاهده مقاله: 240
تعداد دریافت فایل اصل مقاله: 174