Assessment of SPECT images using UHRFB and other low-energy collimators in brain study by Hoffman phantom and manufactured defects
School of Paramedical, Gerash University of Medical Sciences, P.O. Box 7441758666, Gerash, Iran
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Accepted: 20 January 2020
Published online: 18 February 2020
The performance of collimators was investigated using low-energy high-resolution (LEHR) and low-energy ultra-high-resolution (LEUHR) collimators in SPECT system to study the brain physiology by injecting 99mTc-HMPAO radionuclide. Ultra-high-resolution fan beam (UHRFB) images were compared to other low-energy collimator images by constructed defects embedded into Hoffman brain phantom as lateral, deepness and metastasis designs with slices of Perspex. The defects were constructed by CNC machine as circular slices and ring flaws ranging in size from 2 to 16 mm to detect low-concentration regions. The data acquisition was done in tomographic mode with minimum radii and different matrix sizes, data acquisition time and number of projections. The collected data were reconstructed using two methods, filtered backprojection and ordered subset expectation maximization (OSEM). By two radiologists and via thallium and V-shaped markers, the minimum diameters of the constructed flaws inside the abnormal area of the brain phantom were diagnosed to 4.0 ± 0.4, 6.0 ± 0.7 and 8.0 ± 0.9 mm for UHRFB, LEUHR and LEHR, respectively. In OSEM method, the desirable ranges of the filter parameters were 4–8 iterations and 2–4 subsets for FB collimator. The outcomes showed that FB collimator provides the better resolution in axial, coronal and sagittal views using brain perfusion phantom and data from eight patients on tinnitus disease. The UHRFB with converging geometry confirmed the better detection of defect regions due to the lowest ratio of cold/background counts. This study may be useful for early detection of disease transference, monitoring of treatment response and disease progression.
© Società Italiana di Fisica (SIF) and Springer-Verlag GmbH Germany, part of Springer Nature, 2020