• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.10-16
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• 2011

Purpose: The partial volume effect occurs because of limit of the spatial resolution. It makes partial loss of intensity and causes SUV to be lower than it should actually be. So the purpose of this study is to calculate recovery coefficient for correcting PVE from phantom study and to compare before and after SUV correction applying to PET/CT examination. Materials and Methods: The flangeless Esser PET phantom consisting of four hot cylinders was used for this study. All of the hot cylinders were filled with FDG solution of 20.72 MBq per 1000 ml, and the phantom background was filled with FDG solution of different concentrations (33.30, 22.20, 16.65 MBq per 6440 ml) to yield H/B ratios of around 4:1, 6:1 and 8:1. Using the Biograph Truepoint 40(SIEMENS, Germany), we applied recovery coefficient method to 30 patients who were diagnosed with lung cancer after PET/CT exam. And then we analyzed and compared SUV before and after correcting partial volume effect. Results: The smaller the diameter of hot cylinder becomes, the more recovery coefficient decreased. When we applied recovery coefficient to clinical patients and compared SUV before and after correcting PVE, before the correction all lesions gave an average max SUV of 7.83. And after the correction, the average max SUV increases to 10.31. The differences in the max SUV between before and after correction were analyzed by paired t test. As a result, there were statistically significant differences (t=7.21, p=0.000). Conclusion: The SUV for quantification should be measured precisely to give consistent information of tumor uptake. But PVE is one of factors that causes SUV to be lower and to be underestimated. We can correct this PVE and calculate corrected SUV using the recovery coefficient from phantom study. And if we apply this correction method to clinical patients, we can finally assess and provide quantitative analysis more accurately.

• Journal of radiological science and technology
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• v.45 no.3
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• pp.241-248
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• 2022

In this study, a recovery coefficient (RC) calculation was conducted that can correct the underestimation of the standardized uptake value (SUV) due to the partial volume effect (PVE) through phantom measurements and formulas. The experiment was conducted using a dynamic phantom capable of implement cranio-caudal movement at a respiratory rate of 15 times per minute along with the measured phantom experiment of the stopped state, and the RC of the moving state is calculated and compared. Ingenuity TF (Philips Healthcare, Netherland) was used as a positron emission tomography/computed tomography (PET/CT) device. PET-CT Phantom (Biodex Medical System, USA) was used as a phantom for measurement. A phantom image in a stationary state was acquired, and a moving phantom image was acquired using the AZ-733V Respiratory Phantom (Anzai Medical Co, Japan) capable of breathing movement in the cranio-caudal direction under the same acquisition parameters. For RC calculation, the sphere maximum radioactivity concentration and the background mean radioactivity concentration of the acquired images were measured, and the initially determined sphere and background radioactivity concentrations were calculated. The calculated RC was 0.08 to 0.72. The size of sphere smaller, it was confirmed that the RC reduced. And the RC in the moving state reduced than in the stationary state. As a result of this study, the change of the RC was confirmed according to the size of spheres and the phantom moving. Using the RC derived by implement movement of breathing with the respiratory phantom, it is possible to considering correction of underestimated SUV by the partial volume effect of PET images and the patient movements.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.29-37
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• 2019

Purpose DMIDR(Discovery Molecular Imaging Digital Ready, General Electric Healthcare, USA) is a PET/CT scanner designed to allow application of PSF(Point Spread Function), TOF(Time of Flight) and Q.Clear algorithm. Especially, Q.Clear is a reconstruction algorithm which can overcome the limitation of OSEM(Ordered Subset Expectation Maximization) and reduce the image noise based on voxel unit. The aim of this paper is to evaluate the performance of reconstruction algorithms and optimize the algorithm combination to improve the accurate SUV(Standardized Uptake Value) measurement and lesion detectability. Materials and Methods PET phantom was filled with $^{18}F-FDG$ radioactivity concentration ratio of hot to background was in a ratio of 2:1, 4:1 and 8:1. Scan was performed using the NEMA protocols. Scan data was reconstructed using combination of (1)VPFX(VUE point FX(TOF)), (2)VPHD-S(VUE Point HD+PSF), (3)VPFX-S (TOF+PSF), (4)QCHD-S-400((VUE Point HD+Q.Clear(${\beta}-strength$ 400)+PSF), (5)QCFX-S-400(TOF +Q.Clear(${\beta}-strength$ 400)+PSF), (6)QCHD-S-50(VUE Point HD+Q.Clear(${\beta}-strength$ 50)+PSF) and (7)QCFX-S-50(TOF+Q.Clear(${\beta}-strength$ 50)+PSF). CR(Contrast Recovery) and BV(Background Variability) were compared. Also, SNR(Signal to Noise Ratio) and RC(Recovery Coefficient) of counts and SUV were compared respectively. Results VPFX-S showed the highest CR value in sphere size of 10 and 13 mm, and QCFX-S-50 showed the highest value in spheres greater than 17 mm. In comparison of BV and SNR, QCFX-S-400 and QCHD-S-400 showed good results. The results of SUV measurement were proportional to the H/B ratio. RC for SUV is in inverse proportion to the H/B ratio and QCFX-S-50 showed highest value. In addition, reconstruction algorithm of Q.Clear using 400 of ${\beta}-strength$ showed lower value. Conclusion When higher ${\beta}-strength$ was applied Q.Clear showed better image quality by reducing the noise. On the contrary, lower ${\beta}-strength$ was applied Q.Clear showed that sharpness increase and PVE(Partial Volume Effect) decrease, so it is possible to measure SUV based on high RC comparing to conventional reconstruction conditions. An appropriate choice of these reconstruction algorithm can improve the accuracy and lesion detectability. In this reason, it is necessary to optimize the algorithm parameter according to the purpose.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.3 no.2
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• pp.65-71
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• 2017

To assess the effects of filter and reconstruction of Cu-64 PET data on Siemens scanner, the various reconstruction algorithm with various filters were assessed in terms of spatial resolution, non-uniformity (NU), recovery coefficient (RC), and spillover ratio (SOR). Image reconstruction was performed using filtered backprojection (FBP), 2D ordered subset expectation maximization (OSEM), 3D reprojection algorithm (3DRP), and maximum a posteriori algorithms (MAP). For the FBP reconstruction, ramp, butterworth, hamming, hanning, or parzen filters were used. Attenuation or scatter correction were performed to assess the effect of attenuation and scatter correction. Regarding spatial resolution, highest achievable volumetric resolution was $3.08mm^3$ at the center of FOV when MAP (${\beta}=0.1$) reconstruction method was used. SOR was below 4% for FBP when ramp, Hamming, Hanning, or Shepp-logan filter were used. The lowest NU (highest uniform) after attenuation & scatter correction was 5.39% when FBP (parzen filter) was used. Regarding RC, 0.9 < RC < 1.1 was obtained when OSEM (iteration: 10) was used when attenuation and scatter correction were applied. In this study, image quality of Cu-64 on Siemens Inveon PET was investigated. This data will helpful for the quantification of Cu-64 PET data.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.2
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• pp.111-127
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• 2023

Purpose: Gallium-68 (⁶⁸Ga) is increasingly used in nuclear medicine imaging for various conditions such as lymphoma and neuroendocrine tumors by labeling tracers like Prostate Specific Membrane Antigen (PSMA) and DOTA-TOC. However, compared to Fluorine-18 (¹⁸F) used in conventional nuclear medicine imaging, ⁶⁸Ga has lower spatial resolution and relatively higher Signal to Background Ratio (SBR). Therefore, this study aimed to investigate the optimized parameters and reconstruction methods for PET/CT imaging using the ⁶⁸Ga radiotracer through model-based image evaluation. Materials and Methods: Based on clinical images of ⁶⁸Ga-PSMA PET/CT, a NEMA/IEC 2008 PET phantom model was prepared with a Hot vs Background (H/B) ratio of 10:1. Images were acquired for 9 minutes in list mode using DMIDR (GE, Milwaukee WI, USA). Subsequently, reconstructions were performed for 1 to 8 minutes using OS-EM (Ordered Subset Expectation Maximization) + TOF (Time of Flight) + Sharp IR (VPFX-S), and BSREM (Block Sequential Regularized Expectation Maximization) + TOF + Sharp IR (QCFX-S-400), followed by comparative evaluation. Based on the previous experimental results, images were reconstructed for BSREM + TOF + Sharp IR / 2 minutes (QCFX-S-2min) with varying β-strength values from 100 to 700. The image quality was evaluated using AMIDE (freeware, Ver.1.0.1) and Advanced Workstation (GE, USA). Results: Images reconstructed with QCFX-S-400 showed relatively higher values for SNR (Signal to Noise Ratio), CNR (Contrast to Noise Ratio), count, RC (Recovery Coefficient), and SUV (Standardized Uptake Value) compared to VPFX-S. SNR, CNR, and SUV exhibited the highest values at 2 minutes/bed acquisition time. RC showed the highest values for a 10 mm sphere at 2 minutes/bed acquisition time. For small spheres of 10 mm and 13 mm, an inverse relationship between β-strength increase and count was observed. SNR and CNR peaked at β-strength 400 and then decreased, while SUV and RC exhibited a normal distribution based on sphere size for β-strength values of 400 and above. Conclusion: Based on the experiments, PET/CT imaging using the ⁶⁸Ga radiotracer yielded the most favorable quantitative and qualitative results with a 2 minutes/bed acquisition time and BSREM reconstruction, particularly when applying β-strength 400. The application of BSREM can enhance accurate quantification and image quality in ⁶⁸Ga PET/CT imaging, and an optimization process tailored to each institution's imaging objectives appears necessary.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.35-42
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• 2018

Purpose Standardized uptake value(SUV) has been widely used as a quantitative metric of uptake in PET/CT for diagnosis of malignant tumors and evaluation of tumor therapy response. However, the SUV depends on various factor including PET/CT scanner specifications and reconstruction parameter. The purpose of this study is to validate a EQ PET to evaluate SUV across different PET/CT systems. Materials and Methods First, NEMA IEC body phantom data were used to calculate the EQ filter for OSEM3D with PSF and TOF reconstruction from three different PET/CT systems in order to obtain EARL compliant recovery coefficients of each spheres. The Biograph true point 40 PET/CT images were reconstructed with a OSEM3D+PSF reconstruction, images of the Biograph mCT 40 and Biograph mCT 64 PET/CT scanners were reconstructed with a OSEM3D+PSF, OSEM3D+TOF, OSEM3D+PSF+TOF. Post reconstructions, the proprietary EQ filter was applied to the reconstruction data. Recovery coefficient can be estimated by ratio of measured to true activity concentration for spheres of different volume and coefficient variability(CV) value of RC for each sphere was compared. For clinical study, we compared SUVmax applying different reconstruction algorithms in FDG PET images of 61 patients with lung cancer using Biograph mCT 40 PET/CT scanner. Results For the phantom studied, the mean values of CV for OSEM3D, OSEM3D+PSF, OSEM3D+TOF and OSEM3D+PSF+TOF reconstructions were 0.05, 0.04, 0.04 and 0.03 respectively for RC. Application of the proprietary EQ filter, the mean values of CV for OSEM3D, OSEM3D+PSF, OSEM3D+TOF and OSEM3D+PSF+TOF reconstructions were 0.04, 0.03, 0.03 and 0.02 respectively for RC. Clinical study, there were no statistical significance of the difference applying EQ PET on SUVmax of 61 patients FDG PET image. (p=1.000) Conclusion This study indicates that CV values of RC in phantom were decreased after applying EQ PET for different PET/CT system and The EQ PET reduced reconstruction dependent variation in SUVs for 61 lung cancer patients, Therefore, EQ PET will be expected to provide accurate quantification when the patient is scanned on different PET/CT system.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.1
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• pp.47-54
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• 2023

Purpose PET-CT imaging require an appropriate quality assurance system to achieve high efficiency and reliability. Quality control is essential for improving the quality of care and patient safety. Currently, there are performance evaluation methods of UN2-1994 and UN2-2001 proposed by NEMA and IEC for PET-CT image evaluation. In this study, we compare phantom images with the same experiments before and after PET-CT 3D normalization and well counter correction and evaluate the usefulness of quality control. Materials and methods Discovery 690 (General Electric Healthcare, USA) PET-CT equiptment was used to perform 3D normalization and well counter correction as recommended by GE Healthcare. Based on the recovery coefficients for the six spheres of the NEMA IEC Body Phantom recommended by the EARL. 20kBq/㎖ of ¹⁸F was injected into the sphere of the phantom and 2kBq/㎖ of ¹⁸F was injected into the body of phantom. PET-CT scan was performed with a radioacitivity ratio of 10:1. Images were reconstructed by appliying TOF+PSF+TOF, OSEM+PSF, OSEM and Gaussian filter 4.0, 4.5, 5.0, 5.5, 6.0, 6,5 mm with matrix size 128×128, slice thickness 3.75 mm, iteration 2, subset 16 conditions. The PET image was attenuation corrected using the CT images and analyzed using software program AW 4.7 (General Electric Healthcare, USA). The ROI was set to fit 6 spheres in the CT image, RC (Recovery Coefficient) was measured after fusion of PET and CT. Statistical analysis was performed wilcoxon signed rank test using R. Results Overall, after the quality control items were performed, the recovery coefficient of the phantom image increased and measured. Recovery coefficient according to the image reconstruction increased in the order TOF+PSF, TOF, OSEM+PSF, before and after quality control, RCmax increased by OSEM 0.13, OSEM+PSF 0.16, TOF 0.16, TOF+PSF 0.15 and RCmean increased by OSEM 0.09, OSEM+PSF 0.09, TOF 0.106, TOF+PSF 0.10. Both groups showed a statistically significant difference in Wilcoxon signed rank test results (P value<0.001). Conclusion PET-CT system require quality assurance to achieve high efficiency and reliability. Standardized intervals and procedures should be followed for quality control. We hope that this study will be a good opportunity to think about the importance of quality control in PET-CT

• Journal of radiological science and technology
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• v.44 no.6
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• pp.645-653
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• 2021

With the recent development of precision medicine(Theranostics), interest and utilization of the quantitative function of SPECT/CT are increasing. This study aims to investigate the effect on the radioactivity concentration estimate by the increase or decrease in the total time of SPECT/CT imaging conditions. A standard image was obtained by the conditions of a total acquisition time of 600 sec(10 sec/f × 120 frames) by diluting ^99mTc 91.76 MBq in a cylindrical phantom filled with sterile water, and a comparative image was obtained by increasing the total acquisition time by -90%, -75%, -50%, -25%, +50%, +100%. The CNR, radioactive concentration estimate(cps/ml), and the variation rate(%) of the recovery coefficient(RC) were analyzed by measuring the overall coefficient of interest in each image. The results[CNR, Radiation Concentration, RC] by the change in the number of projections for each increase or decrease rate(-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.5%, +3.90%, 1.04] at -90%, [-77.9%, +2.71%, 1.03] at -75%, [-55.6%, +1.85%, 1.02] at -50%, [-33.6%, +1.37%, 1.01] at -25%, [-33.7%, +0.71%, 1.01] at +50%, [+93.2%, +0.32%, 1.00] at +100%. and also The results[CNR, Radiation Concentration, RC] by the acquisition time change for each increase or decrease rate(-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.3%, -3.55%, 0.96] at -90%, [-73.4%, -0.17%, 1.00] at -75%, [-49.6%, -0.34%, 1.00] at -50%, [-24.9%, 0.03%, 1.00] at -25%, [+49.3%, -0.04%, 1.00] at +50%, [+99.0%, +0.11%, 1.00] at +100%. Image quality(CNR) showed a pattern of change in proportion to the increase or decrease in the total acquisition time of SPECT/CT, but the result at quantitative evaluation showed a change of less than 5% in all experimental conditions, maintaining quantitative accuracy(RC less than 0.05) without much influence.

• The Korean Journal of Nuclear Medicine Technology
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• v.25 no.2
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• pp.15-24
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• 2021

Purpose SPECT/CT was noted for its excellent correction method and qualitative functions based on fusion images in the early stages of dissemination, and interest in and utilization of quantitative functions has been increasing with the recent introduction of companion diagnostic therapy(Theranostics). Unlike PET/CT, various conditions like the type of collimator and detector rotation are a challenging factor for image acquisition and reconstruction methods at absolute quantification of SPECT/CT. Therefore, in this study, We want to find out the effect on the radioactivity concentration estimate by the increase or decrease of the total acquisition time according to the number of projections and the acquisition time per projection among SPECT/CT imaging conditions. Materials and Methods After filling the 9,293 ml cylindrical phantom with sterile water and diluting 99mTc 91.76 MBq, the standard image was taken with a total acquisition time of 600 sec (10 sec/frame × 120 frames, matrix size 128 × 128) and also volume sensitivity and the calibration factor was verified. Based on the standard image, the comparative images were obtained by increasing or decreasing the total acquisition time. namely 60 (-90%), 150 (-75%), 300 (-50%), 450 (-25%), 900 (+50%), and 1200 (+100%) sec. For each image detail, the acquisition time(sec/frame) per projection was set to 1.0, 2.5, 5.0, 7.5, 15.0 and 20.0 sec (fixed number of projections: 120 frame) and the number of projection images was set to 12, 30, 60, 90, 180 and 240 frames(fixed time per projection:10 sec). Based on the coefficients measured through the volume of interest in each acquired image, the percentage of variation about the contrast to noise ratio (CNR) was determined as a qualitative assessment, and the quantitative assessment was conducted through the percentage of variation of the radioactivity concentration estimate. At this time, the relationship between the radioactivity concentration estimate (cps/ml) and the actual radioactivity concentration (Bq/ml) was compared and analyzed using the recovery coefficient (RC_Recovery Coefficients) as an indicator. Results The results [CNR, radioactivity Concentration, RC] by the change in the number of projections for each increase or decrease rate (-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.5%, +3.90%, 1.04] at -90%, [-77.9%, +2.71%, 1.03] at -75%, [-55.6%, +1.85%, 1.02] at -50%, [-33.6%, +1.37%, 1.01] at -25%, [-33.7%, +0.71%, 1.01] at +50%, [+93.2%, +0.32%, 1.00] at +100%. and also The results [CNR, radioactivity Concentration, RC] by the acquisition time change for each increase or decrease rate (-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.3%, -3.55%, 0.96] at - 90%, [-73.4%, -0.17%, 1.00] at -75%, [-49.6%, -0.34%, 1.00] at -50%, [-24.9%, 0.03%, 1.00] at -25%, [+49.3%, -0.04%, 1.00] at +50%, [+99.0%, +0.11%, 1.00] at +100%. Conclusion In SPECT/CT, the total coefficient obtained according to the increase or decrease of the total acquisition time and the resulting image quality (CNR) showed a pattern that changed proportionally. On the other hand, quantitative evaluations through absolute quantification showed a change of less than 5% (-3.55 to +3.90%) under all experimental conditions, maintaining quantitative accuracy (RC 0.96 to 1.04). Considering the reduction of the total acquisition time rather than the increasing of the image acquiring time, The reduction in total acquisition time is applicable to quantitative analysis without significant loss and is judged to be clinically effective. This study shows that when increasing or decreasing of total acquisition time, changes in acquisition time per projection have fewer fluctuations that occur in qualitative and quantitative condition changes than the change in the number of projections under the same scanning time conditions.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.655-661
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• 2021

Positron emission tomography (PET) images is affected by acquisition time, short acquisition times results in low gamma counts leading to degradation of image quality by statistical noise. Noise2Void(N2V) is self supervised denoising model that is convolutional neural network (CNN) based deep learning. The purpose of this study is to evaluate denoising performance of N2V for PET image with a short acquisition time. The phantom was scanned as a list mode for 10 min using Biograph mCT40 of PET/CT (Siemens Healthcare, Erlangen, Germany). We compared PET images using NEMA image-quality phantom for standard acquisition time (10 min), short acquisition time (2min) and simulated PET image (S2 min). To evaluate performance of N2V, the peak signal to noise ratio (PSNR), normalized root mean square error (NRMSE), structural similarity index (SSIM) and radio-activity recovery coefficient (RC) were used. The PSNR, NRMSE and SSIM for 2 min and S2 min PET images compared to 10min PET image were 30.983, 33.936, 9.954, 7.609 and 0.916, 0.934 respectively. The RC for spheres with S2 min PET image also met European Association of Nuclear Medicine Research Ltd. (EARL) FDG PET accreditation program. We confirmed generated S2 min PET image from N2V deep learning showed improvement results compared to 2 min PET image and The PET images on visual analysis were also comparable between 10 min and S2 min PET images. In conclusion, noisy PET image by means of short acquisition time using N2V denoising network model can be improved image quality without underestimation of radioactivity.