• The Korean Journal of Nuclear Medicine
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• v.29 no.4
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• pp.533-540
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• 1995

Attenuation correction is important in producing quantitative positron emission tomography (PET) images. Conventionally, photon attenuation effects are corrected using transmission measurements performed before tracer administration. The pre-injection transmission measurement approach may require a time delay between transmission and emission scans for the tracer studies requiring a long uptake period, about 45 minutes for F-18 deoxyglucose study. The time delay will limit patient throughput and increase the likelihood of patient motion. A technique lot performing simultaneous transmission and emission scans (T+E method) after the tracer injection has been validated. The T+E method substracts the emission counts contaminating the transmission measurements to produce accurate attenuation correction coefficients. This method has been evaluated in experiments using a cylindrical phantom filled with background water (5750 cc) containing $0.4{\mu}Ci/cc$ of F-18 fluoride ion and one insert cylinder (276 cc) containing $4.3{\mu}Ci/cc$. GE $Advance^{TM}$ PET scanner and Ge-68 rotating pin sources for transmission scanning were used for this investigation. Post-injection transmission scan and emission scan were peformed alternatively over time. The error in emission images corrected using post-infection transmission scan to emission images corrected transmission scan was 2.6% at the concentration of $1.0{\mu}Ci/cc$. No obvious differences in image quality and noise were apparent between the two images. The attenuation correction can be accomplished with post-injection transmission measurement using rotating pin sources and this method can significantly shorten the time between transmission and omission scans and thereby reduce the likelihood of patient motion and increase scanning throughput in PET.

• Progress in Medical Physics
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• v.13 no.3
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• pp.139-148
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• 2002

The measured attenuation correction with transmission (Tx) scans produced quantitatively accurate images. However, it was not clear for optimal emission (Ex) and Tx scan time in PET imaging. This study was to evaluate acceptable Ex and Tx scan time by simulating clinical situations using various phantoms. Cylindrical and NEMA phantom were used for $^{18}$ F-PET scan using 2D protocol in GE Advance PETTM scanner. Cylindrical phantom was filled with 136 MBq 18F, and five regions of interests (ROI) were drawn on 23 slices. NEMA phantom had three inserts containing water, air and polytetrafluoro-ethylene (PTFE). Outside of these inserts were filled with 309 MBq of $^{18}$ F, and total 12 ROIs were drawn on 23 slices. Scans were carried out according to five Ex scan times: 2, 5, 10, 15, and 30 min, and nine Tx scan times: 2, 3, 4, 5, 7, 10, 15, 20, and 30 min. Images were reconstructed using measured attenuation correction, and ROI analyses were performed for all images, and mean, standard deviation (SD), coefficient of variation and percent errors were calculated. For cylindrical phantom study, ROI mean and SD were decreased as Ex and Tx time increased. Coefficients of variation were kept constant, when Tx was greater than 10 min. The amount of error decreased for the increment of Ex time from 10 min to 15 min was almost the same to that from 15 min to 30 min. In NEMA phantom Tx 15 min showed the lowest er개r level when the percent errors for three inserts were summed for all of the Ex times. This study suggested that Ex 15 min and Tx 15 min were acceptable as optimal scan time for the scanning protocol and the dose of radiopharmaceuticals used in these phantom study.

• The Korean Journal of Nuclear Medicine
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• v.30 no.4
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• pp.560-569
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• 1996

Background and Purpose : Standardized uptake value(SUV) has been used as a quantitative index for differentiating benign and malignant tumors with F-18-FDG PET In this study, we produced whole body parametric images of SUV(WBPIS) by body weight normalization, and validated the values by comparison with SUV's calculated with regional scans. Subjects and Methods : Whole body scans were followed by regional scans sequentially on 23 patients. In whole body study, transmission and emission scans were acquired for 2 minutes and 6 minutes for each bed position, respectively. In regional study, transmission and emission scans were acquired for 20 minutes. Measured and segmented/ smoothed attenuation correction were applied using these 2 min transmission scans in whole body studies. The effects of attenuation correction on SUVs were evaluated quantitatively using F-18 filled cylindrical phantom. The mean and peak SUVs obtained from WBPIS were compared with SUVs of the regional scans. Results : In phantom studies, with any method of attenuation correction using regional or whole body studies of phantom, SUVs were nearly consistent. In whole body scan, SUV obtained using measured attenuation correction method was a little higher than SUV of regional scan. SUV obtained using segmented/smoothed attenuation correction method was a little lower. In patient studies, WBPIS using segmented/smoothed attenuation correction method was much smoother and more readable. SUVs of WBPIS obtained with both methods of attenuation correction were well correlated with SUVs of regional scans(r=0.9). SUVs of WBPIS with measured attenuation correction method were 5% lower than SUVs of regional scans. SUVs of WBPIS with segmented/smoothed attenuation correction method were 10% lower than SUVs of regional scans. The differences of SUVs of WBPIS by the two attenuation correction methods were relatively small compared with the possible differences derived from biological characteristics of tumors. Conclusion : We concluded that WBPIS could be useful in the quantification of tumor as well as in localization of whole body lesions, which were often outside the field of view in regional scan. WBPIS made using segmented/smoothed attenuation correction method could be used in clinical routines and SUVs from attenuation corrected F-18-FDG PET could be used interchangeably with SUVs of regional studies.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.12-16
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• 2015

Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.486-491
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• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.