｀１８´Ｆ−ＦＤＧを用いた脳ＰＥＴ検査の健常者データベースにおける透過撮像および減弱補正法の影響

Standardised Uptake Values (SUVs) are widely used in positron emission tomography (PET) as a semi-quantitative index of fluorine-18 labelled fluorodeoxyglucose uptake. The objective of this study was to investigate any bias introduced in the calculation of SUVs as a result of employing ordered subsets-expectation maximisation (OSEM) image reconstruction and segmented attenuation correction (SAC). Variable emission and transmission time durations were investigated. Both a phantom and a clinical evaluation of the bias were carried out. The software implemented in the GE Advance PET scanner was used. Phantom studies simulating tumour imaging conditions were performed. Since a variable count rate may influence the results obtained using OSEM, similar acquisitions were performed at total count rates of 34kcps and 12kcps. Clinical data consisted of 100 patient studies. Emission datasets of 5 and 15min duration were combined with 15-, 3-, 2- and 1-min transmission datasets for the reconstruction of both phantom and patient studies. Two SUVs were estimated using the average (SUVavg) and the maximum (SUVmax) count density from regions of interest placed well inside structures of interest. The percentage bias of these SUVs compared with the values obtained using a reference image was calculated. The reference image was considered to be the one produced by filtered backprojection (FBP) image reconstruction with measured attenuation correction using the 15-min emission and transmission datasets for each phantom and patient study. A bias of 5%-20% was found for the SUVavg and SUVmax in the case of FBP with SAC using variable transmission times. In the case of OSEM with SAC, the bias increased to 10%-30%. An overall increase of 5%-10% was observed with the use of SUVmax. The 5-min emission dataset led to an increase in the bias of 25%-100%, with the larger increase recorded for the SUVmax. The results suggest that OSEM and SAC with 3 and 2min transmission may be reliably used to reduce the overall data acquisition time without compromising the accuracy of SUVs.

Generally, the Chang method depends on counts for the attenuation correction (AC) method in brain perfusion single-photon emission computed tomography (SPECT), because the head outlined for a uniform attenuation coefficient map is set to the sinogram of the projection data by the threshold (Sinogram Threshold Chang method). Magnetic resonance imaging (MRI) is a routine examination in our hospital. Patients who underwent N-isopropyl-p-[(123)I] iodoamphetamine ((123)I-IMP) SPECT are undergoing MRI. Therefore, we thought it help AC accuracy to set an accurate head outline by using the image. We jointly made "Software for an attenuation coefficient map using MRI" for trial purposes. This paper investigated whether the AC method using MRI promotes the accuracy of brain perfusion SPECT in some clinical samples. With AC methods using gamma ray transmission computed tomography (TCT) or X-ray CT (CT) also being taken into account, the AC method using MRI was compared with the Sinogram Threshold Chang method. As a result, count dependency was excluded by an accurate head outline setting that used MRI, and the AC method using MRI approached the effect of the AC method using TCT and CT more than the Sinogram Threshold Chang method. Therefore, it is suggested that the AC method using MRI is useful for the accuracy of brain perfusion SPECT.

Effects of attenuation correction and reconstruction method on PET activation studies

To characterize ordered-subset expectation maximization algorithm with a fixed 3D Gauss post-reconstruction filtering (OSEM) in 99mTc SPECT as for noise, contrast and spatial resolution with varying number of subset and iteration and to compare OSEM with an optimized set of parameters, with filtered backprojection (FBP) with filter parameters typical of brain and myocardial SPECT, both with and without Chang's method of attenuation correction (AC). SPECT images of a Jaszczak phantom with cold rod inserts, hot and cold spheres and capillary line sources were acquired. Different background activity concentrations of the phantom were simulated as well as different lesion-to-background activity ratios. OSEM reconstructions were halted after 5, 10 and 15 iterations using 4, 8 and 16 subsets. The effect of subset and iteration number over noise is additive: thus, it is possible to define an EM-equivalent iteration number that indicates the product between the subset and the iteration numbers. Noise increases linearly with increasing EM-equivalent iteration number. For each level of nominal contrast, the measured contrast after OSEM shows a little increase with increasing iteration number and saturates after 80 EM-equivalent iterations. The application of AC leads to diminished contrast values both in FBP and OSEM. The contrast of cold lesions after OSEM increases with increasing number of EM-equivalent iteration number: after 80 iterations the contrast values with OSEM overtake the ones obtained with FBP; contrast values diminished as background concentration raised. Resolution values did not change with increasing EM-equivalent iteration number and were higher than those obtained with FBP. The major findings of the present work are the demonstration of additivity of subset and iteration in OSEM over noise, with the possibility of defining an EM equivalent iteration number, and the superiority of OSEM with respect to FBP in terms of spatial resolution.

Background: Whole-body PET images can be obtained by using the “step-and-shoot” (SaS) method (using multiple bed positions) or continuous bed motion (CBM). As transmission scans are not always feasible, an alternative method where attenuation data can be generated via emission-based attenuation correction (AC) maps is of interest. The aim of this preclinical study was to investigate the influence of the acquisition method and AC on the quantitation accuracy of [18F]FDG-PET.Methods: [18F]FDG-PET phantom images were acquired using either SaS or CBM. Transmission scans were recorded for the SaS method using a 57Co-point source. Emission-based attenuation sinograms were obtained from the images after segmentation and inverse Fourier rebinning. PET images were reconstructed without AC, transmission based (TX-AC) and emission-based (EM-AC) attenuation correction. Moreover, [18F]FDG-PET scans of rats bearing mammary carcinomas acquired using either SaS or CBM were analyzed retrospectively and quantification in tissues was compared.Results: Phantom recovery coefficients (RC) varied greatly, ranging from 0.49 ± 0.01 to 1.15 ± 0.07, dependent on acquisition method, reconstruction algorithm and AC method. In CBM acquired images, EM-AC improved quantification accuracy when compared to no-AC images in the phantom studies (RC 0.79 ± 0.02 vs. 0.49 ± 0.01, respectively) and in tumors of rats (DMBA model: 1.16±0.42 SUV vs. 0.86±0.28 SUV, respectively).Conclusion: The method of AC has a strong influence on the quantification of [18F]FDG. Our data indicates that EM-AC improves quantification in images obtained by CBM and SaS. However, the obtained values were still underestimated when compared to TX-AC corrected images.

For PET cameras without septa a transmission source of 0.5 mCi is adequate for attenuation correction while restricting near detector deadtime. However, emission contamination of post-injection transmission scans is then 30% for 1 mCi of emission activity in the FOV. The authors have developed a method to directly measure emission contamination of post-injection transmission scans using a virtual transmission source position offset by 20 degrees from the transmission source. Thus, the authors collect and subtract a masked emission contamination scan from the transmission scan. Intersection of transmission source gamma rays with the virtual source position mask is cancelled by performing the blank scan in the same manner. Thus, simultaneous and direct measurements of emission contamination are performed, removing the need for complex corrections to emission data and insensitive to activity redistributions between emission and transmission scanning. While the camera deadtime for pre-injection transmission (without emission activity in the FOV) is the same as for the blank scan, there is extra deadtime due to emission activity in the FOV during a post-injection transmission scan. This results from camera processing of the additional events from this emission activity. This excess deadtime depends primarily on the amount of emission activity. This activity is measured by detector singles countrates, so that we have generated a lookup table of extra deadtime vs countrate to correct for this. This method is accurate to 4% for 0.5 mCi in the FOV. Limitations to this method are (1) reduced transmission count densities due to deadtime which results in moderate increases in % standard deviations on measured attenuation coefficients, and (2) a transmission source angular dependent deadtime which is higher for transmission source angles that sample more than the average fraction of emission contamination events. This results in some underestimation of attenuation in high activity areas of the body. Clinical imaging using this method is now routine and often superior to pre-injection transmission since there is considerably less chance of patient motion between emission and transmission scans. From patient and phantom data taken with both pre- and post-injection transmission a lookup table of residual underestimation of attenuation correction by this method (due to angular dependent deadtimes) has been generated so that more accurate SUV calculations may be performed using post-injection transmission in a Volume Imaging PET Camera.

Attenuation correction of PET activation studies in the presenceof task-related motion

The acquisition and processing of the Jaszczak phantom is a recommended test by the American College of Radiology for evaluation of gamma camera system performance. To produce the reconstructed phantom image for quality evaluation, attenuation correction is applied. The attenuation of counts originating from the center of the phantom is greater than that originating from the periphery of the phantom causing an artifactual appearance of inhomogeneity in the reconstructed image and complicating phantom evaluation. Chang's mathematical formulation is a common method of attenuation correction applied on most gamma cameras that do not require an external transmission source such as computed tomography, radionuclide sources installed within the gantry of the camera or a flood source. Tomographic acquisition can be obtained in two different acquisition modes for dual-detector gamma camera; one where the two detectors are at 180° configuration and acquire projection images for a full 360°, and the other where the two detectors are positioned at a 90° configuration and acquire projections for only 180°. Though Chang's attenuation correction method has been used for 360° angle acquisition, its applicability for 180° angle acquisition remains a question with one vendor's camera software producing artifacts in the images. This work investigates whether Chang's attenuation correction technique can be applied to both acquisition modes by the development of a Chang's formulation-based algorithm that is applicable to both modes. Assessment of attenuation correction performance by phantom uniformity analysis illustrates improved uniformity with the proposed algorithm (22.6%) compared to the camera software (57.6%).

Attenuation correction (AC), as an essential component of quantitative SPECT imaging, is highly challenging in the absence of CT or transmission scanning in dedicated cardiac SPECT devices. This study investigated the potential of direct attenuation correction (AC) of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">99m</sup> Tc-sestamibi SPECT myocardial perfusion imaging (MPI) in the image domain using residual (ResNet) and UNet deep convolutional neural networks. MPI-SPECT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">99m</sup> Tc-ses-tamibi images of 99 subjects were retrospectively used, considering non-attenuation corrected SPECT images as input and CT-based attenuation corrected (CT-AC) SPECT images as reference. Chang’s AC technique was also performed as a baseline for evaluating the performance of deep learning-based models. The quantitative accuracy of the attenuation corrected SPECT images was validated using the proposed methods considering the corresponding CT-AC SPECT images of 19 external datasets as reference. Image-derived metrics, including the voxel-wise mean absolute error (MAE), relative error (RE), structural similarity index measure (SSIM), as well as clinically relevant indices, such as total perfusion deficit (TPD), were calculated. The quantitative results obtained from the external validation dataset of the deep learning models exhibited good agreement with the reference CT-based attenuation corrected MPI-SPECT images. The deep learning models showed superior performance over Chang’s AC method. The ResNet and UNet models resulted in MAE of 20.24±17.63 and 13.65±11.23 and SSIM of 0.99±0.04 and 0.98±0.05, respectively. In comparison, Chang’s approach led to MAE and SSIM of 80.27±47.56 and 0.93±0.09, respectively. Similarly, the clinical evaluation showed a mean TPD of 12.78±9.22% and 12.57±8.93% for ResNet and UNet models, respectively, compared to TPD of 12.84±8.63% for reference SPECT CT-AC images. In contrast, Chang’s approach led to a mean TPD of 16.68±11.24%. The evaluation of deep learning approaches implemented in this work showed the promising potential of deep learning-based techniques in producing attenuation corrected MPI-SPECT images in the image domain without anatomical imaging.

In pelvic bone SPECT using Tc-99m labeled compounds, physical effects such as nonhomogeneous attenuation and the accumulation of activity into the bladder during the data acquisition process can often result in data inconsistencies. With filtered backprojection (FBP) reconstruction, this may result in streak artifacts. Various methods for attenuation compensation can be employed to account for some of these streaks, but if the rate of uptake of tracer in to the bladder is sufficient, the resultant streaks may be significant enough to impair lesion detection. We have investigated various reconstruction methods in an effort to reduce these artifacts. In order to assess the impact of inconsistent bladder activities on the detection of pelvic lesions, SPECT imaging was simulated using the Zubal voxelized phantom, for cases of both a static bladder activity and a changing activity distribution. Reconstructions were performed using FBP, ordered subset-expectation maximization (OSEM) and dynamic expectation maximization (dEM) and was assessed for lesion detectability using a channelized, nonprewhitening (CNPW) numerical observer model. This observer model was used to optimize reconstruction strategies for a human LROC observer study. The human LROC observer study was performed in order to assess the various reconstruction methods in terms of lesion detectability. Three human observers were used in this test. The results of this test indicate that FBP performs significantly worse than static OSEM iterative reconstruction with attenuation correction when assessed using the area under the LROC curve (maximal ALROC=0.47 for FBP versus 0.71 for OSEM). Visually, the dEM algorithm produces images with slightly reduced streak artifacts compared to OSEM, but this improvement was not reflected in significantly improved ALROC values. In fact, when assessed using human LROC methodology, detectability actually decreased slightly when using dEM (maximal ALROC=0.71 for OSEM versus 0.66 for dEM), although this reduction was not determined to be statistically significant. It is possible that the slightly reduced performance of the dEM algorithm may be due, in part, to not performing an optimization in the number of reconstruction iterations as was performed for the OSEM method

The Siemens Biograph TruePoint TrueV (B-TPTV) positron emission tomography (PET) scanner performs 3D PET reconstruction using a system matrix with point spread function (PSF) modeling (called the True X reconstruction). PET resolution was dramatically improved with the True X method. In this study, we assessed the spatial resolution and image quality on a B-TPTV PET scanner. In addition, we assessed the feasibility of animal imaging with a B-TPTV PET and compared it with a microPET R4 scanner. Spatial resolution was measured at center and at 8 cm offset from the center in transverse plane with warm background activity. True X, ordered subset expectation maximization (OSEM) without PSF modeling, and filtered back-projection (FBP) reconstruction methods were used. Percent contrast (% contrast) and percent background variability (% BV) were assessed according to NEMA NU2-2007. The recovery coefficient (RC), non-uniformity, spill-over ratio (SOR), and PET imaging of the Micro Deluxe Phantom were assessed to compare image quality of B-TPTV PET with that of the microPET R4. When True X reconstruction was used, spatial resolution was <3.65 mm with warm background activity. % contrast and % BV with True X reconstruction were higher than those with the OSEM reconstruction algorithm without PSF modeling. In addition, the RC with True X reconstruction was higher than that with the FBP method and the OSEM without PSF modeling method on the microPET R4. The non-uniformity with True X reconstruction was higher than that with FBP and OSEM without PSF modeling on microPET R4. SOR with True X reconstruction was better than that with FBP or OSEM without PSF modeling on the microPET R4. This study assessed the performance of the True X reconstruction. Spatial resolution with True X reconstruction was improved by 45 % and its % contrast was significantly improved compared to those with the conventional OSEM without PSF modeling reconstruction algorithm. The noise level was higher than that with the other reconstruction algorithm. Therefore, True X reconstruction should be used with caution when quantifying PET data.

BackgroundPositron Emission Tomography (PET), Computed Tomography (CT), PET/CT and Single Photon Emission Tomography (SPECT) are non-invasive imaging tools used for creating two dimensional (2D) cross section images of three dimensional (3D) objects. PET and SPECT have the potential of providing functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules, whereas CT visualizes X-ray density in tissues in the body. PET/CT provides fused images representing both functional and anatomical information with better precision in localization than PET alone.Images generated by these types of techniques are generally noisy, thereby impairing the imaging potential and affecting the precision in quantitative values derived from the images. It is crucial to explore and understand the properties of noise in these imaging techniques. Here we used autocorrelation function (ACF) specifically to describe noise correlation and its non-isotropic behaviour in experimentally generated images of PET, CT, PET/CT and SPECT.MethodsExperiments were performed using phantoms with different shapes. In PET and PET/CT studies, data were acquired in 2D acquisition mode and reconstructed by both analytical filter back projection (FBP) and iterative, ordered subsets expectation maximisation (OSEM) methods. In the PET/CT studies, different magnitudes of X-ray dose in the transmission were employed by using different mA settings for the X-ray tube. In the CT studies, data were acquired using different slice thickness with and without applied dose reduction function and the images were reconstructed by FBP. SPECT studies were performed in 2D, reconstructed using FBP and OSEM, using post 3D filtering. ACF images were generated from the primary images, and profiles across the ACF images were used to describe the noise correlation in different directions. The variance of noise across the images was visualised as images and with profiles across these images.ResultsThe most important finding was that the pattern of noise correlation is rotation symmetric or isotropic, independent of object shape in PET and PET/CT images reconstructed using the iterative method. This is, however, not the case in FBP images when the shape of phantom is not circular. Also CT images reconstructed using FBP show the same non-isotropic pattern independent of slice thickness and utilization of care dose function. SPECT images show an isotropic correlation of the noise independent of object shape or applied reconstruction algorithm. Noise in PET/CT images was identical independent of the applied X-ray dose in the transmission part (CT), indicating that the noise from transmission with the applied doses does not propagate into the PET images showing that the noise from the emission part is dominant. The results indicate that in human studies it is possible to utilize a low dose in transmission part while maintaining the noise behaviour and the quality of the images.ConclusionThe combined effect of noise correlation for asymmetric objects and a varying noise variance across the image field significantly complicates the interpretation of the images when statistical methods are used, such as with statistical estimates of precision in average values, use of statistical parametric mapping methods and principal component analysis. Hence it is recommended that iterative reconstruction methods are used for such applications. However, it is possible to calculate the noise analytically in images reconstructed by FBP, while it is not possible to do the same calculation in images reconstructed by iterative methods. Therefore for performing statistical methods of analysis which depend on knowing the noise, FBP would be preferred.

Low energy (LE) collimator is generally used in I-123 SPECT imaging. However, the septal penetration and scattering of photons emitted with energy above 159 keV will affect the image contrast and quantitative accuracy of images. To reduce this effect, medium energy (ME) collimator has been used with the cost of lower counting statistics and spatial resolution. The effects of collimator dependency on the quantitative accuracy of attenuation corrected (AC) I-123 SPECT images using X-ray-based attenuation map was investigated. Both brain and heart/thorax phantoms were used to evaluate different degree of attenuation effect between brain and thorax. Experiments were performed at different target-to-background ratios to simulate different object contrast. Both photopeak and scatter projections were collected for dual-energy window scatter correction (SC). Images were reconstructed and compared using different reconstruction methods, which included FBP (filtered backprojection), and OSEM (ordered subset expectation maximization) without corrections, with AC, with SC, and with AC and SC. In both phantom studies, the image contrast and quantitative accuracy were both improved with the use of CT-based transmission map for AC. The image contrast provided by ME collimator was better than that of LE collimator, especially in the region with void activity of thorax phantom. From the results of phantom studies, medium energy collimator with CT-based transmission map showed improvements in image contrast and quantitative accuracy of I-123 SPECT images.

The combination of Positron Emission Tomography (PET) with magnetic resonance imaging (MRI) in hybrid PET/MRI scanners offers a number of advantages in investigating brain structure and function. A critical step of PET data reconstruction is attenuation correction (AC). Accounting for bone in attenuation maps (μ-map) was shown to be important in brain PET studies. While there are a number of MRI-based AC methods, no systematic comparison between them has been performed so far. The aim of this work was to study the different performance obtained by some of the recent methods presented in the literature. To perform such a comparison, we focused on [18F]-Fluorodeoxyglucose-PET/MRI neurodegenerative dementing disorders, which are known to exhibit reduced levels of glucose metabolism in certain brain regions. Four novel methods were used to calculate μ-maps from MRI data of 15 patients with Alzheimer's dementia (AD). The methods cover two atlas-based methods, a segmentation method, and a hybrid template/segmentation method. Additionally, the Dixon-based and a UTE-based method, offered by a vendor, were included in the comparison. Performance was assessed at three levels: tissue identification accuracy in the μ-map, quantitative accuracy of reconstructed PET data in specific brain regions, and precision in diagnostic images at identifying hypometabolic areas. Quantitative regional errors of -20--10% were obtained using the vendor's AC methods, whereas the novel methods produced errors in a margin of ±5%. The obtained precision at identifying areas with abnormally low levels of glucose uptake, potentially regions affected by AD, were 62.9 and 79.5% for the two vendor AC methods, the former ignoring bone and the latter including bone information. The precision increased to 87.5-93.3% in average for the four new methods, exhibiting similar performances. We confirm that the AC methods based on the Dixon and UTE sequences provided by the vendor are inferior to alternative techniques. As a novel finding, there was no substantial difference between the recently proposed atlas-based, template-based and segmentation-based methods.

Evaluation of an attenuation correction method for thallium-201 myocardial perfusion tomographic imaging of patients with low likelihood of coronary artery disease