Characterization of ordered-subsets expectation maximization with 3d post-reconstruction gauss filtering and comparison with filtered backprojection in99mTc SPECT

PURPOSE: 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). METHODS: 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. RESULTS: 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. CONCLUSION: 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.     

Does scatter correction of cardiac spect improve image quality in the presence of high extracardiac activity?

BACKGROUND: Extracardiac activity confounds conventional cardiac single photon emission computed tomography (SPECT) image reconstruction. It has been proposed that applying scatter correction (SC) may improve image quality. This study was done to test whether SC improves several quantitative measures of cardiac imaging in the presence of high extracardiac activity. METHODS AND RESULTS: An anatomic anthropomorphic phantom with a cardiac insert filled with technetium 99m was used. We obtained acquisitions using a dual-headed SPECT camera at 13 different levels of liver-to-heart activity. Each acquisition was reconstructed by use of each of 6 different methods: filtered backprojection with or without SC, maximum likelihood with or without SC, and maximum likelihood with attenuation correction (AC) and with or without SC. Three different parameters were used to assess the effect of the processing methods on image quality: image variability, contrast, and signal-to-noise ratio. Only image contrast improved significantly with SC. By adding SC to filtered backprojection, image contrast improved by 13% (P <.01). Maximum likelihood reconstruction with AC resulted in further improvement in contrast (increase of 17%), variability (decrease of 5%), and signal-to-noise ratio (increase of 6%) over filtered backprojection (all P <.01). CONCLUSION: Image quality improved significantly when SC was applied, especially when combined with maximum likelihood reconstruction with AC. This improvement was present despite increased extracardiac activity in close proximity to the heart.     

Differences due to collimator blurring in cardiac images with use of circular and elliptic camera orbits

BACKGROUND: In cardiac imaging systems, an elliptic acquisition orbit about the patient can be used to enhance resolution of single photon emission computed tomography (SPECT) images by minimizing the distance between the object imaged and the rotating detector system. In this study artifacts from images acquired with the standard circular acquisition are compared with those acquired with various elliptic acquisitions. METHODS AND RESULTS: With the use of elliptic camera orbits of different eccentricities, simulated projection data were generated from a slice through the left ventricle (LV). The projection data included a simulation of the degradation due to the depth-dependent response of the collimator. As is common in many clinical systems, SPECT images were reconstructed with the standard filtered backprojection algorithm without correction for the collimator response. When the ratio of the major-to-minor axis of the acquisition arc is changed from 1 (circular) to 1.5 (elliptic), reconstructed SPECT images show an additional loss of counts (about 10%) in the apical region of the LV. The severity of the apical defect is also dependent on the starting angle of the acquisition arc. When the starting angle is changed from 0 degrees (detector parallel to the major axis of the LV) to 60 degrees, the ratio between the minimum count in the apical region and the maximum count in the left ventricular myocardial wall decreases by as much as 20%. CONCLUSIONS: SPECT image artifacts from elliptic acquisitions are significantly more severe than those from circular acquisitions. Because of the significant difference in images reconstructed from circular and elliptic acquisitions, standardized normal files acquired from circular acquisitions should not be used for comparisons with patient data acquired from elliptic acquisitions.     

PET kinetic analysis: wavelet denoising of dynamic PET data with application to parametric imaging

Physiological functions (e.g., cerebral blood flow, glucose metabolism, and neuroreceptor binding) can be investigated as parameters estimated by kinetic modeling using dynamic positron emission tomography (PET) images. Imaging of these physiological parameters, called parametric imaging, can locate the regional distribution of functionalities. However, the most serious technical issue affecting parametric imaging is noise in dynamic PET data. This review describes wavelet denoising of dynamic PET images for improving image quality in estimated parametric images. Wavelet denoising provides significantly improved quality directly to dynamic PET images and indirectly to estimated parametric images. The application of wavelet denoising to radio-ligand and kinetic analysis is still in the development stage, but even so, it is thought that wavelet techniques will have a substantial impact on nuclear medicine in the near future.     

Automatic arm removal in PET and CT images for deformable registration

Positron emission tomography (PET) imaging is rapidly expanding its role in clinical practice for cancer management. The high sensitivity of PET for functional abnormalities associated with cancer can be confounded by the minimal anatomical information it provides for cancer localization. Computed tomography (CT) provides detailed anatomical information but is less sensitive to pathologies than PET. Thus, combining (i.e., registering) PET and CT images would enable both accurate and sensitive cancer localization with respect to detailed patient anatomy. An additional application area of registration is to align CT–CT scans from serial studies on a patient on a PET/CT scanner to facilitate accurate assessment of therapeutic response from the co-aligned PET images. To facilitate image fusion, we are developing a deformable registration software system using mutual information and a B-spline model of the deformation. When applying deformable registration to whole body images, one of the obstacles is that the arms are present in PET images but not in CT images or are in different positions in serial CT images. This feature mismatch requires a preprocessing step to remove the arms where present and thus adds a manual step in an otherwise automatic algorithm. In this paper, we present a simple yet effective method for automatic arm removal. We demonstrate the efficiency and robustness of this algorithm on both clinical PET and CT images. By streamlining the entire registration process, we expect that the fusion technology will soon find its way into clinics, greatly benefiting cancer diagnosis, staging, therapy planning and treatment monitoring.     

Performance evaluation of OSEM reconstruction algorithm incorporating three-dimensional distance-dependent resolution compensation for brain SPECT: A simulation study

Iterative reconstruction techniques such as an ordered subsets-expectation maximization (OSEM) algorithm can easily incorporated various physical models of attenuation or scatter. We implemented OSEM reconstruction algorithm incorporating compensation for distance-dependent blurring due to the collimator in SPECT. The algorithm was examined by computer simulation to estimate the accuracy for brain perfusion study. METHODS: The detector response was assumed to be a two-dimensional Gauss function and the width of the function varied linearly with the source-to-detector distance. The attenuation compensation (AC) was also included. To investigate the properties of the algorithm, we performed computer simulations with the point source and digital brain phantoms. In the point source phantom, the uniformity of FWHM for the radial, tangential and longitudinal directions was evaluated on the reconstruction image. As for the brain phantom, quantitative accuracy was estimated by comparing the reconstructed images with the true image by the mean square error (MSE) and the ratio of gray and white matter counts (G/W). Both noise free and noisy simulations were examined. RESULTS: In the point source simulation, FWHM in radial, tangential and longitudinal directions were 14.7, 14.7 and 15.0 mm at the image center and were 15.9, 9.83 and 10.6 mm at a distance of 15 cm from the center by using FBP, respectively. On the other hand, they were 8.12, 8.12 and 7.83 mm at the image center, and were 7.45, 7.44 and 7.01 mm at 15 cm from the center by OSEM with distance-dependent resolution compensation (DRC). An isotropic and stationary resolution was obtained at any location by OSEM with DRC. The spatial resolution was also improved about 6.5 mm by OSEM with DRC at the image center. In the brain phantom simulation, the blurring at the edge of the brain structure was eliminated by using OSEM with both DRC and AC. The G/W was 2.95 and 2.68 for noise free and noisy cases, respectively, when no compensation was performed. But the values for G/W without and with noise became 3.45 and 3.21 with AC only and were improved to 3.75 and 3.71 with both AC and DRC. The G/W approached the true value (4.00) by using OSEM with both AC and DRC even when there was statistical noise. CONCLUSION: In conclusion, OSEM reconstruction including the distance-dependent resolution compensation algorithm was reasonably successful in achieving isotropic and stationary resolution and improving the quantitative accuracy for brain perfusion SPECT.     

图像重建条件对PET脑显像SPM分析结果的影响

目的 探讨不同图像重建条件对^18F—FDG PET脑显像统计参数图（SPM）处理结果的影响。方法对6名健康受试者分别实施真、假针刺条件下的^18F-FDG PET脑显像。分别用4种重建条件进行图像重建。对每一重建结果均用SPM软件进行对齐、归一化及平滑处理，并进行配对t检验。结果 （1）SPM校正多重比较（P校正〈0．05）的统计学处理示，4种条件的重建结果中无一像素超阈值激活；（2）SPM未校正多重比较（P未校正〈0．001）的统计学处理示，4种重建条件的SPM结果不一致。2种重建算法（滤波反投影法和有序子集最大期望值迭代法）间差异最明显，不仅激活的像素总数及区域个数有差异，激活区的空间位置也大多不一致。结论 PET图像重建条件对SPM未校正多重比较的统计学处理结果有影响，下结论要慎重。     

Comparison of Bayesian penalized likelihood reconstruction versus OS-EM for characterization of small pulmonary nodules in oncologic PET/CT

Objective

To determine whether the recently introduced Bayesian penalized likelihood PET reconstruction (Q.Clear) increases the visual conspicuity and SUV_max of small pulmonary nodules near the PET resolution limit, relative to ordered subset expectation maximization (OS-EM).

Methods

In this institutional review board-approved and HIPAA-compliant study, 29 FDG PET/CT scans performed on a five-ring GE Discovery IQ were retrospectively selected for pulmonary nodules described in the radiologist’s report as “too small to characterize”, or small lung nodules in patients at high risk for lung cancer. Thirty-two pulmonary nodules were assessed, with mean CT diameter of 8 mm (range 2–18). PET images were reconstructed with OS-EM and Q.Clear with noise penalty strength β values of 150, 250, and 350. Lesion visual conspicuity was scored by three readers on a 3-point scale, and lesion SUV_max and background liver and blood pool SUV_mean and SUV_stdev were recorded. Comparison was made by linear mixed model with modified Bonferroni post hoc testing; significance cutoff was p < 0.05.

Results

Q.Clear improved lesion visual conspicuity compared to OS-EM at β = 150 (p < 0.01), but not 250 or 350. Lesion SUV_max was increased compared to OS-EM at β = 150 and 250 (p < 0.01), but not 350.

Conclusion

In a cohort of small pulmonary nodules with size near an 8 mm PET full-width half maximum, Q.Clear significantly increased lesion visual conspicuity and SUV_max compared to our standard non- time-of-flight OS-EM reconstruction, but only with low noise penalization. Q.Clear with β = 150 may be advantageous when evaluation of small pulmonary nodules is of primary concern.

     

An evaluation of the accelerated expectation maximization algorithms for single-photon emission tomography image reconstruction

We previously reported that brain single-photon emission tomography (SPET) images could be improved by using an attenuation coefficient map constructed with transmission data and the iterative expectation maximization (EM) algorithm. However, the conventional EM algorithm (CEM) typically requires 30–80 iterations to provide acceptable results, limiting its clinical applicability. Several methods have been proposed to accelerate the EM algorithm. The purpose of this study was to search for a practical method for accelerating the EM algorithm. The methods investigated here include the accelerated EM algorithm (ACEM) using additive correction, ACEM using multiplicative correction, and Tanaka's filtered iterative reconstruction method (FIR). These methods were assessed by simulated SPET studies of a phantom incorporating nonuniform attenuation and by reference to clinical brain SPET data. In the simulation studies, the above methods were evaluated by using three parameters (root mean square error, log likelihood value, and contrast recovery coefficient); the results showed that FIR had an advantage over other methods in terms of all parameters. The results obtained using the clinical data demonstrated that FIR could reconstruct acceptable images in only five iterations. These results show that FIR offers significant advantages over CEM or other ACEMs, indicating that FIR can make the EM algorithm practical for clinical use in SPET.     

Optimized Bayes variational regularization prior for 3D PET images

A new prior for variational Maximum a Posteriori regularization is proposed to be used in a 3D One-Step-Late (OSL) reconstruction algorithm accounting also for the Point Spread Function (PSF) of the PET system.The new regularization prior strongly smoothes background regions, while preserving transitions. A detectability index is proposed to optimize the prior.The new algorithm has been compared with different reconstruction algorithms such as 3D-OSEM + PSF, 3D-OSEM + PSF + post-filtering and 3D-OSL with a Gauss-Total Variation (GTV) prior.The proposed regularization allows controlling noise, while maintaining good signal recovery; compared to the other algorithms it demonstrates a very good compromise between an improved quantitation and good image quality.     

Value of fusion of PET and MRI for staging of endometrial cancer: Comparison with F-FDG contrast-enhanced PET/CT and dynamic contrast-enhanced pelvic MRI

Purpose

To investigate the diagnostic value of retrospective fusion of pelvic MRI and ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET images for assessment of locoregional extension and nodal staging of endometrial cancer.

Materials and methods

Thirty patients with biopsy-proven endometrial cancer underwent preoperative contrast-enhanced PET/CT (PET/ceCT) and pelvic dynamic contrast-enhanced MRI for initial staging. Diagnostic performance of PET/ceCT, contrast-enhanced MRI, and retrospective image fusion from PET and MRI (fused PET/MRI) for assessing the extent of the primary tumor (T stage) and metastasis to regional LNs (N stage) was evaluated by two experienced readers. Histopathological and follow-up imaging results were used as the gold standard. The McNemar test was employed for statistical analysis.

Results

Fused PET/MRI and MRI detected 96.7% of the primary tumors, whereas PET/ceCT detected 93.3%. Accuracy for T status was 80.0% for fused PET/MRI, and MRI proved significantly more accurate than PET/ceCT, which had an accuracy of 60.0% (p = 0.041). Patient-based sensitivity, specificity and accuracy for detecting pelvic nodal metastasis were 100%, 96.3% and 96.7% for both fused PET/MRI and PET/ceCT, and 66.7%, 100% and 96.7% for MRI, respectively. These three parameters were not statistically significant (p = 1).

Conclusion

Fused PET/MRI, which complements the individual advantages of MRI and PET, is a valuable technique for assessment of the primary tumor and nodal staging in patients with endometrial cancer.     

Optimisation of the OS-EM algorithm and comparison with FBP for image reconstruction on a dual-head camera: a phantom and a clinical <Superscript>18</Superscript>F-FDG study

Iterative reconstruction algorithms, such as the ordered subsets expectation maximisation (OS-EM), are a promising alternative to filtered backprojection (FBP). The aims of this study were first to optimise the OS-EM algorithm in terms of iteration number and to study the usefulness of post-filtering, and second to compare OS-EM and FBP for image reconstruction on a fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) dual-head camera (DHC). These two goals were addressed using phantom acquisitions. The performances of these algorithms were also studied in patient acquisitions performed on a DHC and a PET on the same day. Phantom experiments were performed on a DHC using a Jaszczak phantom containing six spheres filled with ¹⁸F-FDG, two background levels (0.95, 6.80 kBq/ml) and three object contrasts (5.9, 3.7, 2.7). The reconstruction algorithms were FBP with a Gaussian filter (FWHM 0.5–2 pixel width) and OS-EM using 8–128 equivalent iterations (equivalent to the ML-EM algorithm) with and without Gaussian post-filtering [OS-EM (iterations, pixel width)]. Contrast recovery coefficient (CRC) and noise characteristics were assessed. Twenty-two patients (21 male, one female; age 55±15 years) with lung cancer underwent, on the same day, PET (1 h post injection of 37 MBq/kg ¹⁸F-FDG) and DHC acquisitions (3 h post injection). DHC data were reconstructed using six methods: FBP (1), OS-EM (16), (40), (40,1), (64) and (64,1). These sets were evaluated by two observers and compared to PET reconstructed with OS-EM (16). The number of detected lesions and the visual quality were assessed. A marked improvement in CRC was observed with OS-EM as compared with FBP when more than 24 iterations were used. The CRC increased markedly from 8 to 40 iterations and then reached a plateau. The noise was stable until 40 iterations and then increased. The best compromise was obtained for OS-EM (32) and OS-EM (40,1). For the patient study, OS-EM provided images of better visual quality, but with no significant difference in detection sensitivity. OS-EM was superior to FBP in terms of contrast recovery and noise level. The optimal compromise between contrast recovery and noise was obtained for OS-EM (32) and (40,1) on the phantom study. The clinical study showed that OS-EM yielded images of better visual quality but with no improvement in terms of detection of lung cancer.     

Principal component analysis of dynamic positron emission tomography images

Multivariate image analysis can be used to analyse multivariate medical images. The purpose could be to visualize or classify structures in the image. One common multivariate image analysis technique which can be used for visualization purposes is principal component analysis (PCA). The present work concerns visualization of organs and structures with different kinetics in a dynamic sequence utilizing PCA. When applying PCA on positron emission tomography (PET) images, the result is initially not satisfactory. It is illustrated that one major explanation for the behaviour of PCA when applied to PET images is that it is a data-driven technique which cannot separate signals from high noise levels. With a better understanding of the PCA, gained with a strategy of examining the image data set, the transformations, and the results using visualization tools, a surprisingly easily understood methodology can be derived. The proposed methodology can enhance clinically interesting information in a dynamic PET imaging sequence in the first few principal component images and thus should be able to aid in the identification of structures for further analysis.     

Myocardial perfusion SPECT reconstruction: Receiver operating characteristic comparison of CAD detection accuracy of filtered backprojection reconstruction with all of the clinical imaging information available to readers and solely stress slices iteratively reconstructed with combined compensation

BACKGROUND: Past receiver operating characteristic (ROC) studies have demonstrated that single photon emission computed tomography (SPECT) perfusion imaging by use of iterative reconstruction with combined compensation for attenuation, scatter, and detector response leads to higher area under the ROC curve (A(z)) values for detection of coronary artery disease (CAD) in comparison to the use of filtered backprojection (FBP) with no compensations. A new ROC study was conducted to investigate whether this improvement still holds for iterative reconstruction when observers have available all of the imaging information normally presented to clinical interpreters when reading FBP SPECT perfusion slices. METHODS AND RESULTS: A total of 87 patient studies including 50 patients referred for angiography and 37 patients with a lower than 5% likelihood for CAD were included in the ROC study. The images from the two methods were read by 4 cardiology fellows and 3 attending nuclear cardiologists. Presented for the FBP readings were the short-axis, horizontal long-axis, and vertical long-axis slices for both the stress and rest images; cine images of both the stress and rest projection data; cine images of selected cardiac-gated slices; the CEQUAL-generated stress and rest polar maps; and an indication of patient gender. This was compared with reading solely the iterative reconstructed stress slices with combined compensation for attenuation, scatter, and resolution. With A(z) as the criterion, a 2-way analysis of variance showed a significant improvement in detection accuracy for CAD for the 7 observers (P = .018) for iterative reconstruction with combined compensation (A(z) of 0.895 +/- 0.016) over FBP even with the additional imaging information provided to the observers when scoring the FBP slices (A(z) of 0.869 +/- 0.030). When the groups of 3 attending physicians or 4 cardiology fellows were compared separately, the iterative technique was not statistically significantly better; however, the A(z) for each of the 7 observers individually was larger for iterative reconstruction than for FBP. Compared with results from our previous studies, the additional imaging information did increase the diagnostic accuracy of FBP for CAD but not enough to undo the statistically significantly higher diagnostic accuracy of iterative reconstruction with combined compensation. CONCLUSIONS: We have determined through an ROC investigation that included two classes of observers (experienced attending physicians and cardiology fellows in training) that iterative reconstruction with combined compensation provides statistically significantly better detection accuracy (larger A(z)) for CAD than FBP reconstructions even when the FBP studies were read with all of the extra clinical nuclear imaging information normally available.     

Evaluation of dynamic row-action maximum likelihood algorithm reconstruction for quantitative 15O brain PET

Objective  

A modified version of row-action maximum likelihood algorithm (RAMLA) using a ‘subset-dependent’ relaxation parameter for noise suppression, or dynamic RAMLA (DRAMA), has been proposed. The aim of this study was to assess the capability of DRAMA reconstruction for quantitative ¹⁵O brain positron emission tomography (PET).     

Evaluation of regional myocardial function using automated wall motion analysis of cine MR images: Contribution of parametric images, contraction times, and radial velocities

PURPOSE: To develop fast and robust procedures for a clinical evaluation of regional myocardial contractile function. MATERIALS AND METHODS: Parametric analysis of main motion was applied to steady-state free-precession (SSFP) cine MR images. From the time-signal intensity curve associated with each pixel, parametric maps of mean high and low amplitudes and transition times between muscle and cavity were automatically computed. Then, regional time to first contraction, T(fc), mean contraction time, T(mc) and radial component of the endocardial velocity, V(m) were estimated from these parametric maps and a user-defined endocardial end-diastolic contour. The method was applied to short-axis slices in 22 subjects: eight controls, 13 myocardial infarctions (MIs), and one left bundle branch block (LBBB). RESULTS: Typical patterns of normality and pathology on parametric maps are indicated. For controls, the mean values +/- standard deviations (SDs) of T(fc), T(mc), and V(m) were: 70 +/- 25 msec, 318 +/- 43 msec, and 4.6 +/- 1.8 cm second(-1). An apex to base gradient of T(fc), a significant septal delay in T(fc) and T(mc), and a decrease of V(m) between the lateral and septal walls were observed. For MI, T(fc) and T(mc) increased and V(m) decreased significantly in pathological segments. For LBBB, large delays were estimated in the septal wall. CONCLUSION: The proposed method is promising for clinical assessment of regional wall contraction.     

Evaluation of iterative reconstruction (OSEM) versus filtered back-projection for the assessment of myocardial glucose uptake and myocardial perfusion using dynamic PET

Purpose Iterative reconstruction methods based on ordered-subset expectation maximisation (OSEM) has replaced filtered backprojection (FBP) in many clinical settings owing to the superior image quality. Whether OSEM is as accurate as FBP in quantitative positron emission tomography (PET) is uncertain. We compared the accuracy of OSEM and FBP for regional myocardial ¹⁸F-FDG uptake and ¹³NH₃ perfusion measurements in cardiac PET. Methods Ten healthy volunteers were studied. Five underwent dynamic ¹⁸F-FDG PET during hyperinsulinaemic–euglycaemic clamp, and five underwent ¹³NH₃ perfusion measurement during rest and adenosine-induced hyperaemia. Images were reconstructed using FBP and OSEM ± an 8-mm Gaussian post-reconstruction filter. Results Filtered and unfiltered images showed agreement between the reconstruction methods within ±2SD in Bland-Altman plots of K _i values. The use of a Gaussian filter resulted in a systematic underestimation of K _i in the filtered images of 11%. The mean deviation between the reconstruction methods for both unfiltered and filtered images was 1.3%. Agreement within ±2SD between the methods was demonstrated for perfusion rate constants up to 2.5 min⁻¹, corresponding to a perfusion of 3.4 ml g⁻¹ min⁻¹. The mean deviation between the two methods for unfiltered data was 2.7%, and for filtered data, 5.3%. Conclusion The ¹⁸F-FDG uptake rate constants showed excellent agreement between the two reconstruction methods. In the perfusion range up to 3.4 ml g⁻¹ min⁻¹, agreement between ¹³NH₃ perfusion obtained with OSEM and FBP was acceptable. The use of OSEM for measurement of perfusion values higher than 3.4 ml g⁻¹ min⁻¹ requires further evaluation.     

Phantom study of the impact of reconstruction parameters on the detection of mini- and micro-volume lesions with a low-dose PET/CT acquisition protocol

Purpose

Every PET scanner suffers of the partial volume effect (PVE), that is a loss of contrast in small lesions causing a worsening in standardized uptake value (SUV) accuracy, that is critical if quantitative PET/CT imaging is used for diagnosis and therapy.

Methods

In order to quantify PVE and optimize our clinical protocols to minimize this effect in a last generation PET/CT scanner, we utilized a cylindrical phantom equipped with ten mini- and micro-volume hollow spheres. The lesion detectability and the SUV accuracy were evaluated at a fixed spheres to background intrinsic contrast (activity concentration ratio 8:1) but in different scan conditions: (a) acquisition modality (3D vs. 2D), (b) number of subset per iteration, (c) type of post-reconstruction filter and (d) activity concentration (i.e. total counts). Also the effect of different absorber thickness was evaluated.

Results

Small lesion detectability resulted better in images acquired in 3D mode rather than 2D, mainly because of the lower noise produced by the fully-3D algorithm. The number of reconstruction iterations and the post-processing filter used affected both the contrast underestimation and the spatial resolution. Decreasing the ¹⁸F activity injected according to the low-dose protocol, the small lesions could be distinguished from the background down to a diameter of 6.2 mm and the SUV accuracy did not deteriorate. Adding absorber thickness around the phantom, the image noise slightly increased while SUV accuracy did not change.

Conclusions

The hybrid PET/CT scanner we evaluated showed good performances, mainly in 3D acquisition modality. The phantom measurements showed that the most appropriate reconstruction protocol derived from a compromise between the contrast accuracy and the noise variance in PET images. The low-dose protocol clinically used demonstrated no loss in SUV accuracy and an adequate lesion detectability for lesions down to 6.2 mm in diameter.     

Brain FDG PET study of normal aging in Japanese: effect of atrophy correction

Purpose The aim of this study was to investigate the effects of atrophy correction on the results of ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET) in the context of normal aging.Methods Before the human study was performed, a Hoffman 3D brain phantom experiment was carried out in order to validate a newly developed correction method for partial volume effects (PVEs). Brain FDG PET was then performed in 139 healthy Japanese volunteers (71 men, 68 women; age 24–81 years). PET images were corrected for PVEs using grey matter volume, which was segmented from co-registered magnetic resonance images and convoluted with the spatial resolution of the PET scanner. We investigated the correlation between advancing age and relative regional FDG activity, which was normalised to the global activity before and after PVE correction using Statistical Parametric Mapping 99.Results The PET image, when corrected for PVEs, provided more homogeneous tracer distribution in the whole phantom than in the original PET image. The human PET study of both sexes revealed significant negative correlations between age and relative FDG activity in the bilateral perisylvian and medial frontal areas before PVE correction. However, these negative correlations were largely resolved after PVE correction.Conclusion Correction for PVEs was effective in our FDG PET study. The reduction in FDG uptake with advancing age that was detected by FDG PET without PVE correction could be accounted for largely by an age-related cerebral volume loss in the bilateral perisylvian and medial frontal areas.     

数据采集方式对脑PET图像的影响

目的评价不同采集方式对18F-脱氧葡萄糖(FDG)PET脑显像图的影响.方法通过改变条件和参数,分别得到不同采集模式、不同发射计数、不同透射时间下模型脑PET重建图像,并与参考图像相比,研究不同采集模式、不同数据采集对脑PET重建图像的影响.结果与二维采集相比,三维采集条件下重建图像的本底和高频噪音较多,且对颅顶、颅底结构的显示较差,但对大脑中间结构的显示与二维采集基本一致.二维采集条件下灰质/白质放射性比值为2.108±0.183,而三维采集条件下为2.286±0.232,差异无显著性(t=0.73,P>0.05).不同发射计数情况下,1×108、2×108、4×108发射计数下灰质/白质放射性比值分别为2.108±0.183、2.125±0.158、2.161±0.176,差异无显著性(P>0.05).不同透射计数的情况下,随着计数(即扫描时间)的增加,分割图像中脑模型的轮廓和脑内结构的边界趋向完整和清楚.结论不同采集模式、不同透射计数和不同发射计数对PET图像会产生一定影响,临床应加以注意.