Attenuation correction for three-dimensional PET using uncollimated flood-source transmission measurements

An attenuation-correction method for three-dimensional PET imaging, which obtains attenuation-correction factors from transmission measurements using an uncollimated flood source, is described. This correction is demonstrated for two different phantoms using transmission data acquired with QPET, a rotating imaging system with two planar detectors developed for imaging small volumes. The scatter amplitude in the transmission projections was a maximum of 30%; to obtain accurate attenuation-correction factors the scatter distribution was first calculated and subtracted. The attenuation-corrected emission images for both phantoms indicate that their original uniform amplitudes have been restored. The attenuation correction adds only a small amount of noise to the emission images, as evaluated from the standard deviation over a central region. For the first phantom, with maximum attenuation of 48%, the noise added was 2.6%. The second phantom was attenuated by a maximum of 37%, and 1.9% noise was added. Because the transmission data are smoothed, some artifacts are visible at the edges of the phantom where the correction factors change abruptly within the emission image.     

A motion-incorporated reconstruction method for gated PET studies

Cardiac and respiratory motion artefacts in PET imaging have been traditionally resolved by acquiring the data in gated mode. However, gated PET images are usually characterized by high noise content due to their low photon statistics. In this paper, we present a novel 4D model for the PET imaging system, which can incorporate motion information to generate a motion-free image with all acquired data. A computer simulation and a phantom study were conducted to test the performance of this approach. The computer simulation was based on a digital phantom that was continuously scaled during data acquisition. The phantom study, on the other hand, used two spheres in a tank of water, all of which were filled with (18)F water. One of the spheres was stationary while the other moved in a sinusoidal fashion to simulate tumour motion in the thorax. Data were acquired using both 4D CT and gated PET. Motion information was derived from the 4D CT images and then used in the 4D PET model. Both studies showed that this 4D PET model had a good motion-compensating capability. In the phantom study, this approach reduced quantification error of the radioactivity concentration by 95% when compared to a corresponding static acquisition, while signal-to-noise ratio was improved by 210% when compared to a corresponding gated image.     

A multiresolution image based approach for correction of partial volume effects in emission tomography

Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography. They lead to a loss of signal in tissues of size similar to the point spread function and induce activity spillover between regions. Although PVE can be corrected for by using algorithms that provide the correct radioactivity concentration in a series of regions of interest (ROIs), so far little attention has been given to the possibility of creating improved images as a result of PVE correction. Potential advantages of PVE-corrected images include the ability to accurately delineate functional volumes as well as improving tumour-to-background ratio, resulting in an associated improvement in the analysis of response to therapy studies and diagnostic examinations, respectively. The objective of our study was therefore to develop a methodology for PVE correction not only to enable the accurate recuperation of activity concentrations, but also to generate PVE-corrected images. In the multiresolution analysis that we define here, details of a high-resolution image H (MRI or CT) are extracted, transformed and integrated in a low-resolution image L (PET or SPECT). A discrete wavelet transform of both H and L images is performed by using the "à trous" algorithm, which allows the spatial frequencies (details, edges, textures) to be obtained easily at a level of resolution common to H and L. A model is then inferred to build the lacking details of L from the high-frequency details in H. The process was successfully tested on synthetic and simulated data, proving the ability to obtain accurately corrected images. Quantitative PVE correction was found to be comparable with a method considered as a reference but limited to ROI analyses. Visual improvement and quantitative correction were also obtained in two examples of clinical images, the first using a combined PET/CT scanner with a lymphoma patient and the second using a FDG brain PET and corresponding T1-weighted MRI in an epileptic patient.     

Surface and volume rendering in three-dimensional imaging: A comparison

Many surface rendering techniques are currently available for the three-dimensional display of structure data captured by imaging devices. Comparatively fewer volume rendering techniques are also available for the same purpose. The relative performance of these two methodologies in visualization tasks has been a subject of much discussion recently. Although it is very desirable to establish, based on observer studies, objective guidelines stating the relative merits of the two methodologies even for specific situations, it is impossible to conduct meaningful observer studies that take into account the numerousness of the techniques in each methodology, and within each technique, the numerousness of the parameters and their values that control the outcome of the technique. Our aim in this article is to compare the two methodologies purely on a technical basis in an attempt to understand their common weaknesses and disparate strengths. The purpose of this article is twofold--to report a new surface rendering technique and to compare it with two volume rendering techniques reported recently in the literature. The bases of comparison are: ability to portray thin bones; clarity of portrayal of sutures, fractures, fine textures, and gyrations; smoothness of natural ridges and silhouettes; and computational time and storage requirements. We analyze the underlying algorithms to study how they behave under each of these comparative criteria. Our conclusion is that, at the current state of development, the surface method has a slight edge over the volume methods for portrayal of information of the type described above and a significant advantage considering time and storage requirements, for implementations in identical environments.     

Quantification accuracy and partial volume effect in dependence of the attenuation correction of a state-of-the-art small animal PET scanner

Quantification accuracy and partial volume effect (PVE) of the Siemens Inveon PET scanner were evaluated. The influence of transmission source activities (40 and 160 MBq) on the quantification accuracy and the PVE were determined. Dynamic range, object size and PVE for different sphere sizes, contrast ratios and positions in the field of view (FOV) were evaluated. The acquired data were reconstructed using different algorithms and correction methods. The activity level of the transmission source and the total emission activity in the FOV strongly influenced the attenuation maps. Reconstruction algorithms, correction methods, object size and location within the FOV had a strong influence on the PVE in all configurations. All evaluated parameters potentially influence the quantification accuracy. Hence, all protocols should be kept constant during a study to allow a comparison between different scans.     

Fuzzy clustering-based segmented attenuation correction in whole-body PET imaging

Segmented attenuation correction is now a widely accepted technique to reduce noise propagation from transmission scanning in positron emission tomography (PET). In this paper, we present a new method for segmenting transmission images in whole-body scanning. This reduces the noise in the correction maps while still correcting for differing attenuation coefficients of specific tissues. Based on the fuzzy C-means (FCM) algorithm, the method segments the PET transmission images into a given number of clusters to extract specific areas of differing attenuation such as air, the lungs and soft tissue, preceded by a median filtering procedure. The reconstructed transmission image voxels are, therefore, segmented into populations of uniform attenuation based on knowledge of the human anatomy. The clustering procedure starts with an overspecified number of clusters followed by a merging process to group clusters with similar properties (redundant clusters) and removal of some undesired substructures using anatomical knowledge. The method is unsupervised, adaptive and allows the classification of both pre- or post-injection transmission images obtained using either coincident 68Ge or single-photon 137Cs sources into main tissue components in terms of attenuation coefficients. A high-quality transmission image of the scanner bed is obtained from a high statistics scan and added to the transmission image. The segmented transmission images are then forward projected to generate attenuation correction factors to be used for the reconstruction of the corresponding emission scan. The technique has been tested on a chest phantom simulating the lungs, heart cavity and the spine, the Rando-Alderson phantom, and whole-body clinical PET studies showing a remarkable improvement in image quality, a clear reduction of noise propagation from transmission into emission data allowing for reduction of transmission scan duration. There was very good correlation (R2 = 0.96) between maximum standardized uptake values (SUVs) in lung nodules measured on images reconstructed with measured and segmented attenuation correction with a statistically significant decrease in SUV (17.03% +/- 8.4%, P < 0.01) on the latter images, whereas no proof of statistically significant differences on the average SUVs was observed. Finally, the potential of the FCM algorithm as a segmentation method and its limitations as well as other prospective applications of the technique are discussed.     

Method for transforming CT images for attenuation correction in PET/CT imaging

A tube-voltage-dependent scheme is presented for transforming Hounsfield units (HU) measured by different computed tomography (CT) scanners at different x-ray tube voltages (kVp) to 511 keV linear attenuation values for attenuation correction in positron emission tomography (PET) data reconstruction. A Gammex 467 electron density CT phantom was imaged using a Siemens Sensation 16-slice CT, a Siemens Emotion 6-slice CT, a GE Lightspeed 16-slice CT, a Hitachi CXR 4-slice CT, and a Toshiba Aquilion 16-slice CT at kVp ranging from 80 to 140 kVp. All of these CT scanners are also available in combination with a PET scanner as a PET/CT tomograph. HU obtained for various reference tissue substitutes in the phantom were compared with the known linear attenuation values at 511 keV. The transformation, appropriate for lung, soft tissue, and bone, yields the function 9.6 x 10(-5). (HU+ 1000) below a threshold of approximately 50 HU and a (HU+ 1000)+b above the threshold, where a and b are fixed parameters that depend on the kVp setting. The use of the kVp-dependent scaling procedure leads to a significant improvement in reconstructed PET activity levels in phantom measurements, resolving errors of almost 40% otherwise seen for the case of dense bone phantoms at 80 kVp. Results are also presented for patient studies involving multiple CT scans at different kVp settings, which should all lead to the same 511 keV linear attenuation values. A linear fit to values obtained from 140 kVp CT images using the kVp-dependent scaling plotted as a function of the corresponding values obtained from 80 kVp CT images yielded y = 1.003 x -0.001 with an R2 value of 0.999, indicating that the same values are obtained to a high degree of accuracy.     

Attenuation correction of PET cardiac data with low-dose average CT in PET/CT

We proposed a low-dose average computer tomography (ACT) for attenuation correction (AC) of the PET cardiac data in PET/CT. The ACT was obtained from a cine CT scan of over one breath cycle per couch position while the patient was free breathing. We applied this technique on four patients who underwent tumor imaging with 18F-FDG in PET/CT, whose PET data showed high uptake of 18F-FDG in the heart and whose CT and PET data had misregistration. All four patients did not have known myocardiac infarction or ischemia. The patients were injected with 555-740 MBq of 18F-FDG and scanned 1 h after injection. The helical CT (HCT) data were acquired in 16 s for the coverage of 100 cm. The PET acquisition was 3 min per bed of 15 cm. The duration of cine CT acquisition per 2 cm was 5.9 s. We used a fast gantry rotation cycle time of 0.5 s to minimize motion induced reconstruction artifacts in the cine CT images, which were averaged to become the ACT images for AC of the PET data. The radiation dose was about 5 mGy for 5.9 s cine duration. The selection of 5.9 s was based on our analysis of the respiratory signals of 600 patients; 87% of the patients had average breath cycles of less than 6 s and 90% had standard deviations of less than 1 s in the period of breath cycle. In all four patient studies, registrations between the CT and the PET data were improved. An increase of average uptake in the anterior and the lateral walls up to 48% and a decrease of average uptake in the septal and the inferior walls up to 16% with ACT were observed. We also compared ACT and conventional slow scan CT (SSCT) of 4 s duration in one patient study and found ACT was better than SSCT in depicting average respiratory motion and the SSCT images showed motion-induced reconstruction artifacts. In conclusion, low-dose ACT improved registration of the CT and the PET data in the heart region in our study of four patients. ACT was superior than SSCT for depicting average respiration motion in a patient study.     

Rigid-body transformation of list-mode projection data for respiratory motion correction in cardiac PET

High-resolution cardiac PET imaging with emphasis on quantification would benefit from eliminating the problem of respiratory movement during data acquisition. Respiratory gating on the basis of list-mode data has been employed previously as one approach to reduce motion effects. However, it results in poor count statistics with degradation of image quality. This work reports on the implementation of a technique to correct for respiratory motion in the area of the heart at no extra cost for count statistics and with the potential to maintain ECG gating, based on rigid-body transformations on list-mode data event-by-event. A motion-corrected data set is obtained by assigning, after pre-correction for detector efficiency and photon attenuation, individual lines-of-response to new detector pairs with consideration of respiratory motion. Parameters of respiratory motion are obtained from a series of gated image sets by means of image registration. Respiration is recorded simultaneously with the list-mode data using an inductive respiration monitor with an elasticized belt at chest level. The accuracy of the technique was assessed with point-source data showing a good correlation between measured and true transformations. The technique was applied on phantom data with simulated respiratory motion, showing successful recovery of tracer distribution and contrast on the motion-corrected images, and on patient data with C15O and 18FDG. Quantitative assessment of preliminary C15O patient data showed improvement in the recovery coefficient at the centre of the left ventricle.     

A convolution-subtraction scatter correction method for 3D PET

3D acquisition and reconstruction in positron emission tomography (PET) produce data with improved signal-to-noise ratios compared with conventional 2D slice-oriented methods. However, the sensitivity increase is accompanied by an increase in the number of scattered photons and random coincidences detected. This paper presents a scatter correction technique for 3D PET data where an estimate of the scattered photon distribution is subtracted from the data before reconstruction. The scatter distribution is estimated by iteratively convolving the photopeak projections with a mono-exponential kernel. The method accounts for the 3D acquisition geometry and nature of scatter by performing the scatter estimation on 2D projections. The assumptions of the method have been investigated by measuring the variation in the scatter fraction and the scatter function at different positions in a cylinder. Both parameters were found to vary by up to 50% from the centre to the edge of a large water-filled cylinder. Despite this, in a uniform cylinder containing water with different concentrations of radioactivity, scatter was reduced from 25% in a non-radioactive region to less than 5% using the convolution-subtraction method. In addition, the relative concentration of a cylinder containing an increased concentration, which was underestimated by almost 50% without scatter correction, was within 5% of the true concentration after correction.     

Scatter correction for three-dimensional PET based on an analytic model dependent on source and attenuating object

Three-dimensional positron emission tomography admits a significant scatter fraction due to the large aperture of the detectors, and requires accurate scatter subtraction. A scatter-correction method, applicable to both emission and transmission imaging, calculates the projections of the single-scatter distribution, using an approximate image of the source and attenuating object. The scatter background is subtracted in projection space for transmission data and in image space for emission data, yielding corrected attenuation and emission images. The accuracy of this single-scatter distribution is validated for the authors' small imaging system by comparison with Monte Carlo simulations. The correction is demonstrated using transmission and emission data obtained from measurements on the authors' QPET imaging system using two acrylic phantoms. For the transmission data, generated with a flood source, errors of up to 24% in the linear attenuation coefficients resulted with no scatter subtraction, but the correction yielded an accurate value of mu =0.11+or-0.01 cm-1. For the emission data, the corrected images show that the scattered background has been removed to within the level of the background noise outside the source. The residual amplitude within a cold spot in one of the phantoms was reduced from 21% to 3% of the image amplitude.     

Accuracy of CT-based attenuation correction in PET/CT bone imaging

We evaluate the accuracy of scaling CT images for attenuation correction of PET data measured for bone. While the standard tri-linear approach has been well tested for soft tissues, the impact of CT-based attenuation correction on the accuracy of tracer uptake in bone has not been reported in detail. We measured the accuracy of attenuation coefficients of bovine femur segments and patient data using a tri-linear method applied to CT images obtained at different kVp settings. Attenuation values at 511 keV obtained with a (68)Ga/(68)Ge transmission scan were used as a reference standard. The impact of inaccurate attenuation images on PET standardized uptake values (SUVs) was then evaluated using simulated emission images and emission images from five patients with elevated levels of FDG uptake in bone at disease sites. The CT-based linear attenuation images of the bovine femur segments underestimated the true values by 2.9 ± 0.3% for cancellous bone regardless of kVp. For compact bone the underestimation ranged from 1.3% at 140 kVp to 14.1% at 80 kVp. In the patient scans at 140 kVp the underestimation was approximately 2% averaged over all bony regions. The sensitivity analysis indicated that errors in PET SUVs in bone are approximately proportional to errors in the estimated attenuation coefficients for the same regions. The variability in SUV bias also increased approximately linearly with the error in linear attenuation coefficients. These results suggest that bias in bone uptake SUVs of PET tracers ranges from 2.4% to 5.9% when using CT scans at 140 and 120 kVp for attenuation correction. Lower kVp scans have the potential for considerably more error in dense bone. This bias is present in any PET tracer with bone uptake but may be clinically insignificant for many imaging tasks. However, errors from CT-based attenuation correction methods should be carefully evaluated if quantitation of tracer uptake in bone is important.     

Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging

Metallic implants are known to generate bright and dark streaking artifacts in x-ray computed tomography (CT) images, which in turn propagate to corresponding functional positron emission tomography (PET) images during the CT-based attenuation correction procedure commonly used on hybrid clinical PET/CT scanners. Therefore, visual artifacts and overestimation and/or underestimation of the tracer uptake in regions adjacent to metallic implants are likely to occur and as such, inaccurate quantification of the tracer uptake and potential erroneous clinical interpretation of PET images is expected. Accurate quantification of PET data requires metal artifact reduction (MAR) of the CT images prior to the application of the CT-based attenuation correction procedure. In this review, the origins of metallic artifacts and their impact on clinical PET/CT imaging are discussed. Moreover, a brief overview of proposed MAR methods and their advantages and drawbacks is presented. Although most of the presented MAR methods are mainly developed for diagnostic CT imaging, their potential application in PET/CT imaging is highlighted. The challenges associated with comparative evaluation of these methods in a clinical environment in the absence of a gold standard are also discussed.     

Simulation studies on a pseudo-three-dimensional reconstruction algorithm for volume imaging in multi-ring PET

The imaging performance of a pseudo-three-dimensional (3D) reconstruction algorithm has been investigated. The algorithm is based on ID filtering followed by 3D backprojection. High- and low-frequency components of the image are reconstructed separately, and oblique projections are used only for reconstructing the high-frequency component. The cross talk between different slices due to oblique backprojection is eliminated by high-pass filtering. 'Variable filters', the cut-off frequencies of which are proportional to the tilt angles of projections, provide higher signal-to-noise ratio than 'fixed filters' with similar capability for cross-talk rejection. The maximum ring difference used in the reconstruction of each slice is extended as far as possible, while still satisfying the requirement that the total density of backprojection beams deposited in the slice is approximately uniform in the field of view. This allows the use of almost all available projection data to improve signal-to-noise ratio in peripheral slices. The root mean square noise of the reconstructed images evaluated with simulation studies is in good agreement with numerical calculations, and it is shown that the loss in signal-to-noise ratio caused by discarding the low-frequency component of oblique projections is negligibly small as long as suitable variable filters are used.     

Motion correction for three-dimensional chemical exchange saturation transfer imaging without direct water saturation artifacts

In chemical exchange saturation transfer (CEST) MRI, motion correction is compromised by the drastically changing image contrast at different frequency offsets, particularly at the direct water saturation. In this study, a simple extension for conventional image registration algorithms is proposed, enabling robust and accurate motion correction of CEST-MRI data. The proposed method uses weighted averaging of motion parameters from a conventional rigid image registration to identify and mitigate erroneously misaligned images. Functionality of the proposed method was verified by ground truth datasets generated from 10 three-dimensional in vivo measurements at 3 T with simulated realistic random rigid motion patterns and noise. Performance was assessed using two different criteria: the maximum image misalignment as a measure for the robustness against direct water saturation artifacts, and the spectral error as a measure of the overall accuracy. For both criteria, the proposed method achieved the best scores compared with two motion-correction algorithms specifically developed to handle the varying contrasts in CEST-MRI. Compared with a straightforward linear interpolation of the motion parameters at frequency offsets close to the direct water saturation, the proposed method offers better performance in the absence of artifacts. The proposed method for motion correction in CEST-MRI allows identification and mitigation of direct water saturation artifacts that occur with conventional image registration algorithms. The resulting improved robustness and accuracy enable reliable motion correction, which is particularly crucial for an automated and carefree evaluation of spectral CEST-MRI data, e.g., for large patient cohorts or in clinical routines.     

Automatic phase determination for retrospectively gated cardiac CT

The recent improvements in CT detector and gantry technology in combination with new heart rate adaptive cone beam reconstruction algorithms enable the visualization of the heart in three dimensions at high spatial resolution. However, the finite temporal resolution still impedes the artifact-free reconstruction of the heart at any arbitrary phase of the cardiac cycle. Cardiac phases must be found during which the heart is quasistationary to obtain outmost image quality. It is challenging to find these phases due to intercycle and patient-to-patient variability. Electrocardiogram (ECG) information does not always represent the heart motion with an adequate accuracy. In this publication, a simple and efficient image-based technique is introduced which is able to deliver stable cardiac phases in an automatic and patient-specific way. From low-resolution four-dimensional data sets, the most stable phases are derived by calculating the object similarity between subsequent phases in the cardiac cycle. Patient-specific information about the object motion can be determined and resolved spatially. This information is used to perform optimized high-resolution reconstructions at phases of little motion. Results based on a simulation study and three real patient data sets are presented. The projection data were generated using a 16-slice cone beam CT system in low-pitch helical mode with parallel ECG recording.     

基于支持向量回归的PET/CT图像衰减校正方法

目的在电子发射及计算机断层扫描系统(positron emission computed tomography/X-ray computed tomography,PET/CT)图像衰减校正的能量转换过程中,为了改进双线性转换法用线性关系来拟合非线性关系的不足,本文以支持向量回归为基础,提出了一种新的能量转换法即支持向量回归的PET/CT图像衰减校正方法来进行衰减校正,以寻找CT值和511 keV能量下线性衰减系数值之间的最佳转换关系。方法使用仿真软件GATE(Geant4 Application Tomographic Emission)模拟了11组不同材质的圆柱体体模。然后根据GATE仿真的不同材质圆柱体体模,求出其CT值和511 keV能量下线性衰减系数值并代入SVR模型中进行训练,建立CT值和511 keV能量下线性衰减系数值之间的SVR模型。最后与目前PET/CT衰减校正能量转换中常用的双线性能量转换法进行对比分析,并分别应用于GATE仿真的NCAT(NURBs Cardiac Torso)像素体模图像中,评估两种方法准确性的差异。结果支持向量回归的PET/CT图像衰减校正方法得到的511 keV能量下对应物质的线性衰减系数值的相对百分误差值较小(肺的相对百分误差值3.1%和肝脏的相对百分误差值1.08%),且经过支持向量回归法衰减校正的PET图像,其MSE评价值都是最小的(176.9230),其PSNR和AG的评价值都是最大的(31.8621和7.9083)。这说明经过支持向量回归法衰减校正的PET图像相比于双线性转换法衰减校正的PET图像,更接近于静态的图像。结论支持向量回归的PET/CT图像衰减校正方法在PET/CT图像的衰减校正应用中有更好的表现,可以更好地吻合CT值与511 keV能量下线性衰减系数之间的转换关系,从而提高了PET/CT图像的衰减校正效果,改善了PET/CT图像定量的准确性,便于医生做出更精确的临床诊断。