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.     

List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations

Respiratory motion in emission tomography leads to reduced image quality. Developed correction methodology has been concentrating on the use of respiratory synchronized acquisitions leading to gated frames. Such frames, however, are of low signal-to-noise ratio as a result of containing reduced statistics. In this work, we describe the implementation of an elastic transformation within a list-mode-based reconstruction for the correction of respiratory motion over the thorax, allowing the use of all data available throughout a respiratory motion average acquisition. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List-mode-data-based PET-simulated frames were subsequently produced by combining the NCAT datasets with Monte Carlo simulation. A non-rigid registration algorithm based on B-spline basis functions was employed to derive transformation parameters accounting for the respiratory motion using the NCAT dynamic CT images. The displacement matrices derived were subsequently applied during the image reconstruction of the original emission list mode data. Two different implementations for the incorporation of the elastic transformations within the one-pass list mode EM (OPL-EM) algorithm were developed and evaluated. The corrected images were compared with those produced using an affine transformation of list mode data prior to reconstruction, as well as with uncorrected respiratory motion average images. Results demonstrate that although both correction techniques considered lead to significant improvements in accounting for respiratory motion artefacts in the lung fields, the elastic-transformation-based correction leads to a more uniform improvement across the lungs for different lesion sizes and locations.     

The design and implementation of a motion correction scheme for neurological PET

A method is described to monitor the motion of the head during neurological positron emission tomography (PET) acquisitions and to correct the data post acquisition for the recorded motion prior to image reconstruction. The technique uses an optical tracking system, Polaris, to accurately monitor the position of the head during the PET acquisition. The PET data are acquired in list mode where the events are written directly to disk during acquisition. The motion tracking information is aligned to the PET data using a sequence of pseudo-random numbers, which are inserted into the time tags in the list mode event stream through the gating input interface on the tomograph. The position of the head is monitored during the transmission acquisition, and it is assumed that there is minimal head motion during this measurement. Each event, prompt and delayed, in the list mode event stream is corrected for motion and transformed into the transmission space. For a given line of response, normalization, including corrections for detector efficiency, geometry and crystal interference and dead time are applied prior to motion correction and rebinning in the sinogram. A series of phantom experiments were performed to confirm the accuracy of the method: (a) a point source located in three discrete axial positions in the tomograph field of view, 0 mm, 10 mm and 20 mm from a reference point, (b) a multi-line source phantom rotated in both discrete and gradual rotations through +/- 5 degrees and +/- 15 degrees, including a vertical and horizontal movement in the plane. For both phantom experiments images were reconstructed for both the fixed and motion corrected data. Measurements for resolution, full width at half maximum (FWHM) and full width at tenth maximum (FWTM), were calculated from these images and a comparison made between the fixedand motion corrected datasets. From the point source measurements, the FWHM at each axial position was 7.1 mm in the horizontal direction, and increasing from 4.7 mm at the 0 mm position, to 4.8 mm, 20 mm offset, in the vertical direction. The results from the multi-line source phantom with +/- 5 degrees rotations showed a maximum degradation in FWHM, when compared with the stationary phantom, of 0.6 mm, in the horizontal direction, and 0.3 mm in the vertical direction. The corresponding values for the larger rotation, +/- 15 degrees, were 0.7 mm and 1.1 mm, respectively. The performance of the method was confirmed with a Hoffman brain phantom moved continuously, and a clinical acquisition using [11C]raclopride (normal volunteer). A visual comparison of both the motion and non-motion corrected images of the Hoffman brain phantom clearly demonstrated the efficacy of the method. A sample time-activity curve extracted from the clinical study showed irregularities prior to motion correction, which were removed after correction. A method has been developed to accurately monitor the motion of the head during a neurological PET acquisition, and correct for this motion prior to image reconstruction. The method has been demonstrated to be accurate and does not add significantly to either the acquisition or the subsequent data processing.     

Event-based motion correction for PET transmission measurements with a rotating point source

Accurate attenuation correction is important for quantitative positron emission tomography (PET) studies. When performing transmission measurements using an external rotating radioactive source, object motion during the transmission scan can distort the attenuation correction factors computed as the ratio of the blank to transmission counts, and cause errors and artefacts in reconstructed PET images. In this paper we report a compensation method for rigid body motion during PET transmission measurements, in which list mode transmission data are motion corrected event-by-event, based on known motion, to ensure that all events which traverse the same path through the object are recorded on a common line of response (LOR). As a result, the motion-corrected transmission LOR may record a combination of events originally detected on different LORs. To ensure that the corresponding blank LOR records events from the same combination of contributing LORs, the list mode blank data are spatially transformed event-by-event based on the same motion information. The number of counts recorded on the resulting blank LOR is then equivalent to the number of counts that would have been recorded on the corresponding motion-corrected transmission LOR in the absence of any attenuating object. The proposed method has been verified in phantom studies with both stepwise movements and continuous motion. We found that attenuation maps derived from motion-corrected transmission and blank data agree well with those of the stationary phantom and are significantly better than uncorrected attenuation data.     

Design of respiration averaged CT for attenuation correction of the PET data from PET/CT

Our previous patient studies have shown that the use of respiration averaged computed tomography (ACT) for attenuation correction of the positron emission tomography (PET) data from PET/CT reduces the potential misalignment in the thorax region by matching the temporal resolution of the CT to that of the PET. In the present work, we investigated other approaches of acquiring ACT in order to reduce the CT dose and to improve the ease of clinical implementation. Four-dimensional CT (4DCT) data sets for ten patients (17 lung/esophageal tumors) were acquired in the thoracic region immediately after the routine PET/CT scan. For each patient, multiple sets of ACTs were generated based on both phase image averaging (phase approach) and fixed cine duration image averaging (cine approach). In the phase approach, the ACTs were calculated from CT images corresponding to the significant phases of the respiratory cycle: ACT(050phs) from end-inspiration (0%) and end-expiration (50%), ACT(2070phs) from mid-inspiration (20%) and mid-expiration (70%), ACT(4phs) from 0%, 20%, 50% and 70%, and ACT(10phs) from all ten phases, which was the original approach. In the cine approach, which does not require 4DCT, the ACTs were calculated based on the cine images from cine durations of 1 to 6 s at 1 s increments. PET emission data for each patient were attenuation corrected with each of the above mentioned ACTs and the tumor maximum standard uptake value (SUVmax), average SUV (SUVavg), and tumor volume measurements were compared. Percent differences were calculated between PET data corrected with various ACTs and that corrected with ACT(10phs). In the phase approach, the ACT(10phs) can be approximated by the ACT(4phs) to within a mean percent difference of 2% in SUV and tumor volume measurements. In cine approach, ACT(10phs) can be approximated to within a mean percent difference of 3% by ACTs computed from cine durations > or =3 s. Acquiring CT images only at the four significant phases for the ACT can reduce radiation dose to 1/3 of the current 4DCT dose; however, the implementation of this approach requires additional hardware that is not standard equipment on PET/CT scanners. In the cine approach, we recommend a duration of 6 +/- 1 s in order to include variations of respiratory patterns in a larger population. This approach can be easily implemented because cine acquisition mode is available on all GE PET/CT scanners. The CT dose in the cine approach can be reduced to approximately 5 mGy by using the lowest mA setting (10 mA), while still maintaining good quality CT data for PET attenuation correction. In our scanning protocol, the ACT is only acquired if respiration-induced misregistration is observed (determined before the PET scan is completed), and therefore patients do not receive unnecessary CT radiation dose.     

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.     

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.     

Spin saturation artifact correction using slice-to-volume registration motion estimates for fMRI time series

Evaluation of functional magnetic resonance imaging (fMRI) as a reliable clinical imaging tool requires accurate assessment and correction of head motion artifacts. As the correction of bulk head motion is vital, the loss of signal strength from the confounding effect of head motion on spin magnetization may be an additional factor in activation analysis error. This study focuses on the evaluation and correction of the spin saturation artifact that occurs when parts of adjacent slices are selected due to changing head positions in single-shot multislice acquisitions. As a consequence of head movement, the acquired slices constituting a fMRI volume are no longer parallel to each other and the spin magnetization in fMRI voxels becomes dependent on head motion history. Motion corrections applying the same rigid motion estimates to all the slices in a volume may not be a reasonable approximation in cases where the magnitude of head motion exceeds a subvoxel range. For realistic ranges of motion in fMRI, an accurate estimate of rigid motion parameters for each echo planar imaging (EPI) slice is essential to correctly register voxel intensities. Previously we have implemented the map-slice-to-volume (MSV) motion correction method that maps each slice in a time series onto a reference anatomical volume, which proved to be effective in improving activation detection. To correctly evaluate the motion dependence of spin magnetization, each voxel is tracked with movement history that is available from MSV motion estimates. Relatively low in resolution, EPI voxels are composed of varying mixtures of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) and variations in the tissue composition give rise to voxel intensities that are functions of tissue T1 properties. We have developed a weighted-average spin saturation (WASS) correction method that can handle full rigid motion and account for the melange of different brain tissue isochromats at each EPI voxel location. We evaluated the effect of spin saturation artifacts and the performance of the WASS correction using simulated fMRI time series synthesized with known true activation, motion, and the associated spin saturation artifact. Two different ranges of head rotations, [-5,5] and [-2,2] deg, were introduced and the effect of the spin saturation artifact was quantified to show 18% and 13% reduction in activation detection rate, respectively. Following the MSV motion and WASS correction, results indicate that WASS correction can improve activation detection by 17% relative to MSV only correction.     

Attenuation correction for small animal SPECT imaging using x-ray CT data

Photon attenuation in small animal nuclear medicine scans can be significant when using isotopes that emit lower energy photons such as iodine-125. We have developed a method to use microCT data to perform attenuation corrected small animal single-photon emission computed tomography (SPECT). A microCT calibration phantom was first imaged, and the resulting calibration curve was used to convert microCT image values to linear attenuation coefficient values that were then used in an iterative SPECT reconstruction algorithm. This method was applied to reconstruct a SPECT image of a uniform phantom filled with 125I-NaI. Without attenuation correction, the image suffered a 30% decrease in intensity in the center of the image, which was removed with the addition of attenuation correction. This reduced the relative standard deviation in the region of interest from 10% to 6%.     

Region of interest motion compensation for PET image reconstruction

A motion-incorporated reconstruction (MIR) method for gated PET imaging has recently been developed by several authors to correct for respiratory motion artifacts in PET imaging. This method however relies on a motion map derived from images (4D PET or 4D CT) of the entire field of view (FOV). In this study we present a region of interest (ROI)-based extension to this method, whereby only the motion map of a user-defined ROI is required and motion incorporation during image reconstruction is solely performed within the ROI. A phantom study and an NCAT computer simulation study were performed to test the feasibility of this method. The phantom study showed that the ROI-based MIR produced results that are within 1.26% of those obtained by the full image-based MIR approach when using the same accurate motion information. The NCAT phantom study on the other hand, further verified that motion of features of interest in an image can be estimated more efficiently and potentially more accurately using the ROI-based approach. A reduction of motion estimation time from 450 s to 30 and 73 s was achieved for two different ROIs respectively. In addition, the ROI-based approach showed a reduction in registration error of 43% for one ROI, which effectively reduced quantification bias by 44% and 32% using mean and maximum voxel values, respectively.     

Interest of TOF PET for clinical applications.

The interest of PET is now well established in medical research. Recently PET has proved to be also useful in the clinical domain e.g. for the diagnosis of epilepsy, myocardial disease etc... Its use has been so far limited by the cost of the radionuclide production and the cost of the PET itself. However, inexpensive, compact cyclotrons and centralized distribution of F18 are beginning to facilitate the availability of radionuclides. Thanks to its performances in terms of high random rate, sensitivity gain, random reduction, TOF is becoming practical for clinical use, especially with new types of architecture allowing the reduction of the cost of the detection head, so far the main obstacle to the use of TOF PET in clinical domain.     

Joint model of motion and anatomy for PET image reconstruction

Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem.