Compensation for head movement in 3D PET

Respiratory motion is a known image degradation factor in PET imaging. A lot of research has been done in the field of motion correction of PET data. With the recent development of full-body PET/MRI, the morphological data provided by MRI is a promising source of motion information. MRI-based motion correction of PET data is a topic of active research. These approaches, however, usually do not take into account the available information provided by PET data. In this work we show results of a phantom study using a joint motion estimation approach that incorporates motion information from both PET and MRI data.

The impact of a method for MR-based respiratory motion correction of PET data on lesion visibility and quantification in patients with oncologic findings in the lung was evaluated. Twenty patients with one or more lesions in the lung were included. Hybrid imaging was performed on an integrated PET/MR system using 18F-FDG as radiotracer. The standard thoracic imaging protocol was extended by a free-breathing self-gated acquisition of MR data for motion modelling. PET data was acquired simultaneously in list-mode for 5-10 mins. One experienced radiologist and one experienced nuclear medicine specialist evaluated and compared the post-processed data in consensus regarding lesion visibility (scores 1–4, 4 being best), image noise levels (scores 1–3, 3 being lowest noise), SUVmean and SUVmax. Motion-corrected (MoCo) images were additionally compared with gated images. Non-motion-corrected free-breathing data served as standard of reference in this study. Motion correction generally improved lesion visibility (3.19 ± 0.63) and noise ratings (2.95 ± 0.22) compared to uncorrected (2.81 ± 0.66 and 2.95 ± 0.22, respectively) or gated PET data (2.47 ± 0.93 and 1.30 ± 0.47, respectively). Furthermore, SUVs (mean and max) were compared for all methods to estimate their respective impact on the quantification. Deviations of SUVmax were smallest between the uncorrected and the MoCo lesion data (average increase of 9.1% of MoCo SUVs), while SUVmean agreed best for gated and MoCo reconstructions (MoCo SUVs increased by 1.2%). The studied method for MR-based respiratory motion correction of PET data combines increased lesion sharpness and improved lesion activity quantification with high signal-to-noise ratio in a clinical setting. In particular, the detection of small lesions in moving organs such as the lung and liver may thus be facilitated. These advantages justify the extension of the PET/MR imaging protocol by 5–10 minutes for motion correction.

Recently published methods for motion correction in neurological PET include the multiple acquisition frame (MAF) and LOR rebinning methods. The aim of the present work was to compare the accuracy of reconstructions obtained with these methods when multiple, arbitrary movements were applied to a Hoffman brain phantom during 3D list mode acquisition. A reflective target attached to the phantom enabled a Polaris optical motion tracking system to monitor the phantom position and orientation in the scanner coordinate frame. The motion information was used in the motion correction algorithms. The MAF method was applied to the list-mode data after sorting them into a series of dynamic frames, while the LOR rebinning method was applied directly to the list-mode data. A proportion of the list mode events had to be discarded during rebinning because the application of the corrective spatial transformation removed them from the 3D projection space. A correction for these 'lost' events was implemented as a global post-reconstruction scale factor, based on the overall fraction of lost events. Reconstructions from both motion correction methods were compared with a motion-free reference scan of the same phantom. Motion correction produced a marked improvement in image clarity and reduced errors with respect to the reference scan. LOR rebinning with global loss correction was found to be more accurate than the MAF method

Respiratory motion can introduce image artefacts not only in 3D PET but also in 4D PET due to incorrect attenuation correction. In this work the influence of different attenuation correction strategies on 3D and 4D PET has been investigated. An extensive phantom study was carried out, using a normal 3D CT (pitch 1.5), a slow 3D CT (pitch 0.5), an ultraslow 3D CT (pitch 0.15), an average CT and a maximum intensity projection calculated from a 4D CT (pitch 0.1) for attenuation correction of both a 3D and 4D PET of a respiratory motion phantom. Additionally, the 4D PET was corrected phase-wise with a 4D CT (phase-correlated attenuation correction). The reconstructed PET images were analyzed concerning the reconstructed volume, motion amplitude (for 4D PET), activity concentration and activity distribution. Moreover a patient study was carried out investigating the influence of the different attenuation correction strategies for 4D PET to patient data. Therefore 4D PET data from six patients with non-small cell lung cancer (NSCLC) was alternatively attenuation corrected with a normal 3D CT, an average CT and with phase-correlated attenuation correction. The tumor volume was analyzed and the motion amplitude of the tumor was obtained from the 4D PET data sets. For the phantom data the attenuation correction with the slow CT results in the best agreement between expected and measured values of the examined quantities in 3D PET, whereas in 4D PET this was the case for the phase-correlated attenuation correction. In the patient study only small differences between the 4D PET attenuation correction methods were found. This can be explained by the relative small tumor motion in the patient population investigated (peak to peak amplitude below 5 mm except for one patient).

Recently list mode (event-by-event) data acquisition with positron emission tomography (PET) has been widely noticed because the list mode acquisition is superior to the conventional frame mode data acquisition in terms of (1) higher efficiency of data storage, (2) higher temporal resolution and (3) higher flexibility of data manipulation. The aim of this study is to investigate the performance of list mode data acquisition with ECAT HR and HR + PET scanners(CTI PET Systems). The cylindrical phantom (16 cm diameter and 16 cm long) filled with /sup 11/C solution for HR and /sup 15/O solution for HR+ was scanned several times varying the radioactivity with list mode and frame mode acquisitions. The scans with the septa (2D mode) and without the septa (3D mode) were also carried out in order to evaluate the effect of interplane septa on quality of the list mode data. The acquired list mode data were sorted to sinogram and reconstructed using filtered back-projection algorithm. The count rate performance of the list mode data was comparable to the frame mode data. However list mode acquisition could not be performed if radioactivity in the field-of-view was high (more than 3 mCi for 3D mode) due to lack of transfer speed for sending data from memory to hard disk. 10 replicated data set from one list mode data were generated to estimate the noise in the reconstructed image. The reconstructed images with 3D mode has more than 60% better signal-to-noise ratio compared to the image with 2D mode. Generated file size of list mode was also evaluated. In the case of HR+ with 3D list mode, list mode data with 2.31 MBytes/s for 1mCi injection were generated. Out results suggest that careful attention must be paid for protocol of the list mode data acquisition in order to obtain the highest performance of the PET scanner.

Three-dimensional (3D) data acquisition is now standard on PET/computed tomography scanners. The aim of this study was to evaluate the repeatability of myocardial blood flow (MBF) estimation with rubidium-82 (Rb) 3D PET and to validate regional MBF measurements by comparison with two-dimensional (2D) PET. Fifteen healthy individuals (31.6 ± 11.4 years old) were enrolled for the evaluation of the short-term repeatability of rest 3D MBF quantification. Another 19 healthy individuals (35.3 ± 12.6 years old) underwent rest and pharmacological stress PET using 2D and 3D data acquisition within a 1-month interval. The injected dose was 1500 MBq for 2D and 555 MBq for 3D PET acquisition. MBF at rest showed good repeatability [whole left ventricular MBF; 0.54 ± 0.13 vs. 0.52 ± 0.13 mL/min/g, P = 0.98]. Rest MBF, stress MBF, and myocardial flow reserve (MFR) were not significantly different between 3D and 2D data acquisition. 3D MBF correlated well with 2D MBF over a wide flow range for both whole left ventricular (r = 0.97, P < 0.0001) and regional values (r = 0.61, P < 0.0001). MBF measured with 3D PET showed very good test-retest repeatability. Whole left ventricular and regional MBF measurements obtained using lower Rb-dose 3D PET were highly correlated over a wide range with those from 2D PET. Therefore, MBF with 3D PET can be applied using a lower Rb dosage in clinical settings with reduced radiation exposure.

Data-driven respiratory gating techniques in cardiac PET extract respiratory motion signal from the PET data to guide respiratory gating and motion estimation. However, the influence of the quality of the list-mode data including the uptake ratio between the myocardium and background and the detected count level on its performance has never been studied thoroughly. In this project, list-mode PET data derived from realistic Monte Carlo simulation of different uptake ratios and count levels was employed to quantitatively evaluate the respiratory motion signal extraction and estimation techniques. Simulated projection data were generated from the 4D XCAT phantom with known respiratory motion. The list-mode data were rebinned into projection data at 200 msec intervals and the centers-of-mass of a region-of-interest over the heart were calculated. Contributions from the background were subtracted in the centroid calculation. The peak in the Fourier transform of the time sequence of the centroid locations, or the frequency spectrum, was identified as the respiratory motion signal and its SNR was measured. The high frequency components of the frequency spectrum were removed for noise smoothing before extracting the respiratory motion signal for use in respiratory gating estimation. The results show that with background correction, the amplitude of the estimated respiratory motion signal is increased and is closer to the truth. Both lower myocardium to background uptake ratio and lower count level reduce the SNR of the respiratory motion signal. When they become too low, the extraction of the respiratory motion signal becomes difficult or fails completely.

Purpose: Radiation treatment planning with PET/CT has been shown to be beneficial and leads to smaller variations in target delineation than using CT only. This study investigates the 3D maximum intensity projection (MIP) PET images derived from respiratory‐gated 4D PET as a complement to the MIP CT derived from a 4D CT dataset and their use in treatment planning as a means to account for respiratory motion in free‐breathing radiotherapy for lung and abdomen tumors. Methods and materials: 21 PET/CT patient datasets with 31 lesions were acquired. The patient respiratory motion was monitored by the Real‐time Position Management system. PET listmode data were phase‐binned into 5 frames and reconstructed. 3D MIP PET images were derived from the 5‐bin 4D PET datasets. Tumor volumes were determined by an automatic segmentation method and compared for the MIP PET and static PET images. The tumor motion amplitude was determined by measuring the centroid in phase‐gated images. The impact of tumor size and motion amplitude were investigated. In addition, PET data were binned into 10 frames to study the noise change in MIP PET. The comparison between the MIP PET and MIP CT is under study. Results: Compared to static PET, the tumor volumes in the MIP PET increased by 10% 14%, with a maximum increase of 44%. The volume increases are larger for the smaller tumors sizes and larger motion amplitudes. The image noise of the MIP PET is higher than in static PET and increases with number of phase bins. Conclusion: The MIP PET has a potential to complement MIP CT to inform the radiation treatment planning for motion‐encompassing radiotherapy by accounting for respiratory motion.

Motion of the head during brain positron emission tomography (PET) acquisitions has been identified as a source of artifact in the reconstructed image. A number of techniques have been proposed to correct for this motion artifact, but they are unable to correct for a motion during an acquisition. The aim of this study was to develop a sinogram-based motion correction (SBMC) technique to correct directly the head motion during a PET scan using a motion tracking system and list-mode data acquisition. This method uses a rebinning procedure whereby the lines of response (LOR) are geometrically transformed according to the current values of six-dimensional motion data. A Michelogram was recomposed using the rebinned LOR, and the motion-corrected sinogram was generated. In the motion corrected image, the blurring artifact due to the motion was reduced by the SBMC technique. This technique was applied to actual PET data acquired in the list-mode, and demonstrated the potential for real-time motion correction of head movements during a PET acquisition.

PurposePatient motion during PET acquisition may affect measured time-activity curves, thereby reducing accuracy of tracer kinetic analyses. The aim of the present study was to evaluate different off-line frame-by-frame methods to correct patient motion, which is of particular interest when no optical motion tracking system is available or when older data sets have to be reanalysed.MethodsFour different motion correction methods were evaluated. In the first method attenuation-corrected frames were realigned with the summed image of the first 3 min. The second method was identical, except that non-attenuation-corrected images were used. In the third and fourth methods non-attenuation-corrected images were realigned with standard and cupped transmission images, respectively. Two simulation studies were performed, based on [11C]flumazenil and (R)-[11C]PK11195 data sets, respectively. For both simulation studies different types (rotational, translational) and degrees of motion were added. Simulated PET scans were corrected for motion using all correction methods. The optimal method derived from these simulation studies was used to evaluate two (one with and one without visible movement) clinical data sets of [11C]flumazenil, (R)-[11C]PK11195 and [11C]PIB. For these clinical data sets, the volume of distribution (VT) was derived using Logan analysis and values were compared before and after motion correction.ResultsFor both [11C]flumazenil and (R)-[11C]PK11195 simulation studies, optimal results were obtained when realignment was based on non-attenuation-corrected images. For the clinical data sets motion disappeared visually after motion correction. Regional differences of up to 433% in VT before and after motion correction were found for scans with visible movement. On the other hand, when no visual motion was present in the original data set, overall differences in VT before and after motion correction were <1.5 ± 1.3%.ConclusionFrame-by-frame motion correction using non-attenuation-corrected images improves the accuracy of tracer kinetic analysis compared to non-motion-corrected data.Electronic supplementary materialThe online version of this article (doi:10.1007/s00259-009-1193-y) contains supplementary material, which is available to authorised users.

Respiratory motion in emission tomography leads to reduced image quality. Proposed correction methodology has been concentrating on the use of respiratory synchronised acquisitions leading to gated frames. Such frames however are of low signal to noise ratio as a result of containing reduced statistics. Therefore a method accounting for respiratory motion effects without affecting the statistical quality of the reconstructed images is necessary. 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. 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 a Monte Carlo simulation. Transformation parameters accounting for respiratory motion were estimated according to an elastic registration of the NCAT dynamic CT images and were subsequently applied during the image reconstruction of the original emission list mode data. The One-pass list mode EM (OPL-EM) algorithm was modified to integrate the elastic transformation in the sensitivity matrix. Three different implementations have been investigated (no interpolation, trilinear interpolation, b-spline functions incorporation). The corrected images were compared with uncorrected respiratory motion average images. Results demonstrate that the use of elastic transformations in the reconstruction system matrix lead to uniform improvement across the lung field for different lesion sizes. The use of a trilinear interpolation or the incorporation of the b-spline functions lead to times of execution equivalent to standard image reconstruction. However, trilinear interpolation leads to artefacts in areas such as the diaphragm where the largest elastic deformations are occurring.

Inverse-geometry CT (IGCT) employs a large area x-ray source array opposite a small area detector array. The system is expected to provide sub-second volumetric imaging with isotropic resolution and no cone-beam effects. Due to the large amount of data, it is desirable to have an exact 3D reconstruction algorithm that is fast. Currently known IGCT algorithms are either slow, due to 3D backprojection, and/or require a reprojection step, or are inexact. et al. developed an exact Fourier rebinning algorithm (FORE-J) for 3D PET. This algorithm first rebins the 3D PET data into in-plane sinograms and then reconstructs the series of axial slices using any 2D method. FORE-J is fast, exact, and efficiently uses all of the acquired PET data. We modified this algorithm to adapt it to the IGCT geometry. Experiments were performed using a numerical Defrise phantom consisting of high-intensity discs spaced in z to assess the accuracy of the modified algorithm as well as highlight any cone-beam effects. A noise simulation was performed to analyze the noise properties of FORE-J and the modified algorithm. The modified algorithm is very fast and slightly more accurate than the original algorithm with a very small noise penalty in the central axial slices.

This paper presents the results of combining high sensitivity 3D PET whole-body acquisition followed by fast 2D iterative reconstruction methods based on accurate statistical models. This combination is made possible by Fourier rebinning (FORE), which accurately converts a 3D data set to a set of 2D sinograms. The combination of volume imaging with statistical reconstruction allows improvement of noise-bias trade-offs when image quality is dominated by measurement statistics. The rebinning of the acquired data into a 2D data set reduces the computation time of the reconstruction. For both penalized weighted least squares (PWLS) and ordered-subset EM (OSEM) reconstruction methods, the usefulness of a realistic model of the expected measurement statistics is shown when the data are pre-corrected for attenuation and random and scattered coincidences, as required for the FORE rebinning algorithm. The results presented are based on 3D simulations of whole body scans that include the major statistical effects of PET acquisition and data correction procedures. As the PWLS method requires knowledge of the variance of the projection data, a simple model for the effect of FORE rebinning on data variance is developed.

Positron volume images will be produced by the new large-area positron camera PETRRA directly from list mode data acquisition. The present method of image reconstruction is based on the backprojection then filter algorithm and no projection data are produced. A 2D method of correcting images in back-projection space has been developed using measurements made with the existing MUP-PET camera. A relationship between the attenuation and scatter fractions has been derived, for a limited axial field-of-view, for a range of cylindrical and elliptical phantoms. Image-space scatter distributions produced using this relationship are converted to backprojection-space by convolution with an experimentally-derived scatter response function (SRF). These scatter distributions are subtracted from the acquired back-projected image using the integrated scatter fraction for normalization. The resulting data are corrected using a multiplicative backprojection space attenuation matrix and deconvolved with an in-air response function. The method has been applied to a Monte Carlo simulated phantom, an experimental phantom and a patient study. The predicted scatter distribution agrees with the simulation to /spl sim//spl plusmn/10% and the correction method improves image contrast for all three data sets studied. However the use of a spatially invariant SRF leads to over-subtraction of scatter in the center of the phantom. In order for the method to be extended to PETRRA using the whole axial extent (40 cm) of the camera, simulations have been used to generate scatter-attenuation relationships for several phantoms over the whole axial FoV. The scatter response function is fitted to a Gaussian with the center displaced from the point of emission. Improved linearity and contrast were obtained with simulated phantoms. The method could be applied to any large-area positron camera acquiring data in list mode.

Reduction of the injected radionuclide dose in myocardial perfusion imaging (MPI) has become a major effort among clinicians and researchers alike. The aim of this study was to retrospectively determine the relationship between injected radioactivity and total projection counts in the heart region of clinically acquired Tc-99m sestamibi patients in an effort to formulate a strategy to better calculate individual and personalized doses prior to injection using easily measured metrics From a pool of 601 patients (304 female) 101 patients that undergone exercise stress testing and were read as having a normal perfusion distribution or small perfusion defects were included for the initial investigation. For all patients, injected activity at the time of the stress myocardial perfusion imaging (MPI) were determined. All patient BMI's were calculated and circumference measurements of the chest, abdomen and hips obtained. For all patients, list mode acquisitions were available and attenuation maps were derived from cone-beam CT acquisitions (BrightView SPECT/CT scintillation camera, Philips, Cleveland, OH). Total projection counts in the heart region were determined using a fixed region-of-interest (ROI) and counts per injected activity plotted against either BMI or chest circumference. Correlations were calculated. Using this information, 25 patients' list mode data were resampled randomly to create acquisition with only a fraction of the counts in the original study such that the heart region counts in all of the patients were equal to ~750K. Correlations with BMI were again determined using the reduced radioactive dose. The proposed method reduced the radioactive dose by between 29% and 66% while maintaining image fidelity. Therefore, we established an initial strategy to calculate an individual and personalized injected dose for every patient prior to showing up at the MPI clinic using the correlation between BMI and count level in the heart region.