Inki Hong

Motion Correction Strategies for Integrated PET/MR

Integrated whole-body PET/MR facilitates the implementation of a broad variety of respiratory motion correction strategies, taking advantage of the strengths of both modalities. The goal of this study was the quantitative evaluation with clinical data of different MR- and PET-data–based motion correction strategies for integrated PET/MR. Methods: The PET and MR data of 20 patients were simultaneously acquired for 10 min on an integrated PET/MR system after administration of 18F-FDG or 68Ga-DOTANOC. Respiratory traces recorded with a bellows were compared against MR self-gating signals and signals extracted from PET raw data with the sensitivity method, by applying principal component analysis (PCA) or Laplacian eigenmaps and by using a novel variation combining the former and either of the latter two. Gated sinograms and MR images were generated accordingly, followed by image registration to derive MR motion models. Corrected PET images were reconstructed by incorporating this information into the reconstruction. An optical flow algorithm was applied for PET-based motion correction. Gating and motion correction were evaluated by quantitative analysis of apparent tracer uptake, lesion volume, displacement, contrast, and signal-to-noise ratio. Results: The correlation between bellows- and MR-based signals was 0.63 ± 0.19, and that between MR and the sensitivity method was 0.52 ± 0.26. Depending on the PET raw-data compression, the average correlation between MR and PCA ranged from 0.25 ± 0.30 to 0.58 ± 0.33, and the range was 0.25 ± 0.30 to 0.42 ± 0.34 if Laplacian eigenmaps were applied. By combining the sensitivity method and PCA or Laplacian eigenmaps, the maximum average correlation to MR could be increased to 0.74 ± 0.21 and 0.70 ± 0.19, respectively. The selection of the best PET-based signal for each patient yielded an average correlation of 0.80 ± 0.13 with MR. Using the best PET-based respiratory signal for gating, mean tracer uptake increased by 17 ± 19% for gating, 13 ± 10% for MR-based motion correction, and 18 ± 15% for PET-based motion correction, compared with the static images. Lesion volumes were 76 ± 31%, 83 ± 18%, and 74 ± 22% of the sizes in the static images for gating, MR-based motion correction, and PET-based motion correction, respectively. Conclusion: Respiratory traces extracted from MR and PET data are comparable to those based on external sensors. The proposed PET-driven gating method improved respiratory signals and overall stability. Consistent results from MR- and PET-based correction methods enable more flexible PET/MR scan protocols while achieving higher PET image quality.

LSO background radiation as a transmission source using time of flight.

LSO scintillators (Lu2Sio5:Ce) have a background radiation which originates from the isotope Lu-176 that is present in natural occurring lutetium. The decay that occurs in this isotope is a beta decay that is in coincidence with cascade gamma emissions with energies of 307, 202 and 88 keV. The coincidental nature of the beta decay with the gamma emissions allow for separation of the emission data originating from a positron annihilation event from transmission type data from the Lu-176 beta decay. By using the time of flight information, and information of the chord length between two LSO pixels in coincidence as a result of a beta emission and emitted gamma, a second time window can be set to observe transmission events simultaneously to emission events. Using the time when the PET scanner is not actively acquiring positron emission data, a continuous blank can be acquired and used to reconstruct a transmission image. With this blank and the measured transmission data, a transmission image can be reconstructed. This reconstructed transmission image can be used to perform emission data corrections such as attenuation correction and scatter corrections. It is observed that the flux of the background activity is high enough to create good transmission images with an acquisition time of 10 minutes.

LSO background radiation as a transmission source using time of flight information

LSO scintillators (Lu 2 Sio 5 :Ce) have a background radiation which originates from the isotope Lu-176 that is present in natural occurring lutetium. The decay that occurs in this isotope is a beta decay that is in coincidence with cascade gamma emissions with energies of 307, 202 and 88 keV. The coincidental nature of the beta decay with the gamma emissions allow for separation of the emission data originating from a positron annihilation event from transmission type data from the Lu-176 beta decay. By using the time of flight information, and information of the chord length between two LSO pixels in coincidence as a result of a beta emission and emitted gamma, a second time window can be set to observe transmission events simultaneously to emission events. Using the time when the PET scanner is not actively acquiring positron emission data, a continuous blank can be acquired and used to reconstruct a transmission image. With this blank and the measured transmission data, a transmission image can be reconstructed. This reconstructed transmission image can be used to perform emission data corrections such as attenuation correction and scatter corrections. It is observed that the flux of the background activity is high enough to create good transmission images with an acquisition time of 10 minutes.

The strategy of elastic Motion corrections

The Motion in PET studies degrades image quality and introduces bias and partial volume artifacts, which are critical considerations for high resolution scanners. There are two kinds of motion, such as rigid (e.g. brain) and nonrigid (e.g. respiratory and cardiac). Elastic motion correction is needed for nonrigid-motion artifacts. There are three basic steps in this approach, acquisition of a gating signal, extraction of elastic motion, and reconstruction. First, the gating signal is acquired by hardware, such as EKG, Belt, RPM, and MR, or from the analysis PET list-mode data. This is the most important step because, if the data are not properly gated, it is not possible to extract accurate motion vectors. Second, motion information for each gated signal can be extracted from CT for PET/CT or MRI for MR/PET. The motion information can also be extracted from the PET data themselves, and optical flow methods have been shown to be very robust in this approach. Third, image reconstruction with motion correction is commonly performed through summing gated images in a common reference frame. However, the combination of processed data with poor statistics generally results in high image noise and bias in the final image. A better approach is to incorporate motion information into the reconstruction process itself. Motion-correction reconstruction has been shown to produce less noise and bias in the image domain than conventional summing methods. The ideal method for motion correction in emission data should produce quantitatively accurate images which retain noise properties of conventional images, all while introducing no additional subject dose or inconvenience.

Complementary reconstruction: Improving image quality in dynamic PET studies

In dynamic PET studies [1], kinetic model parameters are estimated by recovering temporal tracer uptakes in the targeted tissues inside the subject. There are multiple ways to estimate the model parameters either directly from the PET sonogram (or list mode) data, or indirectly from the reconstructed images. One widely used method is the individual frame-by-frame reconstruction (IFR) method where the whole scan time duration is divided into multiple time frames, and the data in the each individual time frame is reconstructed separately. All the reconstructed images are used to obtain the temporal tracer uptake changes, and estimate kinetic parameters for quantitative studies. The method often has a drawback having low accuracy on the estimation process due to limited count rates when the frames are divided into very short time intervals to achieve enough temporal resolution.

Prompt Gamma Correction for Ga-68 PSMA PET studies

Ga-68 Prostate Specific Membrane Antigen also known as PSMA is currently used in prostate cancer PET imaging. The resulting images show high uptakes in kidney and bladder which could produce a photopenic artifact (halo) and potentially mask tumor lesions or bone metastasis at the level of kidney or bladder. The measured contrasts between these organs and background could be as high as 200:1 and 50:1 for kidney and bladder respectively. The correct quantification in these areas requires precise scatter correction which needs to account for the effect of prompt gamma. Ga-68 has a prompt gamma at 1077 keV with a branching ratio of 3.2%. An unscattered prompt gamma ray of 1077 keV in the object has a small probability to be detected. An object scattered prompt gamma has a higher detection probability. When the contrast is low, more accurate quantification can be achieved. On the contrary, when the contrast is very high, halo artifact can be observed around high uptake organs. The purpose of this work is to evaluate the effect of Ga-68 prompt gamma in clinical PSMA studies. The halo artifact around kidney and bladder is strongly reduced by applying a Prompt Gamma Correction. Selected studies were performed on a Siemens mCT and acquired by Technische Universität München, Germany.

Elastic motion correction for cardiac PET studies

Motion in PET studies degrades image quality and introduces bias, which is critical for high resolution scanners such as mCT, mMR, and HRRT. In this work we describe and compare motion corrected cardiac studies of cardiac gating and dual (cardiac and respiratory) gating. Elastic motion information is extracted using Mass Preservation Optical Flow (MPOF), and motion correction is performed during the reconstruction process. Elastic motion corrected PET cardiac studies show less noise than individual gated images, and higher resolution than images without motion correction. Studies utilizing three different tracers (FDG, Ammonia, and Rubidium) are shown in the results.

True 3D iterative scatter correction for small bore long axial FOV scanner

Two region of interest were selected. A hot region is around the Basal Ganglia, and the other region is around the Cerebellum as shown in both figure 2. A time activity curve was then generated for both the hot and cold region for the same study being generated with 2D and 3D scatter correction. Figure 3-a shows the hot region for both scatter 2D and 3D. Both regions have the same trend and value. However, looking at figure 3-b that shows the cold region, it shows that scatter were over estimated in the 2D scatter correction case.

Simultaneous reconstruction of scatter and unscattered PET coincidences using TOF and energy information

In positron emission tomography (PET), a typical iterative reconstruction algorithm relies on a method to estimate and subtract the scatter from the net trues coincidences: the remaining unscattered coincidences are then used to reconstruct an image of the original activity distribution. The introduction of time-of-flight (TOF) PET opens the possibility to change this scheme, and use the spatial information carried by the scattered events for the reconstruction. The combined knowledge of TOF difference and detected photon energy provide spatial information on the position of the source even after single scattering, and can be used for reconstruction of scattered photons, using a “scatter back projector” in addition to the conventional “trues back projector”. In the scatter back projector, the scattering angle is derived from the energy of the scattered photon through the Compton kinematics, and this identifies a set of possible scattering trajectories, or “broken” line-of-response (LOR). The TOF information localizes the position of the source along the set of broken LOR. The advantages of this proposed method are twofold: including the spatial information about the origin of the scattered pairs could improve the image quality particularly in low counts data set; the lower threshold of energy window can be lowered to include more scatter, increasing sensitivity.

Ultrafast Elastic Motion Correction via Motion Deblurring

Patient motion during PET studies degrades image quality. Some types of motion (e.g. brain) can be modeled as rigid-body transformations, whereas others (e.g. respiratory and cardiac), are more complex, involve deformations of the imaged organs, and require Elastic Motion Correction (EMC). The conventional way (cEMC) to handle the dense information needed for EMC is to divide the acquired data into multiple respiratory, cardiac, or dual “gates”, where motion is minimal within each gate. Motion fields can then be calculated between a reference gate and all other gates via optical flow. These motion fields can then be used in a cEMC iterative reconstruction process by warping the reference image to each gated image before forward projection and transposing the gated correction factors back to the reference image after backward projection. In this algorithm, the number of forward and backprojections, processing time, and memory requirements are proportional to the number of gates. In this paper, we introduce a faster algorithm, Elastic Motion Deblurring (EMDB), which does not depend on the number of gates. Instead, a Mass Preservation Optical Flow (MPOF) algorithm is used to calculate a blurring kernel from the reference gate to the static (motion blurred) image only. This novel approach reduces the processing time and hardware requirements for iterative EMC reconstruction.