Motion tracking using MR micro-coils
Motion monitoring using wired MR active markers dates back to 1986. It has been used for prospective motion correction and device tracking in MR imaging. Recently, wireless MR active markers gained interest in the MR community for prospective motion correction due to its simpler manufacturing, easier setup and better patient-friendliness. We have proposed to use wireless MR active markers to track head motion in real time during a brain PET-MR scan and incorporate the motion measured by the markers in a modified listmode PET reconstruction algorithm. This makes PET images, which are reconstructed from data acquired on a simultaneous PET-MR scanner, free of motion artifacts. Phantom and non-human primate experiments were conducted to evaluate the proposed methods. Our method is dedicated to simultaneous PET-MR scanners.
Motion tracking using PET
In PET, motion (respiratory motion, voluntary motion, cardiac motion, etc) can also be detected using data-driven techniques with PET listmode data. Data-driven gating techniques can be used to avoid external motion tracking device. Some initial attempts were made by study the total counts within manually defined regions of interest (ROIs) across moving organ boundaries on dynamic PET frames. Because the computation time associated with reconstruction of a large number of image frames, sinogram-based and even listmode-based approaches have been proposed.
We have compared respiratory motion derived from MR data, PET listmode and external monitoring device. While PET images reconstructed by MR gating yielded the best image quality, PET listmode respiratory signal outperformed bellow under normal event count. However, it was found that the quality of listmode respiratory signal deteriorates as the event count reduced.
Motion tracking/correction using MR images in the heart
Heart motion, caused by both the pumping action of the heart (cardiac motion) and breathing (respiratory motion), is the most important cause of image resolution degradation in cardiac PET imaging. Although the intrinsic spatial resolution of modern whole-body PET scanners is in the range of 4.5 mm, the displacements of 13-23mm and 4.9-9mm due to cardiac and respiratory motion, respectively, result in more than 10 mm (FWHM) effective spatial resolution. Additionally, the mismatch between emission and attenuation data due to heart motion can cause severe artifacts in cardiac PET as the attenuation characteristics of the lungs may be projected onto the myocardial wall, yielding false-positive ischemia.
Cardiac, respiratory or even dual gating techniques have been explored in static PET because they alleviate motion blurring while being a tool for clinicians to assess ventricular function. However, because each gate is reconstructed using typically 1/8th- and even 1/64th for dual gating- of the PET events, motion effects are removed in the gates at the expenses of the signal to noise ratio (SNR). Also, gating is not effective in dynamic cardiac imaging of rapid dynamic functions, such as myocardial blood flow, due to the substantial noise associated with rejecting a large number of detected events in low counts dynamic frames.
We proposed and evaluated a dedicated simultaneous cardiac PET-MR acquisition and reconstruction framework tackling non-rigid cardiac motion. We obtained accurate non-rigid wall motion by measuring complex intramural motion using MR tagging and incorporate the computed wall motion field directly into the systemmatrix of a list-mode PET OSEM reconstruction with no additional radiation dose to the patient.
Motion tracking/correction using radial FLASH MR in the lung
Accurate lesion characterization is crucial for initial staging, follow up and assessment of response to treatment in non-small cell lung cancer. Conventional PET-CT suffers from a temporal mismatch between PET and CT, due to longer PET than CT acquisitions needed for achieving good PET SNR. This mismatch yields artifacts that affect PET diagnostic specificity as well as quantitation accuracy ("banana" and "mushroom" artifacts). These artifacts lead to underestimation of tumor activity, especially in the region near the diaphragm, where motion effects are greatest. Gated 4D CT can be used to correct for motion; however, this is not usually done routinely due to longer exams and greater radiation dose.
Simultaneous PET-MR is a promising modality which is capable of tracking respiratory motion during the entire course of the PET exam with no additional ionizing radiation. We have shown that MR can be used to monitor the respiratory motion. However, real-time imaging for the entire volume of the lung with good spatial resolution remains challenging due to the limit on acquisition rate. Lack of signal from lung with most MRI sequences makes this endeavor even more challenging.
We presented a slice-interleaved golden-angle radial FLASH sequence with short-duration slice-projection navigation for lung respiratory motion measurement and respiratory motion tracking for motion-corrected PET reconstruction using simultaneous PET-MR.
Motion tracking/correction using TrueFISP MR in the liver
Motion correction in the liver is very similar to in the lung, the major difference is that radial FLASH does not provide good contrast in the liver in order to track the motion accurately. As a result, we used TrueFISP which yields excellent contrast between liver tissue and the vessels. The vessels in the liver are used as landmarks for image registration.
Improved PET images may be obtained by modeling respiratory motion within the PET iterative reconstruction process. Our proposed quantitative PET-MR methods with motion correction can significantly enhance the performance of tumor diagnosis and staging in the liver as compared to conventional methods. This may enable utilization of the full potential of the scanner in oncologic studies of lower abdomen with moving lesions.
Motion correction in brain PET-MRI
Many approaches have been explored in the effort to correct motion artifacts. Depending on whether the motion is estimated from the acquired PET data or by other instrumentation, the approaches can be divided into two groups: auto-correction and assisted-correction.
For the auto-correction techniques, the measured PET data are divided into temporal frames, and the motion is then estimated between temporal frames from the PET data. The estimated motion field can then be used to transform the reconstructed images or the sinograms of each temporal frame to a reference frame. The accuracy of motion estimation using this approach is limited by the noise of PET images, which increases as the data set is divided into temporal frames for a dynamic image sequence. Moreover, the fact that the motion estimation relies on the generation of images or sinograms limits its temporal resolution; this method is not suitable when the activity distribution is fast changing or the object is fast moving.
The reconstruction algorithms of the assisted-correction approaches are similar to auto-correction techniques except that the motion information is instead measured using an instrument other than the PET camera, such as video/infrared cameras, and approaches with structured light. Similar approaches have also been applied to motion correction in MRI. One advantage of these optical motion tracking approaches is that they are independent of the PET-MR acquisition, so that no changes to MR pulse sequence are required, in contrast to MR navigator-based methods. Another advantage is that the optical methods, in principle, are capable of achieving high frame rate. Some of these approaches monitor the motions of the reflectors attached to the subject's head; some observe a portion of the subject's face. But they all require an unobstructed view from the cameras to the reflectors or the subject's face. This is challenging for PET-MR head scan because the view from outside of the scanner is blocked by the head coil, especially for the modern head coils with large number of channels. There are RF contamination and MR compatibility issues associated with installing cameras inside of the scanner. Moreover, these optical systems require complicated calibrations.
We used motion measured by MR micro-coils which was incoporated into listmode PET reconstruction. This makes PET images, which are reconstructed from data acquired on a simultaneous PET-MR scanner, free of motion artifacts. Phantom and non-human primate experimentswere conducted to evaluate the methods