Sinogram-based motion correction of PET images using optical motion tracking system and list-mode data acquisition

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.

Small-animal positron emission tomography as a tool for neuropharmacology

The motion of the head during brain positron emission tomography (PET) acquisitions has been identified as a source of artifact in the reconstructed image. In this study, a method is described to develop an image-based motion correction technique for correcting the post-acquisition data without using external optical motion-tracking system such as POLARIS. In this technique, GATE has been used to simulate PET brain scan using point sources mounted around the head to accurately monitor the position of the head during the time frames. The measurement of head motion in each frame showed a transformation in the image frame matrix, resulting in a fully corrected data set. Using different kinds of phantoms and motions, the accuracy of the correction method is tested and its applicability to experimental studies is demonstrated as well.

A wide array of positron emission tomography (PET) ligands have been developed that provide information relevant to multiple aspects of addiction (1-3).Locations of targets are approximated on this diagram, which is color-coded by functional roles.On the presynaptic side (pink), targets include neurotransmitter precursors (orange, example [ 18 F]-fluorodopa, FDOPA), modulatory receptors (yellow, examples [ 11 C] GR103545, [ 11 C] LY27950509 and [ 18 F] LY2459989 for kappa opioid receptors, KOR; [ 18 F]FMPEP for cannabinoid 1 receptors, CB1), and neurotransmitter reuptake transporters (light green, examples [ 11 C] PE2I and [ 18 F] FE-PE2I for the dopamine transporter, DAT).On the postsynaptic side (purple), targets include neurotransmitter receptors (blue, examples [ 11 C] raclopride and [ 11 C]-(1)-PHNO for dopamine D 2 and D 3 receptors, D 2 R; [ 11 C] carfentanil for mu opioid receptors, MOR; [ 18 F] LY2459989 for both mu and kappa opioid receptors; 2-[ 18 F]fluoro-3-(2(S)-azetidinylmethoxy) pyridine for nicotinic acetylcholine receptors, nAChR).Some PET ligands target more generic functions.[ 18 F]-fluoro-deoxy-glucose (FDG) PET provides a measure of cerebral metabolic rate.

Respiratory motion blurs positron emission tomography (PET) images in thorax and abdominal regions, and can cause attenuation-related errors in quantitative parameters. In addition, this motion can cause localization error and disappearance of tumor(s) near the diaphragm. Respiratory gated PET imaging, or 4D PET imaging, is an attractive solution. For 4D PET, a surrogate measurement of the patient's breathing is made during the scan, and based on this measurement the list-mode PET data are sorted and reconstructed into multiple images. In several studies, it has been reported that 4D PET imaging recovers tumor volume more accurately than 3D PET imaging, and yields more accurate standard uptake values. In spite of its promise, 4D PET images suffer from statistical noise because only a fraction of the acquired data can be used in each image. Moreover, they also suffer from inconsistent attenuation correction due to mismatches between PET and CT images. In this paper, we propose a novel framework for phased attenuation correction and respiratory motion compensation for a 3D PET image by using a 3D CT image and multiple respiratory-phase 3D MR images. For phased attenuation correction, we generate and utilize 4D CT image obtained via non-rigid registrations among a 3D CT image and multiple respiratory-phase 3D MR images. A 3D PET image at a selected respiratory phase is then obtained by adding attenuation corrected multiple 3D PET images through non-rigid transformation. Experimental result for a clinical dataset shows that the proposed algorithm can provide much clearer organ boundary with improved quality than the conventional method in a 3D PET image.

The Case Against Heavy PETing

Purpose: Neurofibromatosis type 1 (NF1), which is caused by mutations of the NF1 gene, is the most frequent single gene disorder to affect the nervous system. Unidentified bright objects (UBOs) are commonly observed on brain magnetic resonance imaging (MRI) in patients with NF1. However, their clinical and pathologic significance is not well understood. The purpose of this study was to investigate the correlation between UBOs and cerebral glucose metabolism measured by F-2Fluoro-2-deoxy-D-glucose (F-FDG) positron emission tomography (PET) in Korean patients with NF1. Materials and Methods: Medical records of 75 patients (34 males and 41 females) with NF1 who underwent brain MRI and PET between 2005 and 2011 were evaluated retrospectively. Clinical data including demographics, neurological symptoms, and brain MRI and PET findings, were reviewed. Results: UBOs were detected in the brain MRI scans of 31 patients (41%). The region most frequently affected by UBOs was the basal ganglia. The most frequent brain PET finding was thalamic glucose hypometabolism (45/75, 60%). Of the 31 patients with UBOs, 26 had thalamic glucose hypometabolism on brain PET, but the other 5 had normal brain PET findings. Conversely, of the 45 patients with thalamic glucose hypometabolism on brain PET, 26 showed UBOs on their brain MRI scans, but 19 had normal findings on brain MRI scans. Conclusion: UBOs on brain MRI scans and thalamic glucose hypometabolism on PET appear to be 2 distinctive features of NF1 rather than correlated symptoms. Because the clinical significance of these abnormal imaging findings remains unclear, a longitudinal follow-up study of changes in clinical manifestations and imaging findings is necessary.

Does positron emission tomography data acquisition impact simultaneous diffusion-weighted imaging in a whole-body PET/MRI system?

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.

We have developed AwakeSPECT, a small animal SPECT/CT system for imaging the live mouse brain using an optical motion tracking system. The system successfully has been used in mouse brain studies without the need of anesthesia. As an extension of this technology we have built a prototype Awake Animal PET system by using the motion tracking system and modular PET detectors. The system consists of a commercial motion tracking system that utilizes four CCD cameras equipped with near infra-red (NIR) strobes and retro-reflective markers, and a modular PET system with 8 detector modules. The motion tracking system measures six degrees of freedom (x, y, z, roll, pitch, and yaw) of then moving target at 60 frames per second. The PET system uses a 32 channel flash ADC system developed at Thomas Jefferson National Accelerator Facility. Each PET detector module is built with a Hamamatsu H8500 position sensitive photomultiplier tubes (PSPMT) optically coupled to a 48 x 48 pixelated 1 mm pitch LYSO scintillator array. Custom built PSPMT read-out electronics were built that uses Anger-logic to provide four channel output per detector module. Geometrical calibration was performed using Na-22 point source phantom using the same method used for AwakeSPECT. Initial proof-ofprinciple tests were performed using a foam mouse phantom with three IR reflectors and an embedded Na-22 point source. During the PET scan, the foam mouse was moved/rotated by hand motion. Image reconstruction with motion compensation resulted in good point image reconstruction.

Positron emission tomography (PET) and single photon emission computed tomography (SPECT) brain imaging are widely used as diagnostic tools for suspected dementia but no studies have directly compared participant views of the two procedures. We used a range of methods to explore preferences for PET and SPECT. Patients and controls (and accompanying carers) completed questionnaires immediately after undergoing PET and SPECT brain scans. Pulse rate data were collected during each scan. Scan attributes were prioritized using a card sorting exercise; carers and controls additionally answered willingness to pay (WTP) questions. Few differences were found either between the scans or groups of participants, although carers marginally preferred SPECT. Diagnostic accuracy was prioritized over other scan characteristics. Mean heart rate during both scans was lower than baseline heart rate measured at home (p < 0.001). Most participants viewed PET and SPECT scans as roughly equivalent and did not have a preference for either scan. Carer preference for SPECT is likely to reflect their desire to be with the patient (routine practice for SPECT but not for PET), suggesting that they should be able to accompany vulnerable patients throughout imaging procedures wherever possible. Pulse rate data indicated that brain imaging was no more stressful than a home visit (HV) from a researcher. The data do not support the anecdotal view that PET is a more burdensome procedure and the use of PET or SPECT scans in dementia should be based on diagnostic accuracy of the technique.

Subject motion in positron emission tomography (PET) studies leads to image blurring and artifacts; simultaneously acquired magnetic resonance imaging (MRI) data provides a means for motion correction (MC) in integrated PET/MRI scanners. To assess the effect of realistic head motion and MR-based MC on static [18 F]-fluorodeoxyglucose (FDG) PET images in dementia patients. Observational study. Thirty dementia subjects were recruited. 3T hybrid PET/MR scanner where EPI-based and T1 -weighted sequences were acquired simultaneously with the PET data. Head motion parameters estimated from high temporal resolution MR volumes were used for PET MC. The MR-based MC method was compared to PET frame-based MC methods in which motion parameters were estimated by coregistering 5-minute frames before and after accounting for the attenuation-emission mismatch. The relative changes in standardized uptake value ratios (SUVRs) between the PET volumes processed with the various MC methods, without MC, and the PET volumes with simulated motion were compared in relevant brain regions. The absolute value of the regional SUVR relative change was assessed with pairwise paired t-tests testing at the P = 0.05 level, comparing the values obtained through different MR-based MC processing methods as well as across different motion groups. The intraregion voxelwise variability of regional SUVRs obtained through different MR-based MC processing methods was also assessed with pairwise paired t-tests testing at the P = 0.05 level. MC had a greater impact on PET data quantification in subjects with larger amplitude motion (higher than 18% in the medial orbitofrontal cortex) and greater changes were generally observed for the MR-based MC method compared to the frame-based methods. Furthermore, a mean relative change of ∼4% was observed after MC even at the group level, suggesting the importance of routinely applying this correction. The intraregion voxelwise variability of regional SUVRs was also decreased using MR-based MC. All comparisons were significant at the P = 0.05 level. Incorporating temporally correlated MR data to account for intraframe motion has a positive impact on the FDG PET image quality and data quantification in dementia patients. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1288-1296.

17113 Background: MPM is a rapidly progressive malignancy with a median survival of 6 to 9 months. Studies in non-small cell lung cancer, gastrointestinal stromal tumours, and breast cancer suggest that Positron Emission Tomography (PET) scanning may predict the clinical outcome of chemotherapy at an early stage of treatment. The role of PET in predicting and monitoring response to treatment in MPM is unclear. In this study we assessed if baseline and early interval PET scanning could be of benefit in MPM, correlating the results with standard Computerised Tomography (CT) assessment using the modified Response Evaluation Criteria In Solid Tumours (RECIST) of Byrne and Nowak. Methods: 10 patients with histologically proven MPM proceeded to baseline PET and CT scanning prior to chemotherapy. In 8 patients a second PET scan was performed within three weeks of commencing treatment. The following PET derived parameters were calculated: Standard Uptake Value (SUV)maximum, SUVaverage, PETvolume, and Total Lesion Glycolysis (TLG). Baseline SUVmaximum and early PET response was compared with CT response and survival. Results: Baseline SUVmaximum predicted subsequent CT response in the 10 patients studied. Four out of 5 patients with baseline SUVmaximum of &lt;15 showed a subsequent partial response on CT, whilst the 5th patient had resolution of a pleural effusion. All 5 patients with baseline SUVmaximum of &gt;15 had stable or progressive disease on CT. In contrast change in early SUVmaximum from baseline to 3 weeks did not predict subsequent CT response (Kappa value 0.07) in the 8 patients evaluated. Change in PET volume and TLG correlated with subsequent CT response (Kappa value= 0.80 for both). Only 1 patient with a partial response on % PETvolume and %TLG has died 14 months after commencing treatment. The other 3 patients are alive at 17+, 19+ and 20+ months. The 4 patients with stable or progressive disease using these parameters were deceased at 5, 6, 10, and 12 months respectively. Conclusion: PET may be useful in predicting and evaluating response to treatment in MPM. Furthermore, the results suggest that PET response may be a useful prognostic tool in this disease. It is important to use the appropriate PET derived parameters. Further study with a larger patient population is warranted. No significant financial relationships to disclose.

BackgroundWhile a great deal of recent effort has focused on addressing a perceived reproducibility crisis within brain structural magnetic resonance imaging (MRI) and functional MRI research communities, less attention has been paid to reproducibility of brain positron emission tomography (PET) research.MethodsWe examined the current landscape of factors that contribute to reproducible neuroimaging data analysis, comparing brain MRI to brain PET. The factors included scientific standards, analytic plan pre‐registration, data and code sharing, containerized workflows, and standardized processing pipelines. To demonstrate the positive impact that further developing such reproducibility factors would have on brain PET research, we conducted one case study in which the brain PET processing pipeline developed for one flagship study (Alzheimer's Disease Neuroimaging Initiative, ADNI) for brain 18F‐florbetapir and 18F‐fluorodeoxyglucose (FDG) analysis was reproduced in our laboratory.ResultsCompared to fMRI, PET research encounters substantial challenges in adopting essential reproducibility practices. While 85% of fMRI studies adhere to the standardized reporting practices, PET is in the early stages of establishing reporting practices, lacking a standardized checklist. Pre‐registration is prevalent for fMRI (57.6%) but notably absent in PET, with no pre‐registered PET studies found on platforms such as the Center for Open Science. The number of shared datasets is higher for fMRI compared to PET, with 92 fMRI datasets and only 9 PET datasets on repositories like OpenNeuro. Moreover, there are very few data repositories for newer PET radiotracers. Containerized software availability also favor fMRI, with platforms like (Brain Imaging Data Structure, BIDS) apps hosting 66% dedicated fMRI tools, while no PET‐specific software is available. Standardized processing pipelines follow the same trend, with fMRI boasting optimized workflows for specific protocols, while PET has few dedicated pipelines and lacks validation studies for existing options. Furthermore, while our case study demonstrated excellent correlation results for both the 18F‐FDG and 18F‐florbetapir methods (Figure 2), the replication of the ADNI PET pipeline posed substantial challenges and implementation delays. These obstacles and delays in execution were due to incomplete documentation and ambiguities in application details.ConclusionPET neuroimaging lags behind its MRI‐related counterparts in achieving robust reproducibility.

Despite its success in many biomedical applications, Positron Emission Tomography (PET) has the drawback of typically having lower spatial resolution and higher noise respect to other medical imaging techniques. The best achievable spatial resolution in PET scanners is limited by factors such as the positron range, non-collinearity and the size of the detector crystals. In this work, we present a novel method that uses series of image reconstructions (super-iterations) to go beyond the expected resolution-noise limits for a given PET acquisition. The image quality improvement is achieved using the projections of the previous image reconstruction to redistribute the measured counts of each line-of-response (LOR) into several subLORs, from which a new activity distribution with better quality is reconstructed. The method was evaluated with data from the preclinical scanner 4R-SuperArgus PET/CT, using the NEMA NU4-2008 image quality phantom, a cold Derenzo phantom, and an in-vivo FDG cardiac study on a rat. Resolution and recovery coefficient (RC) improvement of ~10% was achieved while keeping the same noise level. Qualitative results from the in-vivo study also confirm this improvement in image quality. The proposed method is able to achieve significantly better images at the expense of a modest increase of the computational time, and it could be also applied to other modalities, such as SPECT and Compton Cameras.