Evaluation of elastix-based propagated align algorithm for VOI- and voxel-based analysis of longitudinal F-18-FDG PET/CT data from patients with non-small cell lung cancer (NSCLC)

Background: Deformable image registration allows volume of interest (VOI)- and voxel-based analysis of longitudinal changes in fluorodeoxyglucose (FDG) tumor uptake in patients with non-small cell lung cancer (NSCLC). This study evaluates the performance of the elastix toolbox deformable image registration algorithm for VOI and voxel-wise assessment of longitudinal variations in FDG tumor uptake in NSCLC patients. Methods: Evaluation of the elastix toolbox was performed using F-18-FDG PET/CT at baseline and after 2 cycles of therapy (follow-up) data in advanced NSCLC patients. The elastix toolbox, an integrated part of the IMALYTICS workstation, was used to apply a CT-based non-linear image registration of follow-up PET/CT data using the baseline PET/CT data as reference. Lesion statistics were compared to assess the impact on therapy response assessment. Next, CT-based deformable image registration was performed anew on the deformed follow-up PET/CT data using the original follow-up PET/CT data as reference, yielding a realigned follow-up PET dataset. Performance was evaluated by determining the correlation coefficient between original and realigned follow-up PET datasets. The intra-and extra-thoracic tumors were automatically delineated on the original PET using a 41% of maximum standardized uptake value (SUVmax) adaptive threshold. Equivalence between reference and realigned images was tested (determining 95% range of the difference) and estimating the percentage of voxel values that fell within that range. Results: Thirty-nine patients with 191 tumor lesions were included. In 37/39 and 12/39 patients, respectively, thoracic and non-thoracic lesions were evaluable for response assessment. Using the EORTC/SUVmax-based criteria, 5/37 patients had a discordant response of thoracic, and 2/12 a discordant response of non-thoracic lesions between the reference and the realigned image. FDG uptake values of corresponding tumor voxels in the original and realigned reference PET correlated well (R-2=0.98). Using equivalence testing, 94% of all the voxel values fell within the 95% range of the difference between original and realigned reference PET. Conclusions: The elastix toolbox impacts lesion statistics and therefore therapy response assessment in a clinically significant way. The elastix toolbox is therefore not applicable in its current form and/or standard settings for PET response evaluation. Further optimization and validation of this technique is necessary prior to clinical implementation

A dual-time-window protocol to reduce acquisition time of dynamic tau PET imaging using [F-18]MK-6240

Background [F-18]MK-6240 is a PET tracer with sub-nanomolar affinity for neurofibrillary tangles. Therefore, tau quantification is possible with [F-18]MK-6240 PET/CT scans, and it can be used for assessment of Alzheimer's disease. However, long acquisition scans are required to provide fully quantitative estimates of pharmacokinetic parameters. Therefore, on the present study, dual-time-window (DTW) acquisitions was simulated to reduce PET/CT acquisition time, while taking into consideration perfusion changes and possible scanning protocol non-compliance. To that end, time activity curves (TACs) representing a 120-min acquisition (TAC(120)) were simulated using a two-tissue compartment model with metabolite corrected arterial input function from 90-min dynamic [F-18]MK-6240 PET scans of three healthy control subjects and five subjects with mild cognitive impairment or Alzheimer's disease. Therefore, TACs corresponding to different levels of specific binding were generated and then various perfusion changes were simulated. Next, DTW acquisitions were simulated consisting of an acquisition starting at tracer injection, a break and a second acquisition starting at 90 min post-injection. Finally, non-compliance with the PET/CT scanning protocol were simulated to assess its impact on quantification. All TACs were quantified using reference Logan's distribution volume ratio (DVR) and standardized uptake value ratio (SUVR90) using the cerebellar cortex as reference region. Results It was found that DVR from a DTW protocol with a 60-min break between two 30-min dynamic scans closely approximates the DVR from the uninterrupted TAC(120), with a regional bias smaller than 2.5%. Moreover, SUVR90 estimates were more susceptible (regional bias</p

Monte Carlo simulations of the GE Signa PET/MR for different radioisotopes

NEMA characterization of PET systems is generally based on(18)F because it is the most relevant radioisotope for the clinical use of PET.F-18 has a half-life of 109.7 min and decays into stable(18)O via beta+ emission with a probability of over 96% and a maximum positron energy of 0.633 MeV. Other commercially available PET radioisotopes, such as(82)Rb and(68)Ga have more complex decay schemes with a variety of prompt gammas, which can directly fall into the energy window and induce false coincidence detections by the PET scanner. Methods Aim of this work was three-fold: (A) Develop a GATE model of the GE Signa PET/MR to perform realistic and relevant Monte Carlo simulations (B) Validate this model with published sensitivity and Noise Equivalent Count Rate (NECR) data for(18)F and(68)Ga (C) Use the validated GATE-model to predict the system performance for other PET isotopes including(11)C,O-15,N-13,Rb-82, and(68)Ga and to evaluate the effect of a 3T magnetic field on the positron range. Results Simulated sensitivity and NECR tests performed with the GATE-model for different radioisotopes were in line with literature values. Simulated sensitivities for(18)F and(68)Ga were 21.2 and 19.0/kBq, respectively, for the center position and 21.1 and 19.0 cps/kBq, respectively, for the 10 cm off-center position compared to the corresponding measured values of 21.8 and 20.0 cps/kBq for the center position and 21.1 and 19.6 cps/kBq for the 10 cm off-center position. In terms of NECR, the simulated peak NECR was 216.8 kcps at 17.40 kBq/ml for(18)F and 207.1 kcps at 20.10 kBq/ml for(68)Ga compared to the measured peak NECR of 216.8 kcps at 18.60 kBq/ml and 205.6 kcps at 20.40 kBq/ml for(18)F and(68)Ga, respectively. For(11)C,N-13, and(15)O, results confirmed a peak NECR similar to(18)F with the effective activity concentration scaled by the inverse of the positron fraction. For(82)Rb, and(68)Ga, the peak NECR was lower than for(18)F while the corresponding activity concentrations were higher. For the higher energy positron emitters, the positron range was confirmed to be tissue-dependent with a reduction of the positron range by a factor of 3 to 4 in the plane perpendicular to the magnetic field and an increased positron range along the direction of the magnetic field. Conclusion Monte-Carlo simulations were used to predict sensitivity and NECR performance of GE Signa PET/MR for(18)F,O-15,N-13,C-11,Rb-82, and(68)Ga radioisotopes and were in line with literature data. Simulations confirmed that sensitivity and NECR were influenced by the particular decay scheme of each isotope. As expected, the positron range decreased in the direction perpendicular to the 3T magnetic field. However, this will be only partially improving the resolution properties of a clinical PET/MR system due to the limiting spatial resolution of the PET detector

Tracer-specific PET and SPECT templates for automatic co-registration of functional rat brain images

Objectives: Template based spatial co-registration of PET and SPECT data is an important first step in its semi- automatic processing, facilitating VOI- and voxel-based analysis. Although this procedure is standard in human, using corresponding MRI images, these systems are often not accessible for preclinical research. Alternatively, manual co-registration of images to a MRI template is often performed. However, this is operator dependent and can introduce bias. Therefore, we constructed several tracer-specific PET and SPECT rat brain templates for automatic co-registration, spatially aligned with a widely used MRI-based template in Paxinos stereotactic space [1]. Methods: PET (18F-FDG, 11C-PK11195, and 11C-MeDAS) and SPECT (99mTc-HMPAO) brain scans were acquired from healthy male Sprague-Dawley and Wistar rats. Symmetrical left-right templates were constructed by averaging the scans. Within-modality registration was performed by minimizing the sum of squared difference and template to MRI registration by normalized mutual information maximization algorithm. For validation purposes, PET scans were acquired from a rat model of multiple sclerosis (MS) where focal demyelination was induced by injection of lysolecithin (or control saline) in right corpus callosum and striatum. Parametric SUV images were created for automatic co-registration. The validity of the templates was assessed by estimation of registration accuracy errors, inter-subject variability, right-to-left asymmetry indices, and voxel-based analysis of the MS model [2]. Results: The obtained mean registration errors were 0.097-1.277mm for PET, and 0.059-0.477mm for SPECT. These values are below spatial resolution of the cameras (1.4mm and 0.8mm, respectively) and in agreement with human literature [3]. Results from voxel-based analyses (Figure 1) correspond with those previously reported using VOI-based analysis [4], and correlate with the regions where lesion was induced. Conclusion: The constructed tracer-specific templates allow accurate registration of functional rat brain data, using automatic normalization algorithms available in standard packages (e.g., SPM, FSL), supporting either VOI- or voxel-based analysis. The templates will be made freely available for the research community

Regional accuracy of ZTE-based attenuation correction in static and dynamic brain PET/MR

Accurate MR-based attenuation correction (MRAC) is essential for quantitative PET/MR imaging of the brain. In this study, we analyze the regional bias caused by MRAC based on Zero-Echo-Time MR images (ZTEAC) compared to CT-based AC (CTAC) in static and dynamic PET imaging. In addition the results are compared to the performance of the current default Atlas-based AC (AtlasAC) implemented in the GE SIGNA PET/MR. Methods: Thirty static [18F]FDG and 11 dynamic [18}F]PE2I acquisitions from a GE SIGNA PET/MR were reconstructed using ZTEAC (using a research tool, GE Healthcare), single-subject AtlasAC (the current default AC in GE's SIGNA PET/MR) and CTAC (from a PET/CT acquisition of the same day). In the 30 static [18F]FDG reconstructions, the bias caused by ZTEAC and AtlasAC in the mean uptake of 85 anatomical volumes of interest (VOIs) of the Hammers' atlas was analyzed in PMOD. For the 11 dynamic [18}F]PE2I reconstructions, the bias caused by ZTEAC and AtlasAC in the non displaceable binding potential BPnd in the striatum was calculated with cerebellum as the reference region and a simplified reference tissue model. Results: The regional bias caused by ZTEAC in the static [18F]FDG reconstructions ranged from -8.0% to +7.7% (mean 0.1%, SD 2.0%). For AtlasAC this bias ranged from -31.6% to +16.6% (mean -0.4%, SD 4.3%). The bias caused by AtlasAC showed a clear gradient in the cranio-caudal direction (-4.2% in the cerebellum, +6.6% in the left superior frontal gyrus). The bias in the striatal BPnd for the [18F]PE2I reconstructions ranged from -0.8% to +4.8% (mean 1.5%, SD 1.4%) using ZTEAC and from -0.6% to +9.4% using AtlasAC (mean 4.2%, SD 2.6%). Conclusion: ZTEAC provides excellent quantitative accuracy for static and dynamic brain PET/MR, comparable to CTAC, and is clearly superior to the default AtlasAC currently implemented in the GE SIGNA PET/MR.Comment: 23 pages in total, 7 figures, 1 table, 3 supplementary figures, 5 supplementary table