PET Quantitation Research Articles

Targeting of immune checkpoint regulator V-domain Ig suppressor of T-cell activation (VISTA) with 89Zr-labelled CI-8993

BackgroundCI-8993 is a fully human IgG1κ monoclonal antibody (mAb) that binds specifically to immune checkpoint molecule VISTA (V-domain Ig suppressor of T-cell activation). Phase I safety has been established in patients with advanced cancer (NCT02671955). To determine the pharmacokinetics and biodistribution of CI-8993 in patients, we aimed to develop 89Zr-labelled CI-8993 and validate PET imaging and quantitation in preclinical models prior to a planned human bioimaging trial.MethodsCI-8993 and human isotype IgG1 control were conjugated to the metal ion chelator p-isothiocyanatobenzyl-desferrioxamine (Df). Quality of conjugates were assessed by SE-HPLC, SDS-PAGE, and FACS. After radiolabelling with zirconium-89 (89Zr), radioconjugates were assessed for radiochemical purity, immunoreactivity, antigen binding affinity, and serum stability in vitro. [89Zr]Zr-Df-CI-8993 alone (1 mg/kg, 4.6 MBq) or in combination with 30 mg/kg unlabelled CI-8993, as well as isotype control [89Zr]Zr-Df-IgG1 (1 mg/kg, 4.6 MBq) were assessed in human VISTA knock-in female (C57BL/6 N-Vsirtm1.1(VSIR)Geno, huVISTA KI) or control C57BL/6 mice bearing syngeneic MB49 bladder cancer tumours; and in BALB/c nu/nu mice bearing pancreatic Capan-2 tumours.ResultsStable constructs with an average chelator-to-antibody ratio of 1.81 were achieved. SDS-PAGE and SE-HPLC showed integrity of CI-8993 was maintained after conjugation; and ELISA indicated no impact of conjugation and radiolabelling on binding to human VISTA. PET imaging and biodistribution in MB49 tumour-bearing huVISTA KI female mice showed specific localisation of [89Zr]Zr-Df-CI-8993 to VISTA in spleen and tumour tissues expressing human VISTA. Specific tumour uptake was also demonstrated in Capan-2 xenografted BALB/c nu/nu mice.ConclusionsWe radiolabelled and validated [89Zr]Zr-Df-CI-8993 for specific binding to huVISTA in vivo. Our results demonstrate that 89Zr-labelled CI-8993 is now suitable for targeting and imaging VISTA expression in human trials.Graphical

Impact of PET Reconstruction on Amyloid-β Quantitation in Cross-Sectional and Longitudinal Analyses.

Amyloid-β (Aβ) accumulation in Alzheimer disease (AD) is typically measured using SUV ratio and the centiloid (CL) scale. The low spatial resolution of PET images is known to degrade quantitative metrics because of the partial-volume effect. This article examines the impact of spatial resolution, as determined by the reconstruction configuration, on the Aβ PET quantitation in both cross-sectional and longitudinal data. Methods: The cross-sectional study involved 89 subjects with 20-min [18F]florbetapir scans generated on an mCT (44 Aβ-negative [Aβ-], 45 Aβ-positive [Aβ+]) using 69 reconstruction configurations, which varied in number of iteration updates, point-spread function, time-of-flight, and postreconstruction smoothing. The subjects were classified as Aβ- or Aβ+ visually. For each reconstruction, Aβ CL was calculated using CapAIBL, and the spatial resolution was calculated as full width at half maximum (FWHM) using the barrel phantom method. The change in CLs and the effect size of the difference in CLs between Aβ- and Aβ+ groups with FWHM were examined. The longitudinal study involved 79 subjects (46 Aβ-, 33 Aβ+) with three 20-min [18F]flutemetamol scans generated on an mCT. The subjects were classified as Aβ- or Aβ+ using a cutoff CL of 20. All scans were reconstructed using low-, medium-, and high-resolution configurations, and Aβ CLs were calculated using CapAIBL. Since linear Aβ accumulation was assumed over a 10-y interval, for each reconstruction configuration, Aβ accumulation rate differences (ARDs) between the second and first periods were calculated for all subjects. Zero ARD was used as a consistency metric. The number of Aβ accumulators was also used to compare the sensitivity of CL across reconstruction configurations. Results: In the cross-sectional study, CLs in both the Aβ- and the Aβ+ groups were impacted by the FWHM of the reconstruction method. Without postreconstruction smoothing, Aβ- CLs increased for a FWHM of 4.5 mm or more, whereas Aβ+ CLs decreased across the FWHM range. High-resolution reconstructions provided the best statistical separation between groups. In the longitudinal study, the median ARD of low-resolution reconstructed data for the Aβ- group was greater than zero whereas the ARDs of higher-resolution reconstructions were not significantly different from zero, indicating more consistent rate estimates in the higher-resolution reconstructions. Higher-resolution reconstructions identified 10 additional Aβ accumulators in the Aβ- group, resulting in a 22% increased group size compared with the low-resolution reconstructions. Higher-resolution reconstructions reduced the average CLs of the negative group by 12 points. Conclusion: High-resolution PET reconstructions, inherently less impacted by partial-volume effect, may improve Aβ PET quantitation in both cross-sectional and longitudinal data. In the cross-sectional analysis, separation of CLs between Aβ- and Aβ+ cohorts increased with spatial resolution. Higher-resolution reconstructions also exhibited both improved consistency and improved sensitivity in measures of Aβ accumulation. These features suggest that higher-resolution reconstructions may be advantageous in early-stage AD therapies.

Data-driven gated PET/CT: implications for lesion segmentation and quantitation

BackgroundData-driven gating (DDG) can improve PET quantitation and alleviate many issues with patient motion. However, misregistration between DDG-PET and CT may occur due to the distinct temporal resolutions of PET and CT and can be mitigated by DDG-CT. Here, the effects of misregistration and respiratory motion on PET quantitation and lesion segmentation were assessed with a new DDG-PET/CT method.MethodsA low-dose cine-CT was acquired in misregistered regions to enable both average CT (ACT) and DDG-CT. The following were compared: (1) baseline PET/CT, (2) PET/ACT (attenuation correction, AC = ACT), (3) DDG-PET (AC = helical CT), and (4) DDG-PET/CT (AC = DDG-CT). For DDG-PET, end-expiration (EE) data were derived from 50% of the total PET data at 30% from end-inspiration. For DDG-CT, EE phase CT data were extracted from cine-CT data by lung Hounsfield unit (HU) value and body contour. A total of 91 lesions from 16 consecutive patients were assessed for changes in standard uptake value (SUV), lesion glycolysis (LG), lesion volume, centroid-to-centroid distance (CCD), and DICE coefficients.ResultsRelative to baseline PET/CT, median changes in SUVmax ± σ for all 91 lesions were 20 ± 43%, 26 ± 23%, and 66 ± 66%, respectively, for PET/ACT, DDG-PET, and DDG-PET/CT. Median changes in lesion volume were 0 ± 58%, − 36 ± 26%, and − 26 ± 40%. LG for individual lesions increased for PET/ACT and decreased for DDG-PET, but was not different for DDG-PET/CT. Changes in mean HU from baseline PET/CT were dramatic for most lesions in both PET/ACT and DDG-PET/CT, especially for lesions with mean HU < 0 at baseline. CCD and DICE were both affected more by motion correction with DDG-PET than improved registration with ACT or DDG-CT.ConclusionAs misregistration becomes more prominent, the impact of motion correction with DDG-PET is diminished. The potential benefits of DDG-PET toward accurate lesion segmentation and quantitation could only be fully realized when combined with DDG-CT. These results impress upon the necessity of ensuring both misregistration and motion correction are accounted for together to optimize the clinical utility of PET/CT.

Automated quantification of baseline imaging PET metrics on FDG PET/CT images of pediatric Hodgkin lymphoma patients

PurposeFor pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma.Methods18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson’s correlation coefficient and relative percent differences were calculated between automated and physician-extracted features.ResultsMedian Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78–0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson’s correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of − 4.3% (− 10.0–5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of − 0.4% (− 5.2–7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6–4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR − 7.5–40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically.ConclusionsAn automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.

Evaluation of amyloid and tau PET quantitation methods using a 3D‐printed anatomically accurate brain phantom

AbstractBackgroundA potential source of error in quantifying longitudinal changes in amyloid and tau imaging is the spatial resolution of PET. Partial volume correction (PVC) methods have been developed to account for this, but there remains a lack of consensus in the Alzheimer’s field on their use due to a lack of method evaluation relative to ground truth. The aim of this work was to evaluate various reconstruction and image‐based PVC techniques using an anatomically accurate 3D‐printed PET phantom with physiologically relevant radiotracer distributions.MethodsA lateral temporal phantom (Figure 1) with six fillable, thin‐walled (1.0 mm) chambers corresponding to inferior, middle, and superior temporal gray matter (GM) and white matter (WM) regions was constructed via 3D‐printing (Formlabs Form 3) using the FreeSurfer v5.3 segmented sample subject “bert” as a pattern. Inferior and superior temporal GM regions were filled with a 3.0 kBq/cc concentration of F‐18 solution and WM regions with 1.5 kBq/cc, simulating a high amyloid‐burden subject with a GM‐to‐WM radioactivity ratio of 2:1. The phantom was scanned on a Siemens Biograph mCT and reconstructed using three techniques: FBP; OSEM; and TrueX, an iterative method with system matrix modeling using a spatially variant point spread function. Image‐based geometric transfer matrix (GTM) PVC was applied to the FBP and OSEM images. Regional uncorrected and PVC radioactivity concentrations were compared to known ground truth.ResultsFBP, OSEM, and TrueX PET images are presented in Figure 2. Inferior and superior temporal GM and WM radioactivity concentrations for each of the reconstructions, uncorrected and PVC, are presented in Figure 3.ConclusionGTM PVC resulted in more accurate regional quantification relative to uncorrected data, regardless of reconstruction method. TrueX, which accounts for the system resolution during reconstruction, did not result in improved quantitative accuracy despite apparent differences in image quality. Optimization of TrueX parameters may result in improved quantitation accuracy. This study adhered to one fundamental assumption of the GTM technique: radioactivity uniformity within a region. This assumption may be violated in human imaging. Future studies will address this and will examine varying levels of amyloid and tau burden and cortical atrophy.

Investigating Low-Dose Image Quality in Whole-Body Pediatric 18F-FDG Scans Using Time-of-Flight PET/MRI.

In this study, we investigated the diagnostic performance of whole-body 18F-FDG imaging using a PET/MRI scanner with time-of-flight capability for low-dose clinical imaging of pediatric patients. In addition to clinically acquired image data using a dosing regimen of 3.7 MBq/kg, images from simulated low-dose regimens (1.9-0.41 MBq/kg) were evaluated using several metrics: SUV quantitation, qualitative image quality, and lesion detectability. Methods: Low-dose images were generated by truncating the list-mode PET data to reduce the count statistics. Changes in PET quantitation for low-dose images were assessed using volume-of-interest analysis of healthy tissue and suspected lesions. Three pediatric radiologists reviewed the image volumes without knowing the dose level. Qualitative image quality was assessed on the basis of Likert scoring. Radiologists were also asked to identify suspected lesions within the liver for PET-only and PET/MR images. Lesion detectability was measured using a receiver-operating-characteristic study and quantified using a free-response receiving-operating-characteristic (FROC) methodology to assess changes in performance for low-dose images. Results: Our analysis of volume-of-interest quantitation showed that SUVs remain stable down to ⅓ dose (1.2 MBq/kg). Likert scoring of PET/MR images showed no noticeable trend with dose level; however, scores of PET-only images were lower for low-dose scans, with a 12% reduction for ⅓-dose images compared with full-dose images. There was minimal change in total lesion count for different dose levels; however, all 3 readers had an increase in false-negatives for ⅓-dose images compared with full-dose images. Using the FROC methodology to quantify lesion-detection performance for human observers, no significant differences were observed for the 3 dosing levels when using the averaged reader data (all P values > 0.103). For all readers, the FROC performance was higher for PET/MRI than for PET alone. Conclusion: Reductions to the lowest recommended pediatric dosing regimens are possible when using PET/MRI. The data suggest that the administered dose can be decreased to 2.46 MBq/kg, a 33% reduction in PET activity, with no degradation in image quality, leading to a corresponding reduction in absorbed dose.

Evaluation of PET quantitation accuracy among multiple discovery IQ PET/CT systems via NEMA image quality test

IntroductionQuantitative imaging biomarkers are becoming usual in oncology for assessing therapy response. The harmonization of image quantitation reporting has become of utmost importance due to the multi-center trials increase. The NEMA image quality test is often considered for the evaluation of quantitation and is more accurate with a radioactive solid phantom that reduces variability. The goal of this project is to determine the level of variability among imaging centers if acquisition and imaging protocol parameters are left to the center’s preference while all other parameters are fixed including the scanner type.MethodsA NEMA-IQ phantom filled with radioactive 68Ge solid resin was imaged in five clinical sites throughout Europe. Sites reconstructed data with OSEM and BSREM algorithms applying the sites’ clinical parameters. Images were analyzed according with the NEMA-NU2-2012 standard using the manufacturer-provided NEMA tools to calculate contrast recovery (CR) and background variability (BV) for each sphere and the lung error (LE) estimation. In addition, a 18F-filled NEMA-IQ phantom was also evaluated to obtain a gauge for variability among centers when the sites were provided with identical specific instructions for acquisition and reconstruction protocol (the aggregate of data from 12 additional sites is presented).ResultsThe data using the 68Ge solid phantom showed no statistical differences among different sites, proving a very good reproducibility among the PET center models even if dispersion of data is higher with OSEM compared to BSREM. Furthermore, BSREM shows better CR and comparable BV, while LE is slightly reduced. Two centers exhibit significant differences in CR and BV values for the 18F NEMA NU2-2012 experiments; these outlier results are explained.ConclusionThe same PET system type from the various sites produced similar quantitative results, despite allowing each site to choose their clinical protocols with no restriction on data acquisition and reconstruction parameters. BSREM leads to lower dispersion of quantitative data among different sites. A solid radioactive phantom may be recommended to qualify the sites to perform quantitative imaging.

Improving PET/MR brain quantitation with template-enhanced ZTE

PurposeThe impact of MR-based attenuation correction on PET quantitation accuracy is an ongoing cause of concern for advanced brain research with PET/MR. The purpose of this study was to evaluate a new, template-enhanced zero-echo-time attenuation correction method for PET/MR scanners. Methods30 subjects underwent a clinically-indicated 18F-FDG-PET/CT, followed by PET/MR on a GE SIGNA PET/MR. For each patient, a 42-s zero echo time (ZTE) sequence was used to generate two attenuation maps: one with the standard ZTE segmentation-based method; and another with a modification of the method, wherein pre-registered anatomical templates and CT data were used to enhance the segmentation. CT data, was used as gold standard. Reconstructed PET images were qualified visually and quantified in 68 volumes-of-interest using a standardized brain atlas. ResultsAttenuation maps were successfully generated in all cases, without manual intervention or parameter tuning. One patient was excluded from the quantitative analysis due to the presence of multiple brain metastases. The PET bias with template-enhanced ZTE attenuation correction was measured to be −0.9% ± 0.9%, compared with −1.4% ± 1.1% with regular ZTE attenuation correction. In terms of absolute bias, the new method yielded 1.1% ± 0.7%, compared with 1.6% ± 0.9% with regular ZTE. Statistically significant bias reduction was obtained in the frontal region (from −2.0% to −1.0%), temporal (from −1.2% to −0.2%), parietal (from −1.9% to −1.1%), occipital (from −2.0% to −1.1%) and insula (from −1.4% to −1.1%). ConclusionThese results indicate that the co-registration of pre-recorded anatomical templates to ZTE data is feasible in clinical practice and can be effectively used to improve the performance of segmentation-based attenuation correction.

Technical Note: Deep learning based MRAC using rapid ultrashort echo time imaging.

In this study, we explore the feasibility of a novel framework for MR-based attenuation correction for PET/MR imaging based on deep learning via convolutional neural networks, which enables fully automated and robust estimation of a pseudo CT image based on ultrashort echo time (UTE), fat, and water images obtained by a rapid MR acquisition. MR images for MRAC are acquired using dual echo ramped hybrid encoding (dRHE), where both UTE and out-of-phase echo images are obtained within a short single acquisition (35s). Tissue labeling of air, soft tissue, and bone in the UTE image is accomplished via a deep learning network that was pre-trained with T1-weighted MR images. UTE images are used as input to the network, which was trained using labels derived from co-registered CT images. The tissue labels estimated by deep learning are refined by a conditional random field based correction. The soft tissue labels are further separated into fat and water components using the two-point Dixon method. The estimated bone, air, fat, and water images are then assigned appropriate Hounsfield units, resulting in a pseudo CT image for PET attenuation correction. To evaluate the proposed MRAC method, PET/MR imaging of the head was performed on eight human subjects, where Dice similarity coefficients of the estimated tissue labels and relative PET errors were evaluated through comparison to a registered CT image. Dice coefficients for air (within the head), soft tissue, and bone labels were 0.76±0.03, 0.96±0.006, and 0.88±0.01. In PET quantitation, the proposed MRAC method produced relative PET errors less than 1% within most brain regions. The proposed MRAC method utilizing deep learning with transfer learning and an efficient dRHE acquisition enables reliable PET quantitation with accurate and rapid pseudo CT generation.

Technical Note: Adapting a GE SIGNA PET/MR scanner for radiotherapy.

Simultaneous collection of PET and MR data for radiotherapy purposes are useful for, for example, target definition and dose escalations. However, a prerequisite for using PET/MR in the radiotherapy workflow is the ability to image the patient in treatment position. The aim of this work was to adapt a GE SIGNA PET/MR scanner to image patients for radiotherapy treatment planning and evaluate the impact on signal-to-noise (SNR) of the MR images, and the accuracy of the PET attenuation correction. A flat tabletop and a coil holder were developed to image patients in the treatment position, avoid patient contour deformation, and facilitate attenuation correction of flex coils. Attenuation corrections for the developed hardware and an anterior array flex coil were also measured and implemented to the PET/MR system to minimize PET quantitation errors. The reduction of SNR in the MR images due to the added distance between the coils and the patient was evaluated using a large homogenous saline-doped water phantom, and the activity quantitation errors in PET imaging were evaluated with and without the developed attenuation corrections. We showed that the activity quantitation errors in PET imaging were within ±5% when correcting for attenuation of the flat tabletop, coil holder, and flex coil. The SNR of the MRI images were reduced to 74% using the tabletop, and 66% using the tabletop and coil holders. We present a tabletop and coil holder for an anterior array coil to be used with a GE SIGNA PET/MR scanner, for scanning patients in the radiotherapy work flow. Implementing attenuation correction of the added hardware from the radiotherapy setup leads to acceptable PET image quantitation. The drop in SNR in MR images may require adjustment of the imaging protocols.

Issues in quantification of registered respiratory gated PET/CT in the lung

PET/CT quantification of lung tissue is limited by several difficulties: the lung density and local volume changes during respiration, the anatomical mismatch between PET and CT and the relative contributions of tissue, air and blood to the PET signal (the tissue fraction effect). Air fraction correction (AFC) has been shown to improve PET image quantification in the lungs. Methods to correct for the movement and anatomical mismatch involve respiratory gating and image registration techniques. While conventional registration methods only account for spatial mismatch, the Jacobian determinant of the deformable registration transformation field can be used to estimate local volume changes and could therefore potentially be used to correct (i.e. Jacobian Correction, JC) the PET signal for changes in concentration due to local volume changes. This work aims to investigate the relationship between variations in the lung due to respiration, specifically density, tracer concentration and local volume changes. In particular, we study the effect of AFC and JC on PET quantitation after registration of respiratory gated PET/CT patient data. Six patients suffering from lung cancer with solitary pulmonary nodules underwent F-FDG PET/cine-CT. The PET data were gated into six respiratory gates using displacement gating based on a real-time position management (RPM) signal and reconstructed with matched gated CT. The PET tracer concentration and tissue density were extracted from registered gated PET and CT images before and after corrections (AFC or JC) and compared to the values from the reference images. Before correction, we observed a linear correlation between the PET tracer concentration values and density. Across all gates and patients, the maximum relative change in PET tracer concentration before (after) AFC was found to be 16.2% (4.1%) and the maximum relative change in tissue density and PET tracer concentration before (after) JC was found to be 17.1% (5.5%) and 16.2% (6.8%) respectively. Overall our results show that both AFC or JC largely explain the observed changes in PET tracer activity over the respiratory cycle. We also speculate that a second order effect is related to change in fluid content but this needs further investigation. Consequently, either AFC or JC is recommended when combining lung PET images from different gates to reduce noise.

PET Imaging Stability Measurements During Simultaneous Pulsing of Aggressive MR Sequences on the SIGNA PET/MR System.

The recent introduction of simultaneous whole-body PET/MR scanners has enabled new research taking advantage of the complementary information obtainable with PET and MRI. One such application is kinetic modeling, which requires high levels of PET quantitative stability. To accomplish the required PET stability levels, the PET subsystem must be sufficiently isolated from the effects of MR activity. Performance measurements have previously been published, demonstrating sufficient PET stability in the presence of MR pulsing for typical clinical use; however, PET stability during radiofrequency (RF)-intensive and gradient-intensive sequences has not previously been evaluated for a clinical whole-body scanner. In this work, PET stability of the GE SIGNA PET/MR was examined during simultaneous scanning of aggressive MR pulse sequences. Methods: PET performance tests were acquired with MR idle and during simultaneous MR pulsing. Recent system improvements mitigating RF interference and gain variation were used. A fast recovery fast spin echo MR sequence was selected for high RF power, and an echo planar imaging sequence was selected for its high heat-inducing gradients. Measurements were performed to determine PET stability under varying MR conditions using the following metrics: sensitivity, scatter fraction, contrast recovery, uniformity, count rate performance, and image quantitation. A final PET quantitative stability assessment for simultaneous PET scanning during functional MRI studies was performed with a spiral in-and-out gradient echo sequence. Results: Quantitation stability of a 68Ge flood phantom was demonstrated within 0.34%. Normalized sensitivity was stable during simultaneous scanning within 0.3%. Scatter fraction measured with a 68Ge line source in the scatter phantom was stable within the range of 40.4%-40.6%. Contrast recovery and uniformity were comparable for PET images acquired simultaneously with multiple MR conditions. Peak noise equivalent count rate was 224 kcps at an effective activity concentration of 18.6 kBq/mL, and the count rate curves and scatter fraction curve were consistent for the alternating MR pulsing states. A final test demonstrated quantitative stability during a spiral functional MRI sequence. Conclusion: PET stability metrics demonstrated that PET quantitation was not affected during simultaneous aggressive MRI. This stability enables demanding applications such as kinetic modeling.

QUANTITATIVE DISEASE PHENOTYPING BY SINGLE-TIME-POINT VOXEL-BASED AMYLOID PET DIFFERENTIATES AMYLOID-BETA ACCUMULATOR SUBTYPES

There is considerable interest in characterizing subgroups of patients in the earliest/preclinical disease stage, for therapeutic intervention in AD. Amyloid-beta (Abeta) early-accumulators, defined as subjects with abnormal CSF Abeta-42 but without global amyloid PET positivity present (CSF+/PET-), have been recently found (Palmqvist et al., Brain 2016) to accumulate Abeta in the brain faster than non-accumulators (CSF-/PET-), and at a similar rate as late-accumulators (CSF+/PET+). We have previously developed a fully automated amyloid PET quantitation method for calculating voxel-based-SUVR using PET in conjunction with MRI, for improved localization of deposition, and enhanced performance for identifying subjects with early disease (Mikhno et al., AAIC 2015; HAI 2016). The aim of the present study was to assess the ability of the voxel-based quantitation to differentiate accumulator subgroups in non-demented individuals, with a single integrated measure, but without the need for an invasive lumbar puncture. A total of 205 non-demented subjects (not used for training) were included from the ADNI-GO/ADNI2 cohort. [18F]florbetapir PET amyloid positivity status was established with syngo. PET Amyloid Plaque (sPAP, cutoff >1.12), a region-based quantitation method approved for clinical use. CSF amyloid positivity was established using an Abeta-42 cutoff of 192 ng/l +/- 5% to exclude borderline cases (Palmqvist 2016), and the median batch value used to further reduce variability. Voxel-based-SUVRs from corresponding PET/T1 MRI scan pairs were assessed for differences and discrimination between early-accumulator (CSF+/PET-), late-accumulator (CSF+/PET+), and non-accumulator (CSF-/PET-) subgroups. 28 early-, 83 late-, and 94 non-accumulator subjects were analyzed. Receiver operating characteristic area under the curve (AUC) was 0.967 (non- vs. late-accumulators, two-tailed t-test p=2.9e-35), 0.907 (early- vs. late-accumulators, p=3.2e-11), and 0.660 (non- vs. early-accumulators, p=0.0036). Voxel-based-SUVR showed significant group differences and high accuracy for separating early-accumulators (CSF+/PET-) and late-accumulators (CSF+/PET+), as well as late- and non-accumulators (CSF-/PET-). To our knowledge, this is the first study to show a significant difference between early- and non-accumulators, with a single-time-point integrated SUVR measure, and without the need for training on CSF data. Use of an integrated quantitative phenotype may have potential applications in disease understanding and trial enrichment.

Generalized PSF modeling for optimized quantitation in PET imaging

Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitions with modern commercial PET systems. In the context of oncologic liver FDG PET imaging, we generated 200 noisy datasets per image-set (with clinically realistic noise levels) using an XCAT anthropomorphic phantom with liver tumours of varying sizes. These were subsequently reconstructed using the OS-EM algorithm with varying PSF modelled kernels. We focused on quantitation of both SUVmean and SUVmax, including assessment of contrast recovery coefficients, as well as noise-bias characteristics (including both image roughness and coefficient of-variability), for different tumours/iterations/PSF kernels. It was observed that overestimated PSF yielded more accurate contrast recovery for a range of tumours, and typically improved quantitative performance. For a clinically reasonable number of iterations, edge enhancement due to PSF modeling (especially due to over-estimated PSF) was in fact seen to lower SUVmean bias in small tumours. Overall, the results indicate that exactly matched PSF modeling does not offer optimized PET quantitation, and that PSF overestimation may provide enhanced SUV quantitation. Furthermore, generalized PSF modeling may provide a valuable approach for quantitative tasks such as treatment-response assessment and prognostication.

The effect of respiratory induced density variations on non-TOF PET quantitation in the lung

Accurate PET quantitation requires a matched attenuation map. Obtaining matched CT attenuation maps in the thorax is difficult due to the respiratory cycle which causes both motion and density changes. Unlike with motion, little attention has been given to the effects of density changes in the lung on PET quantitation. This work aims to explore the extent of the errors caused by pulmonary density attenuation map mismatch on dynamic and static parameter estimates. Dynamic XCAT phantoms were utilised using clinically relevant 18F-FDG and 18F-FMISO time activity curves for all organs within the thorax to estimate the expected parameter errors. The simulations were then validated with PET data from 5 patients suffering from idiopathic pulmonary fibrosis who underwent PET/Cine-CT. The PET data were reconstructed with three gates obtained from the Cine-CT and the average Cine-CT. The lung TACs clearly displayed differences between true and measured curves with error depending on global activity distribution at the time of measurement. The density errors from using a mismatched attenuation map were found to have a considerable impact on PET quantitative accuracy. Maximum errors due to density mismatch were found to be as high as 25% in the XCAT simulation. Differences in patient derived kinetic parameter estimates and static concentration between the extreme gates were found to be as high as 31% and 14%, respectively. Overall our results show that respiratory associated density errors in the attenuation map affect quantitation throughout the lung, not just regions near boundaries. The extent of this error is dependent on the activity distribution in the thorax and hence on the tracer and time of acquisition. Consequently there may be a significant impact on estimated kinetic parameters throughout the lung.

Automated Spatial Brain Normalization and Hindbrain White Matter Reference Tissue Give Improved [18F]-Florbetaben PET Quantitation in Alzheimer's Model Mice

Preclinical PET studies of β-amyloid (Aβ) accumulation are of growing importance, but comparisons between research sites require standardized and optimized methods for quantitation. Therefore, we aimed to evaluate systematically the (1) impact of an automated algorithm for spatial brain normalization, and (2) intensity scaling methods of different reference regions for Aβ-PET in a large dataset of transgenic mice. PS2APP mice in a 6 week longitudinal setting (N = 37) and another set of PS2APP mice at a histologically assessed narrow range of Aβ burden (N = 40) were investigated by [18F]-florbetaben PET. Manual spatial normalization by three readers at different training levels was performed prior to application of an automated brain spatial normalization and inter-reader agreement was assessed by Fleiss Kappa (κ). For this method the impact of templates at different pathology stages was investigated. Four different reference regions on brain uptake normalization were used to calculate frontal cortical standardized uptake value ratios (SUVRCTX∕REF), relative to raw SUVCTX. Results were compared on the basis of longitudinal stability (Cohen's d), and in reference to gold standard histopathological quantitation (Pearson's R). Application of an automated brain spatial normalization resulted in nearly perfect agreement (all κ≥0.99) between different readers, with constant or improved correlation with histology. Templates based on inappropriate pathology stage resulted in up to 2.9% systematic bias for SUVRCTX∕REF. All SUVRCTX∕REF methods performed better than SUVCTX both with regard to longitudinal stability (d≥1.21 vs. d = 0.23) and histological gold standard agreement (R≥0.66 vs. R≥0.31). Voxel-wise analysis suggested a physiologically implausible longitudinal decrease by global mean scaling. The hindbrain white matter reference (Rmean = 0.75) was slightly superior to the brainstem (Rmean = 0.74) and the cerebellum (Rmean = 0.73). Automated brain normalization with reference region templates presents an excellent method to avoid the inter-reader variability in preclinical Aβ-PET scans. Intracerebral reference regions lacking Aβ pathology serve for precise longitudinal in vivo quantification of [18F]-florbetaben PET. Hindbrain white matter reference performed best when considering the composite of quality criteria.

Associations of automated voxel-based amyloid PET quantitation with regional SUVR, CSF, memory, and in combination with ApoE genotype for early Alzheimer's disease detection

Associations of automated voxel-based amyloid PET quantitation with regional SUVR, CSF, memory, and in combination with ApoE genotype for early Alzheimer's disease detection

PET imaging with the non-pure positron emitters: 55Co, 86Y and 124I

PET/CT with non-pure positron emitters is a highly valuable tool in immuno-PET and for pretherapeutic dosimetry. However, imaging is complicated by prompt gamma coincidences (PGCs) that add an undesired background activity to the images. Time-of-flight (TOF) reconstruction improves lesion detectability in 18F-PET and can potentially also improve the signal-to-noise ratio in images acquired with non-pure positron emitters. Using the GE Discovery 690 PET/CT system, we evaluated the image quality with 55Co, 86Y and 124I, and the effect of PGC-correction and TOF-reconstruction on image quality and quantitation in a series of phantom studies. PET image quality and quantitation for all isotopes were significantly affected by PGCs. The effect was most severe with 86Y, and less, but comparable, with 55Co and 124I. PGC-correction improved the image quality and the quantitation accuracy dramatically for all isotopes, especially when the activity was limited to a few hot lesions in a warm background. In imaging situations, where high levels of activity were present in the background, activity concentrations were overestimated. TOF-reconstruction improved image quality in isolated lesions but worsened the accuracy of quantitation and uniformity in homogeneous activity distributions. Better modelling of PGCs in the scatter correction can potentially improve the situation.

Evaluation of an Atlas-Based PET Head Attenuation Correction Using PET/CT &amp; MR Patient Data

The goal of this study was to compare MR-based PET patient attenuation correction (AC) to CT-based AC in the head using clinical whole-body FDG-PET patient data obtained from a tri-modality PET/CT & MR setup. The MR-based AC utilizes an atlas-based approach, registering the patient's MR images to a CT-based atlas, producing `pseudoCT' images. Thirteen clinical whole-body FDG patients were included in this study. PET mean activity concentration values were measured and compared in six ~ 15 ml volumes-of-interest throughout the brain tissue. The AC methods compared to CT-based AC were segmentation of the CT (air, fat, soft tissue) and atlas-based MR-AC. Results: PET activity concentration was systematically under-estimated on average by 1.32 kBq/ml (4.9%) when using the segmented CT-based AC, mainly due to lack of attenuation correction for skull bone. Using the atlas-based method, the error was reduced to 0.03 kBq/ml (0.2%) on average. PET image visualization demonstrated spatial variations in activity concentration accuracy induced by the AC methods that were consistent with the approximations in each method. Conclusion: The results demonstrate that the atlas-based AC in the head provides adequate PET quantitation and image quality as compared to methods that do not account for bone.

Ultra-low dose CT attenuation correction for PET/CT

A challenge for positron emission tomography/computed tomography (PET/CT) quantitation is patient respiratory motion, which can cause an underestimation of lesion activity uptake and an overestimation of lesion volume. Several respiratory motion correction methods benefit from longer duration CT scans that are phase matched with PET scans. However, even with the currently available, lowest dose CT techniques, extended duration cine CT scans impart a substantially high radiation dose. This study evaluates methods designed to reduce CT radiation dose in PET/CT scanning. We investigated selected combinations of dose reduced acquisition and noise suppression methods that take advantage of the reduced requirement of CT for PET attenuation correction (AC). These include reducing CT tube current, optimizing CT tube voltage, adding filtration, CT sinogram smoothing and clipping. We explored the impact of these methods on PET quantitation via simulations on different digital phantoms. CT tube current can be reduced much lower for AC than that in low dose CT protocols. Spectra that are higher energy and narrower are generally more dose efficient with respect to PET image quality. Sinogram smoothing could be used to compensate for the increased noise and artifacts at radiation dose reduced CT images, which allows for a further reduction of CT dose with no penalty for PET image quantitation. When CT is not used for diagnostic and anatomical localization purposes, we showed that ultra-low dose CT for PET/CT is feasible. The significant dose reduction strategies proposed here could enable respiratory motion compensation methods that require extended duration CT scans and reduce radiation exposure in general for all PET/CT imaging.