Quantitative implications of the updated EARL 2019 PET-CT performance standards

Purpose Recently, updated EARL specifications (EARL2) have been developed and announced. This study aims at investigating the impact of the EARL2 specifications on the quantitative reads of clinical PET-CT studies and testing a method to enable the use of the EARL2 standards whilst still generating quantitative reads compliant with current EARL standards (EARL1). Methods Thirteen non-small cell lung cancer (NSCLC) and seventeen lymphoma PET-CT studies were used to derive four image datasets-the first dataset complying with EARL1 specifications and the second reconstructed using parameters as described in EARL2. For the third (EARL2F6) and fourth (EARL2F7) dataset in EARL2, respectively, 6 mm and 7 mm Gaussian post-filtering was applied. We compared the results of quantitative metrics (MATV, SUVmax, SUVpeak, SUVmean, TLG, and tumor-to-liver and tumor-to-blood pool ratios) obtained with these 4 datasets in 55 suspected malignant lesions using three commonly used segmentation/volume of interest (VOI) methods (MAX41, A50P, SUV4). Results We found that with EARL2 MAX41 VOI method, MATV decreases by 22%, TLG remains unchanged and SUV values increase by 23-30% depending on the specific metric used. The EARL2F7 dataset produced quantitative metrics best aligning with EARL1, with no significant differences between most of the datasets (p>0.05). Different VOI methods performed similarly with regard to SUV metrics but differences in MATV as well as TLG were observed. No significant difference between NSCLC and lymphoma cancer types was observed. Conclusions Application of EARL2 standards can result in higher SUVs, reduced MATV and slightly changed TLG values relative to EARL1. Applying a Gaussian filter to PET images reconstructed using EARL2 parameters successfully yielded EARL1 compliant data

Quantitative implications of the updated EARL 2019 PET-CT performance standards

Purpose Recently, updated EARL specifications (EARL2) have been developed and announced. This study aims at investigating the impact of the EARL2 specifications on the quantitative reads of clinical PET-CT studies and testing a method to enable the use of the EARL2 standards whilst still generating quantitative reads compliant with current EARL standards (EARL1). Methods Thirteen non-small cell lung cancer (NSCLC) and seventeen lymphoma PET-CT studies were used to derive four image datasets-the first dataset complying with EARL1 specifications and the second reconstructed using parameters as described in EARL2. For the third (EARL2F6) and fourth (EARL2F7) dataset in EARL2, respectively, 6 mm and 7 mm Gaussian post-filtering was applied. We compared the results of quantitative metrics (MATV, SUVmax, SUVpeak, SUVmean, TLG, and tumor-to-liver and tumor-to-blood pool ratios) obtained with these 4 datasets in 55 suspected malignant lesions using three commonly used segmentation/volume of interest (VOI) methods (MAX41, A50P, SUV4). Results We found that with EARL2 MAX41 VOI method, MATV decreases by 22%, TLG remains unchanged and SUV values increase by 23-30% depending on the specific metric used. The EARL2F7 dataset produced quantitative metrics best aligning with EARL1, with no significant differences between most of the datasets (p>0.05). Different VOI methods performed similarly with regard to SUV metrics but differences in MATV as well as TLG were observed. No significant difference between NSCLC and lymphoma cancer types was observed. Conclusions Application of EARL2 standards can result in higher SUVs, reduced MATV and slightly changed TLG values relative to EARL1. Applying a Gaussian filter to PET images reconstructed using EARL2 parameters successfully yielded EARL1 compliant data

Pilot study of 89Zr-bevacizumab positron emission tomography in patients with advanced non-small cell lung cancer

Background: The aim of this pilot study was to evaluate whether the uptake of 89Zr-bevacizumab in non-small cell lung cancer (NSCLC) tumors could be visualized and quantified. The correlation between tumor 89Zr-bevacizumab uptake and tumor response to antitumor therapy with a bevacizumab-based regimen was explored. Methods: Seven NSCLC patients underwent static PET scans at days 4 and 7 after injection of 36.4 ± 0.9 MBq (mean ± SD) 89Zr-bevacizumab, prior to commencing carboplatin-paclitaxel-bevacizumab chemotherapy (CPB). Overall survival (OS) and progression-free survival (PFS) to CPB followed by bevacizumab maintenance therapy was correlated to tumor tracer uptake, quantified using peak standardized uptake values (SUVpeak). Results: Zr-bevacizumab uptake (SUVpeak) was approximately four times higher in tumor tissues (primary tumor and metastases) than in non-tumor tissues (healthy muscle, lung, and fat) on days 4 and 7. A positive trend but no significant correlation could be found between SUVpeak and OS or PFS. Conclusions: This pilot study shows that 89Zr-bevacizumab PET imaging in NSCLC is feasible. Further investigation to validate this technique as a predictive biomarker for selecting patients for bevacizumab treatment is warranted

Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan

Abstract Background Image harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial. Method Hoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using “Hoffman 3D brain Analysis tool,” indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method’s robustness against typical dose-calibrator-based errors was assessed. Results The EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040–0.012), and Contrast SD (0.14–0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR. Conclusion Harmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy

Lessons learned about [F-18]-AV-1451 off-target binding from an autopsy-confirmed Parkinson’s case

Abstract [F-18]-AV-1451 is a novel positron emission tomography (PET) tracer with high affinity to neurofibrillary tau pathology in Alzheimer’s disease (AD). PET studies have shown increased tracer retention in patients clinically diagnosed with dementia of AD type and mild cognitive impairment in regions that are known to contain tau lesions. In vivo uptake has also consistently been observed in midbrain, basal ganglia and choroid plexus in elderly individuals regardless of their clinical diagnosis, including clinically normal whose brains are not expected to harbor tau pathology in those areas. We and others have shown that [F-18]-AV-1451 exhibits off-target binding to neuromelanin, melanin and blood products on postmortem material; and this is important for the correct interpretation of PET images. In the present study, we further investigated [F-18]-AV-1451 off-target binding in the first autopsy-confirmed Parkinson’s disease (PD) subject who underwent antemortem PET imaging. The PET scan showed elevated [F-18]-AV-1451 retention predominantly in inferior temporal cortex, basal ganglia, midbrain and choroid plexus. Neuropathologic examination confirmed the PD diagnosis. Phosphor screen and high resolution autoradiography failed to show detectable [F-18]-AV-1451 binding in multiple brain regions examined with the exception of neuromelanin-containing neurons in the substantia nigra, leptomeningeal melanocytes adjacent to ventricles and midbrain, and microhemorrhages in the occipital cortex (all reflecting off-target binding), in addition to incidental age-related neurofibrillary tangles in the entorhinal cortex. Additional legacy postmortem brain samples containing basal ganglia, choroid plexus, and parenchymal hemorrhages from 20 subjects with various neuropathologic diagnoses were also included in the autoradiography experiments to better understand what [F-18]-AV-1451 in vivo positivity in those regions means. No detectable [F-18]-AV-1451 autoradiographic binding was present in the basal ganglia of the PD case or any of the other subjects. Off-target binding in postmortem choroid plexus samples was only observed in subjects harboring leptomeningeal melanocytes within the choroidal stroma. Off-target binding to parenchymal hemorrhages was noticed in postmortem material from subjects with cerebral amyloid angiopathy. The imaging-postmortem correlation analysis in this PD case reinforces the notion that [F-18]-AV-1451 has strong affinity for neurofibrillary tau pathology but also exhibits off-target binding to neuromelanin, melanin and blood components. The robust off-target in vivo retention in basal ganglia and choroid plexus, in the absence of tau deposits, meningeal melanocytes or any other identifiable binding substrate by autoradiography in the PD case reported here, also suggests that the PET signal in those regions may be influenced, at least in part, by biological or technical factors that occur in vivo and are not captured by autoradiography