Partial volume correction of brain PET studies using iterative deconvolution in combination with HYPR denoising

Background: Accurate quantification of PET studies depends on the spatial resolution of the PET data. The commonly limited PET resolution results in partial volume effects (PVE). Iterative deconvolution methods (IDM) have been proposed as a means to correct for PVE. IDM improves spatial resolution of PET studies without the need for structural information (e.g. MR scans). On the other hand, deconvolution also increases noise, which results in lower signal-to-noise ratios (SNR). The aim of this study was to implement IDM in combination with HighlY constrained back-PRojection (HYPR) denoising to mitigate poor SNR properties of conventional IDM.Methods: An anthropomorphic Hoffman brain phantom was filled with an [F-18]FDG solution of similar to 25 kBq mL(-1) and scanned for 30 min on a Philips Ingenuity TF PET/CT scanner (Philips, Cleveland, USA) using a dynamic brain protocol with various frame durations ranging from 10 to 300 s. Van Cittert IDM was used for PVC of the scans. In addition, HYPR was used to improve SNR of the dynamic PET images, applying it both before and/or after IDM. The Hoffman phantom dataset was used to optimise IDM parameters (number of iterations, type of algorithm, with/without HYPR) and the order of HYPR implementation based on the best average agreement of measured and actual activity concentrations in the regions. Next, dynamic [C-11]flumazenil (five healthy subjects) and [C-11]PIB (four healthy subjects and four patients with Alzheimer's disease) scans were used to assess the impact of IDM with and without HYPR on plasma input-derived distribution volumes (V-T) across various regions of the brain.Results: In the case of [C-11]flumazenil scans, Hypr-IDM-Hypr showed an increase of 5 to 20% in the regional V-T whereas a 0 to 10% increase or decrease was seen in the case of [C-11]PIB depending on the volume of interest or type of subject (healthy or patient). References for these comparisons were the V(T)s from the PVE-uncorrected scans.Conclusions: IDM improved quantitative accuracy of measured activity concentrations. Moreover, the use of IDM in combination with HYPR (Hypr-IDM-Hypr) was able to correct for PVE without increasing noise.</p

Model selection criteria for dynamic brain PET studies

BACKGROUND: Several criteria exist to identify the optimal model for quantification of tracer kinetics. The purpose of this study was to evaluate the correspondence in kinetic model preference identification for brain PET studies among five model selection criteria: Akaike Information Criterion (AIC), AIC unbiased (AICC), model selection criterion (MSC), Schwartz Criterion (SC), and F-test. MATERIALS AND METHODS: Six tracers were evaluated: [11C]FMZ, [11C]GMOM, [11C]PK11195, [11C]Raclopride, [18F]FDG, and [11C]PHT, including data from five subjects per tracer. Time activity curves (TACs) were analysed using six plasma input models: reversible single-tissue model (1T2k), irreversible two-tissue model (2T3k), and reversible two-tissue model (2T4k), all with and without blood volume fraction parameter (V B). For each tracer and criterion, the percentage of TACs preferring a certain model was calculated. RESULTS: For all radiotracers, strong agreement was seen across the model selection criteria. The F-test was considered as the reference, as it is a frequently used hypothesis test. The F-test confirmed the AIC preferred model in 87% of all cases. The strongest (but minimal) disagreement across regional TACs was found when comparing AIC with AICC. Despite these regional discrepancies, same preferred kinetic model was obtained using all criteria, with an exception of one FMZ subject. CONCLUSION: In conclusion, all five model selection criteria resulted in similar conclusions with only minor differences that did not affect overall model selection

Validation and test-retest repeatability performance of parametric methods for [11C]UCB-J PET

[(11)C]UCB-J is a PET radioligand that binds to the presynaptic vesicle glycoprotein 2A. Therefore, [(11)C]UCB-J PET may serve as an in vivo marker of synaptic integrity. The main objective of this study was to evaluate the quantitative accuracy and the 28-day test–retest repeatability (TRT) of various parametric quantitative methods for dynamic [(11)C]UCB-J studies in Alzheimer’s disease (AD) patients and healthy controls (HC). Eight HCs and seven AD patients underwent two 60-min dynamic [(11)C]UCB-J PET scans with arterial sampling over a 28-day interval. Several plasma-input based and reference-region based parametric methods were used to generate parametric images using metabolite corrected plasma activity as input function or white matter semi-ovale as reference region. Different parametric outcomes were compared regionally with corresponding non-linear regression (NLR) estimates. Furthermore, the 28-day TRT was assessed for all parametric methods. Spectral analysis (SA) and Logan graphical analysis showed high correlations with NLR estimates. Receptor parametric mapping (RPM) and simplified reference tissue model 2 (SRTM2) BP(ND), and reference Logan (RLogan) distribution volume ratio (DVR) regional estimates correlated well with plasma-input derived DVR and SRTM BP(ND). Among the multilinear reference tissue model (MRTM) methods, MRTM1 had the best correspondence with DVR and SRTM BP(ND). Among the parametric methods evaluated, spectral analysis (SA) and SRTM2 were the best plasma-input and reference tissue methods, respectively, to obtain quantitatively accurate and repeatable parametric images for dynamic [(11)C]UCB-J PET. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13550-021-00874-8

Case Reports1. A Late Presentation of Loeys-Dietz Syndrome: Beware of TGFβ Receptor Mutations in Benign Joint Hypermobility

Background: Thoracic aortic aneurysms (TAA) and dissections are not uncommon causes of sudden death in young adults. Loeys-Dietz syndrome (LDS) is a rare, recently described, autosomal dominant, connective tissue disease characterized by aggressive arterial aneurysms, resulting from mutations in the transforming growth factor beta (TGFβ) receptor genes TGFBR1 and TGFBR2. Mean age at death is 26.1 years, most often due to aortic dissection. We report an unusually late presentation of LDS, diagnosed following elective surgery in a female with a long history of joint hypermobility. Methods: A 51-year-old Caucasian lady complained of chest pain and headache following a dural leak from spinal anaesthesia for an elective ankle arthroscopy. CT scan and echocardiography demonstrated a dilated aortic root and significant aortic regurgitation. MRA demonstrated aortic tortuosity, an infrarenal aortic aneurysm and aneurysms in the left renal and right internal mammary arteries. She underwent aortic root repair and aortic valve replacement. She had a background of long-standing joint pains secondary to hypermobility, easy bruising, unusual fracture susceptibility and mild bronchiectasis. She had one healthy child age 32, after which she suffered a uterine prolapse. Examination revealed mild Marfanoid features. Uvula, skin and ophthalmological examination was normal. Results: Fibrillin-1 testing for Marfan syndrome (MFS) was negative. Detection of a c.1270G > C (p.Gly424Arg) TGFBR2 mutation confirmed the diagnosis of LDS. Losartan was started for vascular protection. Conclusions: LDS is a severe inherited vasculopathy that usually presents in childhood. It is characterized by aortic root dilatation and ascending aneurysms. There is a higher risk of aortic dissection compared with MFS. Clinical features overlap with MFS and Ehlers Danlos syndrome Type IV, but differentiating dysmorphogenic features include ocular hypertelorism, bifid uvula and cleft palate. Echocardiography and MRA or CT scanning from head to pelvis is recommended to establish the extent of vascular involvement. Management involves early surgical intervention, including early valve-sparing aortic root replacement, genetic counselling and close monitoring in pregnancy. Despite being caused by loss of function mutations in either TGFβ receptor, paradoxical activation of TGFβ signalling is seen, suggesting that TGFβ antagonism may confer disease modifying effects similar to those observed in MFS. TGFβ antagonism can be achieved with angiotensin antagonists, such as Losartan, which is able to delay aortic aneurysm development in preclinical models and in patients with MFS. Our case emphasizes the importance of timely recognition of vasculopathy syndromes in patients with hypermobility and the need for early surgical intervention. It also highlights their heterogeneity and the potential for late presentation. Disclosures: The authors have declared no conflicts of interes

The water-perfusable tissue fraction of colorectal cancer metastases is increased by the selective PDGF-receptor inhibitor imatinib but not the IL-1 receptor antagonist anakinra, a study using serial dynamic 15O-water PET.

High interstitial fluid pressure (IFP) in colorectal cancer metastases may decrease the uptake and, thus, the effects of anti-tumor drugs. Imatinib, a selective inhibitor of PDGF receptors, and anakinra, an interleukin-1 receptor antagonist, respectively, increase drug uptake and/or decrease IFP in preclinical models of carcinoma. Drug-induced decrease in IFP in human metastases has not been objectively shown, but should be reflected by an increase in water-perfusable tissue fraction (PTF) or tumor blood flow (TBF) using [(15)O]water PET/CT and kinetic modelling. Hence, the aim of this study was to assess the effects of imatinib and anakinra on PTF and TBF in colorectal cancer metastases in patients

Feasibility of a brain PET harmonization program for state of the art PET/CT systems

Purpose/Introduction: Use of brain PET studies in multicentre trials or as a quantitative imaging biomarker for (automated) differential diagnosis of neurogenerative diseases require harmonized quantitative image characteristics. In this study we explored the feasibility of developing a harmonizing performance standard for brain PET studies on state of the art PET/CT systems. Subjects &amp; Methods: In this exploratory study 6 state of the art PET/CT systems were included: Philips Gemini TF, Ingenuity TF and digital Vereos systems, 2 Siemens Biograph mCTs and a GE 710. Only systems with EARL compliant (calibration and image quality) performances were included. A 30 min dynamic PET scan of the 3D Hoffmann brain phantom was acquired. The phantom was filled with an exact known FDG stock solution (aimed at 40 kBq/mL). Each scan was reconstructedusing various clinically relevant reconstruction settings. Depending on PET/CT system reconstruction settings were varied as follows: time of flight (TOF) on/off; resolution modelling (RM) on/off, voxel size, number of iterations/subsets and Gaussian smoothing FWHM (mm). The reconstructed images were analysed using a coregistered eroded binary map of both grey (GM) and white matter (WM). GM and WM recovery coefficients were calculated as the ratio of observed and expected activity concentrations. Results: For all systems distinct differences in both GM and WM recoveries and GM/WM ratios were observed between reconstructions that did or did not apply RM. Across the various systems/reconstructions a harmonized GM recovery between 0.77 and 0.85 (RM OFF) or between 0.81 and 0.94 (RM ON) seems feasible. WM recoveries (0.25 expected) were less affected by reconstruction settings, but showed a larger difference between Philips (0.28 to 0.33) versus Siemens (0.20 to 0.20) and GE (0.22 to 0.23) systems. GM/WM ratios were 4.2 to 4.4 for the Siemens and 3.7 to 4.0 for the GE systems, while the Philips systems showed somewhat lower values of 3.1 to 3.5 mainly because of difference in WM recovery. Discussion/Conclusion: Harmonization of PET/CT system performance for brain studies appears to be feasible, in particular for GM uptake assessment. Use of RM increases GM recovery at the cost of a wider (worse) harmonized performance range. There seems to be a vendor specific difference in WM recovery. The cause of this finding (possibly scatter correction) as well as its implication for PET/CT performance harmonization needs to be further explored. Currently, more data are being collected prospectively as part of JPND granted European networks

Combatting the effect of image reconstruction settings on lymphoma [18F]FDG PET metabolic tumor volume assessment using various segmentation methods

Background: [18F]FDG PET-based metabolic tumor volume (MTV) is a promising prognostic marker for lymphoma patients. The aim of this study is to assess the sensitivity of several MTV segmentation methods to variations in image reconstruction methods and the ability of ComBat to improve MTV reproducibility. Methods: Fifty-six lesions were segmented from baseline [18F]FDG PET scans of 19 lymphoma patients. For each scan, EARL1 and EARL2 standards and locally clinically preferred reconstruction protocols were applied. Lesions were delineated using 9 semiautomatic segmentation methods: fixed threshold based on standardized uptake value (SUV), (SUV = 4, SUV = 2.5), relative threshold (41% of SUVmax [41M], 50% of SUVpeak [A50P]), majority vote-based methods that select voxels detected by at least 2 (MV2) and 3 (MV3) out of the latter 4 methods, Nestle thresholding, and methods that identify the optimal method based on SUVmax (L2A, L2B). MTVs from EARL2 and locally clinically preferred reconstructions were compared to those from EARL1. Finally, different versions of ComBat were explored to harmonize the data. Results: MTVs from the SUV4.0 method were least sensitive to the use of different reconstructions (MTV ratio: median = 1.01, interquartile range = [0.96–1.10]). After ComBat harmonization, an improved agreement of MTVs among different reconstructions was found for most segmentation methods. The regular implementation of ComBat (‘Regular ComBat’) using non-transformed distributions resulted in less accurate and precise MTV alignments than a version using log-transformed datasets (‘Log-transformed ComBat’). Conclusion: MTV depends on both segmentation method and reconstruction methods. ComBat reduces reconstruction dependent MTV variability, especially when log-transformation is used to account for the non-normal distribution of MTVs

Effect of Shortening the Scan Duration on Quantitative Accuracy of [18F]Flortaucipir Studies

Purpose: Dynamic positron emission tomography (PET) protocols allow for accurate quantification of [18F]flortaucipir-specific binding. However, dynamic acquisitions can be challenging given the long required scan duration of 130 min. The current study assessed the effect of shorter scan protocols for [18F]flortaucipir on its quantitative accuracy. Procedures: Two study cohorts with Alzheimer’s disease (AD) patients and healthy controls (HC) were included. All subjects underwent a 130-min dynamic [18F]flortaucipir PET scan consisting of two parts (0–60/80–130 min) post-injection. Arterial sampling was acquired during scanning of the first cohort only. For the second cohort, a second PET scan was acquired within 1–4 weeks of the first PET scan to assess test-retest repeatability (TRT). Three alternative time intervals were explored for the second part of the scan: 80–120, 80–110 and 80–100 min. Furthermore, the first part of the scan was also varied: 0–50, 0–40 and 0–30 min time intervals were assessed. The gap in the reference TACs was interpolated using four different interpolation methods: population-based input function 2T4k_VB (POP-IP_2T4k_VB), cubic, linear and exponential. Regional binding potential (BPND) and relative tracer delivery (R1) values estimated using simplified reference tissue model (SRTM) and/or receptor parametric mapping (RPM). The different scan protocols were compared to the respective values estimated using the original scan acquisition. In addition, TRT of the RPM BPND and R1 values estimated using the optimal shortest scan duration was also assessed. Results: RPM BPND and R1 obtained using 0–30/80–100 min scan and POP-IP_2T4k_VB reference region interpolation had an excellent correlation with the respective parametric values estimated using the original scan duration (r2 > 0.95). The TRT of RPM BPND and R1 using the shortest scan duration was − 1 ± 5 % and − 1 ± 6 % respectively. Conclusions: This study demonstrated that [18F]flortaucipir PET scan can be acquired with sufficient quantitative accuracy using only 50 min of dual-time-window scanning time

A scale space theory based motion correction approach for dynamic PET brain imaging studies

Aim/Introduction: Patient head motion poses a significant challenge when performing dynamic PET brain studies. In response, we developed a fast, robust, easily implementable and tracer-independent brain motion correction technique that facilitates accurate alignment of dynamic PET images. Materials and methods: Correction of head motion was performed using motion vectors derived by the application of Gaussian scale-space theory. A multiscale pyramid consisting of three different resolution levels (1/4x: coarse, 1/2x: medium, and 1x: fine) was applied to all image frames (37 frames, framing of 12 × 10s, 15 × 30s, 10 × 300s) of the dynamic PET sequence. Frame image alignment was initially performed at the coarse scale, which was subsequently used to initialise coregistration at the next finer scale, a process repeated until the finest possible scale, that is, the original resolution was reached. In addition, as tracer distribution changes during the dynamic frame sequence, a mutual information (MI) score was used to identify the starting frame for motion correction that is characterised by a sufficiently similar tracer distribution with the reference (last) frame. Validation of the approach was performed based on a simulated F18-fluoro-deoxy-glucose (FDG) dynamic sequence synthesised from the digital Zubal phantom. Inter-frame motion was added to each dynamic frame (except the reference frame). Total brain voxel displacement based on the added motion was constrained to 25 mm, which included both translation (0–15 mm in x, y and z) and rotation (0–0.3 rad for each Euler angle). Twenty repetitions were performed for each dataset with arbitrarily simulated motion, resulting in 20 synthetic datasets, each consisting of 36 dynamic frames (frame 37 was the reference frame). Assessment of motion correction accuracy across the dynamic sequence was performed based on the uncorrected/residual displacement remaining after the application of our algorithm. To investigate the clinical utility of the developed algorithm, three clinically cases that underwent list-mode PET imaging utilising different tracers ([18F]-fluoro-deoxy-glucose [18F]FDG [18F]-fluoroethyl-l-tyrosine [18F]FET [11C]-alpha-methyl-tryptophan [11C]AMT), each characterised by a different temporal tracer distribution were included in this study. Improvements in the Dice score coefficient (DSC) following frame alignment were evaluated as the correlation significance between the identified displacement for each frame of the clinical FDG, FET and AMT dynamic sequences. Results: Sub-millimetre accuracy (0.4 ± 0.2 mm) was achieved in the Zubal phantom for all frames after 5 min p. i., with early frames (30 s–180 s) displaying a higher residual displacement of ∼3 mm (3.2 ± 0.6 mm) due to differences in tracer distribution relative to the reference frame. The effect of these differences was also seen in MI scores; the MI plateau phase was reached at 35s p. i., 2.0 and 2.5 min p. i. At the coarse, medium and fine resolution levels, respectively. For the clinical images, a significant correlation between the identified (and corrected) displacement and the improvement in DSC score was seen in all dynamic studies (FET: R = 0.49, p < 0.001; FDG: R = 0.82, p < 0.001; AMT: R = 0.92, p < 0.001). Conclusion: The developed motion correction method is insensitive to any specific tracer distribution pattern, thus enabling improved correction of motion artefacts in a variety of clinical applications of extended PET imaging of the brain without the need for fiducial markers

Classification of negative and positive 18F-florbetapir brain PET studies in subjective cognitive decline patients using a convolutional neural network

Purpose: Visual reading of 18F-florbetapir positron emission tomography (PET) scans is used in the diagnostic process of patients with cognitive disorders for assessment of amyloid-ß (Aß) depositions. However, this can be time-consuming, and difficult in case of borderline amyloid pathology. Computer-aided pattern recognition can be helpful in this process but needs to be validated. The aim of this work was to develop, train, validate and test a convolutional neural network (CNN) for discriminating between Aß negative and positive 18F-florbetapir PET scans in patients with subjective cognitive decline (SCD). Methods: 18F-florbetapir PET images were acquired and visually assessed. The SCD cohort consisted of 133 patients from the SCIENCe cohort and 22 patients from the ADNI database. From the SCIENCe cohort, standardized uptake value ratio (SUVR) images were computed. From the ADNI database, SUVR images were extracted. 2D CNNs (axial, coronal and sagittal) were built to capture features of the scans. The SCIENCe scans were randomly divided into training and validation set (5-fold cross-validation), and the ADNI scans were used as test set. Performance was evaluated based on average accuracy, sensitivity and specificity from the cross-validation. Next, the best performing CNN was evaluated on the test set. Results: The sagittal 2D-CNN classified the SCIENCe scans with the highest average accuracy of 99% ± 2 (SD), sensitivity of 97% ± 7 and specificity of 100%. The ADNI scans were classified with a 95% accuracy, 100% sensitivity and 92.3% specificity. Conclusion: The 2D-CNN algorithm can classify Aß negative and positive 18F-florbetapir PET scans with high performance in SCD patients