Comorbid amyloid with cerebrovascular disease in domain-specific cognitive and neuropsychiatric disturbances: a cross-sectional memory clinic study

Dementia is a multifactorial disorder that is likely influenced by both Alzheimer's disease (AD) and vascular pathologies. We evaluated domain-specific cognitive and neuropsychiatric dysfunction using a two-neuroimaging biomarker construct (beta-amyloid [Aβ] and cerebrovascular disease [CeVD]). We analyzed data from 216 memory clinic participants (mean age = 75.9 ± 6.9; 56.5% female) with neuropsychological and neuropsychiatric assessments, 3T-MRI, and Aβ-PET imaging. Structural equation modeling showed that the largest Aβ (A+) effect was on memory (B = -1.50) and apathy (B = 0.26), whereas CeVD effects were largest on language (B = -1.62) and hyperactivity (B = 0.32). Group comparisons showed that the A+C+ group had greater memory impairment (B = -1.55), hyperactivity (B = 0.79), and apathy (B = 0.74) compared to A-C+; and greater language impairment (B = -1.26) compared to A+C-. These potentially additive effects of Aβ and CeVD burden underline the importance of early detection and treatment of Aβ alongside optimal control of vascular risk factors as a potential strategy in preventing cognitive and neurobehavioral impairment.

Longitudinal associations between β-amyloid and cortical thickness in mild cognitive impairment

How beta-amyloid accumulation influences brain atrophy in Alzheimer's disease remains contentious with conflicting findings. We aimed to elucidate the correlations of regional longitudinal atrophy with cross-sectional regional and global amyloid in individuals with mild cognitive impairment and no cognitive impairment. We hypothesized that greater cortical thinning over time correlated with greater amyloid deposition, particularly within Alzheimer's disease characteristic regions in mild cognitive impairment, and weaker or no correlations in those with no cognitive impairment. 45 patients with mild cognitive impairment and 12 controls underwent a cross-sectional [¹¹C]-Pittsburgh Compound B PET and two retrospective longitudinal structural imaging (follow-up: 23.65 ± 2.04 months) to assess global/regional amyloid and regional cortical thickness, respectively. Separate linear mixed models were constructed to evaluate relationships of either global or regional amyloid with regional cortical thinning longitudinally. In patients with mild cognitive impairment, regional amyloid in the right banks of the superior temporal sulcus was associated with longitudinal cortical thinning in the right medial orbitofrontal cortex (P = 0.04 after False Discovery Rate correction). In the mild cognitive impairment group, greater right banks amyloid burden and less cortical thickness in the right medial orbitofrontal cortex showed greater visual and verbal memory decline over time, which was not observed in controls. Global amyloid was not associated with longitudinal cortical thinning in any locations in either group. Our findings indicate an increasing influence of amyloid on neurodegeneration and memory along the preclinical to prodromal spectrum. Future multimodal studies that include additional biomarkers will be well-suited to delineate the interplay between various pathological processes and amyloid and memory decline, as well as clarify their additive or independent effects along the disease deterioration.

Brain atrophy and white matter hyperintensities are independently associated with plasma neurofilament light chain in an Asian cohort of cognitively impaired patients with concomitant cerebral small vessel disease

Introduction

Plasma neurofilament light chain (NfL) is a potential biomarker for neurodegeneration in Alzheimer's disease (AD), ischemic stroke, and non‐dementia cohorts with cerebral small vessel disease (CSVD). However, studies of AD in populations with high prevalence of concomitant CSVD to evaluate associations of brain atrophy, CSVD, and amyloid beta (Aβ) burden on plasma NfL are lacking.

Methods

Associations were tested between plasma NfL and brain Aβ, medial temporal lobe atrophy (MTA) as well as neuroimaging features of CSVD, including white matter hyperintensities (WMH), lacunes, and cerebral microbleeds.

Results

We found that participants with either MTA (defined as MTA score ≥2; neurodegeneration [N]+WMH−) or WMH (cut‐off for log‐transformed WMH volume at 50th percentile; N−WMH+) manifested increased plasma NfL levels. Participants with both pathologies (N+WMH+) showed the highest NfL compared to N+WMH−, N−WMH+, and N−WMH− individuals.

Discussion

Plasma NfL has potential utility in stratifying individual and combined contributions of AD pathology and CSVD to cognitive impairment.

Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions

INTRODUCTION

The classification of prostate cancer (PCa) lesions using Prostate Imaging Reporting and Data System (PI-RADS) suffers from poor inter-reader agreement. This study compared quantitative parameters or radiomic features from multiparametric magnetic resonance imaging (mpMRI) or positron emission tomography (PET), as inputs into machine learning (ML) to predict the Gleason scores (GS) of detected lesions for improved PCa lesion classification.

METHODS

20 biopsy-confirmed PCa subjects underwent imaging before radical prostatectomy. A pathologist assigned GS from tumour tissue. Two radiologists and one nuclear medicine physician delineated the lesions on the mpMR and PET images, yielding 45 lesion inputs. Seven quantitative parameters were extracted from the lesions, namely T2-weighted (T2w) image intensity, apparent diffusion coefficient (ADC), transfer constant (K^TRANS), efflux rate constant (K_ep), and extracellular volume ratio (V_e) from mpMR images, and SUV_mean and SUV_max from PET images. Eight radiomic features were selected out of 109 radiomic features from T2w, ADC and PET images. Quantitative parameters or radiomic features, with risk factors of age, prostate-specific antigen (PSA), PSA density and volume, of 45 different lesion inputs were input in different combinations into four ML models - Decision Tree (DT), Support Vector Machine (SVM), k-Nearest-Neighbour (kNN), Ensembles model (EM).

RESULTS

SUV_max yielded the highest accuracy in discriminating detected lesions. Among the 4 ML models, kNN yielded the highest accuracies of 0.929 using either quantitative parameters or radiomic features with risk factors as input.

CONCLUSIONS

ML models' performance is dependent on the input combinations and risk factors further improve ML classification accuracy.

PET image enhancement using artificial intelligence for better characterization of epilepsy lesions

INTRODUCTION

[18F]fluorodeoxyglucose ([18F]FDG) brain PET is used clinically to detect small areas of decreased uptake associated with epileptogenic lesions, e.g., Focal Cortical Dysplasias (FCD) but its performance is limited due to spatial resolution and low contrast. We aimed to develop a deep learning-based PET image enhancement method using simulated PET to improve lesion visualization.

METHODS

We created 210 numerical brain phantoms (MRI segmented into 9 regions) and assigned 10 different plausible activity values (e.g., GM/WM ratios) resulting in 2100 ground truth high quality (GT-HQ) PET phantoms. With a validated Monte-Carlo PET simulator, we then created 2100 simulated standard quality (S-SQ) [18F]FDG scans. We trained a ResNet on 80% of this dataset (10% used for validation) to learn the mapping between S-SQ and GT-HQ PET, outputting a predicted HQ (P-HQ) PET. For the remaining 10%, we assessed Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Root Mean Squared Error (RMSE) against GT-HQ PET. For GM and WM, we computed recovery coefficients (RC) and coefficient of variation (COV). We also created lesioned GT-HQ phantoms, S-SQ PET and P-HQ PET with simulated small hypometabolic lesions characteristic of FCDs. We evaluated lesion detectability on S-SQ and P-HQ PET both visually and measuring the Relative Lesion Activity (RLA, measured activity in the reduced-activity ROI over the standard-activity ROI). Lastly, we applied our previously trained ResNet on 10 clinical epilepsy PETs to predict the corresponding HQ-PET and assessed image quality and confidence metrics.

RESULTS

Compared to S-SQ PET, P-HQ PET improved PNSR, SSIM and RMSE; significatively improved GM RCs (from 0.29 ± 0.03 to 0.79 ± 0.04) and WM RCs (from 0.49 ± 0.03 to 1 ± 0.05); mean COVs were not statistically different. Visual lesion detection improved from 38 to 75%, with average RLA decreasing from 0.83 ± 0.08 to 0.67 ± 0.14. Visual quality of P-HQ clinical PET improved as well as reader confidence.

CONCLUSION

P-HQ PET showed improved image quality compared to S-SQ PET across several objective quantitative metrics and increased detectability of simulated lesions. In addition, the model generalized to clinical data. Further evaluation is required to study generalization of our method and to assess clinical performance in larger cohorts.

Evolving operational guidance and experiences for radiology and nuclear medicine facilities in response to and beyond the COVID-19 pandemic

The resulting pandemic from the novel severe acute respiratory coronavirus 2, SARS-CoV-2 (COVID-19), continues to exert a strain on worldwide health services due to the incidence of hospitalization and mortality associated with infection. The aim of clinical services throughout the period of the pandemic and likely beyond to endemic infections as the situation stabilizes is to enhance safety aspects to mitigate transmission of COVID-19 while providing a high quality of service to all patients (COVID-19 positive and negative) while still upholding excellent medical standards. In order to achieve this, new strategies of clinical service operation are essential. Researchers have published peer-reviewed reference materials such as guidelines, experiences and advice to manage the resulting issues from the unpredictable challenges presented by the pandemic. There is a range of international guidance also from professional medical organizations, including best practice and advice in order to help imaging facilities adjust their standard operating procedures and workflows in line with infection control principles. This work provides a broad review of the main sources of advice and guidelines for radiology and nuclear medicine facilities during the pandemic, and also of rapidly emerging advice and local/national experiences as facilities begin to resume previously canceled non-urgent services as well as effects on imaging research.

Comparison of the performances of machine learning and deep learning in improving the quality of low dose lung cancer PET images

PURPOSE

To compare the performances of machine learning (ML) and deep learning (DL) in improving the quality of low dose (LD) lung cancer PET images and the minimum counts required.

MATERIALS AND METHODS

33 standard dose (SD) PET images, were used to simulate LD PET images at seven-count levels of 0.25, 0.5, 1, 2, 5, 7.5 and 10 million (M) counts. Image quality transfer (IQT), a ML algorithm that uses decision tree and patch-sampling was compared to two DL networks-HighResNet (HRN) and deep-boosted regression (DBR). Supervised training was performed by training the ML and DL algorithms with matched-pair SD and LD images. Image quality evaluation and clinical lesion detection tasks were performed by three readers. Bias in 53 radiomic features, including mean SUV, was evaluated for all lesions.

RESULTS

ML- and DL-estimated images showed higher signal and smaller error than LD images with optimal image quality recovery achieved using LD down to 5 M counts. True positive rate and false discovery rate were fairly stable beyond 5 M counts for the detection of small and large true lesions. Readers rated average or higher ratings to images estimated from LD images of count levels above 5 M only, with higher confidence in detecting true lesions.

CONCLUSION

LD images with a minimum of 5 M counts (8.72 MBq for 10 min scan or 25 MBq for 3 min scan) are required for optimal clinical use of ML and DL, with slightly better but more varied performance shown by DL.

11C-Metomidate PET-CT versus adrenal vein sampling to subtype primary aldosteronism: a prospective clinical trial

OBJECTIVE

Adrenal vein sampling (AVS) is recommended to subtype primary aldosteronism, but it is technically challenging. We compared 11C-Metomidate-PET-computed tomography (PET-CT) and AVS for subtyping of primary aldosteronism.

METHODS

Patients with confirmed primary aldosteronism underwent both AVS and 11C-Metomidate PET-CT (post-dexamethasone). All results were reviewed at a multidisciplinary meeting to decide on final subtype diagnosis. Primary outcome was accuracy of PET versus AVS to diagnosis of unilateral primary aldosteronism based on post-surgical biochemical cure. Secondary outcome was accuracy of both tests to final subtype diagnosis.

RESULTS

All 25 patients recruited underwent PET and successful AVS (100%). Final diagnosis was unilateral in 22 patients, bilateral in two and indeterminate in one due to discordant lateralization. Twenty patients with unilateral primary aldosteronism underwent surgery, with 100% complete biochemical success, and 75% complete/partial clinical success. For the primary outcome, sensitivity of PET was 80% [95% confidence interval (95% CI): 56.3-94.3] and AVS was 75% (95% CI: 50.9-91.3). For the secondary outcome, sensitivity and specificity of PET was 81.9% (95% CI: 59.7-94.8) and 100% (95% CI: 15.8-100), and AVS was 68.2% (95% CI: 45.1-86.1) and 100% (95% CI: 15.8-100), respectively. Twelve out of 20 (60%) patients had both PET and AVS lateralization, four (20%) PET-only, three (15%) AVS-only, while one patient did not lateralize on PET or AVS. Post-surgery outcomes did not differ between patients identified by either test.

CONCLUSION

In our pilot study, 11C-Metomidate PET-CT performed comparably to AVS, and this should be validated in larger studies. PET identified patients with unilateral primary aldosteronism missed on AVS, and these tests could be used together to identify more patients with unilateral primary aldosteronism.

VIDEO ABSTRACT

http://links.lww.com/HJH/B918.

Cerebrovascular disease in Suspected Non-Alzheimer's Pathophysiology and cognitive decline over time

BACKGROUND

The underlying cause of cognitive decline in individuals who are positive for biomarkers of neurodegeneration (N) but negative for biomarkers of amyloid-beta (A), designated as Suspected Non-Alzheimer's Pathophysiology (SNAP), remains unclear. We evaluate whether cerebrovascular disease (CeVD) is more prevalent in those with SNAP compared to A-N- and A+N+ individuals and whether CeVD is associated with cognitive decline over time in SNAP patients.

METHODS

A total of 216 individuals from a prospective memory clinic cohort [mean (SD) age, 72.7(7.3) years, 100 women (56.5%)] were included and were diagnosed as no cognitive impairment (NCI), cognitive impairment no dementia (CIND), Alzheimer's dementia (AD) or Vascular dementia (VaD). All individuals underwent clinical evaluation and neuropsychological assessment annually for up to 5 years. [¹¹ C]-PiB or [¹⁸ F]-Flutafuranol-PET imaging was performed to ascertain amyloid-beta status. MRI was performed to assess neurodegeneration as measured by medial temporal atrophy≥2, as well as significant CeVD (sCeVD) burden, defined by cortical infarct count≥1, Fazekas-score≥2, lacune count≥2 or cerebral microbleed count≥2.

RESULTS

Of the 216 individuals, 50(23.1%) A-N+ were (SNAP), 93(43.1%) A-N-, 36(16.7%) A+N- and 37(17.1%) A+N+. A+N+ individuals were significantly older, while A+N+ and SNAP individuals were more likely to have dementia. The SNAP group had a higher prevalence of sCeVD (90.0%) compared to A-N-. Moreover, SNAP individuals with sCeVD had significantly steeper decline in global cognition compared to A-N- over 5 years (P=0.042).

CONCLUSIONS

These findings suggest that CeVD is a contributing factor to cognitive decline in SNAP. Therefore, SNAP-individuals should be carefully assessed and treated for CeVD.

The Association Between Standard Electrocardiography and Cerebral Small Vessel Disease in a Memory Clinic Study

BACKGROUND

P-wave terminal force in lead V1 (PTFV1) on electrocardiography has been associated with atrial fibrillation and ischemic stroke.

OBJECTIVE

To investigate whether PTFV1 is associated with cerebral small vessel disease (CSVD) markers and etiological subtypes of cognitive impairment and dementia.

METHODS

Participants were recruited from ongoing memory clinic study between August 2010 to January 2019. All participants underwent physical and medical evaluation along with an electrocardiography and 3 T brain magnetic resonance imaging. Participants were classified as no cognitive impairment, cognitive impairment no dementia, vascular cognitive impairment no dementia, and dementia subtypes (Alzheimer's disease and vascular dementia). Elevated PTFV1 was defined as >  4,000μV×ms and measured manually on ECG.

RESULTS

Of 408 participants, 78 (19.1%) had elevated PTFV1 (37 women [47%]; mean [SD] age, 73.8 [7.2] years). The participants with elevated PTFV1 had higher burden of lacunes, cerebral microbleeds (CMB), and cortical microinfarcts. As for the CMB location, persons with strictly deep CMB and mixed CMB had significantly higher PTFV1 than those with no CMB (p = 0.005, p = 0.007). Regardless of adjustment for cardiovascular risk factors and/or heart diseases, elevated PTFV1 was significantly associated with presence of CMB (odds ratio, 2.26; 95% CI,1.33-3.91).

CONCLUSION

Elevated PTFV1 was associated with CSVD, especially deep CMB. PTFV1 in vascular dementia was also higher compared to Alzheimer's disease. Thus, PTFV1 might be a potential surrogate marker of brain-heart connection and vascular brain damage.

Improved amyloid burden quantification with nonspecific estimates using deep learning

PURPOSE

Standardized uptake value ratio (SUVr) used to quantify amyloid-β burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we propose a novel amyloid-PET quantification approach that harnesses the intermodal image translation capability of convolutional networks to remove this undesirable source of variability.

METHODS

Paired MR and PET images exhibiting very low specific uptake were selected from a Singaporean amyloid-PET study involving 172 participants with different severities of CeVD. Two convolutional neural networks (CNN), ScaleNet and HighRes3DNet, and one conditional generative adversarial network (cGAN) were trained to map structural MR to NS PET images. NS estimates generated for all subjects using the most promising network were then subtracted from SUVr images to determine specific amyloid load only (SAβL). Associations of SAβL with various cognitive and functional test scores were then computed and compared to results using conventional SUVr.

RESULTS

Multimodal ScaleNet outperformed other networks in predicting the NS content in cortical gray matter with a mean relative error below 2%. Compared to SUVr, SAβL showed increased association with cognitive and functional test scores by up to 67%.

CONCLUSION

Removing the undesirable NS uptake from the amyloid load measurement is possible using deep learning and substantially improves its accuracy. This novel analysis approach opens a new window of opportunity for improved data modeling in Alzheimer's disease and for other neurodegenerative diseases that utilize PET imaging.

Comparison of metrics for the evaluation of medical segmentations using prostate MRI dataset

Nine previously proposed segmentation evaluation metrics, targeting medical relevance, accounting for holes, and added regions or differentiating over- and under-segmentation, were compared with 24 traditional metrics to identify those which better capture the requirements for clinical segmentation evaluation. Evaluation was first performed using 2D synthetic shapes to highlight features and pitfalls of the metrics with known ground truths (GTs) and machine segmentations (MSs). Clinical evaluation was then performed using publicly-available prostate images of 20 subjects with MSs generated by 3 different deep learning networks (DenseVNet, HighRes3DNet, and ScaleNet) and GTs drawn by 2 readers. The same readers also performed the 2D visual assessment of the MSs using a dual negative-positive grading of -5 to 5 to reflect over- and under-estimation. Nine metrics that correlated well with visual assessment were selected for further evaluation using 3 different network ranking methods - based on a single metric, normalizing the metric using 2 GTs, and ranking the network based on a metric then averaging, including leave-one-out evaluation. These metrics yielded consistent ranking with HighRes3DNet ranked first then DenseVNet and ScaleNet using all ranking methods. Relative volume difference yielded the best positivity-agreement and correlation with dual visual assessment, and thus is better for providing over- and under-estimation. Interclass Correlation yielded the strongest correlation with the absolute visual assessment (0-5). Symmetric-boundary dice consistently yielded good discrimination of the networks for all three ranking methods with relatively small variations within network. Good rank discrimination may be an additional metric feature required for better network performance evaluation.

Plasma P-tau181 to Aβ42 ratio is associated with brain amyloid burden and hippocampal atrophy in an Asian cohort of Alzheimer's disease patients with concomitant cerebrovascular disease

INTRODUCTION

There is increasing evidence that phosphorylated tau (P-tau181) is a specific biomarker for Alzheimer's disease (AD) pathology, but its potential utility in non-White patient cohorts and patients with concomitant cerebrovascular disease (CeVD) is unknown.

METHODS

Single molecule array (Simoa) measurements of plasma P-tau181, total tau, amyloid beta (Aβ)40 and Aβ42, as well as derived ratios were correlated with neuroimaging modalities indicating brain amyloid (Aβ+), hippocampal atrophy, and CeVD in a Singapore-based cohort of non-cognitively impaired (NCI; n = 43), cognitively impaired no dementia (CIND; n = 91), AD (n = 44), and vascular dementia (VaD; n = 22) subjects.

RESULTS

P-tau181/Aβ42 ratio showed the highest area under the curve (AUC) for Aβ+ (AUC = 0.889) and for discriminating between AD Aβ+ and VaD Aβ- subjects (AUC = 0.903). In addition, P-tau181/Aβ42 ratio was associated with hippocampal atrophy. None of the biomarkers was associated with CeVD.

DISCUSSION

Plasma P-tau181/Aβ42 ratio may be a noninvasive means of identifying AD with elevated brain amyloid in populations with concomitant CeVD.

Head-to-head comparison of amplified plasmonic exosome Aβ42 platform and single-molecule array immunoassay in a memory clinic cohort

BACKGROUND AND PURPOSE

Various blood biomarkers reflecting brain amyloid-β (Aβ) load have recently been proposed with promising results. However, to date, no comparative study amongst blood biomarkers has been reported. Our objective was to examine the diagnostic performance and cost effectiveness of three blood biomarkers on the same cohort.

METHODS

Using the same cohort (n = 68), the performances of the single-molecule array (Simoa) Aβ40, Aβ42, Aβ42/Aβ40 and the amplified plasmonic exosome (APEX) Aβ42 blood biomarkers were compared using amyloid positron emission tomography (PET) as the reference standard. The extent to which these blood tests can reduce the recruitment cost of clinical trials was also determined by identifying amyloid positive (Aβ+) participants.

RESULTS

Compared to Simoa biomarkers, APEX-Aβ42 showed significantly higher correlations with amyloid PET retention values and excellent diagnostic performance (sensitivity 100%, specificity 93.3%, area under the curve 0.995). When utilized for clinical trial recruitment, our simulation showed that pre-screening with blood biomarkers followed by a confirmatory amyloid PET imaging would roughly half the cost (56.8% reduction for APEX-Aβ42 and 48.6% for Simoa-Aβ42/Aβ40) compared to the situation where only PET imaging is used. Moreover, with 100% sensitivity, APEX-Aβ42 pre-screening does not increase the required number of initial participants.

CONCLUSIONS

With its high diagnostic performance, APEX is an ideal candidate for Aβ+ subject identification, monitoring and primary care screening, and could efficiently enrich clinical trials with Aβ+ participants whilst halving recruitment costs.

Brain amyloid β, cerebral small vessel disease, and cognition: A memory clinic study

OBJECTIVE

To evaluate the association between brain amyloid β (Aβ) and cerebral small vessel disease (CSVD) markers, as well as their joint effect on cognition, in a memory clinic study.

METHODS

A total of 186 individuals visiting a memory clinic, diagnosed with no cognitive impairment, cognitive impairment no dementia (CIND), Alzheimer dementia (AD), or vascular dementia were included. Brain Aβ was measured by [¹¹C] Pittsburgh compound B-PET global standardized uptake value ratio (SUVR). CSVD markers including white matter hyperintensities (WMH), lacunes, and cerebral microbleeds (CMBs) were graded on MRI. Cognition was assessed by neuropsychological testing.

RESULTS

An increase in global SUVR is associated with a decrease in Mini-Mental State Examination (MMSE) in CIND and AD, as well as a decrease in global cognition Z score in AD, independent of age, education, hippocampal volume, and markers of CSVD. A significant interaction between global SUVR and WMH was found in relation to MMSE in CIND (P for interaction: 0.009), with an increase of the effect size of Aβ (β = -6.57 [-9.62 to -3.54], p < 0.001) compared to the model without the interaction term (β = -2.91 [-4.54 to -1.29], p = 0.001).

CONCLUSION

Higher global SUVR was associated with worse cognition in CIND and AD, but was augmented by an interaction between global SUVR and WMH only in CIND. This suggests that Aβ and CSVD are independent processes with a possible synergistic effect between Aβ and WMH in individuals with CIND. There was no interaction effect between Aβ and lacunes or CMBs. Therefore, in preclinical phases of AD, WMH should be targeted as a potentially modifiable factor to prevent worsening of cognitive dysfunction.

[Telemedicine monitoring for AMD patients]

INTRODUCTION

AMD follow-up is a public health issue in developed countries due to aging of the population and medical demographics. Telemedicine may be a means of improving follow-up.

PURPOSE

To compare the agreement between telemedicine and in-person consultations in terms of indications for intravitreal injections in exudative AMD patients.

MATERIALS AND METHODS

From January 2017 to April 2017, AMD patients followed on a PRN protocol at a single center, Rennes university medical center, were included. The telemedicine evaluation was read by two anonymous experts on the basis of the medical record including visual acuity and fundus photographs. The agreement between conventional follow-up and telemedicine in terms of indications for intravitreal injections, as well as interobserver agreement, were tested with the Cohen's kappa coefficient using SAS statistical software V9.4 (SAS Institute, Cary, NC).

RESULTS

In total, 104 eyes corresponding to 57 consultations for 42 patients were analyzed. The mean age was 82.12 years (standard deviation±6.4). Recommendations for anti-VEGF were similar between the standard and telemedicine visits in 97 % of cases. The Kappa coefficient was 0.8861 [0.76; 1.00], P<0.0001 for agreement between telemedicine and in-person consultation. The Kappa coefficient was 0.8441 [0.70; 0.99], P<0.0001 for interobserver agreement. We observed 5 cases of disagreement between the two observers.

DISCUSSION

The concordance was very good in our study. The few cases of disagreement resulted mainly from poorly interpretable examinations due to poor image quality, major macular changes in patients with a prior examination, and the fact that only a single cut was analyzed.

CONCLUSION

AMD monitoring by telemedicine seems promising and reliable. This approach would allow better follow-up of patients with difficult access to care.

Bayesian Estimation of the ntPET Model in Single-Scan Competition PET Studies

This paper proposes an innovative method, named b-ntPET, for solving a competition model in PET. The model is built upon the state-of-the-art method called lp-ntPET. It consists in identifying the parameters of the PET kinetic model relative to a reference region that rule the steady state exchanges, together with the identification of four additional parameters defining a displacement curve caused by an endogenous neurotransmitter discharge, or by a competing injected drug targeting the same receptors as the PET tracer. The resolution process of lp-ntPET is however suboptimal due to the use of discretized basis functions, and is very sensitive to noise, limiting its sensitivity and accuracy. Contrary to the original method, our proposed resolution approach first estimates the probability distribution of the unknown parameters using Markov-Chain Monte-Carlo sampling, distributions from which the estimates are then inferred. In addition, and for increased robustness, the noise level is jointly estimated with the parameters of the model. Finally, the resolution is formulated in a Bayesian framework, allowing the introduction of prior knowledge on the parameters to guide the estimation process toward realistic solutions. The performance of our method was first assessed and compared head-to-head with the reference method lp-ntPET using well-controlled realistic simulated data. The results showed that the b-ntPET method is substantially more robust to noise and much more sensitive and accurate than lp-ntPET. We then applied the model to experimental animal data acquired in pharmacological challenge studies and human data with endogenous releases induced by transcranial direct current stimulation. In the drug challenge experiment on cats using [¹⁸F]MPPF, a serotoninergic 1A antagonist radioligand, b-ntPET measured a dose response associated with the amount of the challenged injected concurrent 5-HT1A agonist, where lp-ntPET failed. In human [¹¹C]raclopride experiment, contrary to lp-ntPET, b-ntPET successfully detected significant endogenous dopamine releases induced by the stimulation. In conclusion, our results showed that the proposed method b-ntPET has similar performance to lp-ntPET for detecting displacements, but with higher resistance to noise and better robustness to various experimental contexts. These improvements lead to the possibility of detecting and characterizing dynamic drug occupancy from a single PET scan more efficiently.

OR34-01 11C Metomidate PET-CT Identifies More Unilateral Primary Aldosteronism Than Adrenal Vein Sampling

Introduction. Adrenal vein sampling (AVS) is the current reference test to identify unilateral, surgically-curable primary aldosteronism (PA). However, AVS is invasive and technically difficult. Even in AVS-proven unilateral PA, up to 6% of patients with fail to have biochemical cure after surgery using the PASO criteria. 11C-Metomidate PET-CT offers a non-invasive alternative. We compared the accuracy of both PET-CT and AVS using post-surgery cure (PASO criteria) as the reference.

Methods. This multi-centre prospective trial recruited 25 patients with confirmed PA, and all underwent CT, AVS, and PET-CT tests. Sequential AVS under ACTH-stimulation was done by an experienced interventionalist, and cortisol gradient of >5 was taken to be successful cannulation. Lateralization ratio >4 was consistent with unilateral PA. All results were reviewed at a multidisciplinary meeting to decide on the diagnosis (unilateral or bilateral PA) and management (secondary outcome). Primary outcome was biochemical cure using PASO criteria at 6 months post-surgery (ClinicalTrials.gov: NCTxxxxxxxx).

Results. Recruitment for the study has been complete with 25 patients, 49.2 ± 9.5 yr, 14 females (56.0%). All 25 patients had successful AVS. 22 of 25 patients (88.0%) had unilateral PA, and 3 patients (12.0%) had bilateral PA. PET-CT identified unilateral PA in 18 of 22 patients (sensitivity 81.8%), while AVS identified unilateral PA in 15 of 22 patients (sensitivity 68.2%). In one patient, repeat AVS done simultaneously without ACTH-stimulation aided to identify unilateral PA, when initial AVS failed to do so. Other cases where AVS failed to identify unilateral PA were due to venous anomalies, and limitation of the lateralization cut-off of 4. 18 of 22 patients have undergone surgery, with 3 patients awaiting surgery, and 1 opting for medical treatment. Post-surgery, all patients had complete normalization of aldosterone-renin ratio, and hypokalemia (if present). 2 patients had bilateral PA on both PET-CT and AVS. 1 patient had discordant AVS and PET-CT results, with AVS lateralizing to right, and PET-CT to left. This patient was classified as bilateral PA and treated medically.

Conclusion. This is the first study to demonstrate that 11C-Metomidate PET-CT may identify cases of unilateral PA not detected with AVS, using the stringent PASO criteria for post-operative biochemical cure.

Longitudinal trajectory of Amyloid-related hippocampal subfield atrophy in nondemented elderly

Hippocampal atrophy and abnormal β‐Amyloid (Aβ) deposition are established markers of Alzheimer's disease (AD). Nonetheless, longitudinal trajectory of Aβ‐associated hippocampal subfield atrophy prior to dementia remains unclear. We hypothesized that elevated Aβ correlated with longitudinal subfield atrophy selectively in no cognitive impairment (NCI), spreading to other subfields in mild cognitive impairment (MCI). We analyzed data from two independent longitudinal cohorts of nondemented elderly, including global PET‐Aβ in AD‐vulnerable cortical regions and longitudinal subfield volumes quantified with a novel auto‐segmentation method (FreeSurfer v.6.0). Moreover, we investigated associations of Aβ‐related progressive subfield atrophy with memory decline. Across both datasets, we found a converging pattern that higher Aβ correlated with faster CA1 volume decline in NCI. This pattern spread to other hippocampal subfields in MCI group, correlating with memory decline. Our results for the first time suggest a longitudinal focal‐to‐widespread trajectory of Aβ‐associated hippocampal subfield atrophy over disease progression in nondemented elderly.

Improved quantification of amyloid burden and associated biomarker cut-off points: results from the first amyloid Singaporean cohort with overlapping cerebrovascular disease

PURPOSE

The analysis of the [¹¹C]PiB-PET amyloid images of a unique Asian cohort of 186 participants featuring overlapping vascular diseases raised the question about the validity of current standards for amyloid quantification under abnormal conditions. In this work, we implemented a novel pipeline for improved amyloid PET quantification of this atypical cohort.

METHODS

The investigated data correction and amyloid quantification methods included motion correction, standardized uptake value ratio (SUVr) quantification using the parcellated MRI (standard method) and SUVr quantification without MRI. We introduced a novel amyloid analysis method yielding 2 biomarkers: Aβ_L which quantifies the global Aβ burden and ns that characterizes the non-specific uptake. Cut-off points were first determined using visual assessment as ground truth and then using unsupervised classification techniques.

RESULTS

Subject's motion impacts the accuracy of the measurement outcome but has however a limited effect on the visual rating and cut-off point determination. SUVr computation can be reliably performed for all the subjects without MRI parcellation while, when required, the parcellation failed or was of mediocre quality in 10% of the cases. The novel biomarker Aβ_L showed an association increase of 29.5% with the cognitive tests and increased effect size between positive and negative scans compared with SUVr. ns was found sensitive to cerebral microbleeds, white matter hyperintensity, volume, and age. The cut-off points for SUVr using parcellated MRI, SUVr without parcellation, and Aβ_L were 1.56, 1.39, and 25.5. Finally, k-means produced valid cut-off points without the requirement of visual assessment.

CONCLUSION

The optimal processing for the amyloid quantification of this atypical cohort allows the quantification of all the subjects, producing SUVr values and two novel biomarkers: Aβ_L, showing important increased in their association with various cognitive tests, and ns, a parameter sensitive to non-specific retention variations caused by age and cerebrovascular diseases.

Subtyping of circulating exosome-bound amyloid β reflects brain plaque deposition

Despite intense interests in developing blood measurements of Alzheimer’s disease (AD), the progress has been confounded by limited sensitivity and poor correlation to brain pathology. Here, we present a dedicated analytical platform for measuring different populations of circulating amyloid β (Aβ) proteins – exosome-bound vs. unbound – directly from blood. The technology, termed amplified plasmonic exosome (APEX), leverages in situ enzymatic conversion of localized optical deposits and double-layered plasmonic nanostructures to enable sensitive, multiplexed population analysis. It demonstrates superior sensitivity (~200 exosomes), and enables diverse target co-localization in exosomes. Employing the platform, we find that prefibrillar Aβ aggregates preferentially bind with exosomes. We thus define a population of Aβ as exosome-bound (Aβ42+ CD63+) and measure its abundance directly from AD and control blood samples. As compared to the unbound or total circulating Aβ, the exosome-bound Aβ measurement could better reflect PET imaging of brain amyloid plaques and differentiate various clinical groups.

Detecting Alzheimer’s disease from blood samples is challenging because amyloid β blood levels are lower than the ELISA detection limit. Here the authors capture amyloid β bound to circulating exosomes on a plasmonic nanosensor, followed by enzymatic amplification to improve detection sensitivity.

Cardiac motion and spillover correction for quantitative PET imaging using dynamic MRI

PURPOSE

Cardiac positron emission tomography/magnetic resonance imaging (PET/MRI) acquisition presents novel clinical applications thanks to the combination of viability and metabolic imaging (PET) and functional and structural imaging (MRI). However, the resolution of PET, as well as cardiac and respiratory motion in nongated cardiac imaging acquisition protocols, leads to a reduction in image quality and severe quantitative bias. Respiratory or cardiac motion is customarily addressed with gated reconstruction which results in higher noise.

METHODS

Inspired by a method that has been used in brain PET, a practical correction approach, designed to overcome these existing limitations for quantitative PET imaging, was developed and applied in the context of cardiac PET/MRI. The correction approach for PET data consists of computing the mean density map of each underlying moving region, as obtained with MRI, and translating them to the PET space taking into account the PET spatial and temporal resolution. Using these tissue density maps, the method then constructs a system of linear equations that models the activity recovery and cross-contamination coefficients, which can be solved for the true activity values. Physical and numerical cardiac phantoms were employed in order to quantify the proposed correction. The full correction pipeline was then used to assess differences in metabolic function between scar and healthy myocardium in eight patients with recent acute myocardial infarction using [¹¹ C]-acetate. Data from ten additional patients, injected with [¹⁸ F]-FDG, were used to compare the method to the standard electrocardiography (ECG)-gated approach.

RESULTS

The proposed method resulted in better recovery (from 32% to 95% on the simulated phantom model) and less residual activity than the standard approach. Higher signal-to-noise and contrast-to-noise ratios than ECG-gating were also witnessed (Signal-to-noise ratio (SNR) increased from 2.92 to 5.24, contrast-to-noise ratio (CNR) increased from 62.9 to 145.9 when compared to a four-gate reconstruction). Finally, the relevance of this correction using [¹¹ C]-acetate PET patient data, for which erroneous physiological conclusions could have been made based on the uncorrected data, was established as the correction led to the expected clinical results.

CONCLUSIONS

An efficient and simple method to correct for the quantitative biases in PET measurements caused by cardiac motion has been developed. Validation experiments using phantom and patient data showed improved accuracy and reliability with this approach when compared to simpler strategies such as gated acquisition or optimal regions of interest (ROI).

Development of a Dedicated Rebinner with Rigid Motion Correction for the mMR PET/MR Scanner, and Validation in a Large Cohort of 11C-PIB Scans

Head motion occurring during brain PET studies leads to image blurring and to bias in measured local quantities. The objective of this work was to implement a correction method for PET data acquired with the mMR synchronous PET/MR scanner. Methods: A list-mode-based motion-correction approach has been designed. The developed rebinner chronologically reads the recorded events from the Siemens list-mode file, applies the estimated geometric transformations, and frames the detected counts into sinograms. The rigid-body motion parameters were estimated from an initial dynamic reconstruction of the PET data. We then optimized the correction for ¹¹C-Pittsburgh compound B (¹¹C-PIB) scans using simulated and actual data with well-controlled motion. Results: An efficient list-mode-based motion correction approach has been implemented, fully optimized, and validated using simulated and actual PET data. The average spatial resolution loss induced by inaccuracies in motion parameter estimates and by the rebinning process was estimated to correspond to a 1-mm increase in full width at half maximum with motion parameters estimated directly from the PET data with a temporal frequency of 20 s. The results show that the rebinner can be safely applied to the ¹¹C-PIB scans, allowing almost complete removal of motion-induced artifacts. The application of the correction method to a large cohort of ¹¹C-PIB scans led to the following observations: first, that more than 21% of the scans were affected by motion greater than 10 mm (39% for subjects with Mini-Mental State Examination scores below 20), and second, that the correction led to quantitative changes in Alzheimer-specific cortical regions of up to 30%. Conclusion: The rebinner allows accurate motion correction at a cost of minimal resolution reduction. Application of the correction to a large cohort of ¹¹C-PIB scans confirmed the necessity of systematically correcting for motion to obtain quantitative results.

Determining Glucose Metabolism Kinetics Using 18F-FDG Micro-PET/CT

This paper describes the use of ¹⁸F-FDG and micro-PET/CT imaging to determine in vivo glucose metabolism kinetics in mice (and is transferable to rats). Impaired uptake and metabolism of glucose in multiple organ systems due to insulin resistance is a hallmark of type 2 diabetes. The ability of this technique to extract an image-derived input function from the vena cava using an iterative deconvolution method eliminates the requirement of the collection of arterial blood samples. Fitting of tissue and vena cava time activity curves to a two-tissue, three compartment model permits the estimation of kinetic micro-parameters related to the ¹⁸F-FDG uptake from the plasma to the intracellular space, the rate of transport from intracellular space to plasma and the rate of ¹⁸F-FDG phosphorylation. This methodology allows for multiple measures of glucose uptake and metabolism kinetics in the context of longitudinal studies and also provides insights into the efficacy of therapeutic interventions.

In vivo PET imaging with [(18)F]FDG to explain improved glucose uptake in an apolipoprotein A-I treated mouse model of diabetes

AIMS/HYPOTHESIS

Type 2 diabetes is characterised by decreased HDL levels, as well as the level of apolipoprotein A-I (apoA-I), the main apolipoprotein of HDLs. Pharmacological elevation of HDL and apoA-I levels is associated with improved glycaemic control in patients with type 2 diabetes. This is partly due to improved glucose uptake in skeletal muscle.

METHODS

This study used kinetic modelling to investigate the impact of increasing plasma apoA-I levels on the metabolism of glucose in the db/db mouse model.

RESULTS

Treatment of db/db mice with apoA-I for 2 h significantly improved both glucose tolerance (AUC 2574 ± 70 mmol/l × min vs 2927 ± 137 mmol/l × min, for apoA-I and PBS, respectively; p < 0.05) and insulin sensitivity (AUC 388.8 ± 23.8 mmol/l × min vs 194.1 ± 19.6 mmol/l × min, for apoA-I and PBS, respectively; p < 0.001). ApoA-I treatment also increased glucose uptake by skeletal muscle in both an insulin-dependent and insulin-independent manner as evidenced by increased uptake of fludeoxyglucose ([(18)F]FDG) from plasma into gastrocnemius muscle in apoA-I treated mice, both in the absence and presence of insulin. Kinetic modelling revealed an enhanced rate of insulin-mediated glucose phosphorylation (k 3) in apoA-I treated mice (3.5 ± 1.1 × 10(-2) min(-1) vs 2.3 ± 0.7 × 10(-2) min(-1), for apoA-I and PBS, respectively; p < 0.05) and an increased influx constant (3.7 ± 0.6 × 10(-3) ml min(-1) g(-1) vs 2.0 ± 0.3 × 10(-3) ml min(-1) g(-1), for apoA-I and PBS, respectively; p < 0.05). Treatment of L6 rat skeletal muscle cells with apoA-I for 2 h indicated that increased hexokinase activity mediated the increased rate of glucose phosphorylation.

CONCLUSIONS/INTERPRETATION

These findings indicate that apoA-I improves glucose disposal in db/db mice by improving insulin sensitivity and enhancing glucose phosphorylation.

OSSI-PET: Open-Access Database of Simulated [(11)C]Raclopride Scans for the Inveon Preclinical PET Scanner: Application to the Optimization of Reconstruction Methods for Dynamic Studies

A wide range of medical imaging applications benefits from the availability of realistic ground truth data. In the case of positron emission tomography (PET), ground truth data is crucial to validate processing algorithms and assessing their performances. The design of such ground truth data often relies on Monte-Carlo simulation techniques. Since the creation of a large dataset is not trivial both in terms of computing time and realism, we propose the OSSI-PET database containing 350 simulated [(11)C]Raclopride dynamic scans for rats, created specifically for the Inveon pre-clinical PET scanner. The originality of this database lies on the availability of several groups of scans with controlled biological variations in the striata. Besides, each group consists of a large number of realizations (i.e., noise replicates). We present the construction methodology of this database using rat pharmacokinetic and anatomical models. A first application using the OSSI-PET database is presented. Several commonly used reconstruction techniques were compared in terms of image quality, accuracy and variability of the activity estimates and of the computed kinetic parameters. The results showed that OP-OSEM3D iterative reconstruction method outperformed the other tested methods. Analytical methods such as FBP2D and 3DRP also produced satisfactory results. However, FORE followed by OSEM2D reconstructions should be avoided. Beyond the illustration of the potential of the database, this application will help scientists to understand the different sources of noise and bias that can occur at the different steps in the processing and will be very useful for choosing appropriate reconstruction methods and parameters.

Simultaneous scanning of two mice in a small-animal PET scanner: a simulation-based assessment of the signal degradation

In PET imaging, research groups have recently proposed different experimental set ups allowing multiple animals to be simultaneously imaged in a scanner in order to reduce the costs and increase the throughput. In those studies, the technical feasibility was demonstrated and the signal degradation caused by additional mice in the FOV characterized, however, the impact of the signal degradation on the outcome of a PET study has not yet been studied. Here we thoroughly investigated, using Monte Carlo simulated [18F]FDG and [11C]Raclopride PET studies, different experimental designs for whole-body and brain acquisitions of two mice and assessed the actual impact on the detection of biological variations as compared to a single-mouse setting. First, we extended the validation of the PET-SORTEO Monte Carlo simulation platform for the simultaneous simulation of two animals. Then, we designed [18F]FDG and [11C]Raclopride input mouse models for the simulation of realistic whole-body and brain PET studies. Simulated studies allowed us to accurately estimate the differences in detection between single- and dual-mode acquisition settings that are purely the result of having two animals in the FOV. Validation results showed that PET-SORTEO accurately reproduced the spatial resolution and noise degradations that were observed with actual dual phantom experiments. The simulated [18F]FDG whole-body study showed that the resolution loss due to the off-center positioning of the mice was the biggest contributing factor in signal degradation at the pixel level and a minimal inter-animal distance as well as the use of reconstruction methods with resolution modeling should be preferred. Dual mode acquisition did not have a major impact on ROI-based analysis except in situations where uptake values in organs from the same subject were compared. The simulated [11C]Raclopride study however showed that dual-mice imaging strongly reduced the sensitivity to variations when mice were positioned side-by-side while no sensitivity reduction was observed when they were facing each other. This is the first study showing the impact of different experimental designs for whole-body and brain acquisitions of two mice on the quality of the results using Monte Carlo simulated [18F]FDG and [11C]Raclopride PET studies.

4D PET iterative deconvolution with spatiotemporal regularization for quantitative dynamic PET imaging

Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity.

Assessment of a fast generated analytical matrix for rotating slat collimation iterative reconstruction: a possible method to optimize the collimation profile

In SPECT imaging, improvement or deterioration of performance is mostly due to collimator design. Classical SPECT systems mainly use parallel hole or pinhole collimators. Rotating slat collimators (RSC) can be an interesting alternative to optimize the tradeoff between detection efficiency and spatial resolution. The present study was conducted using a RSC system for small animal imaging called CLiR. The CLiR system was used in planar mode only. In a previous study, planar 2D projections were reconstructed using the well-known filtered backprojection algorithm (FBP). In this paper, we investigated the use of the statistical reconstruction algorithm maximum likelihood expectation maximization (MLEM) to reconstruct 2D images with the CLiR system using a probability matrix calculated using an analytic approach. The primary objective was to propose a method to quickly generate a light system matrix, which facilitates its handling and storage, while providing accurate and reliable performance. Two other matrices were calculated using GATE Monte Carlo simulations to investigate the performance obtained using the matrix calculated analytically. The first matrix calculated using GATE took all the physics processes into account, where the second did not consider for the scattering, as the analytical matrix did not take this physics process into account either. 2D images were reconstructed using FBP and MLEM with the three different probability matrices. Both simulated and experimental data were used. A comparative study of these images was conducted using different metrics: the modulation transfert function, the signal-to-noise ratio and quantification measurement. All the results demonstrated the suitability of using a probability matrix calculated analytically. It provided similar results in terms of spatial resolution (about 0.6 mm with differences <5%), signal-to-noise ratio (differences <10%), or quality of image.

A data driven method for estimation of B(avail) and appK(D) using a single injection protocol with [¹¹C]raclopride in the mouse

PURPOSE

The partial saturation approach (PSA) is a simple, single injection experimental protocol that will estimate both B(avail) and appK(D) without the use of blood sampling. This makes it ideal for use in longitudinal studies of neurodegenerative diseases in the rodent. The aim of this study was to increase the range and applicability of the PSA by developing a data driven strategy for determining reliable regional estimates of receptor density (B(avail)) and in vivo affinity (1/appK(D)), and validate the strategy using a simulation model.

METHODS

The data driven method uses a time window guided by the dynamic equilibrium state of the system as opposed to using a static time window. To test the method, simulations of partial saturation experiments were generated and validated against experimental data. The experimental conditions simulated included a range of receptor occupancy levels and three different B(avail) and appK(D) values to mimic diseases states. Also the effect of using a reference region and typical PET noise on the stability and accuracy of the estimates was investigated.

RESULTS

The investigations showed that the parameter estimates in a simulated healthy mouse, using the data driven method were within 10±30% of the simulated input for the range of occupancy levels simulated. Throughout all experimental conditions simulated, the accuracy and robustness of the estimates using the data driven method were much improved upon the typical method of using a static time window, especially at low receptor occupancy levels. Introducing a reference region caused a bias of approximately 10% over the range of occupancy levels.

CONCLUSIONS

Based on extensive simulated experimental conditions, it was shown the data driven method provides accurate and precise estimates of B(avail) and appK(D) for a broader range of conditions compared to the original method.

Simulation-based optimisation of the PET data processing for partial saturation approach protocols

Positron emission tomography (PET) with [(11)C]Raclopride is an important tool for studying dopamine D2 receptor expression in vivo. [(11)C]Raclopride PET binding experiments conducted using the Partial Saturation Approach (PSA) allow the estimation of receptor density (B(avail)) and the in vivo affinity appK(D). The PSA is a simple, single injection, single scan experimental protocol that does not require blood sampling, making it ideal for use in longitudinal studies. In this work, we generated a complete Monte Carlo simulated PET study involving two groups of scans, in between which a biological phenomenon was inferred (a 30% decrease of B(avail)), and used it in order to design an optimal data processing chain for the parameter estimation from PSA data. The impact of spatial smoothing, noise removal and image resolution recovery technique on the statistical detection was investigated in depth. We found that image resolution recovery using iterative deconvolution of the image with the system point spread function associated with temporal data denoising greatly improves the accuracy and the statistical reliability of detecting the imposed phenomenon. Before optimisation, the inferred B(avail) variation between the two groups was underestimated by 42% and detected in 66% of cases, while a false decrease of appK(D) by 13% was detected in more than 11% of cases. After optimisation, the calculated B(avail) variation was underestimated by only 3.7% and detected in 89% of cases, while a false slight increase of appK(D) by 3.7% was detected in only 2% of cases. We found during this investigation that it was essential to adjust a factor that accounts for difference in magnitude between the non-displaceable ligand concentrations measured in the target and in the reference regions, for different data processing pathways as this ratio was affected by different image resolutions.

Imaging capabilities of the Inveon SPECT system using single-and multipinhole collimators

The Inveon small-animal SPECT system comes with several types of multipinhole collimator plates. We evaluate here the performance measurements of the Inveon SPECT system using 6 different collimators: 3 dedicated for mouse imaging and 3 for rat imaging.

METHODS

The measured performance parameters include the sensitivity, the spatial resolution using line sources, the ultra-micro Derenzo phantom, the recovery coefficient and the noise measurements using the National Electrical Manufacturers Association NU-4 image quality phantom, obtained with the 2 reconstruction algorithms available with the Inveon Acquisition Workplace, version 1.5-the 3-dimensional ordered-subset expectation maximization (3DOSEM) and the 3-dimensional maximum a posteriori (3DMAP). Further, the overall performance of the system is illustrated by an animal experiment.

RESULTS

The results show that the Inveon SPECT scanner offers a spatial resolution, measured at the center of the field of view, ranging from 0.6 to 1 mm with the collimator plates dedicated to mouse imaging and from 1.2 to less than 2 mm with rat collimator plates. The system sensitivity varies from 29 to 404 cps/MBq for mouse collimators and from 53 to 175 cps/MBq for rat collimators. The image quality study showed that 3DMAP allows better noise reduction while preserving the recovery coefficient, compared with other regularization strategies such as the premature termination of the 3DOSEM reconstruction or 3DOSEM followed by gaussian filtering.

CONCLUSION

The acquisition parameters, such as the collimator set and the radius of rotation, offer a wide range of possibilities to apply to a large number of biologic studies. However, special care must be taken because this increase in sensitivity can be offset by image degradation, such as image artifacts caused by projection overlap and statistical noise due to a higher number of iterations required for convergence. 3DMAP allowed better noise reduction while maintaining relatively constant recovery coefficients, as compared with other reconstruction strategies.

Evaluation of three MRI-based anatomical priors for quantitative PET brain imaging

In emission tomography, image reconstruction and therefore also tracer development and diagnosis may benefit from the use of anatomical side information obtained with other imaging modalities in the same subject, as it helps to correct for the partial volume effect. One way to implement this, is to use the anatomical image for defining the a priori distribution in a maximum-a-posteriori (MAP) reconstruction algorithm. In this contribution, we use the PET-SORTEO Monte Carlo simulator to evaluate the quantitative accuracy reached by three different anatomical priors when reconstructing positron emission tomography (PET) brain images, using volumetric magnetic resonance imaging (MRI) to provide the anatomical information. The priors are: 1) a prior especially developed for FDG PET brain imaging, which relies on a segmentation of the MR-image (Baete , 2004); 2) the joint entropy-prior (Nuyts, 2007); 3) a prior that encourages smoothness within a position dependent neighborhood, computed from the MR-image. The latter prior was recently proposed by our group in (Vunckx and Nuyts, 2010), and was based on the prior presented by Bowsher (2004). The two latter priors do not rely on an explicit segmentation, which makes them more generally applicable than a segmentation-based prior. All three priors produced a compromise between noise and bias that was clearly better than that obtained with postsmoothed maximum likelihood expectation maximization (MLEM) or MAP with a relative difference prior. The performance of the joint entropy prior was slightly worse than that of the other two priors. The performance of the segmentation-based prior is quite sensitive to the accuracy of the segmentation. In contrast to the joint entropy-prior, the Bowsher-prior is easily tuned and does not suffer from convergence problems.

[18F]Fallypride PET measurement of striatal and extrastriatal dopamine D 2/3 receptor availability in recently abstinent alcoholics

Positron emission tomography (PET) shows reduced binding of the dopamine D(2/3) antagonist [(11) C]raclopride in striatum of withdrawn psychostimulant abusers, but not consistently in patients with alcohol dependence (AD). We make first use of the high affinity ligand [(18) F]fallypride to obtain serial measures of D(2/3) receptor availability in striatal and extrastriatal regions of AD patients undergoing detoxification. Seventeen patients (mean age 44 ± 5y) with AD and 14 age-matched healthy volunteers participated. Each patient underwent [(18) F]fallypride PET upon hospital admission, and again 1-2 weeks later; two patients achieving abstinence, and two with substantial harm reduction had additional PET follow-up at 1 year. Dynamic 180-minute PET recordings were used for volume of interest (VOI)-based and voxel-wise analysis of [(18) F]fallypride binding potential (BP(ND) ). Mean baseline BP(ND) in striatum of the AD patients (15.7 ± 3.6) was unaltered during short-term follow-up, and did not differ from that in healthy controls (16.8 ± 3.0); however, BP(ND) was 10-20% lower in thalamus, hippocampus, and insular and temporal cortex of the AD patients (P < 0.05). Age-dependent declines in BP(ND) were very small in controls, but more pronounced and widespread in the AD group. Striatal and thalamic BP(ND) increased by 30% in four patients with long-term abstinence or reduced alcohol consumption. VOI-based [(18) F]fallypride PET analyses revealed group differences in D(2/3) receptor availability primarily in extra-striatal regions. Age-related loss of dopamine D(2/3) receptors was more pronounced in AD patients. Receptor availability was unaltered by acute withdrawal, but increased in the subgroup of patients with long-term follow-up, suggesting reversibility of receptor changes.

Characterisation of partial volume effect and region-based correction in small animal positron emission tomography (PET) of the rat brain

Accurate quantification of PET imaging data is required for a useful interpretation of the measured radioactive tracer concentrations. The partial volume effect (PVE) describes signal dilution and mixing due to spatial resolution and sampling limitations, which introduces bias in quantitative results. In the present study we investigated the magnitude of PVE for volumes of interest (VOIs) in the rat brain and the effect of positron range. In simulated (11)C-raclopride studies we examined the influence of PVE on time activity curves in striatal and cerebellar VOIs and binding potential estimation. The performance of partial volume correction (PVC) was studied using the region-based geometric transfer matrix (GTM) method including the question of whether a spatially variant point spread function (PSF) is necessary for PVC of a rat brain close to the centre of the field of view. Furthermore, we determined the effect of spillover from activity outside the brain. The results confirmed that PVE is significant in rat brain PET and showed that positron range is an important factor that needs to be included in the PSF. There was considerable bias in time activity curves for the simulated (11)C-raclopride studies and significant underestimation of binding potential even for very small centred VOIs. Good activity recovery was achieved with the GTM PVC using a spatially invariant simulated PSF when no activity was present outside the brain. PVC using a simple Gaussian fit point spread function was not sufficiently accurate. Spillover from regions outside the brain had a significant impact on measured activity concentrations and reduced the accuracy of PVC with the GTM method using rat brain regions alone, except for the smallest VOI size but at the cost of increased noise. Voxel-based partial volume correction methods which inherently compensate for spillover from outside the brain might be a more suitable choice.

Analytical positron range modelling in heterogeneous media for PET Monte Carlo simulation

Monte Carlo simulation codes that model positron interactions along their tortuous path are expected to be accurate but are usually slow. A simpler and potentially faster approach is to model positron range from analytical annihilation density distributions. The aims of this paper were to efficiently implement and validate such a method, with the addition of medium heterogeneity representing a further challenge. The analytical positron range model was evaluated by comparing annihilation density distributions with those produced by the Monte Carlo simulator GATE and by quantitatively analysing the final reconstructed images of Monte Carlo simulated data. In addition, the influence of positronium formation on positron range and hence on the performance of Monte Carlo simulation was investigated. The results demonstrate that 1D annihilation density distributions for different isotope-media combinations can be fitted with Gaussian functions and hence be described by simple look-up-tables of fitting coefficients. Together with the method developed for simulating positron range in heterogeneous media, this allows for efficient modelling of positron range in Monte Carlo simulation. The level of agreement of the analytical model with GATE depends somewhat on the simulated scanner and the particular research task, but appears to be suitable for lower energy positron emitters, such as (18)F or (11)C. No reliable conclusion about the influence of positronium formation on positron range and simulation accuracy could be drawn.

Voxel-based analysis of asymmetry index maps increases the specificity of 18F-MPPF PET abnormalities for localizing the epileptogenic zone in temporal lobe epilepsies

(18)F-4-(2'-methoxyphenyl)-1-[2'-(N-2-pyridinyl)-p-fluorobenzamido]-ethyl-piperazine ((18)F-MPPF) PET has proved to be a sensitive technique in the presurgical evaluation of patients with drug-resistant temporal lobe epilepsy (TLE), but a significant proportion of visually detected abnormalities failed to be detected by standard statistical parametric mapping (SPM) analysis. This study aimed at describing a voxel-based method for computing interhemispheric asymmetric index (AI) using statistical software and applying and validating the clinical relevance of this method for analyzing asymmetries of (18)F-MPPF PET images in patients with drug-resistant TLE.

METHODS

(18)F-MPPF PET scans of 24 TLE patients who achieved an Engel class I outcome after epilepsy surgery and of 41 controls were analyzed visually, with standard SPM, and by computing voxel-based AIs. Both SPM methods were assessed using 2 different statistical thresholds (P < 0.05, corrected at the cluster level, and P < 0.05, familywise error (FWE) corrected at the voxel level). Sensitivity and specificity of each method were estimated and compared using McNemar tests.

RESULTS

The sensitivity of AI analysis to detect decreases of (18)F-MPPF binding potential ipsilateral to the epileptogenic lobe was 92% (P < 0.05, corrected at the cluster level) and 96% (P < 0.05, familywise error corrected at the voxel level), whereas specificity (defined as the congruence between the localization of the voxel associated with the greatest z score and that of the epileptogenic zone) was 88% at both thresholds. AI analysis was significantly more sensitive (P < 0.05) and specific (P < 0.005) than standard SPM analysis, regardless of the applied threshold. AI analysis also proved to be more sensitive than visual analysis.

CONCLUSION

AI analysis of (18)F-MPPF PET was more sensitive and specific than previous methods of analysis. This noninvasive imaging procedure was especially informative for the presurgical assessment of patients presenting with clinical histories atypical of mesial TLE or with normal brain MRI results.

SORTEO: Monte Carlo-based simulator with list-mode capabilities

Monte Carlo-based PET simulators are powerful tools in the evaluation and validation of new PET algorithms. Accurate generation of projection data from spatiotemporal tracer distributions enable, for a given scanner specification and attenuating media distribution, quantitative analysis based on known ground truth. High activity-related phenomena, such as the contribution of randoms, as well as block and system deadtimes, corrupt actual PET scan data and therefore must be integrated within the simulation model, along with photon interactions within tissue and scanner materials. The PET-SORTEO Monte Carlo simulator, dedicated to full ring tomographs, is able to generate scattered, unscattered, and randoms event distributions from voxelized phantoms, accounting for data losses due to system deadtime. We show the results of extending the simulator to include accurate generation of list-mode data. Our implementation avoids incorrect event distribution and event timing inaccuracies cause by local and propagating temporal rounding errors. List-mode events produced by the PET-SORTEO simulator, when rebinned, are now consistent with sinograms produced by the simulator.

Non-motor dopamine withdrawal syndrome after surgery for Parkinson's disease: predictors and underlying mesolimbic denervation

Apathy has been reported to occur after subthalamic nucleus stimulation, a treatment of motor complications in advanced Parkinson's disease. We carried out a prospective study of the occurrence of apathy and associated symptoms, predictors and mechanisms in the year following subthalamic stimulation. Dopamine agonist drugs were discontinued immediately after surgery and levodopa was markedly reduced within 2 weeks. Apathy and depression were assessed monthly, using the Starkstein apathy scale and the Beck Depression Inventory. Dopamine agonists were re-introduced if patients developed apathy or depression. Preoperative non-motor fluctuations were evaluated using the Ardouin Scale. Depression, apathy and anxiety were evaluated both on and off levodopa. Analysis of predictors of apathy was performed using a Cox proportional hazard model. Twelve patients who developed apathy and a control group of 13 patients who did not underwent [11C]-raclopride positron emission tomography scanning before and after oral intake of methylphenidate. In 63 patients with Parkinson's disease treated with subthalamic stimulation, dopaminergic treatment was decreased by 82% after surgery. Apathy occurred after a mean of 4.7 (3.3-8.2) months in 34 patients and was reversible in half of these by the 12-month follow-up. Seventeen patients developed transient depression after 5.7 (4.7-9.3) months and these fell into the apathy group with one single exception. At baseline, fluctuations in depression, apathy and anxiety scores were greater in the group with apathy. Fluctuations in apathy, depression and anxiety ratings during a baseline levodopa challenge were also significant predictors of postoperative apathy in univariate analysis, but not motor and cognitive states or the level of reduction of dopaminergic medication. The multivariate model identified non-motor fluctuations in everyday life and anxiety score during the baseline levodopa challenge as two independent significant predictors of postoperative apathy. Without methylphenidate, [11C]-raclopride binding potential values were greater in apathetic patients bilaterally in the orbitofrontal, dorsolateral prefrontal, posterior cingulate and temporal cortices, left striatum and right amygdala, reflecting greater dopamine D2/D3 receptor density and/or reduced synaptic dopamine level in these areas. The variations of [11C]-raclopride binding potential values induced by methylphenidate were greater in non-apathetic patients in the left orbitofrontal cortex, dorsolateral prefrontal cortex, thalamus and internal globus pallidus and bilaterally in the anterior and posterior cingulate cortices, consistent with a more important capacity to release dopamine. Non-motor fluctuations are related to mesolimbic dopaminergic denervation. Apathy, depression and anxiety can occur after surgery as a delayed dopamine withdrawal syndrome. A varying extent of mesolimbic dopaminergic denervation and differences in dopaminergic treatment largely determine mood, anxiety and motivation in patients with Parkinson's disease, contributing to different non-motor phenotypes.