Image reconstruction in fluorescence molecular tomography with sparsity-initialized maximum-likelihood expectation maximization

We present a reconstruction method involving maximum-likelihood expectation maximization (MLEM) to model Poisson noise as applied to fluorescence molecular tomography (FMT). MLEM is initialized with the output from a sparse reconstruction-based approach, which performs truncated singular value decomposition-based preconditioning followed by fast iterative shrinkage-thresholding algorithm (FISTA) to enforce sparsity. The motivation for this approach is that sparsity information could be accounted for within the initialization, while MLEM would accurately model Poisson noise in the FMT system. Simulation experiments show the proposed method significantly improves images qualitatively and quantitatively. The method results in over 20 times faster convergence compared to uniformly initialized MLEM and improves robustness to noise compared to pure sparse reconstruction. We also theoretically justify the ability of the proposed approach to reduce noise in the background region compared to pure sparse reconstruction. Overall, these results provide strong evidence to model Poisson noise in FMT reconstruction and for application of the proposed reconstruction framework to FMT imaging

Four decades of mapping and quantifying neuroreceptors at work in vivo by positron emission tomography

Decryption of brain images is the basis for the necessary translation of the findings from imaging to information required to meet the demands of clinical intervention. Tools of brain imaging, therefore, must satisfy the conditions dictated by the needs for interpretation in terms of diagnosis and prognosis. In addition, the applications must serve as fundamental research tools that enable the understanding of new therapeutic drugs, including compounds as diverse as antipsychotics, antidepressants, anxiolytics, and drugs serving the relief of symptoms from neurochemical disorders as unrelated as multiple sclerosis, stroke, and dementia. Here we review and explain the kinetics of methods that enable researchers to describe the brain\u27s work and functions. We focus on methods invented by neurokineticists and expanded upon by practitioners during decades of experimental work and on the methods that are particularly useful to predict possible future approaches to the treatment of neurochemical disorders. We provide an overall description of the basic elements of kinetics and the underlying quantification methods, as well as the mathematics of modeling the recorded brain dynamics embedded in the images we obtai

Incorporating reflection boundary conditions in the Neumann series radiative transport equation: Application to photon propagation and reconstruction in diffuse optical imaging

We propose a formalism to incorporate boundary conditions in a Neumann-series-based radiative transport equation. The formalism accurately models the reflection of photons at the tissue-external medium interface using Fresnel’s equations. The formalism was used to develop a gradient descent-based image reconstruction technique. The proposed methods were implemented for 3D diffuse optical imaging. In computational studies, it was observed that the average root-mean-square error (RMSE) for the output images and the estimated absorption coefficients reduced by 38% and 84%, respectively, when the reflection boundary conditions were incorporated. These results demonstrate the importance of incorporating boundary conditions that model the reflection of photons at the tissue-external medium interface

Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts

Alzheimer\u27s disease biomarkers are becoming increasingly important for characterizing the longitudinal course of disease, predicting the timing of clinical and cognitive symptoms, and for recruitment and treatment monitoring in clinical trials. In this work, we develop and evaluate three methods for modelling the longitudinal course of amyloid accumulation in three cohorts using amyloid PET imaging. We then use these novel approaches to investigate factors that influence the timing of amyloid onset and the timing from amyloid onset to impairment onset in the Alzheimer\u27s disease continuum. Data were acquired from the Alzheimer\u27s Disease Neuroimaging Initiative (ADNI), the Baltimore Longitudinal Study of Aging (BLSA) and the Wisconsin Registry for Alzheimer\u27s Prevention (WRAP). Amyloid PET was used to assess global amyloid burden. Three methods were evaluated for modelling amyloid accumulation using 10-fold cross-validation and holdout validation where applicable. Estimated amyloid onset age was compared across all three modelling methods and cohorts. Cox regression and accelerated failure time models were used to investigate whether sex, apolipoprotein E genotype and e4 carriage were associated with amyloid onset age in all cohorts. Cox regression was used to investigate whether apolipoprotein E (e4 carriage and e3e3, e3e4, e4e4 genotypes), sex or age of amyloid onset were associated with the time from amyloid onset to impairment onset (global clinical dementia rating ≥1) in a subset of 595 ADNI participants that were not impaired before amyloid onset. Model prediction and estimated amyloid onset age were similar across all three amyloid modelling methods. Sex and apolipoprotein E e4 carriage were not associated with PET-measured amyloid accumulation rates. Apolipoprotein E genotype and e4 carriage, but not sex, were associated with amyloid onset age such that e4 carriers became amyloid positive at an earlier age compared to non-carriers, and greater e4 dosage was associated with an earlier amyloid onset age. In the ADNI, e4 carriage, being female and a later amyloid onset age were all associated with a shorter time from amyloid onset to impairment onset. The risk of impairment onset due to age of amyloid onset was non-linear and accelerated for amyloid onset age \u3e65. These findings demonstrate the feasibility of modelling longitudinal amyloid accumulation to enable individualized estimates of amyloid onset age from amyloid PET imaging. These estimates provide a more direct way to investigate the role of amyloid and other factors that influence the timing of clinical impairment in Alzheimer\u27s disease

The association of long-term exposure to criteria air pollutants, fine particulate matter components, and airborne trace metals with late-life brain amyloid burden in the Atherosclerosis Risk in Communities (ARIC) study

BACKGROUND: Studies suggest associations between long-term ambient air pollution exposure and outcomes related to Alzheimer\u27s disease (AD). Whether a link exists between pollutants and brain amyloid accumulation, a biomarker of AD, is unclear. We assessed whether long-term air pollutant exposures are associated with late-life brain amyloid deposition in Atherosclerosis Risk in Communities (ARIC) study participants. METHODS: We used a chemical transport model with data fusion to estimate ambient concentrations of PM RESULTS: At PET imaging, eligible participants (N = 318) had a mean age of 78 years, 56% were female, 43% were Black, and 27% had mild cognitive impairment. We did not find evidence of associations between long-term exposure to any pollutant and brain amyloid positivity in adjusted models. Findings were materially unchanged in sensitivity analyses using alternate air pollution estimation approaches for PM CONCLUSIONS: Air pollution may impact cognition and dementia independent of amyloid accumulation, though whether air pollution influences AD pathogenesis later in the disease course or at higher exposure levels deserves further consideration

Association of PET-measured myocardial flow reserve with echocardiography-estimated pulmonary artery systolic pressure in patients with hypertrophic cardiomyopathy

BackgroundPulmonary hypertension (PH) is a known complication of HCM and is a strong predictor of mortality. We aim to investigate the relationship between microvascular dysfunction measured by quantitative PET and PH in HCM patients.MethodsEighty-nine symptomatic HCM patients were included in the study. Each patient underwent two 20-min 13N-NH3 dynamic PET scans for rest and stress conditions, respectively. A 2-tissue irreversible compartmental model was used to fit the segments time activity curves for estimating segmental and global myocardial blood flow (MBF) and myocardial flow reserve (MFR). Echocardiographic derived PASP was utilized to estimate PH.ResultsPatients were categorized into two groups across PASP: PH (PASP > 36 mmHg) and no-PH (PASP ≤ 36 mmHg). patients with PH had larger left atrium, ratio of higher inflow early diastole (E) and atrial contraction (A) waves, E/A, and ratio of inflow and peak early diastolic waves, E/e', significantly reduced global stress MBF (1.85 ± 0.52 vs. 2.13 ± 0.56 ml/min/g; p = 0.024) and MFR (2.21 ± 0.57 vs. 2.62 ± 0.75; p = 0.005), while the MBFs at rest between the two groups were similar. There were significant negative correlations between global stress MBF/MFR and PASP (stress MBF: r = -0.23, p = 0.03; MFR: r = -0.32, p = 0.002); for regional MBF and MFR measurements, the highest linear correlation coefficients were observed in the septal wall (stress MBF: r = -0.27, p = 0.01; MFR: r = -0.31, p = 0.003). Global MFR was identified to be independent predictor for PH in multivariate regression analysis.ConclusionEchocardiography-derived PASP is negatively correlated with global MFR measured by 13N-NH3 dynamic PET. Global MFR is suggested to be an index of PH in HCM patients.</div

Radioligand binding analysis of α₂ adrenoceptors with [¹¹C]yohimbine in brain in vivo:Extended Inhibition Plot correction for plasma protein binding

Abstract We describe a novel method of kinetic analysis of radioligand binding to neuroreceptors in brain in vivo, here applied to noradrenaline receptors in rat brain. The method uses positron emission tomography (PET) of [11C]yohimbine binding in brain to quantify the density and affinity of α 2 adrenoceptors under condition of changing radioligand binding to plasma proteins. We obtained dynamic PET recordings from brain of Spraque Dawley rats at baseline, followed by pharmacological challenge with unlabeled yohimbine (0.3 mg/kg). The challenge with unlabeled ligand failed to diminish radioligand accumulation in brain tissue, due to the blocking of radioligand binding to plasma proteins that elevated the free fractions of the radioligand in plasma. We devised a method that graphically resolved the masking of unlabeled ligand binding by the increase of radioligand free fractions in plasma. The Extended Inhibition Plot introduced here yielded an estimate of the volume of distribution of non-displaceable ligand in brain tissue that increased with the increase of the free fraction of the radioligand in plasma. The resulting binding potentials of the radioligand declined by 50–60% in the presence of unlabeled ligand. The kinetic unmasking of inhibited binding reflected in the increase of the reference volume of distribution yielded estimates of receptor saturation consistent with the binding of unlabeled ligand

Performance assessment of a NaI(Tl) gamma counter for PET applications with methods for improved quantitative accuracy and greater standardization

BACKGROUND: Although NaI(Tl) gamma counters play an important role in many quantitative positron emission tomography (PET) protocols, their calibration for positron-emitting samples has not been standardized across imaging sites. In this study, we characterized the operational range of a gamma counter specifically for positron-emitting radionuclides, and we assessed the role of traceable (68)Ge/(68)Ga sources for standardizing system calibration. METHODS: A NaI(Tl) gamma counter was characterized with respect to count rate performance, adequacy of detector shielding, system stability, and sample volume effects using positron-emitting radionuclides (409- to 613-keV energy window). System efficiency was measured using (18)F and compared with corresponding data obtained using a long-lived (68)Ge/(68)Ga source that was implicitly traceable to a national standard. RESULTS: One percent count loss was measured at 450 × 10(3) counts per minute. Penetration of the detector shielding by 511-keV photons gave rise to a negligible background count rate. System stability tests showed a coefficient of variation of 0.13% over 100 days. For a sample volume of 4 mL, the efficiencies relative to those at 0.1 mL were 0.96, 0.94, 0.91, 0.78, and 0.72 for (11)C, (18)F, (125)I, (99m)Tc, and (51)Cr, respectively. The efficiency of a traceable (68)Ge/(68)Ga source was 30.1% ± 0.07% and was found to be in close agreement with the efficiency for (18)F after consideration of the different positron fractions. CONCLUSIONS: Long-lived (68)Ge/(68)Ga reference sources, implicitly traceable to a national metrology institute, can aid standardization of gamma counter calibration for (18)F. A characteristic feature of positron emitters meant that accurate calibration could be maintained over a wide range of sample volumes by using a narrow energy window centered on the 511-keV peak