Perfusion Imaging and Inflammation Biomarkers Provide Complementary Information in Alzheimer's Disease.

BACKGROUND: Single photon emission tomography (SPECT) can detect early changes in brain perfusion to support the diagnosis of dementia. Inflammation is a driver for dementia progression and measures of inflammation may further support dementia diagnosis. OBJECTIVE: In this study, we assessed whether combining imaging with markers of inflammation improves prediction of the likelihood of Alzheimer's disease (AD). METHODS: We analyzed 91 participants datasets (Institutional Ethics Approval 20/NW/0222). AD biomarkers and markers of inflammation were measured in cerebrospinal fluid. Statistical parametric mapping was used to quantify brain perfusion differences in perfusion SPECT images. Logistic regression models were trained to evaluate the ability of imaging and inflammation markers, both individually and combined, to predict AD. RESULTS: Regional perfusion reduction in the precuneus and medial temporal regions predicted Aß42 status. Increase in inflammation markers predicted tau and neurodegeneration. Matrix metalloproteneinase-10, a marker of blood-brain barrier regulation, was associated with perfusion reduction in the right temporal lobe. Adenosine deaminase, an enzyme involved in sleep homeostasis and inflammation, was the strongest predictor of neurodegeneration with an odds ratio of 10.3. The area under the receiver operator characteristic curve for the logistic regression model was 0.76 for imaging and 0.76 for inflammation. Combining inflammation and imaging markers yielded an area under the curve of 0.85. CONCLUSIONS: Study results showed that markers of brain perfusion imaging and markers of inflammation provide complementary information in AD evaluation. Inflammation markers better predict tau status while perfusion imaging measures represent amyloid status. Combining imaging and inflammation improves AD prediction.

Offline reinforcement learning for safer blood glucose control in people with type 1 diabetes.

The widespread adoption of effective hybrid closed loop systems would represent an important milestone of care for people living with type 1 diabetes (T1D). These devices typically utilise simple control algorithms to select the optimal insulin dose for maintaining blood glucose levels within a healthy range. Online reinforcement learning (RL) has been utilised as a method for further enhancing glucose control in these devices. Previous approaches have been shown to reduce patient risk and improve time spent in the target range when compared to classical control algorithms, but are prone to instability in the learning process, often resulting in the selection of unsafe actions. This work presents an evaluation of offline RL for developing effective dosing policies without the need for potentially dangerous patient interaction during training. This paper examines the utility of BCQ, CQL and TD3-BC in managing the blood glucose of the 30 virtual patients available within the FDA-approved UVA/Padova glucose dynamics simulator. When trained on less than a tenth of the total training samples required by online RL to achieve stable performance, this work shows that offline RL can significantly increase time in the healthy blood glucose range from 61.6±0.3% to 65.3±0.5% when compared to the strongest state-of-art baseline (p<0.001). This is achieved without any associated increase in low blood glucose events. Offline RL is also shown to be able to correct for common and challenging control scenarios such as incorrect bolus dosing, irregular meal timings and compression errors. The code for this work is available at: https://github.com/hemerson1/offline-glucose.

Open-Path Atmospheric Transmission of Diode-Pumped Alkali Lasers in Maritime and Desert Environments.

A tunable diode laser absorption spectroscopy (TDLAS) device has been developed to study long-path atmospheric transmission near diode pumped alkali laser (DPAL) emission wavelengths. By employing a single aperture and retro reflector in a mono-static configuration, the noise associated with atmospheric and platform jitter were reduced by a factor of ∼30 and the open-air path length was extended to 4.4 km and over a very broad spectral range, up to 120 cm-1. Water vapor absorption lines near the rubidium (Rb) and cesium (Cs) variants of the DPAL near 795 and 894 nm, oxygen lines near the potassium (K) DPAL near 770 nm, and water vapor absorption in the vicinity of the neodymium-doped yttrium aluminum garnet (Nd:YAG) laser 1.064 µm and chemical oxygen iodine laser (COIL) 1.3 µm lines were studied. The detection limit for path absorbance increases from ΔA = 0.0017 at 100 m path length to 0.085 for the 4.4 km path. Comparison with meteorological instruments for maritime and desert environments yields agreement for the 2.032 km path to within 1.5% for temperature, 4.5% for pressure, and 5.1% for concentration, while agreements for the 4.4 km path are within 1.4% for temperature, 7.7% for pressure, and 23.5% for concentration. An intra cavity output spectroscopy (ICOS) device was also used as a spectral reference to verify location of atmospheric lines. Implications of TDLAS collection system design on signal-to-noise (S/N) are discussed as well as the effect of path turbulence on baseline noise and inform the selection of the DPAL variant least affected by molecular absorption.

Biomarkers of Inflammation Increase with Tau and Neurodegeneration but not with Amyloid-ß in a Heterogenous Clinical Cohort.

BACKGROUND: Neuroinflammation is an integral part of Alzheimer's disease (AD) pathology. Inflammatory mediators can exacerbate the production of amyloid-ß (Aß), the propagation of tau pathology and neuronal loss. OBJECTIVE: To evaluate the relationship between inflammation markers and established markers of AD in a mixed memory clinic cohort. METHODS: 105 cerebrospinal fluid (CSF) samples from a clinical cohort under investigation for cognitive complaints were analyzed. Levels of Aß42, total tau, and phosphorylated tau were measured as part of the clinical pathway. Analysis of inflammation markers in CSF samples was performed using multiplex immune assays. Participants were grouped according to their Aß, tau, and neurodegeneration status and the Paris-Lille-Montpellier (PLM) scale was used to assess the likelihood of AD. RESULTS: From 102 inflammatory markers analyzed, 19 and 23 markers were significantly associated with CSF total tau and phosphorylated tau levels respectively (p < 0.001), while none were associated with Aß42. The CSF concentrations of 4 inflammation markers were markedly elevated with increasing PLM class indicating increased likelihood of AD (p < 0.001). Adenosine deaminase, an enzyme involved in sleep homeostasis, was the single best predictor of high likelihood of AD (AUROC 0.788). Functional pathway analysis demonstrated a widespread role for inflammation in neurodegeneration, with certain pathways explaining over 30% of the variability in tau values. CONCLUSION: CSF inflammation markers increase significantly with tau and neurodegeneration, but not with Aß in this mixed memory clinic cohort. Thus, such markers could become useful for the clinical diagnosis of neurodegenerative disorders alongside the established Aß and tau measures.

Explainable Machine Learning for Real-Time Hypoglycemia and Hyperglycemia Prediction and Personalized Control Recommendations.

BACKGROUND: The occurrences of acute complications arising from hypoglycemia and hyperglycemia peak as young adults with type 1 diabetes (T1D) take control of their own care. Continuous glucose monitoring (CGM) devices provide real-time glucose readings enabling users to manage their control proactively. Machine learning algorithms can use CGM data to make ahead-of-time risk predictions and provide insight into an individual's longer term control. METHODS: We introduce explainable machine learning to make predictions of hypoglycemia (<70 mg/dL) and hyperglycemia (>270 mg/dL) up to 60 minutes ahead of time. We train our models using CGM data from 153 people living with T1D in the CITY (CGM Intervention in Teens and Young Adults With Type 1 Diabetes)survey totaling more than 28 000 days of usage, which we summarize into (short-term, medium-term, and long-term) glucose control features along with demographic information. We use machine learning explanations (SHAP [SHapley Additive exPlanations]) to identify which features have been most important in predicting risk per user. RESULTS: Machine learning models (XGBoost) show excellent performance at predicting hypoglycemia (area under the receiver operating curve [AUROC]: 0.998, average precision: 0.953) and hyperglycemia (AUROC: 0.989, average precision: 0.931) in comparison with a baseline heuristic and logistic regression model. CONCLUSIONS: Maximizing model performance for glucose risk prediction and management is crucial to reduce the burden of alarm fatigue on CGM users. Machine learning enables more precise and timely predictions in comparison with baseline models. SHAP helps identify what about a CGM user's glucose control has led to predictions of risk which can be used to reduce their long-term risk of complications.

Trade and dietary preferences can determine micronutrient security in the United Kingdom.

Food production, dietary choices, climate change, trade tariffs and future responses to the SARS-CoV-2 pandemic are some of the factors affecting global food security. Here we examine how micronutrient security has varied in the United Kingdom from 1961 to 2017, before Brexit, taking supply and demand driver changes into account. We also introduce future scenarios to see how a more plant-based diet and/or differing trade arrangement post-European Union exit and COVID-19 pandemic could affect the supply of nutrients. Results show that trading agreements have affected several key micronutrients during the past 60 years and are likely to be influential in a post-Brexit United Kingdom. Changes in dietary patterns, which influence how much animal- and plant-based products are consumed, have also affected micronutrient security and are likely to do so in the future with increased interest in consuming a more plant-based diet.

Quantitative Assessment of Regional Mucociliary Clearance in Smokers with Mild-to-Moderate Chronic Obstructive Pulmonary Disease and Chronic Bronchitis from Planar Radionuclide Imaging.

Background: Mucociliary clearance (MCC) rate from the lung has been shown to be reduced in chronic obstructive pulmonary disease (COPD). This study investigates the value of regional clearance measurements in assessing MCC in mild-to-moderate disease. Methods: Measurement of lung MCC using planar gamma camera imaging was performed in three groups: (i) healthy nonsmoking controls (NSCs) (n = 9), (ii) smoking controls (SCs) who were current smokers with normal lung function (n = 10), and (iii) current smokers with mild-to-moderate COPD and bronchitis (n = 15). The mean (±standard deviation) forced expiratory volumes at 1 second (FEV1) for the three groups were 109 (± 18), 94 (± 5), and 78 (± 12), respectively. After inhalation of a technetium-99m labeled aerosol, planar imaging was performed over 4 hours and then at 24 hours. Both lung clearance and tracheobronchial clearance (TBC) (normalized to 24 hours clearance) were calculated for inner and outer lung zones. Inner zone clearance was corrected for input from the outer zone. A novel parameter, the bronchial airways clearance index (BACI), which combined clearance data from both zones, was also evaluated. Regional results were compared with whole lung clearance in the same subjects. Results: Corrected inner zone clearance at 3 hours was not reduced compared with NSC in either SCs or COPD. Outer zone clearance was higher in COPD than in the other groups. Corrected inner zone TBC showed significant reductions in SC and COPD compared with NSC. BACI was significantly reduced in COPD compared with NSC and also correlated with FEV1. The mean BACI for SC was also reduced compared with NSC, but the distribution of results was bimodal, with a significant proportion of subjects having values in the NSC range. Conclusions: Regional MCC demonstrated differences between NSCs, SCs, and subjects with mild-to-moderate COPD, which were not apparent with whole lung measurements.

A general framework in single and multi-modality registration for lung imaging analysis using statistical prior shapes.

BACKGROUND AND OBJECTIVE: A fusion of multi-slice computed tomography (MSCT) and single photon emission computed tomography (SPECT) represents a powerful tool for chronic obstructive pulmonary disease (COPD) analysis. In this paper, a novel and high-performance MSCT/SPECT non-rigid registration algorithm is proposed to accurately map the lung lobe information onto the functional imaging. Such a fusion can then be used to guide lung volume reduction surgery. METHODS: The multi-modality fusion method proposed here is developed by a multi-channel technique which performs registration from MSCT scan to ventilation and perfusion SPECT scans simultaneously. Furthermore, a novel function with less parameters is also proposed to avoid the adjustment of the weighting parameter and to achieve a better performance in comparison with the exisitng methods in the literature. RESULTS: A lung imaging dataset from a hospital and a synthetic dataset created by software are employed to validate single- and multi-modality registration results. Our method is demonstrated to achieve the improvements in terms of registration accuracy and stability by up to 23% and 54% respectively. Our multi-channel technique proposed here is also proved to obtain improved registration accuracy in comparison with single-channel method. CONCLUSIONS: The fusion of lung lobes onto SPECT imaging is achievable by accurate MSCT/SPECT alignment. It can also be used to perform lobar lung activity analysis for COPD diagnosis and treatment.

Standardised quantitative radioiodine SPECT/CT Imaging for multicentre dosimetry trials in molecular radiotherapy.

The SEL-I-METRY trial (EudraCT No 2015-002269-47) is the first multicentre trial to investigate the role of 123I and 131I SPECT/CT-based tumour dosimetry to predict response to radioiodine therapy. Standardised dosimetry methodology is essential to provide a robust evidence-base for absorbed dose-response thresholds for molecular radiotherapy (MRT). In this paper a practical standardised protocol is used to establish the first network of centres with consistent methods of radioiodine activity quantification. Nine SPECT/CT systems at eight centres were set-up for quantitative radioiodine imaging. The dead-time of the systems was characterised for up to 2.8 GBq 131I. Volume dependent calibration factors were measured on centrally reconstructed images of 123I and 131I in six (0.8-196 ml) cylinders. Validation of image quantification using these calibration factors was performed on three systems, by imaging a 3D-printed phantom mimicking a patient's activity distribution. The percentage differences between the activities measured in the SPECT/CT image and those measured by the radionuclide calibrator were calculated. Additionally uncertainties on the SPECT/CT-based activities were calculated to indicate the limit on the quantitative accuracy of this method. For systems set-up to image high 131I count rates, the count rate versus activity did not peak below 2.8 GBq and fit a non-paralysable model. The dead-times and volume-dependent calibration factors were comparable between systems of the same model and crystal thickness. Therefore a global calibration curve could be fitted to each. The errors on the validation phantom activities' were comparable to the measurement uncertainties derived from uncertainty analysis, at 10% and 16% on average for 123I and 131I respectively in a 5 cm sphere. In conclusion, the dead-time and calibration factors varied between centres, with different models of system. However, global calibration factors may be applied to the same system model with the same crystal thickness, to simplify set-up of future multi-centre MRT studies.

Quantitative Assessment of Mucociliary Clearance in Smokers with Mild-to-Moderate Chronic Obstructive Pulmonary Disease and Chronic Bronchitis from Planar Radionuclide Imaging Using the Change in Penetration Index.

Background: Mucociliary clearance (MCC) rate from the lung has been shown to be reduced in chronic obstructive pulmonary disease (COPD). This study compared the use of change in penetration index (PI) with conventional whole lung clearance in assessing MCC in mild-to-moderate disease. Methods: Measurement of lung MCC using planar gamma camera imaging was performed in three groups: (1) healthy nonsmoking controls (n = 9), (2) smoking controls who were current smokers with normal lung function (n = 10), and (3) current smokers with mild-to-moderate COPD and bronchitis (n = 15). The mean (±standard deviation) forced expiratory volume at 1 second (FEV1) for the three groups was 109 (±18), 94 (±5), and 78 (±12), respectively. Following inhalation of a technetium-99m labeled aerosol, planar imaging was performed over 4 hours and then at 24 hours. Total lung clearance and tracheobronchial clearance (TBC; normalized to 24-hour clearance) were calculated. A novel parameter, the normalized change in PI (NOCHIP), was also evaluated. PI is the ratio of counts between outer and inner lung zones normalized to lung volume. Results: More aerosol was deposited in central airways in COPD compared to nonsmoking controls, using 24-hour clearance measurements (p < 0.001). Smoking controls had intermediate values. The optimal endpoint for MCC assessment was chosen to be 3 hours, when intersubject variability was minimal, while preserving a measure of early clearance. There was no statistical difference between the three groups in mean total lung clearance, or TBC, at 3 hours. NOCHIP at 3 hours was reduced significantly, compared to nonsmoking controls, in both smoking controls (p = 0.007) and COPD (p < 0.0001). It also correlated with FEV1 (p = 0.003). A higher proportion of smoking control subjects had NOCHIP values in the nonsmoking control range than in the COPD group. Conclusions: NOCHIP was a more sensitive measure of MCC than whole lung clearance and TBC in mild-to-moderate COPD.

Discovery Molecular Imaging Digital Ready PET/CT performance evaluation according to the NEMA NU2-2012 standard.

OBJECTIVES: The aim of this study was to evaluate and benchmark the performance characteristics of the General Electric (GE) Discovery Molecular Imaging (MI) Digital Ready (DR) PET/CT. MATERIALS AND METHODS: Performance evaluation against the National Electrical Manufacturers Association (NEMA) 2012 standard was performed on three GE Discovery MI DR PET/CT systems installed across different UK centres. The Discovery MI DR performance was compared with the Siemens Biograph mCT Flow, Phillips Ingenuity TF and GE Discovery 690 fully analogue PET/CT systems. In addition, as the Discovery MI DR is upgradable to the Digital MI with silicon photomultipliers, performance characteristics between analogue and digital were compared with assess potential benefits of a system upgrade. RESULTS: The average NEMA results across three Discovery MI DR scanners were: sensitivity 7.3 cps/kBq, spatial resolution full-width-half-maximum radial 5.5 mm, tangential 4.5 mm and axial 6 mm at 10 cm from the centre of the field-of-view, peak noise equivalent count rate 142 kcps, scatter fraction 37.1%, contrast recovery coefficients from the International Electrotechnical Commission phantom ranged from 52 to 87% for 10-37-mm diameter spheres. CONCLUSION: All three Discovery MI DR systems tested in this study exceeded the manufacturer's NEMA specification, yet variability between scanners was noted. Discovery MI DR showed similar performance to Discovery 690 and Ingenuity TF, but lower sensitivity and spatial resolution than Biograph mCT Flow. The Discovery MI DR showed lower spatial resolution and contrast recovery than the 20-cm field-of-view Digital MI.

High power Nd:YAG spinning disk laser.

We report on a high power Nd:YAG spinning disk laser. The eight cm diameter disk generated 200 W CW output with 323 W of absorbed pump in a near diffraction-limited beam. The power conversion efficiency was 64%. The pulsed result, 5 ms pulses at 10 Hz PRF, was nearly identical to the CW result indicating good thermal management. Rotated at 1200-1800 RPM with He impingement cooling the disk temperature increased by only 17 °C reaching a maximum temperature of ~31 °C. The thermal dissipation per unit of output power was 0.61 watt of heat generated per watt of laser output, which is below the typical range of 0.8-1.1 for 808 nm diode pumped Nd:YAG lasers.

(111)In WBC SPECT/CT detection of a radiographically occult solitary infected renal cyst in polycystic kidney disease.

Renal cyst infection-pyocystis-is a potentially life-threatening complication of autosomal-dominant polycystic kidney disease. Differentiation of pyocystis from pyelonephritis is important for antibiotic management. A 56-year-old woman with autosomal-dominant polycystic kidney disease and recurrent urinary tract infections was admitted to the hospital with suspicion of pyelonephritis. CT and static planar In-labeled WBC examinations failed to show a specific focus of infection. Abdominal imaging with In-labeled WBC SPECT/CT revealed abnormal leukocyte accumulation within a solitary right renal cyst. Precise SPECT/CT localization of the infected renal cyst is illustrated along with comparative CT images.

18F-FDG PET/CT metabolic variability in functioning oncocytic parathyroid adenoma with brown tumors.

A 29-year-old female patient exhibited a solitary neck mass, severe hypercalcemia, and multiple skeletal lytic lesions consistent with metastatic neoplastic disease. Fine-needle aspiration (FNA) cytology of the neck lesion indicated a follicular thyroid neoplasm. CT-guided bone biopsy was non-diagnostic. Subsequent 18F-FDG PET/CT examination demonstrated avid glucose uptake within the neck mass and diffuse bony lesions of variable metabolic activity. Repeat biopsy utilizing PET/CT guidance produced core tissue with classic histologic features of a brown tumor. Postoperative histology revealed an exclusively oncocytic parathyroid adenoma. Atypical radiotracer uptake of this rare functioning adenoma subtype is illustrated with discussion of improved procedural diagnostic yield utilizing PET/CT.

MRI of the axillary arch muscle: prevalence, anatomic relations, and potential consequences.

OBJECTIVE: The purpose of this study was to use MRI of the shoulder to analyze the axillary arch muscle and its anatomic relations to lymph nodes and the brachial plexus. MATERIALS AND METHODS: In this retrospective study at a single clinic, five observers blinded to the patient's condition assessed images from 1,109 consecutive initial shoulder MRI examinations for the presence and anatomic relations of the axillary arch. MRI interpretation reports were reviewed for documentation of previous injuries and upper extremity radicular pain or numbness for possible correlations between presence of the arch and symptoms of nerve entrapment. Results were reported as prevalence percentage or mean ± SD with 95% CI. Groups were compared by use of Student's t test or chi-square test as indicated (p < 0.05). RESULTS: An arch muscle was found in 71 of 1,109 (6%) examinations, and variability was found in arch insertion and visualization. A statistically significant 65 of 71 (92%) arches had a course superficial to the lymph nodes. The insertion of 50 of 71 (70%) arches was within 5 mm of the brachial neurovascular bundle. Excluding documented injuries, significantly more patients with an arch had upper extremity neurologic abnormalities than did patients without an arch (p = 0.02). CONCLUSION: The axillary arch muscle is situated in such a way that it can conceal lymph nodes and impinge on the brachial plexus, causing symptoms of upper extremity nerve entrapment. Radiologists' familiarity with the arch can improve their recognition of this muscular variant so that they can communicate appropriate clinical correlations to referring physicians.