Association between Low-Density Lipoprotein Cholesterol and Vascular Biomarkers in Primary Prevention.

Several noninvasive vascular biomarkers have been proposed to improve risk stratification for atherothrombotic events. To identify biomarkers suitable for detecting intermediate-risk individuals who might benefit from lipid-lowering treatment in primary prevention, the present study tested the association of plasma LDL-cholesterol with coronary artery calcification (CAC) Agatston score, high carotid and femoral intima-media thickness (IMT), low carotid distensibility and high carotid-femoral pulse-wave velocity in 260 asymptomatic individuals at intermediate cardiovascular risk and without diabetes and lipid-lowering treatment. High or low vascular biomarkers were considered when their value was above the 95th or below the 5th percentile, respectively, of the distribution in the healthy or in the study population. LDL-cholesterol was independently associated with the CAC score = 0 (OR 0.67; 95%CI 0.48-0.92, p = 0.01), CAC score > 100 (1.59; 1.08-2.39, p = 0.01) and high common femoral artery (CFA) IMT (1.89; 1.19-3.06, p < 0.01), but not with other biomarkers. Our data confirm that in individuals at intermediate risk, lipid-lowering treatment can be avoided in the presence of a CAC score = 0, while it should be used with a CAC score > 100. CFA IMT could represent a useful biomarker for decisions regarding lipid-lowering treatment. However, sex- and age-specific reference values should be established in a large healthy population.

Locus Coeruleus magnetic resonance imaging in cognitively intact elderly subjects.

The locus coeruleus is the main noradrenergic nucleus of the brain and is often affected in neurodegenerative diseases. Recently, magnetic resonance imaging with specific T1-weighted sequences for neuromelanin has been used to evaluate locus coeruleus integrity in patients with these conditions. In some of these studies, abnormalities in locus coeruleus signal have also been found in healthy controls and related to ageing. However, this would be at variance with recent post-mortem studies showing that the nucleus is not affected during normal ageing. The present study aimed at evaluating locus coeruleus features in a well-defined cohort of cognitively healthy subjects who remained cognitively intact on a one-year follow-up. An ad-hoc semiautomatic analysis of locus coeruleus magnetic resonance was applied. Sixty-two cognitively intact subjects aged 60-80 years, without significant comorbidities, underwent 3 T magnetic resonance with specific sequences for locus coeruleus. A semi-automatic tool was used to estimate the number of voxels belonging to locus coeruleus and its intensity was obtained for each subject. Each subject underwent extensive neuropsychological testing at baseline and 12 months after magnetic resonance scan. Based on neuropsychological testing 53 subjects were cognitively normal at baseline and follow up. No significant age-related differences in locus coeruleus parameters were found in this cohort. In line with recent post-mortem studies, our in vivo study confirms that locus coeruleus magnetic resonance features are not statistically significantly affected by age between 60 and 80 years, the age range usually evaluated in studies on neurodegenerative diseases. A significant alteration of locus coeruleus features in a cognitively intact elderly subject might be an early sign of pathology.

Big gamma-glutamyltransferase is associated with epicardial fat volume and cardiovascular outcome in the general population.

AIMS: Gamma-glutamyltransferase (GGT) has been recognized as a cardiovascular risk factor, and its highest molecular weight fraction [big GGT (b-GGT)] is found in vulnerable atherosclerotic plaques. We explored the relationship between b-GGT, computed tomography findings, and long-term outcomes in the general population. METHODS AND RESULTS: Between May 2010 and October 2011, subjects aged 45-75 years living in a Tuscan city and without known cardiac disease were screened. The primary endpoint was a composite of cardiovascular death or acute coronary syndrome requiring urgent coronary revascularization. Gamma-glutamyltransferase fractions were available in 898 subjects [median age 65 years (25th-75th percentile 55-70), 46% men]. Median plasma GGT was 20 IU (15-29), and b-GGT was 2.28 (1.28-4.17). Coronary artery calcium (CAC) score values were 0 (0-60), and the volume of pro-atherogenic epicardial fat was 155 mL (114-204). In a model including age, sex, low-density lipoprotein (LDL) cholesterol, current or previous smoking status, hypertension, diabetes, obesity, b-GGT independently predicted epicardial fat volume (EFV) (r = 0.162, P < 0.001), but not CAC (P = 0.198). Over a 10.3-year follow-up (9.6-10.8), 27 subjects (3%) experienced the primary endpoint. We evaluated couples of variables including b-GGT and a cardiovascular risk factor, CAC or EFV. Big GGT yielded independent prognostic significance from age, LDL cholesterol, current or previous smoking status, hypertension, diabetes, obesity, but not CAC or EFV. Conversely, GGT predicted the primary endpoint even independently from CAC and EFV. CONCLUSION: Big GGT seemed at least as predictive as the commonly available GGT assay; therefore, the need for b-GGT rather than GGT measurement should be carefully examined.

Patient Perceptions and Knowledge of Ionizing Radiation From Medical Imaging.

Importance: Although imaging has become a standard tool of modern medicine, its widespread use has been paralleled by an increasing cumulative radiation dose to patients despite technological advancements and campaigns calling for better awareness and minimization of unnecessary exposures. Objective: To assess patients' knowledge about medical radiation and related risks. Design, Setting, and Participants: A survey study of hospitals in Italy was conducted; all patients in waiting rooms for medical imaging procedures before undergoing imaging examinations at 16 teaching and nonteaching hospitals were approached to take the survey. The survey was performed from June 1, 2019, to May 31, 2020. Main Outcomes and Measures: Survey respondents' basic knowledge of ionizing radiation levels and health risks, earlier imaging tests performed, and information and communication about radiation protection issues. Results: Among 3039 patients invited to participate, the response rate was 94.3% (n = 2866). Participants included 1531 women (53.4%); mean (SD) age was 44.9 (17.3) years. Of the 2866 participants, 1529 (53.3%) were aware of the existence of natural sources of ionizing radiation. Mammography (1101 [38.4%]) and magnetic resonance imaging (1231 [43.0%]) were categorized as radiation-based imaging modalities. More than half of the 2866 patients (1579 [55.1%]; P = .03) did not know that chest computed tomography delivers a larger dose of radiation than chest radiography, and only 1499 (52.3%) knew that radiation can be emitted after nuclear medicine examinations (P = .004). A total of 667 patients (23.3%) believed that radiation risks were unrelated to age, 1273 (44.4%) deemed their knowledge about radiation risks inadequate, and 2305 (80.4%) preferred to be informed about radiation risks by medical staff. A better knowledge of radiation issues was associated with receiving information from health care professionals (odds ratio [OR], 1.71; 95% CI, 1.43-2.03; P < .001) and having a higher educational level (intermediate vs low: OR, 1.48; 95% CI, 1.17-1.88; P < .001; high vs low: OR, 2.68; 95% CI, 2.09-3.43; P < .001). Conclusions and Relevance: The results of this survey suggest that patients undergoing medical imaging procedures have overall limited knowledge about medical radiation. Intervention to achieve better patient awareness of radiation risks related to medical exposures may be beneficial.

Noninvasive carotid pressure-diameter loops to identify viscoelastic properties in ageing, hypertension and type 2 diabetes.

OBJECTIVES: Arterial stiffness as pulse wave velocity (PWV) predicts cardiovascular events independently of blood pressure (BP). PWV does not distinguish between stiffness in systole and diastole. This cross-sectional study aimed to test the hypothesis that viscous and elastic carotid wall properties differ between systole and diastole, distinguishing effects of ageing, hypertension and T2 diabetes (T2DM). METHODS: We examined carotid visco-elasticity in 307 people (180 men), with hypertension alone (n = 69), combined hypertension/T2DM (H-T2DM, n = 99), normotensive (N-T2DM, n = 25) and healthy controls (n = 114). Diameter (D)/pressure (P) waveforms were measured at right /left common carotid arteries, respectively. Local carotid PWV and distensibility in systole and diastole were evaluated by the D2P-loop method, and wall viscosity from hysteresis, the area (HA) within the P--D loop, as a dynamic measure of systolic loading and diastolic unloading. RESULTS: Controls' hysteresis fell quadratically with age (R2 = 0.23, P < 0.001). Yet mean HA in hypertensive patients (0.95, 95% CI 0.65-1.23) was six-fold higher than in age-matched controls (0.14, -0.20 to 0.49, P < 0.001) with a 2.5× difference between diastolic (dDs) to systolic (sDs) distensibility (P < 0.05) in hypertensive patients. HA was higher in hypertensive patients and H-T2DMs (0.80, 0.58-1.04) than N-T2DMs (0.20, -0.17 to 0.54, P < 0.05), but similar between controls and N-T2DMs. BP-adjusted carotid diameters in all T2DM were significantly greater compared with controls and hypertensive patients. CONCLUSION: Higher BP increased wall viscosity, hysteresis and relative difference between systolic and diastolic distensibility across groups. Carotid diameters were increased in all T2DMs, more in H-T2DM, probably altering BP-flow dynamics in T2DM.

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography.

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

Locus Coeruleus Magnetic Resonance Imaging in Neurological Diseases.

PURPOSE OF REVIEW: Locus coeruleus (LC) is the main noradrenergic nucleus of the brain, and its degeneration is considered to be key in the pathogenesis of neurodegenerative diseases. In the last 15 years,MRI has been used to assess LC in vivo, both in healthy subjects and in patients suffering from neurological disorders. In this review, we summarize the main findings of LC-MRI studies, interpreting them in light of preclinical and histopathological data, and discussing its potential role as diagnostic and experimental tool. RECENT FINDINGS: LC-MRI findings were largely in agreement with neuropathological evidences; LC signal showed to be not significantly affected during normal aging and to correlate with cognitive performances. On the contrary, a marked reduction of LC signal was observed in patients suffering from neurodegenerative disorders, with specific features. LC-MRI is a promising tool, which may be used in the future to explore LC pathophysiology as well as an early biomarker for degenerative diseases.

Deep learning to diagnose cardiac amyloidosis from cardiovascular magnetic resonance.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the likelihood of CA. METHODS: 1.5 T CMR was performed in 206 subjects with suspected CA (n = 100, 49% with unexplained left ventricular (LV) hypertrophy; n = 106, 51% with blood dyscrasia and suspected light-chain amyloidosis). Patients were randomly assigned to the training (n = 134, 65%), validation (n = 30, 15%), and testing subgroups (n = 42, 20%). Short axis, 2-chamber, 4-chamber late gadolinium enhancement (LGE) images were evaluated by 3 networks (DL algorithms). The tags "amyloidosis present" or "absent" were attributed when the average probability of CA from the 3 networks was ≥ 50% or < 50%, respectively. The DL strategy was compared to a machine learning (ML) algorithm considering all manually extracted features (LV volumes, mass and function, LGE pattern, early blood-pool darkening, pericardial and pleural effusion, etc.), to reproduce exam reading by an experienced operator. RESULTS: The DL strategy displayed good diagnostic accuracy (88%), with an area under the curve (AUC) of 0.982. The precision (positive predictive value), recall score (sensitivity), and F1 score (a measure of test accuracy) were 83%, 95%, and 89% respectively. A ML algorithm considering all CMR features had a similar diagnostic yield to DL strategy (AUC 0.952 vs. 0.982; p = 0.39). CONCLUSIONS: A DL approach evaluating LGE acquisitions displayed a similar diagnostic performance for CA to a ML-based approach, which simulates CMR reading by experienced operators.

Shifting the Paradigm: The Dress-COV Telegram Bot as a Tool for Participatory Medicine.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. It aims to establish a lasting link between the user and the tool; thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual's self-empowerment. The system uses bot technology of the Telegram application. The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The main results reflect: (a) the individual's compliance with the tool; (b) the security and versatility of the architecture; (c) support and promotion of self-management of behavior to accommodate surveillance system delays; (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). These results are unique to Dress-COV and distinguish our system from classical surveillance applications.

Genetic and nutritional factors determining circulating levels of lipoprotein(a): results of the "Montignoso Study".

Increasing evidence shows an association between high lipoprotein(a) [Lp(a)] levels and atherothrombotic diseases. Lp(a) trait is largely controlled by kringle-IV type 2 (KIV-2) size polymorphism in LPA gene, encoding for apo(a). Environmental factors are considered to determinate minor phenotypic variability in Lp(a) levels. In the present study, we investigated the possible gene-environment interaction between KIV-2 polymorphism and Mediterranean diet adherence or fish weekly intake in determining Lp(a) levels. We evaluated Lp(a), KIV-2 polymorphism, fish intake and Mediterranean diet adherence in 452 subjects [median age (range) 66 (46-80)years] from Montignoso Heart and Lung Project (MEHLP) population. In subjects with high KIV-2 repeats number, influence of Mediterranean diet adherence in reducing Lp(a) levels was observed (p = 0.049). No significant difference in subjects with low KIV-2 repeats according to diet was found. Moreover, in high-KIV-2-repeat subjects, we observed a trend towards influence of fish intake on reducing Lp(a) levels (p = 0.186). At multivariate linear regression analysis, high adherence to Mediterranean diet remains a significant and independent determinant of lower Lp(a) levels (ß = - 64.97, standard error = 26.55, p = 0.015). In conclusion, this study showed that only subjects with high KIV-2 repeats can take advantage to lower Lp(a) levels from correct nutritional habits and, in particular, from Mediterranean diet.

Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging.

Cluster of microcalcifications can be an early sign of breast cancer. In this paper, we propose a novel approach based on convolutional neural networks for the detection and segmentation of microcalcification clusters. In this work, we used 283 mammograms to train and validate our model, obtaining an accuracy of 99.99% on microcalcification detection and a false positive rate of 0.005%. Our results show how deep learning could be an effective tool to effectively support radiologists during mammograms examination.

4-Dimensional Velocity Mapping Cardiac Magnetic Resonance of Extracardiac Bypass for Aortic Coarctation Repair.

This report describes a case of a young lady who, following extracardiac bypass between ascending and descending aorta for severe aortic coarctation, underwent 4-dimensional flow cardiac magnetic resonance, a technique that, by 3-dimensional flow assessment over time (4-dimensional), allows not only quantification of flows but also wall shear stress. In this case, increased wall shear stress was observed in the conduit's acute angle (kinking) as well as at the distal anastomosis level. The authors postulate that increased wall shear stress could help identify and risk stratify adult congenital heart disease who could develop vascular complications in the future. (Level of Difficulty: Intermediate.).

Direct Parametric Maps Estimation from Dynamic PET Data: An Iterated Conditional Modes Approach.

We propose and test a novel approach for direct parametric image reconstruction of dynamic PET data. We present a theoretical description of the problem of PET direct parametric maps estimation as an inference problem, from a probabilistic point of view, and we derive a simple iterative algorithm, based on the Iterated Conditional Mode (ICM) framework, which exploits the simplicity of a two-step optimization and the efficiency of an analytic method for estimating kinetic parameters from a nonlinear compartmental model. The resulting method is general enough to be flexible to an arbitrary choice of the kinetic model, and unlike many other solutions, it is capable to deal with nonlinear compartmental models without the need for linearization. We tested its performance on a two-tissue compartment model, including an analytical solution to the kinetic parameters evaluation, based on an auxiliary parameter set, with the aim of reducing computation errors and approximations. The new method is tested on simulated and clinical data. Simulation analysis led to the conclusion that the proposed algorithm gives a good estimation of the kinetic parameters in any noise condition. Furthermore, the application of the proposed method to clinical data gave promising results for further studies.

Accelerated PET kinetic maps estimation by analytic fitting method.

In this work, we propose and test a new approach for non-linear kinetic parameters' estimation from dynamic PET data. A technique is discussed, to derive an analytical closed-form expression of the compartmental model used for kinetic parameters' evaluation, using an auxiliary parameter set, with the aim of reducing the computational burden and speeding up the fitting of these complex mathematical expressions to noisy TACs. Two alternative algorithms based on numeric calculations are considered and compared to the new proposal. We perform a simulation study aimed at (i) assessing agreement between the proposed method and other conventional ways of implementing compartmental model fitting, and (ii) quantifying the reduction in computational time required for convergence. It results in a speed-up factor of ∼120 when compared to a fully numeric version, or ∼38, with respect to a more conventional implementation, while converging to very similar values for the estimated model parameters. The proposed method is also tested on dynamic 3D PET clinical data of four control subjects. The results obtained supported those of the simulation study, and provided input and promising perspectives for the application of the proposed technique in clinical practice.

Effect of iodinated contrast medium on thyroid function: a study in children undergoing cardiac computed tomography.

BACKGROUND: Few studies, and with conflicting results, have evaluated the potential effects of iodinated contrast media on children's thyroid function. OBJECTIVE: To investigate the effects of iodinated contrast medium on thyroid function in neonates, infants and young children with congenital heart disease undergoing cardiac computed tomography (CT). MATERIALS AND METHODS: We retrospectively evaluated 10 neonates (group 1) and 23 infants and young children (group 2) without thyroid or renal disease for serum levels of thyroid-stimulating hormone, free triiodothyronine and free thyroxine before contrast-enhanced cardiac CT, 48 h after CT and at discharge from the hospital. Cardiac CT was performed with intravenous administration of 1.14±0.17 mL/kg of body weight of iopromide (containing 370 mg of iodine/mL). RESULTS: Group 1 had a reduction of thyroid-stimulating hormone from baseline to 48 h post injection (P=0.002). Group 2 had a reduction of thyroid-stimulating hormone median levels from baseline to 48 h post injection and an increase from 48 h to discharge (P=0.0005 and P=0.0001, respectively). CONCLUSION: Intravenous iodinated contrast medium in children with congenital heart disease caused transient thyroid-stimulating hormone decrease 48 h after CT, with thyroid-stimulating hormone returning to normal range at discharge.

Diagnostic performance of a Lattice Boltzmann-based method for CT-based fractional flow reserve.

AIMS: Fractional flow reserve (FFR) estimated from coronary computed tomography angiography (CT-FFR) offers non-invasive detection of lesion-specific ischaemia. We aimed to develop and validate a fast CT-FFR algorithm utilising the Lattice Boltzmann method for blood flow simulation (LBM CT-FFR). METHODS AND RESULTS: Sixty-four patients with clinically indicated CTA and invasive FFR measurement from three institutions were retrospectively analysed. CT-FFR was performed using an onsite tool interfacing with a commercial Lattice Boltzmann fluid dynamics cloud-based platform. Diagnostic accuracy of LBM CT-FFR ≤0.8 and percent diameter stenosis >50% by CTA to detect invasive FFR ≤0.8 were compared using area under the receiver operating characteristic curve (AUC). Sixty patients successfully underwent LBM CT-FFR analysis; 29 of 73 lesions in 69 vessels had invasive FFR ≤0.8. Total time to perform LBM CT-FFR was 40±10 min. Compared to invasive FFR, LBM CT-FFR had good correlation (r=0.64), small bias (0.009) and good limits of agreement (-0.223 to 0.206). The AUC of LBM CT-FFR (AUC=0.894, 95% confidence interval [CI]: 0.792-0.996) was significantly higher than CTA (AUC=0.685, 95% CI: 0.576-0.794) to detect FFR ≤0.8 (p=0.0021). Per-lesion specificity, sensitivity, and accuracy of LBM CT-FFR were 97.7%, 79.3%, and 90.4%, respectively. CONCLUSIONS: LBM CT-FFR has very good diagnostic accuracy to detect lesion-specific ischaemia (FFR ≤0.8) and can be performed in less than one hour.

A Conway-Maxwell-Poisson (CMP) model to address data dispersion on positron emission tomography.

Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics occurs on PET projection data prior to reconstruction due to physical effects, measurement errors, correction of deadtime, scatter, and random coincidences. A model that describes the statistical behavior of measured and corrected PET data can aid in understanding the statistical nature of the data: it is a prerequisite to develop efficient reconstruction and processing methods and to reduce noise. The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter λ and the dispersion parameter ν, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter ν allows quantifying over-dispersion (ν<1) or under-dispersion (ν>1) of data. A simple and efficient method for λ and ν parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values. The application of the method to simulated and experimental PET phantom data demonstrated that the CMP distribution parameters could detect deviation from the Poisson distribution both in raw and corrected PET data. It may be usefully implemented in image reconstruction algorithms and quantitative PET data analysis, especially in low counting emission data, as in dynamic PET data, where the method demonstrated the best accuracy.

Multimodality imaging in preoperative assessment of left atrial appendage transcatheter occlusion with the Amplatzer Cardiac Plug.

AIMS: Percutaneous left atrial appendage occlusion (LAAO) with the Amplatzer Cardiac Plug (ACP) emerged as a valid alternative in patients with a formal contraindication to oral anticoagulant therapy. Transoesophageal echocardiography (TEE), cardiac computed tomography angiography (CCTA), intracardiac echocardiography (ICE), and conventional cardiac angiography (CCA) are used to evaluate LAA diameters. The aim of our study was to compare pre- and intraprocedural imaging techniques in determining the correct selection of the device size, with a retrospective evaluation of the results obtained at post-procedural CCTA follow-up. METHODS AND RESULTS: Between September 2009 and July 2013, 66 consecutive patients underwent to LAAO with the ACP at our institution. Preoperative LAA evaluation was realized with TEE, CCTA, ICE, and CCA. Fifty-eight (58) patients underwent to post-procedural CCTA to confirm the LAA complete exclusion, the number and extent of the residual leaks, and the positioning of the device. LAA diameters measured by CCTA correlate with the diameters obtained with CCA and ICE, but they are sized slightly larger than the others. TEE has a lower correlation with every other imaging method and a likely tendency to underestimate. The distribution of the leaks and the positioning of the device in post-procedural CCTA show no substantial differences between the devices used greater or equal to the one selected with CCTA in terms of LAA exclusion. CONCLUSION: The sizing of the device decided using CCTA in the phase of maximum LAA expansion reduces the risk of high-flow leaks and device malposition due to undersizing.

Using SUV as a guide to 18F-FDG dose reduction.

UNLABELLED: This article explores how one can lower the injected (18)F-FDG dose while maintaining validity in comparing standardized uptake values (SUVs) between studies. Variations of the SUV within each lesion were examined at different acquisition times. METHODS: Our protocol was approved by either the Human Investigation Committee or the Institutional Review Board. All 120 PET datasets were acquired continuously for 180 s per bed position in list mode and were reconstructed to obtain 30-, 60-, 90-, 120-, 150-, and 180-s-per-bed-position PET images with registration to a single set of nondiagnostic CT images. Qualitative assessment of the images was performed separately for correlation. The SUV measurements of each lesion were computed and normalized to the 180-s acquisition values to create a stabilization factor. These stabilization factors were used to demonstrate a predictable trend of stabilization over time. The variances of the stabilization factors over the entire dataset, composed of several tumor types over a range of sizes, were compared for each time point with the corresponding 150-s time point using a 2-sided F test, which has similar values to the 180-s time point. RESULTS: The variance of the data decreased with increasing acquisition time and with increasing dose but leveled off for sufficiently long acquisitions. CONCLUSION: Through the statistical analysis of SUVs for increasing acquisition times and visual evaluation of the plots, we developed and hereby propose an algorithm that can be used to seek the maximum reduction in administered (18)F-FDG dose while preserving the validity of SUV comparisons.