Search

The main goal of this work is to describe a phantom design, data acquisition and data analysis methodology enabling comparison of small lesion detectability between PET imaging systems and reconstruction algorithms. Several methods are currently available to characterize intrinsic and image quality performance, but none focus exclusively on small lesion detectability.We previously developed a small-lesion detection phantom and described initial results using a head-size phantomRepeat acquisitions of the phantom enabled estimation of model observer performance and surrogates of detectability. As anticipated, estimated detectability increased with the square root of system sensitivity and TOF offered marked improvement in detectability, especially for the body sized object. The proposed approach characterizing detectability at different times during the decay of the phantom enabled comparison of small lesion detectability at matched activity concentrations (and scan durations) across different scanners.The proposed approach offers a reproducible tool for evaluating relative tradeoffs of system performance on small lesion detectability. This article is protected by copyright. All rights reserved.

Diffusiophoresis refers to the movement of colloidal particles in the presence of a concentration gradient of a solute and enables directed motion of colloidal particles in geometries that are inaccessible, such as dead-end pores, without imposing an external field. Previous experimental reports on dead-end pore geometries show that, even in the absence of mean flow, colloidal particles moving through diffusiophoresis exhibit significant dispersion. Existing models of diffusiophoresis are not able to predict the dispersion and thus the comparison between the experiments and the models is largely qualitative. To address these quantitative differences between the experiments and models, we derive an effective one-dimensional equation, similar to a Taylor dispersion analysis, that accounts for the dispersion created by diffusioosmotic flow from the channel sidewalls. We derive the effective dispersion coefficient and validate our results by comparing them with direct numerical simulations. We also compare our model with experiments and obtain quantitative agreement for a wide range of colloidal particle sizes. Our analysis reveals two important conclusions. First, in the absence of mean flow, dispersion is driven by the flow created by diffusioosmotic wall slip such that spreading can be reduced by decreasing the channel wall diffusioosmotic mobility. Second, the model can explain the spreading of colloids in a dead-end pore for a wide range of particle sizes. We note that, while the analysis presented here focuses on a dead-end pore geometry with no mean flow, our theoretical framework is general and can be adapted to other geometries and other background flows.

SUMMARY: Adenosine deaminase 2 deficiency (OMIM #615688) is an autosomal recessive disorder characterized by a wide clinical spectrum, including small- and medium-sized vessel vasculopathies, but data focusing on the associated neuroimaging features are still scarce in the literature. Here, we describe the clinical neuroimaging features of 12 patients with genetically proven adenosine deaminase 2 deficiency (6 males; median age at disease onset, 1.3 years; median age at genetic diagnosis, 15.5 years). Our findings expand the neuroimaging phenotype of this condition demonstrating, in addition to multiple, recurrent brain lacunar ischemic and/or hemorrhagic strokes, spinal infarcts, and intracranial aneurysms, also cerebral microbleeds and a peculiar, likely inflammatory, perivascular tissue in the basal and peripontine cisterns. Together with early clinical onset, positive family history, inflammatory flares and systemic abnormalities, these findings should raise the suspicion of adenosine deaminase 2 deficiency, thus prompting genetic evaluation and institution of tumor necrosis factor inhibitors, with a potential great impact on neurologic outcome.

Active transportation is defined as self-propelled, human-powered transportation modes, such as walking and bicycling. In this article, we review the evidence that reliance on gasoline-powered transportation is contributing to global climate change, air pollution, and physical inactivity and that this is harmful to human health. Global climate change poses a major threat to human health and in the future could offset the health gains achieved over the last 100 yr. Based on hundreds of scientific studies, there is strong evidence that human-caused greenhouse gas emissions are contributing to global climate change. Climate change is associated with increased severity of storms, flooding, rising sea levels, hotter climates, and drought, all leading to increased morbidity and mortality. Along with increases in atmospheric CO2, other pollutants such as nitrogen dioxide, ozone, and particulate matter (e.g., PM2.5) are released by combustion engines and industry, which can lead to pulmonary and cardiovascular diseases. Also, as car ownership and vehicle miles traveled have increased, the shift toward motorized transport has contributed to physical inactivity. Each of these global challenges has resulted in, or is projected to result in, millions of premature deaths each year. One of the ways that nations can mitigate the health consequences of climate change, air pollution, and chronic diseases is through the use of active transportation. Research indicates that populations that rely heavily on active transportation enjoy better health and increased longevity. In summary, active transportation has tremendous potential to simultaneously address three global public health challenges of the 21st century.

OBJECTIVE. Altered concentrations of essential trace metals have been associated with the development of abdominal tumors. We developed a method to quantify trace metals (iron, copper, and zinc) using monochromatic data from commercially available dual-energy CT (DECT) implementations. CONCLUSION. Our data provide a foundation for the use of DECT for noninvasive quantification of essential trace metals. Minimum detectable concentrations of iron and zinc estimated with DECT overlap with in vivo hepatic concentrations reported in the literature.

Opportunities to share or sell images are common in radiology. But because these images typically originate as protected health information, their use admits a host of ethical and regulatory considerations. This article discusses four scenarios that reflect data sharing or selling arrangements in radiology, especially as they might occur in “big data” systems or applications. The objective of this article is to acquaint radiologists with a variety of regulatory standards and ethical perspectives that pertain to certain data use agreements, such that the attitudes and practices of data holders and their sharers or purchasers can withstand ethical or regulatory scrutiny and not invite undesirable outcomes.

PREAMBLEThe Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional nonprofit medical association founded in 1985 to facilitate communication worldwide among individuals pursuing clinical and academic excellence in nuclear medicine. SNMMI and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine.The SNMMI and EANM will periodically put forth new standards/guidelines for nuclear medicine practice to help advance the science of nuclear medicine and improve service to patients. Existing standards/guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated. Each standard/guideline, representing a policy statement by the SNMMI/EANM, has undergone a thorough consensus process, entailing extensive review. The SNMMI and EANM recognize that the safe and effective use of diagnostic nuclear medicine imaging requires particular training and skills, as described in each document. These standards/guidelines are educational tools designed to assist practitioners in providing appropriate and effective nuclear medicine care for patients. These guidelines are consensus documents, and are not inflexible rules or requirements of practice. They are not intended, nor should they be used, to establish a legal standard of care. For these reasons and those set forth below, the SNMMI and the EANM cautions against the use of these standards/guidelines in litigation in which the clinical decisions of a practitioner are called into question.The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by medical professionals taking into account the unique circumstances of each case. Thus, there is no implication that action differing from what is laid out in the standards/guidelines, standing alone, is below standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the standards/guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources, or advances in knowledge or technology subsequent to publication of the standards/guidelines.The practice of medicine involves not only the science, but also the art of dealing with the prevention, diagnosis, alleviation, and treatment of disease. The variety and complexity of human conditions make it impossible for general guidelines to consistently allow for an accurate diagnosis to be reached or a particular treatment response to be predicted. Therefore, it should be recognized that adherence to these standards/guidelines will not ensure a successful outcome. All that should be expected is that the practitioner follows a reasonable course of action, based on their level of training, the current knowledge, the available resources, and the needs/context of the particular patient being treated.PET and computerized tomography (CT) have been widely used in oncology. 18F-FDG is the most common radiotracer used for PET imaging. The purpose of this document is to provide imaging specialists and clinicians guidelines for recommending, performing, and interpreting 18F-FDG PET/CT in pediatric patients in oncology. There is not a high level of evidence for all recommendations suggested in this paper. These recommendations represent the expert opinions of experienced leaders in this field. Further studies are needed to have evidence-based recommendations for the application of 18F-FDG PET/CT in pediatric oncology. These recommendations should be viewed in the context of good practice of nuclear medicine and are not intended to be a substitute for national and international legal or regulatory provisions.

Purpose Physical and digital phantoms play a key role in the development and testing of nuclear medicine instrumentation and processing algorithms for clinical and research applications, including neuroimaging using positron emission tomography (PET). We have developed and tested a digital reference object (DRO) version of the original segmented magnetic resonance imaging (MRI) data used for the three-dimensional (3D) PET brain phantom developed by Hoffman et al., which is used as the basis of a commercially available physical test phantom. Methods The DRO was constructed by subdividing the MRI image planes the original phantom was based on to create equal-thickness slices and re-labeling voxels. The digital data was then embedded in a PET Digital Imaging and Communications in Medicine format and tested for compliance. Results We then tested the DRO by comparing it to computed tomography (CT) images of the physical phantom summed to form composite slices with axial extent similar to the DRO, but with a factor of two better in-slice resolution. For composite slices, 91% of voxels were labeled in full agreement, 5% of the voxels were 50-75% accurate, and the remaining 4% of voxels had 25% or less agreement. Conclusions This DRO can be used as an input for PET scanner simulation studies or for comparing simulations to measured Hoffman phantom images.

Ovarian torsion is a common concern in girls presenting to emergency care with pelvic or abdominal pain. The diagnosis is challenging to make accurately and quickly, relying on a combination of physical exam, history and radiologic evaluation. Failure to establish the diagnosis in a timely fashion can result in irreversible ovarian ischemia with implications for future fertility. Ultrasound is the mainstay of evaluation for ovarian torsion in the pediatric population. However, even with a high index of suspicion, imaging features are not pathognomonic. We sought to develop an algorithm to aid radiologists in diagnosing ovarian torsion using machine learning from sonographic features and to evaluate the frequency of each sonographic element. All pediatric patients treated for ovarian torsion at a quaternary pediatric hospital over an 11-year period were identified by both an internal radiology database and hospital-based International Statistical Classification of Diseases and Related Health Problems (ICD) code review. Inclusion criteria were surgical confirmation of ovarian torsion and available imaging. Patients were excluded if the diagnosis could not be confirmed, no imaging was available for review, the ovary was not identified by imaging, or torsion involved other adnexal structures but spared the ovary. Data collection included: patient age; laterality of torsion; bilateral ovarian volumes; torsed ovarian position, i.e. whether medialized with respect to the mid-uterine line; presence or absence of Doppler signal within the torsed ovary; visualization of peripheral follicles; and presence of a mass or cyst, and free peritoneal fluid. Subsequently, we evaluated a non-torsed control cohort from April 2015 to May 2016. This cohort consisted of sequential girls and young adults presenting to the emergency department with abdominopelvic symptoms concerning for ovarian torsion but who were ultimately diagnosed otherwise. These features were then fed into supervised machine learning systems to identify and develop viable decision algorithms. We divided data into training and validation sets and assessed algorithm performance using sub-sets of the validation set. We identified 119 torsion-confirmed cases and 331 torsion-absent cases. Of the torsion-confirmed cases, significant imaging differences were evident for girls younger than 1 year; these girls were then excluded from analysis, and 99 pediatric patients older than 1 year were included in our study. Among these 99, all variables demonstrated statistically significant differences between the torsion-confirmed and torsion-absent groups with P-values

Purpose This study aims to assess the effectiveness of Microfragmented Autologous Fat Tissue (MFAT) treatment for knee osteoarthritis and to investigate whether patients’ pre-treatment clinical condition, such as synovitis, correlates with clinical outcomes, to identify potential predicting factors for the success or failure of the treatment. Methods In this prospective Cohort Study Level II multicentric trial, consecutive patients with a diagnosis of early/mild osteoarthritis and failure of previous conservative measures were enrolled to undergo diagnostic arthroscopy and a single MFAT injection. Patients were assessed with repeated scoring systems at baseline, 6 months, and 12 months after surgery. The demographic features, the arthroscopic findings, the immunophenotype of injected tissue and the histologic examination of synovia of failed patients were analyzed. Results Data from 91 patients showed a significant improvement in Lysholm, WOMAC scores at 1-year follow-up (p Age and synovitis were identified as significant factors influencing the clinical outcome (p Conclusion MFAT is effective in reducing pain when used with a single dose injection in early/mild OA of the knee, without major complications. Age over 60 and synovitis may be predictive for persistent pain at one year and should be considered before indications.

Autonomic cardiac function can be indirectly detected non-invasively by measuring the variation in microtiming of heart beats by a method known as heart rate variability (HRV). Aerobic training for sport is associated with reduced risk for some factors associated with cardiovascular diseases (CVD), but effects on autonomic function in different athlete types are less known. To compare cardiac autonomic modulation using a standard protocol and established CVD risk factors in highly trained intercollegiate athletes competing in aerobic, explosive, and cross-trained sports. A total of 176 college athletes were categorized in distinct sports as explosive (EA), aerobic (AA), or cross-trained (mixed) athletes. Eight different HRV measures obtained at rest were compared across training type and five health factors: systolic (SBP), diastolic blood pressure (DBP), body weight (BW), sex, and race. All athletic types shared favorable HRV measures that correlated with low CVD risk factors and indicated normal sympathovagal balance. A significant correlation was reported between DBP and pNN50 (% RR intervals &gt, 50 ms) (β = −0.214, p = 0.011) and between BW and low-frequency (LF) power (β = 0.205, p = 0.006). Caucasian and African American athletes differed significantly (p &lt, 0.05) with respect to four HRV variables: pNN50, HF power, LF power, and LF/HF ratios. Explosive, aerobic and mixed athletes had similar cardiovascular and autonomic HRV results in all eight HRV parameters measured. All athletes reported LF and pNN50 values that were significantly correlated with two CVD risk factors: DBP and BW. Compared with Caucasian teammates, African American athletes demonstrated lower LF/HF and higher pNN50, indicating an even more favorable resting sympathovagal activity and healthy CV function.

Introduction: Systemic juvenile idiopathic arthritis (sJIA) accounts for 10-20% of all patients with JIA. The demonstration of a key role of IL-1 and IL-6 in the pathogenesis of the disease, led to consider sJIA an autoinflammatory disease: this explain the successfully use of IL-1 and IL-6 inhibitors. While the efficacy and safety of anakinra in sJIA is widely documented, there are no reports on large series of patients treated with canakinumab outside of the setting of clinical trials. Objectives: The aim of this study was to evaluate clinical response rate and disease course of canakinumab in Italian cohort of patients with sJIA. Methods: This is a retrospective multicenter study. Demographic features, previous medical history and therapies was evaluated for each patients. Clinical features, laboratory parameters and adverse events were collected at baseline and after 6 months from starting canakinumab. Clinically inactive disease (CID) was defined according to Wallace criteria. Results: We enrolled 82 (50 F) patients with sJIA treated with canakinumab from 2006 to 2020; 75 of them reached a follow up of 6 months. At baseline 49 patients (59.8%), of which 36 in active disease (AD) and 13 in CID, were previously treated with anakinra, while 33 patients in AD (40.2%) were naïve. At 6 months of follow-up 51/75 patients (68%) met criteria of CID off-glucocorticoids, including all 13 patients in CID at baseline, 19 patients in AD previously treated with anakinra and 19 patients naïve. Twenty-four patients (32%) maintained AD. To evaluated if the response to canakinumab might be related to the baseline features we excluded 13 patients in CID at baseline; we divided the 62 patients in responders (38/62, 61.3%) and non-responders (24/62, 38.7%). There were no significant differences between the two groups regarding demographic, clinical and laboratory parameters, except for a higher number of active joints (p=0.021) and for a greater use of disease-modifying antirheumatic drugs (DMARDs) (p

Introduction: Colchicine is the standard treatment for Familiar Mediterranean Fever (FMF), however about 5% of patients (pts) experience colchicine resistance. There is no standard definition of colchicine resistance. Recently a panel of experts elaborated a new definition based on a Delphi consensus approach. Objectives: We aim to describe main features of the disease and clinical outcome of a cohort of FMF pts with particular interest on the colchicine resistance and tolerability according to the definitions proposed by the recent consensus.

In many diagnostic imaging settings, including positron emission tomography (PET), images are typically used for multiple tasks such as detecting disease and quantifying disease. Unlike conventional image reconstruction that optimizes a single objective, this work proposes a multi-objective optimization algorithm for PET image reconstruction to identify a set of images that are optimal for more than one task. This work is reliant on a genetic algorithm to evolve a set of solutions that satisfies two distinct objectives. In this paper, we defined the objectives as the commonly used Poisson log-likelihood function, typically reflective of quantitative accuracy, and a variant of the generalized scan-statistic model, to reflect detection performance. The genetic algorithm uses new mutation and crossover operations at each iteration. After each iteration, the child population is selected with non-dominated sorting to identify the set of solutions along the dominant front or fronts. After multiple iterations, these fronts approach a single non-dominated optimal front, defined as the set of PET images for which none the objective function values can be improved without reducing the opposing objective function. This method was applied to simulated 2D PET data of the heart and liver with hot features. We compared this approach to conventional, single-objective approaches for trading off performance: maximum likelihood estimation with increasing explicit regularization and maximum a posteriori estimation with varying penalty strength. Results demonstrate that the proposed method generates solutions with comparable to improved objective function values compared to the conventional approaches for trading off performance amongst different tasks. In addition, this approach identifies a diverse set of solutions in the multi-objective function space which can be challenging to estimate with single-objective formulations.

Active transportation is defined as self-propelled, human-powered transportation modes, such as walking and bicycling. In this article, we review the evidence that reliance on gasoline-powered transportation is contributing to global climate change, air pollution, and physical inactivity and that this is harmful to human health. Global climate change poses a major threat to human health and in the future could offset the health gains achieved over the last 100 yr. Based on hundreds of scientific studies, there is strong evidence that human-caused greenhouse gas emissions are contributing to global climate change. Climate change is associated with increased severity of storms, flooding, rising sea levels, hotter climates, and drought, all leading to increased morbidity and mortality. Along with increases in atmospheric CO2, other pollutants such as nitrogen dioxide, ozone, and particulate matter (e.g., PM2.5) are released by combustion engines and industry, which can lead to pulmonary and cardiovascular diseases. Also, as car ownership and vehicle miles traveled have increased, the shift toward motorized transport has contributed to physical inactivity. Each of these global challenges has resulted in, or is projected to result in, millions of premature deaths each year. One of the ways that nations can mitigate the health consequences of climate change, air pollution, and chronic diseases is through the use of active transportation. Research indicates that populations that rely heavily on active transportation enjoy better health and increased longevity. In summary, active transportation has tremendous potential to simultaneously address three global public health challenges of the 21st century.