Plate-specific gain map correction for the improvement of detective quantum efficiency in computed radiography.

PURPOSE: The purpose of this work is to improve the noise power spectrum (NPS), and thus the detective quantum efficiency (DQE), of computed radiography (CR) images by correcting for spatial gain variations specific to individual imaging plates. CR devices have not traditionally employed gain-map corrections, unlike the case with flat-panel detectors, because of the multiplicity of plates used with each reader. The lack of gain-map correction has limited the DQE(f) at higher exposures with CR. This current work describes a feasible solution to generating plate-specific gain maps. METHODS: Ten high-exposure open field images were taken with an RQA5 spectrum, using a sixth generation CR plate suspended in air without a cassette. Image values were converted to exposure, the plates registered using fiducial dots on the plate, the ten images averaged, and then high-pass filtered to remove low frequency contributions from field inhomogeneity. A gain-map was then produced by converting all pixel values in the average into fractions with mean of one. The resultant gain-map of the plate was used to normalize subsequent single images to correct for spatial gain fluctuation. To validate performance, the normalized NPS (NNPS) for all images was calculated both with and without the gain-map correction. Variations in the quality of correction due to exposure levels, beam voltage/spectrum, CR reader used, and registration were investigated. RESULTS: The NNPS with plate-specific gain-map correction showed improvement over the noncorrected case over the range of frequencies from 0.15 to 2.5 mm(-1). At high exposure (40 mR), NNPS was 50%-90% better with gain-map correction than without. A small further improvement in NNPS was seen from carefully registering the gain-map with subsequent images using small fiducial dots, because of slight misregistration during scanning. Further improvement was seen in the NNPS from scaling the gain map about the mean to account for different beam spectra. CONCLUSIONS: This study demonstrates that a simple gain-map can be used to correct for the fixed-pattern noise in a given plate and thus improve the DQE of CR imaging. Such a method could easily be implemented by manufacturers because each plate has a unique bar code and the gain-map for all plates associated with a reader could be stored for future retrieval. These experiments indicated that an improvement in NPS (and hence, DQE) is possible, depending on exposure level, over a wide range of frequencies with this technique.

Establishing a regional, multisite database for quality improvement and service planning in community-based palliative care and hospice.

BACKGROUND: Outpatient palliative care, an evolving delivery model, seeks to improve continuity of care across settings and to increase access to services in hospice and palliative medicine (HPM). It can provide a critical bridge between inpatient palliative care and hospice, filling the gap in community-based supportive care for patients with advanced life-limiting illness. Low capacities for data collection and quantitative research in HPM have impeded assessment of the impact of outpatient palliative care. APPROACH: In North Carolina, a regional database for community-based palliative care has been created through a unique partnership between a HPM organization and academic medical center. This database flexibly uses information technology to collect patient data, entered at the point of care (e.g., home, inpatient hospice, assisted living facility, nursing home). HPM physicians and nurse practitioners collect data; data are transferred to an academic site that assists with analyses and data management. Reports to community-based sites, based on data they provide, create a better understanding of local care quality. CURRENT STATUS: The data system was developed and implemented over a 2-year period, starting with one community-based HPM site and expanding to four. Data collection methods were collaboratively created and refined. The database continues to grow. Analyses presented herein examine data from one site and encompass 2572 visits from 970 new patients, characterizing the population, symptom profiles, and change in symptoms after intervention. CONCLUSION: A collaborative regional approach to HPM data can support evaluation and improvement of palliative care quality at the local, aggregated, and statewide levels.

Traumatic brain injury exacerbates neurodegenerative pathology: improvement with an apolipoprotein E-based therapeutic.

Cognitive impairment is common following traumatic brain injury (TBI), and neuroinflammatory mechanisms may predispose to the development of neurodegenerative disease. Apolipoprotein E (apoE) polymorphisms modify neuroinflammatory responses, and influence both outcome from acute brain injury and the risk of developing neurodegenerative disease. We demonstrate that TBI accelerates neurodegenerative pathology in double-transgenic animals expressing the common human apoE alleles and mutated amyloid precursor protein, and that pathology is exacerbated in the presence of the apoE4 allele. The administration of an apoE-mimetic peptide markedly reduced the development of neurodegenerative pathology in mice homozygous for apoE3 as well as apoE3/E4 heterozygotes. These results demonstrate that TBI accelerates the cardinal neuropathological features of neurodegenerative disease, and establishes the potential for apoE mimetic therapies in reducing pathology associated with neurodegeneration.

A randomized clinical trial of a coping improvement group intervention for HIV-infected older adults.

This research tested if a 12-session coping improvement group intervention (n = 104) reduced depressive symptoms in HIV-infected older adults compared to an interpersonal support group intervention (n = 105) and an individual therapy upon request (ITUR) control condition (n = 86). Participants were 295 HIV-infected men and women 50-plus years of age living in New York City, Cincinnati, OH, and Columbus, OH. Using A-CASI assessment methodology, participants provided data on their depressive symptoms using the Geriatric Depression Screening Scale (GDS) at pre-intervention, post-intervention, and 4- and 8-month follow-up. Whether conducted with all participants (N = 295) or only a subset of participants diagnosed with mild, moderate, or severe depressive symptoms (N = 171), mixed models analyses of repeated measures found that both coping improvement and interpersonal support group intervention participants reported fewer depressive symptoms than ITUR controls at post-intervention, 4-month follow-up, and 8-month follow-up. The effect sizes of the differences between the two active interventions and the control group were greater when outcome analyses were limited to those participants with mild, moderate, or severe depressive symptoms. At no assessment period did coping improvement and interpersonal support group intervention participants differ in depressive symptoms.

How actions create--not just reveal--preferences.

The neo-classical economics view that behavior is driven by - and reflective of - hedonic utility is challenged by psychologists' demonstrations of cases in which actions do not merely reveal preferences but rather create them. In this view, preferences are frequently constructed in the moment and are susceptible to fleeting situational factors; problematically, individuals are insensitive to the impact of such factors on their behavior, misattributing utility caused by these irrelevant factors to stable underlying preferences. Consequently, subsequent behavior might reflect not hedonic utility but rather this erroneously imputed utility that lingers in memory. Here we review the roles of these streams of utility in shaping preferences, and discuss how neuroimaging offers unique possibilities for disentangling their independent contributions to behavior.

An evaluation of remifentanil-sevoflurane response surface models in patients emerging from anesthesia: model improvement using effect-site sevoflurane concentrations.

INTRODUCTION: We previously reported models that characterized the synergistic interaction between remifentanil and sevoflurane in blunting responses to verbal and painful stimuli. This preliminary study evaluated the ability of these models to predict a return of responsiveness during emergence from anesthesia and a response to tibial pressure when patients required analgesics in the recovery room. We hypothesized that model predictions would be consistent with observed responses. We also hypothesized that under non-steady-state conditions, accounting for the lag time between sevoflurane effect-site concentration (Ce) and end-tidal (ET) concentration would improve predictions. METHODS: Twenty patients received a sevoflurane, remifentanil, and fentanyl anesthetic. Two model predictions of responsiveness were recorded at emergence: an ET-based and a Ce-based prediction. Similarly, 2 predictions of a response to noxious stimuli were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. RESULTS: While patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). However, after termination of the anesthetic, models exhibited a wide range of predictions at emergence (1%-97%). Although wide, the Ce-based predictions of responsiveness were better distributed over a percentage ranking of observations than the ET-based predictions. For the ET-based model, 45% of the patients awoke within 2 min of the 50% model predicted probability of unresponsiveness and 65% awoke within 4 min. For the Ce-based model, 45% of the patients awoke within 1 min of the 50% model predicted probability of unresponsiveness and 85% awoke within 3.2 min. Predictions of a response to a painful stimulus in the recovery room were similar for the Ce- and ET-based models. DISCUSSION: Results confirmed, in part, our study hypothesis; accounting for the lag time between Ce and ET sevoflurane concentrations improved model predictions of responsiveness but had no effect on predicting a response to a noxious stimulus in the recovery room. These models may be useful in predicting events of clinical interest but large-scale evaluations with numerous patients are needed to better characterize model performance.

Signal Improvement and Contrast Enhancement in Magnetic Resonance Imaging

This thesis reports advances in magnetic resonance imaging (MRI), with the ultimate goal of improving signal and contrast in biomedical applications. More specifically, novel MRI pulse sequences have been designed to characterize microstructure, enhance signal and contrast in tissue, and image functional processes. In this thesis, rat brain and red bone marrow images are acquired using iMQCs (intermolecular multiple quantum coherences) between spins that are 10 μm to 500 μm apart. As an important application, iMQCs images in different directions can be used for anisotropy mapping. We investigate tissue microstructure by analyzing anisotropy mapping. At the same time, we simulated images expected from rat brain without microstructure. We compare those with experimental results to prove that the dipolar field from the overall shape only has small contributions to the experimental iMQC signal. Besides magnitude of iMQCs, phase of iMQCs should be studied as well. The phase anisotropy maps built by our method can clearly show susceptibility information in kidneys. It may provide meaningful diagnostic information. To deeply study susceptibility, the modified-crazed sequence is developed. Combining phase data of modified-crazed images and phase data of iMQCs images is very promising to construct microstructure maps. Obviously, the phase image in all above techniques needs to be highly-contrasted and clear. To achieve the goal, algorithm tools from Susceptibility-Weighted Imaging (SWI) and Susceptibility Tensor Imaging (STI) stands out superb useful and creative in our system.

Improvement in visual search with practice: mapping learning-related changes in neurocognitive stages of processing.

Practice can improve performance on visual search tasks; the neural mechanisms underlying such improvements, however, are not clear. Response time typically shortens with practice, but which components of the stimulus-response processing chain facilitate this behavioral change? Improved search performance could result from enhancements in various cognitive processing stages, including (1) sensory processing, (2) attentional allocation, (3) target discrimination, (4) motor-response preparation, and/or (5) response execution. We measured event-related potentials (ERPs) as human participants completed a five-day visual-search protocol in which they reported the orientation of a color popout target within an array of ellipses. We assessed changes in behavioral performance and in ERP components associated with various stages of processing. After practice, response time decreased in all participants (while accuracy remained consistent), and electrophysiological measures revealed modulation of several ERP components. First, amplitudes of the early sensory-evoked N1 component at 150 ms increased bilaterally, indicating enhanced visual sensory processing of the array. Second, the negative-polarity posterior-contralateral component (N2pc, 170-250 ms) was earlier and larger, demonstrating enhanced attentional orienting. Third, the amplitude of the sustained posterior contralateral negativity component (SPCN, 300-400 ms) decreased, indicating facilitated target discrimination. Finally, faster motor-response preparation and execution were observed after practice, as indicated by latency changes in both the stimulus-locked and response-locked lateralized readiness potentials (LRPs). These electrophysiological results delineate the functional plasticity in key mechanisms underlying visual search with high temporal resolution and illustrate how practice influences various cognitive and neural processing stages leading to enhanced behavioral performance.

Computational Methods for RNA Structure Validation and Improvement.

With increasing recognition of the roles RNA molecules and RNA/protein complexes play in an unexpected variety of biological processes, understanding of RNA structure-function relationships is of high current importance. To make clean biological interpretations from three-dimensional structures, it is imperative to have high-quality, accurate RNA crystal structures available, and the community has thoroughly embraced that goal. However, due to the many degrees of freedom inherent in RNA structure (especially for the backbone), it is a significant challenge to succeed in building accurate experimental models for RNA structures. This chapter describes the tools and techniques our research group and our collaborators have developed over the years to help RNA structural biologists both evaluate and achieve better accuracy. Expert analysis of large, high-resolution, quality-conscious RNA datasets provides the fundamental information that enables automated methods for robust and efficient error diagnosis in validating RNA structures at all resolutions. The even more crucial goal of correcting the diagnosed outliers has steadily developed toward highly effective, computationally based techniques. Automation enables solving complex issues in large RNA structures, but cannot circumvent the need for thoughtful examination of local details, and so we also provide some guidance for interpreting and acting on the results of current structure validation for RNA.

CT Scan Dosimetric Parameters Routine Monitoring: First Results of Radiation Dose Optimization Strategies Promptly Provided by a Multidisciplinary Team

CONCLUSION Radiation dose reduction, while saving image quality could be easily implemented with this approach. Furthermore, the availability of a dosimetric data archive provides immediate feedbacks, related to the implemented optimization strategies. Background JCI Standards and European Legislation (EURATOM 59/2013) require the implementation of patient radiation protection programs in diagnostic radiology. Aim of this study is to demonstrate the possibility to reduce patients radiation exposure without decreasing image quality, through a multidisciplinary team (MT), which analyzes dosimetric data of diagnostic examinations. Evaluation Data from CT examinations performed with two different scanners (Siemens DefinitionTM and GE LightSpeed UltraTM) between November and December 2013 are considered. CT scanners are configured to automatically send images to DoseWatch© software, which is able to store output parameters (e.g. kVp, mAs, pitch ) and exposure data (e.g. CTDIvol, DLP, SSDE). Data are analyzed and discussed by a MT composed by Medical Physicists and Radiologists, to identify protocols which show critical dosimetric values, then suggest possible improvement actions to be implemented. Furthermore, the large amount of data available allows to monitor diagnostic protocols currently in use and to identify different statistic populations for each of them. Discussion We identified critical values of average CTDIvol for head and facial bones examinations (respectively 61.8 mGy, 151 scans; 61.6 mGy, 72 scans), performed with the GE LightSpeed CTTM. Statistic analysis allowed us to identify the presence of two different populations for head scan, one of which was only 10% of the total number of scans and corresponded to lower exposure values. The MT adopted this protocol as standard. Moreover, the constant output parameters monitoring allowed us to identify unusual values in facial bones exams, due to changes during maintenance service, which the team promptly suggested to correct. This resulted in a substantial dose saving in CTDIvol average values of approximately 15% and 50% for head and facial bones exams, respectively. Diagnostic image quality was deemed suitable for clinical use by radiologists.

Competing Actions of Type 1 Angiotensin II Receptors Expressed on T Lymphocytes and Kidney Epithelium during Cisplatin-Induced AKI.

Inappropriate activation of the renin-angiotensin system (RAS) contributes to many CKDs. However, the role of the RAS in modulating AKI requires elucidation, particularly because stimulating type 1 angiotensin II (AT1) receptors in the kidney or circulating inflammatory cells can have opposing effects on the generation of inflammatory mediators that underpin the pathogenesis of AKI. For example, TNF-α is a fundamental driver of cisplatin nephrotoxicity, and generation of TNF-α is suppressed or enhanced by AT1 receptor signaling in T lymphocytes or the distal nephron, respectively. In this study, cell tracking experiments with CD4-Cre mT/mG reporter mice revealed robust infiltration of T lymphocytes into the kidney after cisplatin injection. Notably, knockout of AT1 receptors on T lymphocytes exacerbated the severity of cisplatin-induced AKI and enhanced the cisplatin-induced increase in TNF-α levels locally within the kidney and in the systemic circulation. In contrast, knockout of AT1 receptors on kidney epithelial cells ameliorated the severity of AKI and suppressed local and systemic TNF-α production induced by cisplatin. Finally, disrupting TNF-α production specifically within the renal tubular epithelium attenuated the AKI and the increase in circulating TNF-α levels induced by cisplatin. These results illustrate discrepant tissue-specific effects of RAS stimulation on cisplatin nephrotoxicity and raise the concern that inflammatory mediators produced by renal parenchymal cells may influence the function of remote organs by altering systemic cytokine levels. Our findings suggest selective inhibition of AT1 receptors within the nephron as a promising intervention for protecting patients from cisplatin-induced nephrotoxicity.