15 resultados para Early detection

em Duke University


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The early detection of hepatocellular carcinoma (HCC) presents a challenge because of the lack of specific biomarkers. Serum/plasma microRNAs (miRNAs) can discriminate HCC patients from controls. We aimed to identify and evaluate HCC-associated plasma miRNAs originating from the liver as early biomarkers for detecting HCC. In this multicenter three-phase study, we first performed screening using both plasma (HCC before and after liver transplantation or liver hepatectomy) and tissue samples (HCC, para-carcinoma and cirrhotic tissues). Then, we evaluated the diagnostic potential of the miRNAs in two case-control studies (training and validation sets). Finally, we used two prospective cohorts to test the potential of the identified miRNAs for the early detection of HCC. During the screening phase, we identified ten miRNAs, eight of which (miR-20a-5p, miR-25-3p, miR-30a-5p, miR-92a-3p, miR-132-3p, miR-185-5p, miR-320a and miR-324-3p) were significantly overexpressed in the HBV-positive HCC patients compared with the HBV-positive cancer-free controls in both the training and validation sets, with a sensitivity of 0.866 and specificity of 0.646. Furthermore, we assessed the potential for early HCC detection of these eight newly identified miRNAs and three previously reported miRNAs (miR-192-5p, miR-21-5p and miR-375) in two prospective cohorts. Our meta-analysis revealed that four miRNAs (miR-20a-5p, miR-320a, miR-324-3p and miR-375) could be used as preclinical biomarkers (pmeta  < 0.05) for HCC. The expression profile of the eight-miRNA panel can be used to discriminate HCC patients from cancer-free controls, and the four-miRNA panel (alone or combined with AFP) could be a blood-based early detection biomarker for HCC screening.

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Carbon Capture and Storage may use deep saline aquifers for CO(2) sequestration, but small CO(2) leakage could pose a risk to overlying fresh groundwater. We performed laboratory incubations of CO(2) infiltration under oxidizing conditions for >300 days on samples from four freshwater aquifers to 1) understand how CO(2) leakage affects freshwater quality; 2) develop selection criteria for deep sequestration sites based on inorganic metal contamination caused by CO(2) leaks to shallow aquifers; and 3) identify geochemical signatures for early detection criteria. After exposure to CO(2), water pH declines of 1-2 units were apparent in all aquifer samples. CO(2) caused concentrations of the alkali and alkaline earths and manganese, cobalt, nickel, and iron to increase by more than 2 orders of magnitude. Potentially dangerous uranium and barium increased throughout the entire experiment in some samples. Solid-phase metal mobility, carbonate buffering capacity, and redox state in the shallow overlying aquifers influence the impact of CO(2) leakage and should be considered when selecting deep geosequestration sites. Manganese, iron, calcium, and pH could be used as geochemical markers of a CO(2) leak, as their concentrations increase within 2 weeks of exposure to CO(2).

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Quantitative optical spectroscopy has the potential to provide an effective low cost, and portable solution for cervical pre-cancer screening in resource-limited communities. However, clinical studies to validate the use of this technology in resource-limited settings require low power consumption and good quality control that is minimally influenced by the operator or variable environmental conditions in the field. The goal of this study was to evaluate the effects of two sources of potential error: calibration and pressure on the extraction of absorption and scattering properties of normal cervical tissues in a resource-limited setting in Leogane, Haiti. Our results show that self-calibrated measurements improved scattering measurements through real-time correction of system drift, in addition to minimizing the time required for post-calibration. Variations in pressure (tested without the potential confounding effects of calibration error) caused local changes in vasculature and scatterer density that significantly impacted the tissue absorption and scattering properties Future spectroscopic systems intended for clinical use, particularly where operator training is not viable and environmental conditions unpredictable, should incorporate a real-time self-calibration channel and collect diffuse reflectance spectra at a consistent pressure to maximize data integrity.

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OBJECTIVES: To compare the predictive performance and potential clinical usefulness of risk calculators of the European Randomized Study of Screening for Prostate Cancer (ERSPC RC) with and without information on prostate volume. METHODS: We studied 6 cohorts (5 European and 1 US) with a total of 15,300 men, all biopsied and with pre-biopsy TRUS measurements of prostate volume. Volume was categorized into 3 categories (25, 40, and 60 cc), to reflect use of digital rectal examination (DRE) for volume assessment. Risks of prostate cancer were calculated according to a ERSPC DRE-based RC (including PSA, DRE, prior biopsy, and prostate volume) and a PSA + DRE model (including PSA, DRE, and prior biopsy). Missing data on prostate volume were completed by single imputation. Risk predictions were evaluated with respect to calibration (graphically), discrimination (AUC curve), and clinical usefulness (net benefit, graphically assessed in decision curves). RESULTS: The AUCs of the ERSPC DRE-based RC ranged from 0.61 to 0.77 and were substantially larger than the AUCs of a model based on only PSA + DRE (ranging from 0.56 to 0.72) in each of the 6 cohorts. The ERSPC DRE-based RC provided net benefit over performing a prostate biopsy on the basis of PSA and DRE outcome in five of the six cohorts. CONCLUSIONS: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider multiple factors, including an estimate of prostate volume.

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BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

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The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated which promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests that behavioral signs can be observed late in the first year of life. Many of these studies involve extensive frame-by-frame video observation and analysis of a child's natural behavior. Although nonintrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are burdensome for clinical and large population research purposes. This work is a first milestone in a long-term project on non-invasive early observation of children in order to aid in risk detection and research of neurodevelopmental disorders. We focus on providing low-cost computer vision tools to measure and identify ASD behavioral signs based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure responses to general ASD risk assessment tasks and activities outlined by the AOSI which assess visual attention by tracking facial features. We show results, including comparisons with expert and nonexpert clinicians, which demonstrate that the proposed computer vision tools can capture critical behavioral observations and potentially augment the clinician's behavioral observations obtained from real in-clinic assessments.

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The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.

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Our long-term goal is the detection and characterization of vulnerable plaque in the coronary arteries of the heart using intravascular ultrasound (IVUS) catheters. Vulnerable plaque, characterized by a thin fibrous cap and a soft, lipid-rich necrotic core is a precursor to heart attack and stroke. Early detection of such plaques may potentially alter the course of treatment of the patient to prevent ischemic events. We have previously described the characterization of carotid plaques using external linear arrays operating at 9 MHz. In addition, we previously modified circular array IVUS catheters by short-circuiting several neighboring elements to produce fixed beamwidths for intravascular hyperthermia applications. In this paper, we modified Volcano Visions 8.2 French, 9 MHz catheters and Volcano Platinum 3.5 French, 20 MHz catheters by short-circuiting portions of the array for acoustic radiation force impulse imaging (ARFI) applications. The catheters had an effective transmit aperture size of 2 mm and 1.5 mm, respectively. The catheters were connected to a Verasonics scanner and driven with pushing pulses of 180 V p-p to acquire ARFI data from a soft gel phantom with a Young's modulus of 2.9 kPa. The dynamic response of the tissue-mimicking material demonstrates a typical ARFI motion of 1 to 2 microns as the gel phantom displaces away and recovers back to its normal position. The hardware modifications applied to our IVUS catheters mimic potential beamforming modifications that could be implemented on IVUS scanners. Our results demonstrate that the generation of radiation force from IVUS catheters and the development of intravascular ARFI may be feasible.

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BACKGROUND: Automated reporting of estimated glomerular filtration rate (eGFR) is a recent advance in laboratory information technology (IT) that generates a measure of kidney function with chemistry laboratory results to aid early detection of chronic kidney disease (CKD). Because accurate diagnosis of CKD is critical to optimal medical decision-making, several clinical practice guidelines have recommended the use of automated eGFR reporting. Since its introduction, automated eGFR reporting has not been uniformly implemented by U. S. laboratories despite the growing prevalence of CKD. CKD is highly prevalent within the Veterans Health Administration (VHA), and implementation of automated eGFR reporting within this integrated healthcare system has the potential to improve care. In July 2004, the VHA adopted automated eGFR reporting through a system-wide mandate for software implementation by individual VHA laboratories. This study examines the timing of software implementation by individual VHA laboratories and factors associated with implementation. METHODS: We performed a retrospective observational study of laboratories in VHA facilities from July 2004 to September 2009. Using laboratory data, we identified the status of implementation of automated eGFR reporting for each facility and the time to actual implementation from the date the VHA adopted its policy for automated eGFR reporting. Using survey and administrative data, we assessed facility organizational characteristics associated with implementation of automated eGFR reporting via bivariate analyses. RESULTS: Of 104 VHA laboratories, 88% implemented automated eGFR reporting in existing laboratory IT systems by the end of the study period. Time to initial implementation ranged from 0.2 to 4.0 years with a median of 1.8 years. All VHA facilities with on-site dialysis units implemented the eGFR software (52%, p<0.001). Other organizational characteristics were not statistically significant. CONCLUSIONS: The VHA did not have uniform implementation of automated eGFR reporting across its facilities. Facility-level organizational characteristics were not associated with implementation, and this suggests that decisions for implementation of this software are not related to facility-level quality improvement measures. Additional studies on implementation of laboratory IT, such as automated eGFR reporting, could identify factors that are related to more timely implementation and lead to better healthcare delivery.

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The goal of my Ph.D. thesis is to enhance the visualization of the peripheral retina using wide-field optical coherence tomography (OCT) in a clinical setting.

OCT has gain widespread adoption in clinical ophthalmology due to its ability to visualize the diseases of the macula and central retina in three-dimensions, however, clinical OCT has a limited field-of-view of 300. There has been increasing interest to obtain high-resolution images outside of this narrow field-of-view, because three-dimensional imaging of the peripheral retina may prove to be important in the early detection of neurodegenerative diseases, such as Alzheimer's and dementia, and the monitoring of known ocular diseases, such as diabetic retinopathy, retinal vein occlusions, and choroid masses.

Before attempting to build a wide-field OCT system, we need to better understand the peripheral optics of the human eye. Shack-Hartmann wavefront sensors are commonly used tools for measuring the optical imperfections of the eye, but their acquisition speed is limited by their underlying camera hardware. The first aim of my thesis research is to create a fast method of ocular wavefront sensing such that we can measure the wavefront aberrations at numerous points across a wide visual field. In order to address aim one, we will develop a sparse Zernike reconstruction technique (SPARZER) that will enable Shack-Hartmann wavefront sensors to use as little as 1/10th of the data that would normally be required for an accurate wavefront reading. If less data needs to be acquired, then we can increase the speed at which wavefronts can be recorded.

For my second aim, we will create a sophisticated optical model that reproduces the measured aberrations of the human eye. If we know how the average eye's optics distort light, then we can engineer ophthalmic imaging systems that preemptively cancel inherent ocular aberrations. This invention will help the retinal imaging community to design systems that are capable of acquiring high resolution images across a wide visual field. The proposed model eye is also of interest to the field of vision science as it aids in the study of how anatomy affects visual performance in the peripheral retina.

Using the optical model from aim two, we will design and reduce to practice a clinical OCT system that is capable of imaging a large (800) field-of-view with enhanced visualization of the peripheral retina. A key aspect of this third and final aim is to make the imaging system compatible with standard clinical practices. To this end, we will incorporate sensorless adaptive optics in order to correct the inter- and intra- patient variability in ophthalmic aberrations. Sensorless adaptive optics will improve both the brightness (signal) and clarity (resolution) of features in the peripheral retina without affecting the size of the imaging system.

The proposed work should not only be a noteworthy contribution to the ophthalmic and engineering communities, but it should strengthen our existing collaborations with the Duke Eye Center by advancing their capability to diagnose pathologies of the peripheral retinal.

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Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

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Visual inspection with Acetic Acid (VIA) and Visual Inspection with Lugol’s Iodine (VILI) are increasingly recommended in various cervical cancer screening protocols in low-resource settings. Although VIA is more widely used, VILI has been advocated as an easier and more specific screening test. VILI has not been well-validated as a stand-alone screening test, compared to VIA or validated for use in HIV-infected women. We carried out a randomized clinical trial to compare the diagnostic accuracy of VIA and VILI among HIV-infected women. Women attending the Family AIDS Care and Education Services (FACES) clinic in western Kenya were enrolled and randomized to undergo either VIA or VILI with colposcopy. Lesions suspicious for cervical intraepithelial neoplasia 2 or greater (CIN2+) were biopsied. Between October 2011 and June 2012, 654 were randomized to undergo VIA or VILI. The test positivity rates were 26.2% for VIA and 30.6% for VILI (p = 0.22). The rate of detection of CIN2+ was 7.7% in the VIA arm and 11.5% in the VILI arm (p = 0.10). There was no significant difference in the diagnostic performance of VIA and VILI for the detection of CIN2+. Sensitivity and specificity were 84.0% and 78.6%, respectively, for VIA and 84.2% and 76.4% for VILI. The positive and negative predictive values were 24.7% and 98.3% for VIA, and 31.7% and 97.4% for VILI. Among women with CD4+ count < 350, VILI had a significantly decreased specificity (66.2%) compared to VIA in the same group (83.9%, p = 0.02) and compared to VILI performed among women with CD4+ count ≥ 350 (79.7%, p = 0.02). VIA and VILI had similar diagnostic accuracy and rates of CIN2+ detection among HIV-infected women.

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BACKGROUND: A number of studies have identified male involvement as an important factor affecting reproductive health outcomes, particularly in the areas of family planning, antenatal care, and HIV care. As access to cervical cancer screening programs improves in resource-poor settings, particularly through the integration of HIV and cervical cancer services, it is important to understand the role of male partner support in women's utilization of screening and treatment. METHODS: We administered an oral survey to 110 men in Western Kenya about their knowledge and attitudes regarding cervical cancer and cervical cancer screening. Men who had female partners eligible for cervical cancer screening were recruited from government health facilities where screening was offered free of charge. RESULTS: Specific knowledge about cervical cancer risk factors, prevention, and treatment was low. Only half of the men perceived their partners to be at risk for cervical cancer, and many reported that a positive screen would be emotionally upsetting. Nevertheless, all participants said they would encourage their partners to get screened. CONCLUSIONS: Future interventions should tailor cervical cancer educational opportunities towards men. Further research is needed among both men and couples to better understand barriers to male support for screening and treatment and to determine how to best involve men in cervical cancer prevention efforts.

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There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.

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Traumatic brain injury (TBI) has been increasingly accepted as a major external risk factor for neurodegenerative morbidity and mortality. Recent evidence indicates that the resultant chronic neurobiological sequelae following head trauma may, at least in part, contribute to a pathologically distinct disease known as Chronic Traumatic Encephalopathy (CTE). The clinical manifestation of CTE is variable, but the symptoms of this progressive disease include impaired memory and cognition, affective disorders (i.e., impulsivity, aggression, depression, suicidality, etc.), and diminished motor control. Notably, mounting evidence suggests that the pathology contributing to CTE may be caused by repetitive exposure to subconcussive hits to the head, even in those with no history of a clinically evident head injury. Given the millions of athletes and military personnel with potential exposure to repetitive subconcussive insults and TBI, CTE represents an important public health issue. However, the incidence rates and pathological mechanisms are still largely unknown, primarily due to the fact that there is no in vivo diagnostic tool. The primary objective of this manuscript is to address this limitation and discuss potential neuroimaging modalities that may be capable of diagnosing CTE in vivo through the detection of tau and other known pathological features. Additionally, we will discuss the challenges of TBI research, outline the known pathology of CTE (with an emphasis on Tau), review current neuroimaging modalities to assess the potential routes for in vivo diagnosis, and discuss the future directions of CTE research.