NOVEL METHODS OF MERIDIONAL AND CIRCUMFERENTIAL ANTERIOR CHAMBER ANGLE IMAGING

Ph.DDOCTOR OF PHILOSOPH

Translational Medicine in the Era of Social Media: A Survey of Scientific and Clinical Communities

Background: The integration of new scientific discoveries into clinical practice costs considerable time and resources. With the increased use of social media for scientific communication, new opportunities arise to "bridge the gap" in translational medicine. The present study aimed to investigate how medical professionals access scientific information and understand their view on the role of social media in translational medicine. Methods: A questionnaire regarding (i) the use of social media for scientific updates, (ii) the opportunities and challenges of social media for translational medicine, (iii) social media function Chatbot, and (iv) participant demographics was developed. The survey link was posted online from February, 2018, until April, 2018. Results: A total of 555 professionals responded to the survey. Respondents identified themselves predominantly as researcher/scientists (27%) or medical/biomedical students (15%). The majority of participants was employed at a university or research institute (59%), and most practiced either in Europe (48%) or in Asia (37%). Seventy-eight percent of respondents reported receiving most of scientific news and updates via non-social media options, such as journal websites and newspapers. Fifty-one percent of respondents believed that social media could contribute to closing the gap between scientific discovery and translation to medical application. The most crucial opportunity created by social media was found to be "connecting the right scientist to the right clinician." Participants rated "the translation of scientific finding to clinical practice is too fast before the safety is properly demonstrated" as the most crucial challenge. Half of the respondents were aware of their institutions policy on the professional use of social media. Only 2% of respondents had previously used Chatbot. Conclusions: Overall, medical professionals were positive about the idea that social media could contribute to the progress of translational medicine. However, it is clear that they are still being cautious about using social media for professional purposes. To fully harness the potential of social media on translational medicine, the medical community needs to be provided with educational programs, guidelines, and support infrastructure within social media.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Comorbidities in children hospitalized with severe acute malnutrition

Background: As per the National Family Health Survey-4 data, 7.9% of under-five children in the state of Tamil Nadu are severely wasted. The outcome of hospitalized severe acute malnutrition (SAM) children is dependent on the comorbidities present. Objective: The objective of this study is to describe the comorbid conditions in SAM children hospitalized in a tertiary care center. Methodology: This study was a hospital-based descriptive study, conducted from July 2015 to June 2016. A total number of 200 children, who were admitted with SAM as per the World Health Organization criteria, were included in the study. Systemic illness, anemia, vitamin deficiencies, sepsis, retroviral infection, tuberculosis, pneumonia, acute gastroenteritis, urinary tract infection (UTI), measles, skin infections, and worm infestations were the comorbidities considered. Results: Among 200 hospitalized SAM children, the median (interquartile) age was 15 (11–21.75) months; there were 93 (46.5%) boys. Acute gastroenteritis (57.5%) was the most common comorbidity, followed by pneumonia (44.5%), anemia (27%), systemic illness (17%), worm infestation (13.5%), UTI (13.5%), sepsis (13%), skin infection (8%), measles (6%), vitamin deficiency (4%), retroviral infections (3.5%), and tuberculosis (1%). The case fatality rate was 10.5%. Conclusion: Prompt identification of comorbidities is crucial in hospitalized SAM children, which will pave way for their treatment, resulting in better outcomes

Anterior Chamber Angle Assessment System

In this paper, we propose an automatic anterior chamber angle assessment system for Anterior Segment Optical Coherence Tomography (AS-OCT). In our system, the automatic segmentation method is used to segment the clinical structures, which are then used to recover standard clinical ACA measurements. Our measurements can not only support clinical assessments, but also be utilized as features for detecting anterior angle closure in automatic glaucoma diagnosis

Angle-Closure Detection in Anterior Segment OCT based on Multi-Level Deep Network

Irreversible visual impairment is often caused by primary angle-closure glaucoma, which could be detected via Anterior Segment Optical Coherence Tomography (AS-OCT). In this paper, an automated system based on deep learning is presented for angle-closure detection in AS-OCT images. Our system learns a discriminative representation from training data that captures subtle visual cues not modeled by handcrafted features. A Multi-Level Deep Network (MLDN) is proposed to formulate this learning, which utilizes three particular AS-OCT regions based on clinical priors: the global anterior segment structure, local iris region, and anterior chamber angle (ACA) patch. In our method, a sliding window based detector is designed to localize the ACA region, which addresses ACA detection as a regression task. Then, three parallel sub-networks are applied to extract AS-OCT representations for the global image and at clinically-relevant local regions. Finally, the extracted deep features of these sub-networks are concatenated into one fully connected layer to predict the angle-closure detection result. In the experiments, our system is shown to surpass previous detection methods and other deep learning systems on two clinical AS-OCT datasets.Comment: 9 pages, accepted by IEEE Transactions on Cybernetic

In vivo measurements of prelamina and lamina cribrosa biomechanical properties in humans

Purpose: To develop and use a custom virtual fields method (VFM) to assess the biomechanical properties of human prelamina and lamina cribrosa (LC) in vivo. Methods: Clinical data of 20 healthy, 20 ocular hypertensive (OHT), 20 primary open-angle glaucoma, and 16 primary angle-closure glaucoma eyes were analyzed. For each eye, the intraocular pressure (IOP) and optical coherence tomography (OCT) images of the optic nerve head (ONH) were acquired at the normal state and after acute IOP elevation. The IOP-induced deformation of the ONH was obtained from the OCT volumes using a three-dimensional tracking algorithm and fed into the VFM to extract the biomechanical properties of the prelamina and the LC in vivo. Statistical measurements and P values from the Mann-Whitney-Wilcoxon tests were reported. Results: The average shear moduli of the prelamina and the LC were 64.2 ± 36.1 kPa and 73.1 ± 46.9 kPa, respectively. The shear moduli of the prelamina of healthy subjects were significantly lower than those of the OHT subjects. Comparisons between healthy and glaucoma subjects could not be made robustly due to a small sample size. Conclusions: We have developed a methodology to assess the biomechanical properties of human ONH tissues in vivo and provide preliminary comparisons in healthy and OHT subjects. Our proposed methodology may be of interest for glaucoma management

Multidisciplinary Ophthalmic Imaging Automated Analysis of Angle Closure From Anterior Chamber Angle Images

PURPOSE. To evaluate a novel software capable of automatically grading angle closure on EyeCam angle images in comparison with manual grading of images, with gonioscopy as the reference standard. METHODS. In this hospital-based, prospective study, subjects underwent gonioscopy by a single observer, and EyeCam imaging by a different operator. The anterior chamber angle in a quadrant was classified as closed if the posterior trabecular meshwork could not be seen. An eye was classified as having angle closure if there were two or more quadrants of closure. Automated grading of the angle images was performed using customized software. Agreement between the methods was ascertained by j statistic and comparison of area under receiver operating characteristic curves (AUC). RESULTS. One hundred forty subjects (140 eyes) were included, most of whom were Chinese (102/140, 72.9%) and women (72/140, 51.5%). Angle closure was detected in 61 eyes (43.6%) with gonioscopy in comparison with 59 eyes (42.1%, P ¼ 0.73) using manual grading, and 67 eyes (47.9%, P ¼ 0. CONCLUSIONS. Customized software for automated grading of EyeCam angle images was found to have good agreement with gonioscopy. Human observation of the EyeCam images may still be needed to avoid gross misclassification, especially in eyes with extensive angle closure