A Structural and Functional Analysis of Human Brain MRI with Attention Deficit Hyperactivity Disorder

Attention Deficit Hyperactivity Disorder (ADHD) affects 5-10% of children worldwide. Its effects are mainly behavioral, manifesting in symptoms such as inattention, hyperactivity, and impulsivity. If not monitored and treated, ADHD may adversely affect a child\u27s health, education, and social life. Furthermore, the neurological disorder is currently diagnosed through interviews and opinions of teachers, parents, and physicians. Because this is a subjective method of identifying ADHD, it is easily prone to error and misdiagnosis. Therefore, there is a clear need to develop an objective diagnostic method for ADHD. The focus of this study is to explore the use of machine language classifiers on information from the brain MRI and fMRI of both ADHD and non-ADHD subjects. The imaging data are preprocessed to remove any intra-subject and inter-subject variation. For both MRI and fMRI, similar preprocessing stages are performed, including normalization, skull stripping, realignment, smoothing, and co-registration. The next step is to extract features from the data. For MRI, anatomical features such as cortical thickness, surface area, volume, and intensity are obtained. For fMRI, region of interest (ROI) correlation coefficients between 116 cortical structures are determined. A large number of image features are collected, yet many of them may include redundant and useless information. Therefore, the features used for training and testing the classifiers are selected in two separate ways, feature ranking and stability selection, and their results are compared. Once the best features from MRI and fMRI are determined, the following classifiers are trained and tested through leave-one-out cross validation, experimenting with varying feature numbers, for each imaging modality and feature selection method: support vector machine, support vector regression, random forest, and elastic net. Thus, there are four experiments (MRI-rank, MRI-stability, fMRI-rank, fMRI-stability) with four classifiers in each for a total of 16 classifiers trained per each feature count attempted. The results of each classifier are the decisions of each subject, ADHD or non-ADHD. Finally, a classifier decision ensemble is created through the combination of the outputs of the best classifiers in a majority voting method that includes results of both the MRI and fMRI classifiers and keeps both feature selection results independent. The results suggest that ADHD is more easily identified through fMRI because the classification accuracies are a lot higher using fMRI data rather than MRI data. Furthermore, significant activity correlation differences exist between the brain\u27s frontal lobe and cerebellum and also the left and right hemispheres among ADHD and non-ADHD subjects. When including MRI decisions with fMRI in the classifier ensemble, performance is boosted to a high ADHD detection accuracy of 96.2%, suggesting that MRI information assists in validating fMRI classification decisions. This study is an important step towards the development of an automatic and objective method for ADHD diagnosis. While more work is needed to externally validate and improve the classification accuracy, new applications of current methods with promising results are introduced here

Microbiome and immune-mediated dry eye: a review

In this review, we aim to summarise key articles that explore relationships between the gut and ocular surface microbiomes (OSMs) and immune-mediated dry eye. The gut microbiome has been linked to the immune system by way of stimulating or mitigating a proinflammatory or anti-inflammatory lymphocyte response, which may play a role in the severity of autoimmune diseases. Although the ‘normal’ gut microbiome varies among individuals and demographics, certain autoimmune diseases have been associated with characteristic gut microbiome changes. Less information is available on relationships between the OSM and dry eye. However, microbiome manipulation in multiple compartments has emerged as a therapeutic strategy, via diet, prebiotics and probiotics and faecal microbial transplant, in individuals with various autoimmune diseases, including immune-mediated dry eye

The Microbiome and Ocular Surface Disease

The human body lives in a symbiotic relationship with the bacteria, viruses, fungi, and protozoa that make up the microbiome. In this review, we discuss the compositions of the gut and ocular surface microbiomes in relationship to health and disease.The gut microbiome is dominated by Firmicutes, whereas the ocular surface is dominated by Proteobacteria. The compositions of the microbiome are similar between individuals at the phyla level, but differ at the genus level. Alterations in the microbiome have been associated with disease. For example, ocular diseases such as uveitis, dry eye, and keratitis have been associated with gut dysbiosis. In addition, ocular surface dysbiosis has been reported in diseases including dry eye, blepharitis, keratitis, and diabetic retinopathy.Compositions of the gut and ocular surface microbiomes have been found to differ in disease states compared with controls. Further understanding of dysbiosis specific to a disease is needed to target these surfaces for therapeutic strategies

Surgeon demographic and surgical volume trends in adult strabismus surgery in the United States

To explore the influence of career stage, gender, and age on procedural trends of surgeons performing strabismus surgery. Data on ophthalmologists who performed strabismus surgery and on the Medicare beneficiaries who underwent surgery between 2012 and 2017 was retrieved from Medicare Provider Utilization and Payment Data. A total of 133 strabismus surgeons (78.9% male and 21.1% female) were reimbursed by Centers for Medicare and Medicaid Services for 10,598 strabismus procedures during the study period. The overall number of strabismus surgeries increased (P = 0.039) over time. Most surgeons were 50-59 years of age (n = 45 [33.8%]), with an average age of 54.5 ± 9.5 years. The number of services per physician did not differ by gender (85 ± 97 procedures/male surgeon and 60 ± 149 procedures/female surgeon [P = 0.13]). There was no difference in the gender proportion of physicians, with 0-9 post-fellowship years of experience (P = 0.32), but there were significantly more men with 10-19 (P = 0.003), 20-29 (P < 0.001), and 30-39 (P < 0.001) years of post-fellowship experience. There was no difference in the number of procedures performed between women and men 30-39 (P = 0.83) or 60-69 (P = 0.48) years of age; however, women 40-49 (P = 0.009) and 50-59 (P < 0.001) years of age performed significantly fewer procedures per surgeon than men. Women performed significantly fewer surgeries midcareer compared to their male counterparts

Automatic Segmentation And Quantification Of White And Brown Adipose Tissues From Pet/Ct Scans

In this paper, we investigate the automatic detection of white and brown adipose tissues using Positron Emission Tomography/Computed Tomography (PET/CT) scans, and develop methods for the quantification of these tissues at the whole-body and body-region levels. We propose a patient-specific automatic adiposity analysis system with two modules. In the first module, we detect white adipose tissue (WAT) and its two sub-types from CT scans: Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT). This process relies conventionally on manual or semi-automated segmentation, leading to inefficient solutions. Our novel framework addresses this challenge by proposing an unsupervised learning method to separate VAT from SAT in the abdominal region for the clinical quantification of central obesity. This step is followed by a context driven label fusion algorithm through sparse 3D Conditional Random Fields (CRF) for volumetric adiposity analysis. In the second module, we automatically detect, segment, and quantify brown adipose tissue (BAT) using PET scans because unlike WAT, BAT is metabolically active. After identifying BAT regions using PET, we perform a co-segmentation procedure utilizing asymmetric complementary information from PET and CT. Finally, we present a new probabilistic distance metric for differentiating BAT from non-BAT regions. Both modules are integrated via an automatic body-region detection unit based on one-shot learning. Experimental evaluations conducted on 151 PET/CT scans achieve state-of-the-art performances in both central obesity as well as brown adiposity quantification

Ocular Surface Squamous Neoplasia Masquerading as Recalcitrant Epithelial Keratitis

PURPOSEThe purpose of this study was to report a unique case of ocular surface squamous neoplasia that masqueraded as a nonresolving toxic epithelial keratitis. METHODSThis was a case report and review of the literature. RESULTSA 79-year-old man presented with decreased vision, redness, and a foreign body sensation in his right eye that was refractory to treatment with lubrication and topical nonsteroidal antiinflammatory drops. Before presentation, the referring provider believed that he had medicamentosa-related keratitis and placed him on oral methazolamide. Slitlamp biomicroscopy of the right eye revealed diffuse epitheliopathy with punctate fluorescein staining and subtle underlying corneal epithelial opalescence. A mildly thickened and inflamed pinguecula was noted from 2 to 5 o'clock at the limbus of the right eye. An anterior segment high-resolution optical coherence tomography revealed thickened, hyperreflective epithelium with an abrupt transition. An incisional biopsy confirmed conjunctival and corneal intraepithelial neoplasia. The patient improved after 4 cycles of topical chemotherapy with 1% 5-fluorouracil eye drops with complete resolution of the corneal and conjunctival pathology. CONCLUSIONSOcular surface squamous neoplasia can rarely masquerade as a recalcitrant medicamentosa and epithelial keratitis. In subtle cases or in cases with combined ocular surface morbidities, anterior segment high-resolution optical coherence tomography can be helpful to diagnose and direct therapy

Fraud Claims Filed Involving Practicing Ophthalmologists from 1985 Through 2020

Like all United States physicians, ophthalmologists may be implicated in lawsuits claiming fraudulent medical practice. In order to educate, raise awareness, and mitigate fraudulent practice, we reviewed a legal database and analyzed fraud claims in ophthalmology lawsuits. A retrospective legal literature review was performed on jury verdicts and settlements from the online legal database LexisNexis Academic from 1985 through 2020 that were filed by or against an ophthalmologist, involved a fraud claim, and included a final decision or settlement. Cases were evaluated for factors including demographics of plaintiffs and defendants, type of fraud claim, ophthalmologist party status (plaintiff or defendant), decision outcome, and amount awarded (when applicable). Of the 27 cases analyzed, all ophthalmologist defendants involved were male and the most common sub-specialty for an ophthalmologist defendant was refractive surgery. The most common fraud type was a fraud claim involving a malpractice lawsuit (12 of 27), followed by contract fraud and billing fraud. While the ophthalmologists in malpractice-related fraud cases experienced more rulings in favor of the defendant on the fraud claims (8 of 12), ophthalmologists in billing fraud cases experienced fewer rulings in their favor (0 of 5). Ophthalmology lawsuits involving fraud claims occurred in various settings, including malpractice lawsuits, contract cases, and Medicare and Medicaid billing. Defendants were all male and most commonly refractive surgeons

Trends in Intravitreal Corticosteroid Agent Use by US Ophthalmologists in Medicare Beneficiaries and Association with Physician-Industry Interactions

PURPOSE: To report trends of intravitreal corticosteroid use and explore the relationship between career experience, reported industry payments, and prescribing habits. DESIGN: Retrospective review of ophthalmologists who administered intravitreal dexamethasone implants (DEX) and triamcinolone acetonide (TA) injections between August 2013 to December 2017. RESULTS: A total of 1070 US ophthalmologists were reimbursed by Medicare for 522,804 DEX injections and 2.6 million TA injections. There was a significant positive trend in the number of DEX (P=.01), but not TA, injections per year. Mid- and late-career physicians performed significantly greater total injections on average compared to early-career physicians (both P<.001). Early-career physicians performed a greater proportion of DEX injections than late-career physicians (P=.006). Industry payments were positively associated with the proportion of DEX used and inversely correlated with the proportion of TA administered (P<.001). On multivariate analysis, years in practice, number of payments, and total value of payments were significantly associated with the number of DEX injections administered (all P<.001). CONCLUSION: From 2013 to 2017, the use of DEX increased while TA use remained stable. There was a positive association between DEX use and physician-industry interactions, which may be explained by seniority and experience. This study does not define a causal relationship