Attitudes toward and difficulties with childhood amblyopia patching treatment

Amblyopia is the leading cause of visual loss in children and young adults, affecting up to 5% of people of all ages. Patching and atropine eyedrops successfully treat this condition. However, adherence to treatment is often poor. Current literature has identified factors impacting compliance, but less is known about successful interventions to improve adherence. This study's purpose is to identify parent attitudes towards amblyopia treatment and barriers to treatment compliance in order to inform future provider and multidisciplinary approaches to improve adherence

Evaluation of a Deep Learning-Derived Quantitative Retinopathy of Prematurity Severity Scale

Purpose To evaluate the clinical usefulness of a quantitative deep learning-derived vascular severity score for retinopathy of prematurity (ROP) by assessing its correlation with clinical ROP diagnosis and by measuring clinician agreement in applying a novel scale. Design Analysis of existing database of posterior pole fundus images and corresponding ophthalmoscopic examinations using 2 methods of assigning a quantitative scale to vascular severity. Participants Images were from clinical examinations of patients in the Imaging and Informatics in ROP Consortium. Four ophthalmologists and 1 study coordinator evaluated vascular severity on a scale from 1 to 9. Methods A quantitative vascular severity score (1–9) was applied to each image using a deep learning algorithm. A database of 499 images was developed for assessment of interobserver agreement. Main Outcome Measures Distribution of deep learning-derived vascular severity scores with the clinical assessment of zone (I, II, or III), stage (0, 1, 2, or 3), and extent (6 clock hours) of stage 3 evaluated using multivariate linear regression and weighted κ values and Pearson correlation coefficients for interobserver agreement on a 1-to-9 vascular severity scale. Results For deep learning analysis, a total of 6344 clinical examinations were analyzed. A higher deep learning-derived vascular severity score was associated with more posterior disease, higher disease stage, and higher extent of stage 3 disease (P < 0.001 for all). For a given ROP stage, the vascular severity score was higher in zone I than zones II or III (P < 0.001). Multivariate regression found zone, stage, and extent all were associated independently with the severity score (P < 0.001 for all). For interobserver agreement, the mean ± standard deviation weighted κ value was 0.67 ± 0.06, and the Pearson correlation coefficient ± standard deviation was 0.88 ± 0.04 on the use of a 1-to-9 vascular severity scale. Conclusions A vascular severity scale for ROP seems feasible for clinical adoption; corresponds with zone, stage, extent of stage 3, and plus disease; and facilitates the use of objective technology such as deep learning to improve the consistency of ROP diagnosis

A Multicenter Analysis of Nucleic Acid Quantification Using Aqueous Humor Liquid Biopsy in Retinoblastoma: Implications for Clinical Testing

PURPOSE: Retinoblastoma (RB) is most often diagnosed with clinical features and not diagnosed with tumor biopsy. This study describes tumor-derived analyte concentrations from aqueous humor (AH) liquid biopsy and its use in clinical assays. DESIGN: Case series study. PARTICIPANTS: Sixty-two RB eyes from 55 children and 14 control eyes from 12 children from 4 medical centers. METHODS: This study included 128 RB AH samples including: diagnostic (DX) samples, samples from eyes undergoing treatment (TX), samples after completing treatment (END), and during bevacizumab injection for radiation therapy after completing RB treatment (BEV). Fourteen-control AH were analyzed for unprocessed analytes (double-stranded DNA [dsDNA], single-stranded DNA [ssDNA], micro-RNA [miRNA], RNA, and protein) with Qubit fluorescence assays. Double-stranded DNA from 2 RB AH samples underwent low-pass whole-genome sequencing to detect somatic copy number alterations. Logistic regression was used to predict disease burden given analyte concentrations. MAIN OUTCOME MEASURES: Unprocessed analyte (dsDNA, ssDNA, miRNA, RNA and protein) concentrations. RESULTS: Results revealed dsDNA, ssDNA, miRNA, and proteins, but not RNA, were quantifiable in most samples (up to 98%) with Qubit fluorescence assays. Median dsDNA concentration was significantly higher in DX (3.08 ng/μl) compared to TX (0.18 ng/μl; CONCLUSIONS: Aqueous humor liquid biopsy in RB is a high-yield source of dsDNA, ssDNA, miRNA, and protein. Diagnostic samples are most useful for RB 1 gene mutational analyses. Genomic analysis may be more informative of tumor activity status than quantification alone and can be performed even with smaller analyte concentrations obtained from TX samples. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found after the references

Peter Colhoun, VMI Alumnus, ca. 1880

Peter Dudley Colhoun (Class of 1879). This photo was taken shortly after he left VMI