Automated lesion segmentation and quantification for prediction of paradoxical worsening in patients with tubercular serpiginous-like choroiditis

• Published in: Scientific reports 2022-03, Vol.12 (1), p.5392-5392, Article 5392
• Main Authors: Kalra, Gagan, Agarwal, Aniruddha, Marchese, Alessandro, Agrawal, Rupesh, Bansal, Reema, Gupta, Vishali
• Format: Article
• Language: English
• Subjects: 692/699/3161/3175; 692/699/3161/3177; Adult; Algorithms; Automation; Choroiditis; Choroiditis - diagnosis; Correlation coefficient; Female; Fundus Oculi; Humanities and Social Sciences; Humans; Image processing; Lesions; Male; Middle Aged; multidisciplinary; Optic nerve; Pipelines; Reproducibility of Results; Retrospective Studies; Science; Science (multidisciplinary); Segmentation
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-09338-y

To develop and evaluate a fully automated pipeline that analyzes color fundus images in patients with tubercular serpiginous-like choroiditis (TB SLC) for prediction of paradoxical worsening (PW). In this retrospective study, patients with TB SLC with a follow-up of 9 months after initiation of anti-tubercular therapy were included. A fully automated custom-designed pipeline was developed which was initially tested using 12 baseline color fundus photographs for assessment of repeatability. After confirming reliability using Bland–Altman plots and intraclass correlation coefficient (ICC), the pipeline was deployed for all patients. The images were preprocessed to exclude the optic nerve from the fundus photo using a single-shot trainable WEKA segmentation algorithm. Two automatic thresholding algorithms were applied, and quantitative metrics were generated. These metrics were compared between PW + and PW- groups using non-parametric tests. A logistic regression model was used to predict probability of PW for assessing binary classification performance and receiver operator curves were generated to choose a sensitivity-optimized threshold. The study included 139 patients (139 eyes; 92 males and 47 females; mean age: 44.8 ± 11.3 years) with TB SLC. Pilot analysis of 12 images showed an excellent ICC for measuring the mean area, intensity, and integrated pixel intensity (all ICC > 0.89). The PW + group had significantly higher mean lesion area ( p  = 0.0152), mean pixel intensity ( p  = 0.0181), and integrated pixel intensity ( p