ArticleScientific reports2021
Automated quantification of posterior vitreous inflammation: optical coherence tomography scan number requirements.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Qualitative and Quantitative Assessment of Vitreous Inflammation in Uveitis: Current Limitations and Emerging Diagnostic Approaches.Diagnostics (Basel, Switzerland) · 2026Review
- The expanding horizon: Role of widefield imaging in uveitis.Indian journal of ophthalmology · 2026Review
- Scan Density Matters: Reproducibility of AI-Derived OCT Biomarkers in Diabetic Macular Edema.Translational vision science & technology · 2026Article
- Deep Ensemble Learning to Detect Retinal Vascular Leakage on Ultrawide-Field Fundus Photographs of Patients With Uveitis.Translational vision science & technology · 2026Article
- Bridging Hypoxia and Vision Loss: The Emerging Role of Connexins in Local and Systemic Eye Diseases.International journal of molecular sciences · 2026Review
- Artificial Intelligence in Uveitis: Innovations in Diagnosis and Therapeutic Strategies.Clinical ophthalmology (Auckland, N.Z.) · 2024Review
- Diagnosis, Classification, and Assessment of the Underlying Etiology of Uveitis by Artificial Intelligence: A Systematic Review.Journal of clinical medicine · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Quantifying intraocular inflammation is crucial in managing uveitis patients. We assessed the minimum B-scan density for reliable automated vitreous intensity (VI) assessment, using a novel approach based on optical coherence tomography (OCT). OCT volume scans centered on the macula were retrospectively collected in patients with uveitis. Nine B-scans per volume scan at fixed locations were automatically analyzed. The following B-scan selections were compared against the average score of 9 B-scans per volume scan as a reference standard: 1/3/5/7 central scans (1c/3c/5c/7c), 3 widely distributed scans (3w). Image data of 49 patients (31 females) were included. The median VI was 0.029 (IQR: 0.032). The intra-class-correlation coefficient of the VI across the 9 B-scans was 0.923. The median difference from the reference standard ranged between 0.001 (7c) and 0.006 (1c). It was significantly lower for scan selection 3w than 5c, p(adjusted) = 0.022, and lower for selection 7c than 3w, p(adjusted) = 0.003. The scan selections 7c and 3w showed the two highest areas under the receiver operating curve (0.985 and 0.965, respectively). Three widely distributed B-scans are sufficient to quantify VI reliably. Highest reliability was achieved using 7 central B-scans. Automated quantification of VI in uveitis is reliable and requires only few OCT B-scans.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.