A telerehabilitation program to improve visual perception in children and adolescents with hemianopia consecutive to a brain tumor: a single-arm feasibility and proof-of-concept trial
Bibliographic record
Abstract
Background: Brain tumor in children can induce hemianopia, a loss of conscious vision, profoundly impacting their development and quality of life, yet no effective intervention exists for this pediatric population. This study aimed to explore the feasibility, safety, and potential effectiveness of a home-based audiovisual stimulation in immersive virtual-reality (3D-MOT-IVR) to improve visual function and functional vision. Methods: In a phase 2a, open-labeled, nonrandomized, single-arm study, conducted from July 2022 to October 2023 (NCT05065268), 10 children and adolescents with stable hemianopia were enrolled to perform 20-min sessions of 3D-MOT-IVR every other day for six weeks from home. We assessed feasibility by monitoring adoption, adherence and completion rates, remote data transfer and qualitative feedback. Safety was evaluated using validated cybersickness questionnaires. Comprehensive vision assessments following standardized low-vision evaluation procedures were conducted pre- and post-intervention, with follow-ups at 1- and 6 months. Findings: The home-based 3D-MOT-IVR intervention proved both feasible and safe, with no reported adverse events. All participants completed the prescribed stimulations and the pre- and post-intervention assessment points, 90% completed the follow-ups. Nine out of ten participants showed clinically meaningful enhancement in visual function and/or functional vision, namely binocular visual field restoration and increased reading speed, but two showed concomitant deterioration in monocular visual field. These positive effects were sustained at the 6-month follow-up. Exploratory outcomes revealed a significant positive correlation between the performance at the 3D-MOT-IVR intervention and the visual perception at the binocular visual field test. Interpretation: Our findings underscore the feasibility and safety of home-based audiovisual stimulation in immersive virtual-reality as a potential intervention for improving visual perception in children/adolescents with hemianopia consecutive to a pediatric brain tumor. These promising results lay a strong foundation for a larger randomized controlled trial, offering hope for a meaningful breakthrough in visual rehabilitation for this vulnerable population. Funding: Meagan Bebenek Foundation and University Health Network Foundation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".