Multimodal neuroimaging markers in amblyopia.
Poster No:
319
Submission Type:
Abstract Submission
Authors:
Himanshu Singh1, Himani Gupta2, Rebika Dhiman3, S Senthil Kumaran4, Rohit Saxena3
Institutions:
1All India Institute of Medical Sciences, New Delhi, Delhi, 2R.P.C Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, Delhi, 3R.P.C Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India, 4All India Institute of Medical Sciences, South East Delhi, Delhi
First Author:
Co-Author(s):
Introduction:
Amblyopia is a neurodevelopmental disorder that affects visual acuity and ocular function. Early intervention with occlusion treatment (OCT) in amblyopia is recommended for improvement in visual acuity1. The efficacy of treatment varies with age of onset. However, not all patients respond to this treatment modality. The mechanisms underlying treatment response remains unclear2. Neuroimaging based studies in the amblyopia have been limited at baseline. In the current study, we employed imaging markers with resting state, visual acuity task, and diffusion tensor imaging at baseline and post-therapy to understand the effect of treatment and how patient stratification can be established using neuroimaging markers in the early phase for treatment efficacy3,4. This approach aims to identify predictive factors for treatment response and stratify populations that may be non-responsive to occlusion therapy at early stages.
Methods:
A study was conducted on 21 amblyopia patients (mean age: 10 years, standard deviation: 3.00 years). All patients received baseline assessments, including cycloplegic refraction, visual acuity, contrast sensitivity, color vision, stereoacuity, and OCTA imaging. Similar investigations at 6 months used a 2-line visual acuity improvement as the minimum treatment response.Imaging was performed on a 3T MR scanner (Ingenia 3T, M/s Philips). The resting and Functional flickering Checkboard (at 18 Hz frequency) visual acuity task were acquired at two timepoints (baseline & 6 Months FUP), using multiband factor of 3 with repetition time (TR) 1 sec, 300/480 dynamics in resting and task-based fMRI respectively. Diffusion tensor imaging was acquired using B values of 0 and 1000, with a slice thickness of 2 mm, TR/ Echo time (TE) = 4797/92 ms, in 32 directions with 2 averages. Data were preprocessed using the default pipeline of conn toolbox for fMRI and DSI Studio connectome analysis for Diffusion Imaging. To isolate the temporal effect across task and resting fMRI, the data were processed to examine any changes in functional connectivity patterns using ROI/Seed to Voxel functional connectivity. Group level covariates for Pre and Post therapy were input for statistical inference through General Linear Model.
Results:
Of 21 subjects, 11 responders and 10 non-responders were categorized based on visual acuity test results. In ROI-based analysis, no significant results were observed across the resting phase. Across task-based modulation, non-responders' pre-task analysis revealed significant correlation between Salience and Visual networks. In post-task analysis, Dorsal Attention network exhibited correlation with Language networks in the responder group. Seed-to-Voxel Network analysis demonstrated major network modulation, representing functional activity changes associated with responders and non-responders groups. Default Mode (DMN), Frontal-Parietal, Dorsal Attention (DAN), and Salience networks exhibited major functional connectivity (Figure 1). Diffusion imaging Connectome analysis across the two groups revealed modulation in the corpus callosum frontal region in non-responders and the superior longitudinal fasciculus in responders, with a significance of FDR <0.001. Diffusion metrics complemented the seed-to-voxel modulation observed across task and resting state activity in the two groups (Figure 2).
·Figure 2: Structural and functional neuroimaging results in non-responders and responders.
·Figure 1: Seed to voxel result across resting and task based modulation in responders (n=11) and non-responders (n=10) groups.
Conclusions:
The present study's fMRI and DTI techniques complement OCT's clinical treatment efficacy, highlighting the roles of the Attention and Saliency networks in differentiating responders from non-responders. Region-based seed networks in resting-state fMRI corroborated these findings. This suggests that combining task-based fMRI, resting-state fMRI, and DTI offers a comprehensive understanding of amblyopia's visual computational aspects and treatment efficacy. Notably, amblyopia's impact on the DAN/DMN and salience networks extends beyond visual processing.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling
Novel Imaging Acquisition Methods:
Multi-Modal Imaging
Perception, Attention and Motor Behavior:
Perception: Visual 2
Perception and Attention Other
Keywords:
Acquisition
FUNCTIONAL MRI
PEDIATRIC
Pediatric Disorders
Perception
Tractography
Treatment
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
Abstract Information
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
2. Yang, C. I. et al. Functional MRI of amblyopia before and after levodopa. Neurosci Lett 339, (2003).
3. Peng, J. et al. Alternations of interhemispheric functional connectivity in children with strabismus and amblyopia: a resting-state fMRI study. Sci Rep 11, (2021).
4. Wang, Y., Wu, Y., Luo, L. & Li, F. Structural and functional alterations in the brains of patients with anisometropic and strabismic amblyopia: a systematic review of magnetic resonance imaging studies. Neural Regeneration Research vol. 18 Preprint at https://doi.org/10.4103/1673-5374.371349 (2023).