ArticlePlastic and reconstructive surgery. Global open2026
Artificial Intelligence-assisted Multimodal Quantification of Facial Pore Reduction After Microneedling With Adipose-derived Stem Cell Exosomes.
Article in Plastic and reconstructive surgery. Global open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Abstract
Background: Enlarged facial pores are a common cosmetic concern, exacerbated by age-related collagen degradation and sebaceous hyperactivity. Despite clinical demand, objective quantification methods for pore improvement remain limited. This study used 3 independent analytical platforms-QuantifiCare 3-dimensional (3D) imaging, Gwyddion-based surface roughness analysis, and artificial intelligence (AI)-assisted image segmentation-to evaluate the efficacy of microneedling combined with adipose-derived stem cell exosome (ASCE+) therapy. Methods: Thirty subjects underwent 3 sessions of microneedling with topical ASCE+ application. Standardized high-resolution facial images were obtained via the LifeViz Mini system under controlled lighting and positioning. QuantifiCare software generated regional pore scores across 6 facial zones. Gwyddion software quantified 3D surface roughness ( Results: QuantifiCare pore scores significantly increased across all regions ( Conclusions: This is the first study to integrate 3D imaging, roughness mapping, and AI segmentation for pore analysis after microneedling and exosome therapy. The combined modality demonstrates significant improvement in pore architecture and skin texture, highlighting its utility in aesthetic dermatology.
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