Multi-Parametric Optical Coherence Tomography Angiography Quantifies Heterogeneous Therapeutic Responses in Port Wine Stains

Port wine stains (PWS), congenital vascular malformation, affecting 3 ‰–5 ‰ of newborns, pose significant psychological and social challenges. Current treatments, including vascular-targeted photodynamic therapy (V-PDT), exhibit variable efficacy due to interpatient heterogeneity in vascular characteristics. Here, we present a multi-parametric quantitative method using optical coherence tomography angiography (OCTA) to characterize PWS lesions, analyzing 26 vascular indicators in 100 patients. Our method effectively discriminates patients with distinct therapeutic responses and identifies morphological vascular changes linked to treatment outcomes. By integrating quantitative vascular data with clinical parameters via machine learning, we developed a predictive model that distinguished no-response (NR) from moderate-improvement (MI) and high-improvement (HI) groups with accuracies of 75% and 91%, respectively. This study highlights the importance of understanding vascular pathology to advance personalized treatment strategies for PWS, offering a novel framework for non-invasive evaluation and management of vascular lesions.

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Publication Details

Journal
IEEE Journal of Selected Topics in Quantum Electronics
Published
2025-09-12
DOI
https://doi.org/10.1109/jstqe.2025.3609623
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Multi-Parametric Optical Coherence Tomography Angiography Quantifies Heterogeneous Therapeutic Responses in Port Wine Stains

IEEE Journal of Selected Topics in Quantum Electronics
Geochemistry and Geologic Mapping
article

Multi-Parametric Optical Coherence Tomography Angiography Quantifies Heterogeneous Therapeutic Responses in Port Wine Stains

article en

Abstract

Port wine stains (PWS), congenital vascular malformation, affecting 3 ‰–5 ‰ of newborns, pose significant psychological and social challenges. Current treatments, including vascular-targeted photodynamic therapy (V-PDT), exhibit variable efficacy due to interpatient heterogeneity in vascular characteristics. Here, we present a multi-parametric quantitative method using optical coherence tomography angiography (OCTA) to characterize PWS lesions, analyzing 26 vascular indicators in 100 patients. Our method effectively discriminates patients with distinct therapeutic responses and identifies morphological vascular changes linked to treatment outcomes. By integrating quantitative vascular data with clinical parameters via machine learning, we developed a predictive model that distinguished no-response (NR) from moderate-improvement (MI) and high-improvement (HI) groups with accuracies of 75% and 91%, respectively. This study highlights the importance of understanding vascular pathology to advance personalized treatment strategies for PWS, offering a novel framework for non-invasive evaluation and management of vascular lesions.

IEEE Journal of Selected Topics in Quantum ElectronicsVol. 32(4: Adv. Biophoton. in Emerg.)
Beijing Institute of Technology (CN), Chinese PLA General Hospital (CN)
Zero hunger
Openalex Percentile: Top 37%
Geochemistry and Geologic Mapping
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