Advancing Wound Care With 3-D Imaging: Clinical Applications, Performance and Future Directions.

Chronic wounds pose a growing global health challenge. Accurate assessment is essential for monitoring healing, yet traditional two-dimensional methods lack volumetric analysis. Emerging three-dimensional imaging technologies offer enhanced precision, but their clinical validation and prognostic utility remain unclear. This scoping review aimed to map and synthesise the available evidence on the clinical application and predictive potential of three-dimensional wound assessment technologies in adults with chronic wounds. A systematic search was performed across five electronic databases-MEDLINE via PubMed, EMBASE, Web of Science, CINAHL, and IEEE Xplore-to identify peer-reviewed studies published between 2014 and 2024. Eligible studies included original research evaluating the clinical application, reliability, accuracy, or predictive performance of three-dimensional wound assessment technologies. Two independent reviewers performed title/abstract screening, full-text eligibility assessment, and data extraction. Data were synthesised narratively, with emphasis on methodological quality, clinical applicability, and standardisation practices across technologies. Eleven studies were included, encompassing 734 wounds and 307 patients. Technologies evaluated included optical coherence tomography, structured-light scanners, stereophotogrammetry, and smartphone-based structure-from-motion systems. Most platforms demonstrated high reproducibility for surface area measurement (ICC > 0.95) and moderate accuracy for depth and volume. Methodological heterogeneity and limited standardisation of validation protocols hindered cross-platform comparability. No study integrated volumetric metrics into predictive healing models. Three-dimensional wound assessment technologies show strong potential to enhance wound measurement precision, documentation, and non-invasive monitoring. Robust validation frameworks and integration of volumetric metrics into predictive models are needed to realise their clinical value in precision wound care.