3D Measurement of Chronic Wounds in Routine Care: A Review with Practical Guidance for Smartphone Photogrammetry
摘要
Chronic wounds impose a considerable clinical and economic burden, and their effective management requires objective, repeatable monitoring over time. Smartphone-based photogrammetry may enable acquisition of 3D metrics without the need for expensive dedicated scanners.
ObjectiveThis scoping review aimed to identify and organize digital methodologies applicable to wound measurement and monitoring, with particular emphasis on smartphone photogrammetry as a practical approach for routine care.
MethodsA scoping review was conducted to identify digital wound measurement methodologies. The included approaches were organized according to the main pipeline stages: acquisition, reconstruction, and analysis. Reported metrics, including area, depth, volume, and tissue-assessment elements, were catalogued, and validation approaches, comparison methods, and implementation factors were summarized. In addition, a practical photogrammetry workflow with basic quality control (QC) gates is presented as pragmatic guidance informed by the reviewed literature for use during routine dressing changes.
ResultsA review of the literature reveals that trend analysis, such as the percentage reduction over time appears to have high clinical relevance. Furthermore, the literature indicates that consistency and repeatability of measurement appear to be more important than single-measurement accuracy. Two-dimensional measurements can underestimate wound size on anatomically curved surfaces. In contrast, three-dimensional metrics, such as depth and volume, along with depth maps, may provide a more informative description of deep wounds. In deeper wounds, reductions in depth or volume (Z-axis changes) may precede visible reductions in the two-dimensional outline. The quality of the results appears to be strongly influenced by the acquisition conditions, such as angle, lighting, stability, and marker. The comparability of volumes is limited by the lack of clear definitions of the reference surface and inconsistent reporting of agreement and error metrics.
ConclusionsSmartphone photogrammetry is an attractive implementation solution for clinics and telemedicine; however, its efficacy is contingent upon the standardization of acquisition, the integration of simple QC gates, and the establishment of transparent definitions of 3D metrics and compliance reporting. These measures may enhance comparability, facilitating reliable assessments between visits and centers.