Dynamic Infrared Thermography for Quantitative Assessment of Peripheral Microcirculation: Models, Metrics, and Clinical Translation

Peripheral microcirculation assessment is critical for understanding tissue oxygenation, thermoregulation and metabolic function, but conventional techniques such as laser Doppler perfusion imaging and indocyanine green angiography are constrained by contact requirements, invasiveness or limited field of view. Dynamic infrared thermography (DIRT) provides a non-contact method that quantifies microvascular function by analyzing skin temperature recovery following a controlled thermal challenge, thereby offering functional insights into perfusion dynamics beyond static anatomical imaging. This narrative review synthesizes the bioheat models, quantitative metrics and clinical evidence supporting DIRT for peripheral microcirculation assessment. Following PRISMA-adapted searches, 71 studies and key modelling papers with dynamic protocols and perfusion-related quantitative endpoints were included. Bioheat transfer models, from the Pennes formulation to non-Fourier dual-phase-lag extensions, enable inverse estimation of perfusion parameters from temperature time-series. Validated metrics include rewarming rate, thermal time constant, area under the temperature vs time curve, maximum recovery percentage and spatial hotspot detection for perforator mapping. These parameters correlate strongly with laser Doppler and laser speckle contrast imaging, particularly in Raynaud's phenomenon, and achieve high diagnostic performance for preoperative perforator mapping and postoperative flap monitoring in reconstructive microsurgery. Evidence is most mature in surgical applications, supporting DIRT as a repeatable adjunct for planning and surveillance. In Raynaud's phenomenon, peripheral arterial disease and diabetic foot disease, DIRT metrics detect microvascular impairment and show promise for early ulceration risk prediction, although heterogeneity in protocols and scarcity of large-scale outcome data hinder broader adoption. As a conclusion, DIRT offers practical advantages of portability, negligible consumable cost and absence of contrast or ionizing radiation. Its transition to routine quantitative clinical use requires standardized acquisition protocols, integration of advanced signal processing and machine learning, and adequately powered multicenter trials linking metrics to patient-centered outcomes across populations.