Noninvasive Bedside Approaches for Assessing Microvascular Dysfunction

Abstract

Background

Microvascular dysfunction is implicated in a range of acute and chronic conditions, ranging from cardiovascular disease to sepsis, often preceding organ damage and clinical symptoms. Within conditions such as diabetes or septic shock, microvascular compromise frequently correlates with disease severity and outcomes, emphasizing the importance of timely, targeted assessment. Noninvasive bedside methods for evaluating microvascular function have rapidly evolved, driven by advances in computational power, artificial intelligence, and novel imaging hardware.

Summary

This review provides an overview of clinically feasible noninvasive techniques – including optical coherence tomography angiography, handheld videomicroscopy, laser speckle contrast imaging, reflectance spectroscopy, and related techniques. These methods allow observation under resting conditions and can be combined with functional tests such as post-occlusive reactive hyperemia, heating provocation, or iontophoresis to evaluate microvascular function.

Key Messages

Collectively, these methods provide valuable insights into the structural and functional aspects of the microcirculation, but their clinical application is constrained by need for standardized protocols, validation, and evidence linking microvascular metrics to meaningful patient outcomes. Collaborations among academia, industry, and healthcare remain pivotal to transitioning these methods into regulated, accessible devices. As standardization progresses and evidence grows, this integrative approach of evaluating microvascular function may emerge as a mainstay in clinical practice and translational research.

Introduction

Since the development of methods to assess microvascular function, it has been linked to a range of disease across various organ systems, as well as the natural aging process [1]. Chronic conditions such as atherosclerotic vascular disease [2], cardiac angina with nonobstructive coronary arteries [3], diabetes [4], renal disease [5], and cognitive disorders [6], along with acute conditions like sepsis and septic shock [7], have all been associated with microvascular impairment. Given that several of these conditions often occur concomitantly, systemic microvascular dysfunction is hypothesized to either play a causal role or arise as a consequence of these diseases [8].

Assessing microvascular function has been shown valuable for identifying early abnormalities that often precede overt organ damage or clinical symptoms, and early detection may allow for preventative interventions to prevent or mitigate disease progression [9–12]. Consensus documents and scientific literature underscore the need for continued research to refine and expand the application of methods for evaluating microvascular function, particularly in the contexts of cardiovascular disease [13, 14] and sepsis [15, 16]. For example, in patients with hypertension, microvascular function assessments may be able to detect abnormalities before manifestation, thereby facilitating timely therapeutic interventions [9, 10]. Among patients with septic shock, microvascular dysfunction has been linked to higher mortality [11]. Moreover, early fluid resuscitation, as advocated by Surviving Sepsis Campaign guidelines [17], was found associated with increased microvascular perfusion in early stages of sepsis, potentially improving oxygen transport and tissue perfusion [12].

Multiple techniques are available for assessing microvascular function, and their clinical utility is often determined by the specific context and methodology. For instance, cardiac-specific evaluations include invasive procedures such as coronary flow assessments and thermodilution, as well as noninvasive modalities like positron emission tomography and echocardiography [18]. Among diabetic populations, the high incidence of retinopathy has led to routine implementation of optical coherence tomography angiography (OCTA) at some outpatient clinics, alongside fundus photography [19, 20]. Despite these advances, there is a growing interest in bedside techniques that minimize invasiveness and streamline data analysis. Such approaches may enable rapid assessment and earlier identification of microvascular dysfunction, ultimately improving patient outcomes through timely therapeutic interventions.

This review provides an overview of noninvasive methods and techniques for evaluating microvascular dysfunction at the bedside, rather than aiming to catalog all possible techniques. It is important to note that, in this context, “microvascular function” refers to the integrated behavior of multiple cellular components and mechanisms within the microvasculature – not exclusively endothelium‐dependent relaxation. Instrument-specific confounding factors and physiological nuances will not be discussed here, and readers are encouraged to investigate these considerations in depth before designing their own studies. Although advanced imaging modalities such as magnetic resonance imaging and positron emission tomography can be informative, they are excluded here due to their complexity and limited bedside applicability. Likewise, emerging methods that demand extensive time or resources for application have been omitted. Instead, we focus on clinically feasible approaches that combine ease of use with diagnostic value, offering solutions for both clinical and research settings.

Methods

A comprehensive literature search was conducted using PubMed on December 13, 2024, to identify studies on microvascular diagnostic techniques and dysfunction. The search combined keywords from PubMed’s MeSH database and title/abstract queries, targeting microvascular structures, diagnostic methods, and dysfunction, for articles published between 1990 and 2024 involving clinical investigations of humans above 18 years of age evaluating systemic microvascular dysfunction. Non-English articles, as well as reviews and meta-analyses, were excluded. Screening was performed using a fine-tuned GPT-4o mini model, and the remaining studies were subsequently categorized by a separate and similarly fine-tuned GPT-4o mini model, described in depth in online supplementary material (for all online suppl. material, see https://doi.org/10.1159/000547636) [21].

Results

The initial search yielded 66,213 records; after removing 2,512 duplicates and 485 ineligible articles, titles and abstracts were screened for relevance. In total, 8,755 articles were deemed relevant and classified by modality, population, and functional provocation for encyclopedic purposes. Of the 8,755 articles reviewed, flow-mediated dilatation was the most common evaluation method, appearing in 2,957 articles. Among the structural optical imaging techniques, optical coherence tomography (OCT) was most frequently used, with 849 articles, followed by capillaroscopy (400 articles) and sidestream dark field (SDF) microscopy (273 articles). For perfusion-based methods, laser Doppler flowmetry (LDF) appeared in 1,183 articles, compared to laser speckle contrast imaging (LSCI) in 140 articles. Reflectance spectroscopy-based approaches were less common, with near-infrared spectroscopy (NIRS) featured in 162 articles and hyperspectral imaging (HSI) in 50. In addition, emerging techniques – such as incident dark field (IDF) microscopy (18 articles), multi-exposure laser speckle contrast imaging (MELSCI) (2 articles), and spatial frequency domain imaging (SFDI) (11 articles) – were included in the review because they are new, may indicate the future direction of their respective technology domain, and offer nuanced insights. A summary of the presented techniques is shown in Table 1.

Table 1.

Summary of select instruments to evaluate microvascular function

Instrument	Provocation	Strengths	Weaknesses	Common areas of application
Retinal OCTA	Dynamic vessel analysis	Widely used	Limited bedside applicability; sparse validation to systemic microvascular dysfunction; organ specific	Ophthalmology; limited trials in critical care
Dermal OCTA	LTH, Ionto, PORH	High structural fidelity	Low FPS; susceptibility to motion artifacts; low FOV	Histology; tissue characteristics
SDF	–	Good bedside applicability	Qualitative or semiquantitative; operator dependency; limited functional assessment, low FOV	Critical care
IDF	–	Good bedside applicability	Qualitative or semiquantitative; operator dependency (improvement over SDF); limited functional assessment; low FOV	Critical care
NVC	PORH	Good bedside applicability	Mostly semiquantitative; need for high operator expertise; limited functional assessment; low FOV	Connective tissue disease; critical care
LDF	LTH, Ionto, PORH	Proven; high temporal fidelity	Low FOV; low reproducibility in select areas; sensitivity to environmental factors	Cardiovascular medicine; critical care; diabetology; infectious medicine
LDPI	LTH, Ionto, PORH	Wide FOV	Low FPS; susceptibility to motion artifacts; sensitivity to environmental factors	Cardiovascular medicine; diabetology
LSCI	LTH, Ionto, PORH	Proven; wide FOV; high FPS	Susceptibility to motion artifacts; sensitivity to environmental factors	Cardiovascular medicine; critical care; diabetology; infectious medicine; burn wounds; plastic surgery; neurosurgery
MELSCI	LTH, Ionto, PORH	Wide FOV; high FPS; higher accuracy versus LSCI	Sensitivity to environmental factors; novel device for clinical use	None as of yet
NIRS	PORH	Good depth; high FPS	Limited depth differentiation; low FOV	Skeletal muscle physiology; anesthesia; critical care; pediatrics
HSI	PORH	Wide FOV; high FPS	Limited depth; novel medical application	Tissue characteristics; critical care; diabetology
SFDI	PORH, LTH	Wide FOV; depth differentiation	Novel medical application; low FPS; susceptibility to motion artifacts	Diabetology

OCTA, optical coherence tomography angiography; LTH, local thermal hyperemia; Ionto, iontophoresis; PORH, post-occlusive reactive hyperemia; FPS, frames per second; FOV, field of view; SDF, sidestream dark field imaging; IDF, incident dark field imaging; NVC, nailfold videocapillaroscopy; LDF, laser Doppler flowmetry; LDPI, laser Doppler perfusion imaging; LSCI, laser speckle contrast imaging; MELSCI, multi-exposure laser speckle contrast imaging; NIRS, near-infrared reflectance spectroscopy; HSI, hyperspectral imaging; SFDI, spatial frequency domain imaging.

Functional Assessments

Functional assessments play a crucial role in providing a comprehensive evaluation of microvascular function by complementing other diagnostic examinations. Analysis of baseline conditions alone is not sufficient to capture the dynamic nature of microcirculatory adaptation. Unlike macrovascular disease, which often involves structural vessel damage, impaired microvascular function is primarily due to a mismatch in blood distribution relative to organ demand. It is important to recognize that optimal assessment time points and the overall shape of the response curve differ for each provocation and modality, so readers should choose their measurement windows and examine full response dynamics based on their specific hypothesis and protocol. Therefore, provocative tests allow for the assessment of functional reserve and can help reveal the mechanisms contributing to microvascular insufficiency. As each provocation may engage multiple signaling pathways – such as endothelium-dependent, neurogenic, or metabolic mechanisms – multiple provocations and complementary devices are often employed to pinpoint the pathways driving increased perfusion. This chapter highlights three commonly used functional assessment methods: iontophoresis (Ionto), post-occlusive reactive hyperemia (PORH), and local thermal hyperemia (LTH).

Iontophoresis

Ionto delivers pharmacological agents, most commonly acetylcholine (ACh) or sodium nitroprusside (SNP), into the skin via a low-voltage electrical current, thereby provoking local microvascular responses. The use of ACh and SNP allows for the assessment of endothelium-dependent and endothelium-independent vasodilation, often monitored with laser Doppler-based imaging to quantify perfusion changes, as shown in Figure 1. In addition to these well-established pathways, alternative agents such as histamine [22], insulin [23], and calcitonin gene-related peptide [24] have been used to investigate complementary vasodilatory routes. Compared to subcutaneous injections, direct transcutaneous application, or systemic administration, Ionto localizes drug delivery, minimizes systemic effects and invasiveness, and enables bedside evaluations by reducing confounding responses related to invasive procedures [25].

Fig. 1.

Example of MELSCI of the palmar side of forearm, used in conjunction with Ionto of SNP in the right chamber and ACh in the left. Higher signals are illustrated as brighter in this visual representation.

Limitations of Ionto include current-induced reactivity and variability in skin resistance. Current-induced vasodilation, often referred to as the “galvanic response,” can occur independently of the pharmacological agent and has been observed even when using water alone [26]. This phenomenon is thought to be mediated by an axon reflex via a COX-1 pathway [27]. Employing voltages below a specified threshold and using saline as the vehicle (due to its ionic content) can help mitigate this confounding effect. Skin resistance, influenced by factors such as epidermal thickness, skin type (e.g., glabrous vs. non-glabrous), and electrode placement, also determines the current needed for effective drug diffusion. Higher currents necessitated by higher resistance increase the likelihood of current-induced artifacts. To address these issues, recommended strategies include adhering to established current and charge density limits, and using standardized electrode placement protocols. For instance, limiting current density (<0.01 mA/cm²) and charge density (<7.8 mC/cm²) has been shown to minimize nonspecific effects [28].

Beyond the electrode charge protocol, the reproducibility of ACh and SNP Ionto is also influenced by the imaging modality. ACh Ionto generally demonstrates fair reproducibility, whereas SNP Ionto displays poorer reproducibility when assessed with single-point techniques such as LDF – a phenomenon that some authors attribute to partial, heterogeneous neurogenically mediated vasodilation arising from variable sensory nerve activation [29]. However, this limitation is mitigated when larger areas are evaluated using laser Doppler imaging or LSCI, reflecting the inherent heterogeneity of the dermal microcirculation. These findings underscore the importance of using imaging methods and study designs that account for spatial variability [30, 31].

Post-Occlusive Reactive Hyperemia

PORH is the transient increase in skin blood flow that follows the release of a brief arterial occlusion, typically lasting 3 to 5 min in a functional assessment [32, 33]. Occlusion pressures are commonly set at 50 mm Hg above systolic blood pressure, although a fixed pressure of 250 mm Hg can produce similar results [34]. However, because some individuals experience discomfort during PORH, using an individualized suprasystolic pressure may be more appropriate. Although PORH has been widely applied to assess endothelial function in conductance arteries (e.g., the brachial or radial artery) through flow-mediated dilation, it encompasses a broader range of physiological processes – including sensory nerve activation, local vasodilatory pathways, and myogenic responses – that together shape the overall hyperemic response. Axon reflexes, mediated by sensory nerves, contribute partially, while large-conductance calcium-activated potassium channels play a more substantial role, suggesting an involvement of endothelium-derived hyperpolarization (EDH) [35]. The contribution of prostaglandins remains unclear, with conflicting evidence in existing research, whereas nitric oxide (NO) may exert an effect dependent on localization and skin type (glabrous or non-glabrous) [36]. Given the multifactorial nature of PORH, it is regarded less as a direct measure of microvascular endothelial function and more as a global index of microvascular function and reactivity.

The reproducibility of PORH is influenced by multiple factors, including imaging modality, skin site selection, experimental conditions, and data expression methods. As with other stimulus-based tests, single-point LDF often shows inconsistent reproducibility due to the inherently heterogeneous spatial nature of the microvascular response. By contrast, full-field techniques such as LSCI mitigate spatial variability and thus yield higher reproducibility [37]. However, the absence of standardized protocols complicates cross-study comparisons, with variations in occlusion duration, cuff pressure, and skin temperature homogenization. In addition, with the rapid emergence of new imaging techniques, the parameters used to quantify perfusion responses vary considerably across studies, underscoring the need for standardized reporting and calibration to facilitate cross-study and cross-instrument comparisons [38].

Local Thermal Hyperemia

LTH is characterized by an initial peak in blood flow, followed by a transient decline, and a subsequent sustained plateau phase during heating, typically to a skin temperature of 39–44°C [39], to elicit thermal vasodilation in a functional assessment [40]. The initial peak is primarily driven by sensory nerve activation, with axon reflexes mediated by transient receptor potential vanilloid channels contributing to this response, alongside neuropeptides such as calcitonin gene-related peptide and substance P [41]. By contrast, the plateau phase is largely dependent on NO, involving heat shock protein 90-mediated activation of endothelial NO synthase, with a contribution of EDH [42–44]. The initial peak is often easier to distinguish from the increase to the plateau phase if lower temperatures are used, whereas the plateau is reached faster when higher temperatures are used.

Several parameters can be derived from LTH, including the initial peak perfusion and oxygenation saturation (largely axon reflex-dependent), the plateau perfusion (primarily NO and EDH-dependent), and the area under the curve for the entire response [45]. The choice of parameter should align with the specific research question; for instance, peak perfusion is commonly used to assess neurovascular reactivity, whereas plateau perfusion evaluates endothelial function via NO [38, 40].

LTH has shown good reproducibility when combined with one- and two-dimensional, perfusion-based imaging modalities, which will be discussed later in this review [37]. By employing LTH in tandem with other techniques, a broader range of vasoactive pathways and triggers can be investigated, thereby providing a more comprehensive view of microvascular function. However, as with the other functional testing methods broached in this review, further standardization of LTH protocols is necessary to ensure consistent, comparable results across studies and platforms.

In addition to the methodological considerations of functional assessments, it is important to account for ambient conditions and the subject’s state of mind. Variations in ambient temperature can affect perfusion measurements, in part due to thermoregulatory vasoconstriction and systemic sympathomimetic responses [46]. Moreover, mental stress has been shown to reduce endothelium-dependent flow-mediated dilation and microvascular reactivity [47], underscoring the importance of standardized ambient environment and the need for a calm study participant.

Structural Imaging

Optical Coherence Tomography Angiography

OCT operates on principles similar to ultrasound but uses near-infrared light instead of sound waves. Because light travels too quickly for direct timing of reflections, OCT relies on low-coherence interferometry. A light beam is split, with one portion directed toward the sample and the other to a reference arm of known length. The returning signals are recombined, and interference occurs only when the path length difference is within the coherence length of the broadband light source, typically a few micrometers. By scanning the sample and measuring these interference signals, OCT produces depth-resolved images, in a manner analogous to ultrasound but with finer spatial detail [48].

Building on this concept, OCTA extracts blood flow information by examining changes in the OCT signal over repeated B-scans (2D images) of the same tissue location. Static tissue produces a consistent speckle pattern, whereas moving red blood cells in vessels cause changes in that pattern. By analyzing these temporal signal variations and combining them across multiple adjacent B-scans, OCTA constructs volumetric maps of retinal vasculature. Although current clinical OCT systems usually cannot measure blood flow velocity directly, OCTA enables precise delineation of perfused vessels from surrounding static tissue [49].

OCTA can be used on different bodily surfaces. Traditionally, OCTA has been extensively utilized in ophthalmology for retinal imaging, where numerous microvascular parameters have been linked to clinical outcomes. For example, changes in retinal metrics such as foveal avascular zone dimensions [50], vascular density, and choriocapillaris flow area [51] have been associated with severe obesity, even showing improvements following weight loss. Additionally, OCTA-measured choriocapillaris flow deficits correlate with the severity of hypertension, kidney function, and albuminuria [52]. In the field of cardiology, retinal OCTA has successfully been used to identify reduced superficial vascular density in patients with cardiac angina with nonobstructive coronary arteries [53, 54]. It has been proposed to be a useful microvascular biomarker for systemic cardiovascular disease [55], including hypertension, atherosclerotic disease, and congestive heart failure [56].

Cutaneous OCTA is a relatively new application compared to retinal imaging and has been used to characterize local lesions such as wounds and acne [57, 58]. However, its broader adoption is limited by a narrow field of view (FOV) (approximately 10 × 10 millimeters), low temporal fidelity as each scan may take up to 6 s to obtain, and shallow imaging depth of 2–3 mm [49, 59, 60]. This limited coverage fails to capture the heterogeneous nature of cutaneous microcirculation and may lead to reproducibility issues, similar to single-point techniques such as LDF. Effective assessment of dermal microcirculation requires a larger FOV. Until OCTA technology advances to provide larger imaging areas and faster image acquisition, its use for evaluating microvascular function remains constrained to retinal imaging.

In critical care settings, retinal OCT and OCTA have been explored in feasibility studies and proposed as potential biomarkers for assessing microvascular status [61, 62]. However, widespread implementation in ICUs faces several challenges. Among patients with cerebral impairment requiring critical care, elevated intracranial pressure (ICP) is common in conditions such as neurotrauma, central nervous system infections, ischemic stroke, intracranial hemorrhages, and tumors. Research has shown that OCTA parameters are affected by high ICP, in patients with intracranial hypertension [63, 64], thus presenting as a potential confounding parameter. Additionally, while the need for facial access may pose challenges for using OCTA in orally intubated patients, Liu et al. [62] demonstrated that it remains partly feasible under these circumstances, despite the added procedural complexity.

In conclusion, retinal OCTA offers a valuable window into the microvasculature and can be used to assess microvascular status in systemic conditions like obesity and hypertension. In critical care, retinal OCTA has demonstrated feasibility for bedside monitoring of retinal microvasculature. However, its application is limited by challenges in facial access for orally intubated patients and potential confounding from elevated ICP. Cutaneous OCTA, while promising, faces restrictions due to its small FOV, low temporal fidelity, and heterogeneity of dermal microcirculation. Despite these limitations, OCTA holds potential as a bedside tool for microvascular assessment, though its use in critical care settings remains innovative and requires further development and validation.

Handheld Videomicroscopy

Nailfold Videocapillaroscopy

Videocapillaroscopy enables direct visualization of illuminated skin capillaries via a microscope equipped with video-transmission capabilities, often incorporated into a handheld device with recording functions. The periungual region is the most frequently examined site owing to the parallel alignment of nailfold capillaries relative to the skin surface, as shown in Figure 2. By visualizing only erythrocytes and not the vessel walls, this technique effectively captures only the actively perfused capillaries [65].

Fig. 2.

Example frame of NVC.

Traditionally, capillaroscopy has found extensive application in rheumatology for the diagnosis and monitoring of systemic sclerosis, scleroderma spectrum disorders, Raynaud’s phenomenon, systemic lupus erythematosus, and related conditions [66]. In patients with type 1 diabetes, capillary ischemia is indicated by reduced capillary blood cell velocity despite preserved total microcirculatory perfusion, as measured by LDF in the same area [67]. Early approaches were mostly qualitative or semiquantitative. However, advances in computing power and analytical methods are now driving the establishment of computer-derived standardized quantitative techniques, thereby hopefully improving diagnostic precision, reproducibility, and accessibility for nonexpert clinicians [68, 69].

Nailfold videocapillaroscopy (NVC) supports a range of assessments for both basal and functional aspects of microvascular status. Basal parameters include capillary density, apex dimension, morphology, hemorrhage detection, and blood cell velocity [70]. Moreover, functional assessments such as PORH, venous congestion, and fluorescein dye administration have demonstrated correlations with clinical outcomes and could be used in conjunction [71].

However, NVC also presents several limitations. As alluded to, it requires operator expertise, as inadequate training can result in unrepresentative data and potentially misleading conclusions. Achieving validated reproducibility, therefore, demands skilled personnel. Additionally, while capillary morphology can be determined directly at the patient bedside, data analysis of certain variables, such as blood cell velocity and capillary density, is calculated after measurements often through complex algorithms, which can be time-intensive, reducing its feasibility in more resource-limited or fast-paced clinical settings, such as emergency departments or intensive care units. Finally, the largely qualitative nature of many assessments complicates both validation and comparisons across studies.

Additionally, the suitability of NVC for critically ill patients has been questioned due to concerns about the confounding influence of body temperature on vasoreactivity [72]. While fingertip temperature has indeed been associated with reduced capillary density in individuals without cardiovascular disease aged 20–39 years [73], studies involving critically ill individuals found no such correlation with NVC parameters [74]. This discrepancy suggests that the effect of temperature on nailfold capillary measurements may be negligible in the setting of acute, severe illness. Nonetheless, further studies are needed to clarify the role of temperature-driven vasoreactivity changes in capillaroscopic findings, in critically ill populations.

Despite these challenges, advancements in automated image analysis, improved acquisition techniques, and standardized protocols are poised to enhance the reliability and clinical applicability of NVC. These innovations could facilitate its integration into routine bedside assessments and broaden its use across various clinical settings. Additionally, the shift toward quantitative metrics is expected to improve diagnostic precision and reproducibility, potentially making NVC more accessible to nonexpert clinicians.

SDF Imaging

SDF imaging builds on the principles of orthogonal polarization spectral (OPS) imaging, a reflection-based technique that visualizes superficial microvessels in sublingual or other mucosal tissues without requiring external contrast agents [75]. Both methods rely on selecting a wavelength at the isoabsorptive point for oxyhemoglobin (HbO2) and deoxyhemoglobin (Hb), enhancing contrast by making circulating red blood cells appear as dark silhouettes against the illuminated background [75, 76]. However, SDF introduces significant advancements over OPS by employing an annular arrangement of LEDs around a central light guide to create sidestream illumination, which prevents surface reflections and improves image clarity and depth [76].

SDF imaging is commonly used in the sublingual mucosa, where the LED lights flash in sync with the camera’s frame rate (intravital stroboscopy), effectively “freezing” red blood cell motion to reduce blurring and enhance visualization. Like OPS, SDF enables both qualitative and semiquantitative analyses, with the most common parameters being perfused capillary density and visible capillary flow [77, 78]. The technique has been widely applied in intensive care settings, where sublingual microvascular measurements have been linked to worse outcomes in critically ill patients [11]. Furthermore, SDF has been used as a goal-directed assessment tool in randomized controlled trials, although such studies have yielded mixed results [79].

Beyond perfused capillary density and flow, advanced semiquantitative methods using SDF imaging have been proposed to assess microvascular dysfunction by measuring glycocalyx thickness through leukocyte passage and evaluating the perfused boundary region, which reflects erythrocyte penetration into the glycocalyx and its structural integrity [80–83]. Additionally, leukocyte kinetics, such as their passage through capillaries and rolling behavior, have been studied in sepsis and cardiac surgery patients [84, 85]. While these techniques offer novel insights into microvascular health, their clinical significance remains uncertain and requires further investigation.

IDF Imaging

IDF imaging is a third-generation handheld microscopy technology that offers advancements over OPS and SDF imaging. While retaining the principle of green light illumination for hemoglobin absorption, IDF incorporates high-resolution digital sensors, ultrashort LED pulse illumination, and automated piezoelectric focusing [86]. These innovations deliver sharper RBC flow visualization, a larger FOV, and enhanced optical resolution, whereas the lightweight design claims to reduce pressure artifacts [87]. Unlike earlier analog systems, IDF enables real-time image analysis and vessel segmentation, potentially reducing operator dependency and reducing time required for post-processing. While the technology has been validated regarding feasibility in a clinical [88] and perioperative settings [89], it remains relatively novel, and large-scale studies evaluating its clinical validation and impact are yet to be conducted.

In conclusion, handheld videomicroscopy techniques have advanced significantly, offering valuable tools for assessing the microcirculation. Despite their strengths, these methods face several notable challenges. They often lack widely adopted protocols for evaluating the microvasculature’s dynamic responses – such as those seen with PORH, LTH, or Ionto assessments – focusing primarily on structural visualization rather than dynamics. Additionally, the relatively small FOV may introduce sampling bias and limit generalizability due to heterogeneity of the microvascular bed. Practical limitations, such as the reliance on sublingual imaging, can also pose challenges in orally intubated or uncooperative patients. Innovations like IDF imaging, with its smaller form factor, and the exploration of sublabial measurements as a surrogate approach, offer promising solutions [90]. However, further research and standardization are essential to fully integrate these methods into routine clinical and research applications.

Perfusion-Based Imaging

LDF and Laser Doppler Perfusion Imaging

LDF measures tissue blood flow by analyzing the Doppler-induced frequency shift of low-power, monochromatic laser light scattered by moving red blood cells. Early applications used single-point measurements via fiber-optic probes with sampling depths of up to 1 mm to capture capillary-level flow as well as deeper arterioles and venules. However, since single-point measurements were susceptible to spatial variability, laser Doppler perfusion imaging (LDPI) was developed to scan a laser beam across a larger field, generating two-dimensional, color-coded perfusion maps [91].

Both LDF and LDPI have been used across diverse clinical and research contexts. In patients with cardiac angina, LDF combined with functional assessment tools has demonstrated correlations with angina and nonobstructive and obstructive coronary artery disease [92]. In individuals with congestive heart failure, retinal LDPI parameters correlate with the degree of hypertrophic remodeling [93]. In pediatric sepsis, LDPI combined with Ionto shows an association with pSOFA scores [94]. Additionally, in an experimental septic shock model involving obese participants exposed to endotoxins, LDF-based LTH plateau responses revealed reduced microvascular vasoreactivity [95]. These findings highlight the versatility and clinical relevance of LDF and LDPI in evaluating microvascular function across a wide spectrum of pathological conditions and patient groups.

Despite offering quantitative perfusion data and broad-area imaging capabilities, LDF and LDPI each face notable limitations. Single-point LDF can suffer from poor reproducibility due to dermal microvascular heterogeneity, whereas LDPI’s slower data capture may limit real-time monitoring. Moreover, both methods require careful consideration of factors such as measurement site, ambient conditions, and patient-specific variables for optimal data quality [70, 91].

Laser Speckle Contrast Imaging

LSCI addresses a key limitation of LDPI by offering real-time, full-field imaging of microvascular blood flow. Its principle relies on measuring the dynamic “speckle” pattern created when laser light scatters off moving erythrocytes – the same physical principle as utilized with LDF and LDPI. Short-exposure images capture variations in speckle contrast that is decreased by motion blur when the dynamics of the speckle pattern increase. After processing, this yields an index proportional to blood flow speed and amount of blood, i.e., perfusion. Because each image is obtained in a single exposure – capturing the entire FOV at once rather than through a scanning process – LSCI achieves faster frame rates compared with LDPI’s raster-scanning approach [96].

Clinically, LSCI has been frequently used in cardiovascular medicine and critical care. For instance, in patients with untreated and masked hypertension, LSCI parameters measured in conjunction with PORH were significantly different from healthy controls; these parameters also showed negative associations with blood pressure, lipid levels, and smoking [97]. In patients with critical COVID-19, LSCI combined with Ionto revealed increased basal skin perfusion and reduced microvascular reactivity compared to controls matched for age and comorbidities [98]. In sepsis and septic shock, fingertip LSCI discriminated between septic and septic shock patients and correlated inversely with APACHE II severity scores [99]. In coronary artery disease, LSCI with PORH distinguished microvascular dysfunction in individuals with nonobstructive coronary artery disease from those with obstructive coronary artery disease and from healthy controls [100]. LSCI has also demonstrated good performance in wound healing potential prediction in patients with burn wounds [101].

While proven valuable for investigating microvascular perfusion dynamics, LSCI has inherent limitations that impact its clinical utility. One significant challenge is its susceptibility to noise, particularly from motion artifacts, which can distort measurements and compromise accuracy [102]. Due to its reliance on single-exposure imaging, LSCI struggles to differentiate between flow types such as venous, arterial, and capillary blood flow, as well as biological zero – the minimal signal arising from non-perfused tissue, such as from occlusion in PORH [103–105], however the significance of biological zero value in the context if LSCI is limited due to interpretation of data using dynamic rather than static variables. This ambiguity arises because speckle contrast values are influenced by both flow dynamics and the optical properties of tissue, making it difficult to isolate specific flow components [104]. Consequently, LSCI measurements are relative rather than absolute, which limits its ability to provide precise, quantitative data necessary for clinical applications [106].

Multi-Exposure Laser Speckle Contrast Imaging

MELSCI uses multiple exposure times to capture both fast- and slow-moving matter in tissue, enhancing the accuracy and fidelity of microvascular blood flow assessments, as shown in Figure 3 [107]. By recording speckle contrast at various exposures, MELSCI generates a more comprehensive dataset than single-exposure LSCI, reducing susceptibility to noise and providing a more linear correlation to perfusion in certain measurements [108], also improving feasibility of frequency component analysis for flowmotion analysis [109]. Machine learning algorithms convert these contrast measurements into robust perfusion maps in real time and may enable conversion to absolute units in contrast to relative single-exposure LSCI [108, 110–112]. It also enables the division of perfusion into different flow speeds, so-called speed-resolved perfusion. This enables the discrimination of flow conditions of high speed and low concentration from low speed and high concentration that may otherwise give rise to identical perfusion values although representing two different physiological states [112].

Fig. 3.

Example of speed-resolved MELSCI. The leftmost showing perfusion equivalent to LDI, the center picture showing 0–1 mm/s perfusion illustrated by a more homogenous network of perfusion, and the rightmost depicting above 1 mm/s and thus emphasizing larger vessels. All perfusion images are calculated from the same raw MELSCI data. Higher signals are illustrated as brighter in this visual representation.

Although Hultman et al. [108, 112] have demonstrated the clinical applicability of MELSCI by combining it with frequency-based analyses to derive absolute perfusion units [113], only limited pilot studies have been conducted so far [114]. If validated in larger cohorts, flowmotion-based analysis could prove valuable for patient stratification and individualized therapy. Although still a novel concept, these insights highlight the potential for MELSCI-based frequency component analysis to enhance diagnostic precision and guide targeted interventions, provided larger clinical trials affirm its utility.

Reflectance Spectroscopy Imaging

Near-Infrared Spectroscopy

NIRS is a noninvasive optical imaging modality that uses near-infrared light (650–1,000 nm) to penetrate biological tissues and assess tissue oxygenation and metabolism. NIRS exploits the transparency of tissue in the near-infrared spectrum and the distinct absorption spectra of chromophores such as HbO2 and Hb to estimate hemoglobin oxygen saturation based on the Beer-Lambert law [115–117].

NIRS for medical research use was initially developed for monitoring cerebral oxygenation, particularly in neonatology, perioperative and critical care settings, but its applications have expanded to include tissue and muscle oxygenation assessment in cardiac, vascular, and thoracic surgery [118, 119]. It has proven particularly valuable in settings such as extracorporeal membrane oxygenation and left ventricular assist device implantation, where it helps monitor nonpulsatile flow and detect perfusion abnormalities [120]. NIRS has been used in critical care settings to evaluate regional cerebral oxygen saturation differences between different sedation agents [121], detecting traumatic intracranial hematomas [122], and serving as an indirect marker for systemic microvascular dysfunction [123].

Despite its utility, NIRS has notable limitations. It primarily measures regional oxygen saturation in semi-deep tissues, in transcranial applications commonly the outermost 10–15 mm of intracranial space, making it unsuitable for shallow tissue assessment, the most common depth for organ-agnostic microvascular investigation [124, 125]. Additionally, NIRS has limited spatial fidelity, providing only coarse spatial resolution with narrow FOV that makes it difficult to resolve dysfunction exhibiting heterogeneity [126]. Furthermore, NIRS provides relative rather than absolute measurements, much like some perfusion-based methods [119, 127].

Hyperspectral Imaging

HSI, also known as multispectral imaging, builds on the principles of optical spectroscopy by measuring reflectance at multiple discrete wavelengths, generating a three-dimensional “hypercube.” Each pixel in this hypercube contains a full reflectance spectrum, enabling quantification of tissue chromophores such as HbO2 and Hb across an FOV as large as 8 × 8 centimeters, and some devices may provide even larger fields [128–130]. While NIRS assesses hemoglobin oxygenation, it usually provides limited spatial coverage or point-based measurements, although to a greater depth. By contrast, HSI’s full-field data acquisition allows for more detailed mapping of microvascular structure and function at a shallower depth.

HSI has demonstrated utility in oncology by identifying local oxygenation gradients and microvasculature patterns suggestive of malignancy [131–134]. Beyond oncology, it has been used to evaluate tissue saturation in patients with diabetic foot ulcers – particularly in those with neuropathy – and to differentiate microvascular changes in peripheral artery disease [135, 136]. In hemorrhagic shock models, HSI measurements of both HbO2 and Hb consistently track decreases in perfusion, showing reversibility upon resuscitation [137]. Despite these promising applications, widespread clinical adoption faces several challenges. The large datasets generated by HSI require powerful computing capabilities for real-time data handling and spectral unmixing, increasing both cost and complexity [128]. Matching measured spectra to specific tissue properties can be difficult, potentially leading to ambiguous interpretations [138].

Spatial Frequency Domain Imaging

SFDI projects patterns of light at different frequencies onto tissue, as shown in Figure 4. By analyzing how the tissue absorbs and scatters these light patterns, SFDI can separately measure absorption and scattering components [139]. By quantifying both light-absorbing structures (e.g., hemoglobin, melanin) and the microscopic structures responsible for light scattering (e.g., collagen, cell nuclei), SFDI reveals information about tissue dynamics as well as structure [139, 140]. Further, it is able to measure parameters in a two-layer model by adjusting the patterns of light at different frequencies, allowing for discrimination between superficial dermal capillaries and deeper arterioles and venules [140].

Fig. 4.

Example of SFDI: the left frame shows light grid of visible light, to the right; color-graded oxygenation map.

SFDI is used in medical imaging to measure tissue properties such as oxygenation saturation, hemoglobin concentration, and water content. It has currently been applied in wound assessment, burn severity stratification, and surgical guidance, providing quantitative maps of tissue features across large dermal areas [141–146]. In clinical research, SFDI has been used to assess vascular complications in diabetic patients, demonstrating greater diagnostic accuracy than standard methods like the ankle-brachial or toe-brachial indices [147]. In patients with peripheral artery disease undergoing surgical reperfusion, improvements measured using SFDI have been shown to correlate with positive clinical outcomes [148].

The reliance on depth resolution and two-layer modeling makes SFDI inherently sensitive to surface profiling and calibration errors, where even minor patient or instrument movement can introduce inaccuracies, partly due to restricted temporal fidelity [149]. This sensitivity, coupled with the need for precise calibration, poses challenges to its efficient application in dynamic or urgent clinical settings. These limitations may hinder the use of this device in fast-paced environments such as emergency rooms and intensive care units, where rapid and reliable measurements are critical. Despite these challenges, SFDI remains a valuable spatial imaging tool for determining chromophore content, such as oxygenated tissue hemoglobin, offering significant promise for assessing the microvascular milieu.

Conclusion

The rapid evolution of noninvasive microvascular assessment methods is driven by innovations in computational power, AI-driven modeling, and novel imaging hardware. Current techniques span structural modalities – such as OCTA and handheld videomicroscopy – to perfusion-based systems like LSCI and MELSCI, as well as spectral-based tools like NIRS, HSI, and SFDI. Some of these methods can be enhanced by functional provocations (e.g., PORH, Ionto), offering a more comprehensive view of microvascular health and reactivity. Collectively, these advances have expanded the researcher’s possibilities, facilitating in vivo visualization and quantification of both anatomical and functional parameters to stratify the microvasculature.

Although the methods promise in research contexts, widespread clinical adoption remains constrained by the need for standardized protocols and further validation that connect microvascular metrics to patient outcomes. Integrating multiple techniques – such as imaging the microarchitecture (e.g., OCTA, IDF), assessing flow dynamics (e.g., LSCI), and capturing tissue characteristics through reflectance spectroscopy – can improve diagnostic accuracy, deepen understanding of disease pathways, and strengthen patient stratification. For clinicians or researchers focusing on specific components of microvascular function, a complementary suite of structural, functional, perfusion-based, and tissue-characterizing methods may offer a more nuanced assessment.

For researchers and clinicians planning to employ microvascular evaluation techniques, it is essential to first clearly define the study objective or hypothesis to select the appropriate methodology. For instance, if the goal is to assess tissue characteristics such as oxygenation, water content, and baseline vascularization, then spectral imaging methods (e.g., HSI) or structural techniques like OCTA may be optimal. Conversely, if the aim is to evaluate dynamic microvascular functionality, devices designed for functional assessments – such as perfusion-based imaging systems – are more suitable. Considerations must also be made in regard to convenience, FOV, and tissue depth. In many research applications, a multimodal approach that integrates both perfusion metrics and tissue characteristic analysis may be informative to evaluate different aspects of microvascular function, while addressing potential confounding variables.

Looking ahead, collaborations among academic institutions, healthcare providers, and private-sector partners – including device manufacturers – will be key to transitioning laboratory prototypes into user-friendly, regulated medical devices. As evidence accumulates and protocols become more uniform, these technologies are poised to assume a larger role in everyday clinical practice and translational research, ultimately improving patient management and outcomes.

Acknowledgments

The generative artificial intelligence model o1, by OpenAI, was utilized for grammar review, wording adjustments, and synonym suggestions in the preparation of this manuscript [150]. All interpretations and conclusions remain solely the responsibility of the authors.

Conflict of Interest Statement

Ingemar Fredriksson is employed by Perimed AB that is marketing products related to some of the techniques described in this publication. However, he or Perimed AB has not been involved in the selection of techniques included in the publication. All other authors have no conflicts of interest to declare.

Funding Sources

This study was not supported by any sponsor or funder.

Author Contributions

Jacob Widaeus, MD: conceptualization, methodology, and writing – original draft, review, and editing. Ingemar Fredriksson, PhD: review and editing. Sara Tehrani, MD, PhD: validation, review, and editing.

Funding Statement

This study was not supported by any sponsor or funder.