Dynamic microvascular monitoring with miniaturized omnidirectional broadband photoacoustic imaging system for living entities (MOBILE)

Domain: physics
Published: 2026-01-08
Editorial outcome: major_revision

Abstract
Microcirculation monitoring is crucial for evaluating cardiovascular health and detecting organ dysfunction early, but existing bedside imaging techniques often cannot provide sufficient resolution and depth for dynamic assessment during natural physiological activities. Here, we present MOBILE (Miniaturized Omnidirectional Broadband Photoacoustic Imaging System for Living Entities), a photoacoustic imaging system that allows unrestricted microcirculatory monitoring with 40 µm resolution and penetration depth of 10 mm, allowing stratified visualization of dynamic vascular responses. This platform features an ultracompact fibre-optic sensor capable of omnidirectional ultrasound-based detection across a large bandwidth (0.3–80 MHz). The compact design of the system facilitates point-of-care monitoring through seamless integration with portable devices or existing clinical systems. Through a comprehensive evaluation of the patient’s haemodynamic parameters, MOBILE reveals distinct dynamic responses of vessels at different tissue depths, from superficial microvessels to deep subcutaneous vessels, capturing vessel-specific changes in diameter, haemoglobin concentration, and tissue oxygenation during numerous physiological challenges. This platform offers possibilities for understanding microcirculatory responses and improving critical care management through high-resolution vessel monitoring.

Introduction
The microcirculation, an intricate network of small blood vessels, serves as an important conduit for maintaining tissue functionality and metabolic activities through the dynamic regulation of the local blood supply 1–3. Understanding the dynamics of the microcirculation during natural physiological activities is crucial, as the most significant microcirculatory adaptations occur in response to exercise, postural changes, and environmental stimuli. Moreover, microcirculatory dysfunction is increasingly recognized as an early indicator of multiple pathological conditions, including cardiovascular diseases, sepsis, and diabetes; therefore, continuous assessment of microcirculatory dynamics could aid in both early diagnosis and therapeutic monitoring 4–10. However, comprehensive assessment of these dynamics remains technically challenging, as it simultaneously requires high spatiotemporal resolution, adequate imaging depth, and continuous monitoring capabilities during unrestricted movement. Current imaging technologies are unable to meet all these requirements: conventional modalities such as CT and MRI, while offering whole-body scanning capabilities, are impractical for continuous monitoring because of operational constraints; microbubble contrast agent-based ultrasound allows only intermittent visualization 11–13; and optical approaches, including video microscopy 14 and optical coherence tomography 15,16, are fundamentally limited in terms of either penetration depth or spatial resolution.

Photoacoustic imaging has emerged as a promising approach to address these challenges by combining optical excitation with ultrasonic detection, allowing high-resolution visualization of vascular structures at clinically relevant depths 17–23. While conventional photoacoustic systems have demonstrated effectiveness in analyzing haemodynamics 24–28 and characterizing the microcirculation under various pathological conditions 29–32, their reliance on bulky ultrasound transducer arrays has limited applications primarily to stationary diagnostic imaging tasks, such as breast cancer detection 33,34. Recent developments in small 35, wearable photoacoustic devices 36 represent progress towards dynamic monitoring, but current systems can only visualize a few isolated vessels, which is unsuitable for achieving a comprehensive assessment of the microvasculature.

In this study, we introduce MOBILE (Miniaturized Omnidirectional Broadband Photoacoustic Imaging System for Living Entities), a novel approach for imaging the microcirculation that employs a miniaturized photoacoustic probe based on a compact fiber-optic ultrasound sensor. Our sensor leverages isotropic vibrations within an optical fiber to achieve omnidirectional, broadband (0.3–80 MHz) ultrasound detection and exceptional sensitivity. Through these technical advancements, MOBILE allows visualization of vessels spanning multiple scales (40 µm to 1.5 mm diameter) within the dermis and subcutaneous tissues up to a depth of 1 cm with high resolution. The compact sensor design—including a sensing area 300-times smaller than that of conventional piezoelectric transducers—facilitates versatile implementation in both handheld and wearable formats while maintaining high performance across a wide range of angles. We demonstrate the clinical utility of MOBILE through comprehensive monitoring of the peripheral microcirculation during various physiological challenges, revealing vessel-specific dynamics in terms of hemoglobin concentration, diameter, and oxygen saturation across the vascular tree. Notably, our system allows the simultaneous characterization of distinct responses across vessel sizes and depths, from superficial capillaries to deep subcutaneous vessels, providing novel insights into the heterogeneous behavior of the microcirculation during natural physiological activities. The results of this study bridge a critical gap in our understanding of vessel-resolved microcirculatory dynamics and their role in systemic haemodynamic regulation.

Results
MOBILE system design and performance characterization
Figure 1 presents our MOBILE system for dynamic microvascular imaging. The miniaturized design features a fiber-optic ultrasound sensor positioned horizontally along the y-axis, with linear scanning performed along the x-axis within a suitable range at increments optimized for Nyquist sampling. The cylindrical sensor acts as a point detector in the x-z dimension and an integrating detector in the y-dimension, enabling volumetric coverage (Supplementary Note S2a). During image acquisition, nanosecond laser pulses uniformly illuminate the region of interest. Hemoglobin within the tissue absorbs the optical energy and converts it into ultrasound waves via the photoacoustic effect, radiating omnidirectionally. The flight time and amplitude of these ultrasound waves encode the spatial position and concentration of vascular absorbers, respectively. The system employs acoustic tomographic reconstruction to precisely localize these absorbers by coherently synthesizing time-delayed signals through back-projection algorithms (Supplementary Note S2a,b). To expand the detectable volumetric field, we extended the cavity length to 3 mm, creating a cylindrical detection zone whose thickness is determined by this cavity dimension. This configuration enables volumetric information capture within a single linear scan. The imaging field-of-view is defined by three key parameters: the scanning range, which determines the lateral extent of coverage, the sensitivity and angular acceptance of each sensor position, which governs the depth range that can be effectively imaged. The modular sensor design enables flexible optimization between field-of-view and detection sensitivity to meet specific monitoring requirements.

For omnidirectional and broadband ultrasound detection, we implemented a single-polarization, single-longitudinal-mode fiber laser sensor that leverages isotropic fiber vibrations across the transverse plane, the sensor fabrication based on erbium-doped fiber Bragg grating (see Methods and Supplementary Note S1). These vibrations couple efficiently with intracore light to produce measurable optical phase variations. Figure 1b demonstrates the omnidirectional response capability through temporal waveforms captured from ultrasound waves at various incident angles (0–180°), providing the extensive angular coverage essential for comprehensive tomographic imaging. This capability stems from the radially symmetric fiber structure, which responds equally to acoustic waves arriving from any transverse direction. Combined with the small sensor dimension (62.5 μm diameter, comparable to the acoustic wavelength at tens of MHz), this geometry enables a 180° angular acceptance range in the transverse plane. The compact size also effectively alleviates the spatial averaging effect, ensuring broad bandwidth ultrasonic detection capabilities.

The sensor’s phase variations are detected through a self-delayed heterodyne mechanism implemented via a custom unbalanced fiber-optic interferometer (Supplementary Note S1a). The customized unbalanced fiber-optic interferometer comprises one arm with a frequency downshifted by Ω = 2π × 200 MHz through an acoustic-optical modulator (AOM), while the other arm is delayed by τ using a segment of single-mode optical fiber. Upon recombination and detection by a photodetector, these light beams generate a beat signal at Ω with a phase modulation represented by Θ(Ω) = G · Θ(Ω), where Θ(Ω) and Θ(Ω) are the spectral profile of beat signal after downconvert and laser phase vibration induced by incident ultrasound, respectively. The gain factor |G| = 2 sin(Ωτ/2) allows sensitivity adjustment over a broad frequency, where Ω denotes ultrasound frequency (Supplementary Note S1a). The rare-earth-doped active fiber enables the integration of the laser source and acoustic sensor into a single device by forming a laser resonant cavity within the fiber itself. This integrated design offers two key advantages: (1) it provides intrinsically low-noise laser emission, eliminating the need for external laser sources and associated coupling losses, providing a more compact and stable detection system particularly advantageous for in vivo applications. (2) it produces significantly larger phase shifts in response to acoustic perturbations due to the intracavity amplification effect, thereby enhancing acoustic sensing sensitivity. The operating wavelength, pump configuration, grating parameters, and signal acquisition electronics were selected from commercially available telecommunication-grade components, facilitating seamless system integration and cost control while maintaining high performance (Supplementary Table S5).

This detection strategy increases the operational bandwidth to 0.3–80 MHz (Fig. 1e, linear coordinates in Supplementary Fig. S2b), wherein the experimentally validated frequency response achieves across macroscale (0.3–1 MHz), mesoscale (1–10 MHz), and microscale (10–80 MHz) vascular imaging regimes 28,37. The observed fluctuations in sensitivity at high frequencies originate from acoustic resonance modes within the fiber structure (Supplementary Note S1c). The heterodyne approach effectively cancels common-mode noise from thermal fluctuations and environmental vibrations. Characterization of spatial resolution (Fig. 1c) demonstrated a consistent axial resolution of ~50 μm throughout the 1–14 mm depth range, which is determined primarily by the sensor’s detection bandwidth. The lateral resolution, governed by the central frequency and effective angular coverage, ranges from 33 µm (superficial) to 96 µm (deep) with increasing tissue depth (see Supplementary Note S3a). Notably, our system maintains sub-100 µm resolution up to a depth of 14 mm, which is critical for detailed microvascular visualization. Signal-to-noise ratio (SNR) analysis (Fig. 1d) revealed excellent performance, with 54 dB at a depth of 4 mm, which gradually decreased to 12 dB at 22 mm, confirming the system’s suitability for deep tissue imaging.

Figure 1f illustrates the imaging system architecture, which comprises three main sections: the excitation section with a pulsed laser and fiber bundle for light delivery, the detection section with fiber sensor, multiplexable fiber-optic interferometry, photodetector and the data processing module. A field-programmable gate array (FPGA) based control unit is utilized to synchronize the operations of the laser, scanning, and data acquisition systems. The imaging probe connects these components to the biological tissue. Two imaging protocols are demonstrated: Protocol 1 employs linear scanning configuration with water tank coupling, providing stable imaging conditions for anesthetized animals, and stationary human subjects; protocol 2 is a handheld probe with miniaturized water chamber, enabling flexible point-of-care monitoring during unrestricted movements, postural changes, and physiological challenges.

Small-animal imaging
We validated the imaging capabilities of MOBILE through comprehensive vascular mapping in rodent brain and kidney models with monitoring protocol 1, which present significant challenges owing to their complex, multiscale vascular networks. In the brain imaging model, our system achieved detailed coronal visualization to a depth of 7 mm with near-infrared excitation light, revealing intricate vascular structures from the cortical surface to deep thalamic regions (Fig. 2a). Similarly, the system demonstrated robust performance in rat kidney imaging, where sagittal and axial sections revealed the complete hierarchical vascular organization from the cortex to the medulla (Fig. 2b,c), demonstrating the system’s capability to resolve vessels across multiple tissue depths and organizational scales. The anatomical accuracy was validated through comparative analysis with high-field magnetic resonance angiography (9.4 T MRA, the Biospec 94/20 USR from Bruker), which confirmed consistent vascular patterns, particularly for sub-100 µm vessels in the hippocampus and cortical regions (Supplementary Note S5a and Supplementary Fig. S18) 38.

A critical challenge in compact photoacoustic imaging is the detection of steeply oriented vessels, which are abundant in both cerebral and renal microvasculature yet emit ultrasound signals at large propagation angles that exceed the acceptance range of conventional transducers. This limitation is particularly problematic for penetrating vessels—such as cortical penetrating arterioles in the brain and interlobular arterioles in the kidney—which typically propagate perpendicular to the tissue surface and play essential roles in delivering oxygen and nutrients to metabolically active tissues (neurons, glomeruli, and renal tubules). Dysfunction of these vessels is implicated in severe pathologies, including cerebral infarction and renal ischemia 38,39. Traditional linear photoacoustic probes, constrained by ±40° acceptance angle, fundamentally limit their utility for comprehensive microvascular assessment (Supplementary Table S2). To quantitatively demonstrate our system’s angular detection advantage, we employed angle-encoded color mapping (Fig. 2d,e), where vessel orientation is color-coded relative to the horizontal plane (0–180°). Vessels appearing in green/blue correspond to signals within the conventional ±40° acceptance range, while vessels in red/orange represent signals arriving at steep angles (40–82.5°) that would be missed by traditional configurations. In the mouse brain (Fig. 2d), numerous penetrating arterioles in the cortex and hippocampus exhibit steep angles (>50°), appearing predominantly in red/orange hues. In the rat kidney (Fig. 2e), the angle-encoded map reveals the characteristic radial vascular architecture: medullary vessels (primarily arcuate and interlobar arteries) exhibit predominantly steep angles (>50°) due to their perpendicular orientation to the imaging plane, while cortical vessels show more diverse angular distributions. This omnidirectional detection capability, enabled by our fiber-optic sensor’s wide acceptance angles, ensures comprehensive visualization of the complete vascular network regardless of vessel orientation.

Furthermore, the frequency-encoded visualization (Fig. 2f) shows that the system is capable of effective multiscale imaging across a diameter range corresponding to one octave, wherein high-frequency components (>30 MHz) allow detailed mapping of fine vascular structures. This comprehensive detection capability, spanning both the angular and frequency domains, makes MOBILE a powerful tool for investigating complex vascular networks across multiple tissue depths and vessel orientations.

Imaging of subcutaneous vessels in humans
We performed in vivo imaging of the vasculature of the human hand with MOBILE at specific monitoring sites (S1, S2) that included the finger and palm (Fig. 3a, details in Supplementary Note S3c and Supplementary Figs. S12, S13) with monitoring protocol 1. All measurements strictly followed ANSI safety standards for laser exposure (See Supplementary Table S3), and ethical approval was granted by the Jinan University Ethics Committee (Approval Number: JNUKY-2023-0151, n=9 healthy volunteers). Excitation at 532 nm (Fig. 3b), at which strong hemoglobin absorption occurs, resulted in excellent visualization of superficial structures, including capillary and the vascular plexus. Imaging at 1064 nm achieved greater penetration (~1 cm, shown in Supplementary Fig. S13a) due to reduced scattering while clearly delineating deeper vessels such as proper palmar digital arteries.

Dual-wavelength imaging (532 nm and 1064 nm) enabled functional assessment of tissue oxygenation through differential hemoglobin absorption. At 532 nm, oxyhemoglobin (HbO₂) and deoxyhemoglobin (Hb) exhibit nearly level absorption coefficients (μa ≈ 22.48 mm⁻¹ for HbO₂ and 18.66 mm⁻¹ for Hb), approximating an isosbestic point where photoacoustic signals are relatively insensitive to oxygenation variations. In contrast, at 1064 nm, HbO₂ shows significantly higher absorption (μa ≈ 0.45 mm⁻¹) compared to Hb (μa ≈ 0.2 mm⁻¹), enabling oxygenation-dependent contrast 40–44. We quantified tissue oxygenation using the S factor, defined as the signal ratio S = I₁₀₆₄/I₅₃₂, where I₁₀₆₄ and I₅₃₂ represent the PA amplitudes at 532 nm and 1064 nm and higher S values indicate greater oxygenation. While the S factor serves as a relative indicator rather than an absolute oxygen saturation measurement—owing to wavelength-dependent optical scattering and tissue heterogeneity—it remains valuable for comparative analysis within similar tissue types and for monitoring dynamic oxygenation changes in response to physiological perturbations.

Dual-wavelength composite images of the finger and palm (Fig. 3d,g) revealed distinct spatial distributions of the S factor across anatomical layers, including the epidermis (EP), papillary dermis (PD), reticular dermis (RD), and subcutaneous tissue (ST). Quantitative comparisons across anatomical sites (Fig. 3h) showed significant regional variations, with the finger exhibiting higher S factors (0.46 ± 0.07) compared to the palm (0.41 ± 0.08) and arm (0.17 ± 0.11) in the papillary dermis layer (p < 0.05). These regional differences align with established variations in cutaneous vascular density and metabolic demands 39,45, reflecting the functional specialization of microcirculation across different anatomical sites (more images presented in Supplementary Fig. S13).

The omnidirectional broadband detection capability of the system enabled comprehensive vessel characterization through frequency encoding (Fig. 3e). Vessels were classified on the basis of their acoustic signatures: high-frequency components (>30 MHz, blue) correspond to the microvasculature, while lower-frequency components (<30 MHz, red) represent larger vessels. This ability to image vessels at multiple scales, including arteriole (40 μm) and arteries (1.5 mm), was validated through structural analysis (Fig. 3e, inset), which demonstrated consistent vessel diameter measurements across the entire range. Depth-encoded visualization (Fig. 3f) revealed clear stratification of vascular networks from superficial to deep tissues (0–10 mm). Correlation analysis (Fig. 3i) revealed the relationship between vessel diameter and anatomical depth, demonstrating the ability of our system to detect vessels across multiple scales throughout the entire imaging volume while maintaining the advantages of a flexible fiber-optic implementation.

Haemodynamic response monitoring with venous occlusion
To validate the ability of MOBILE to capture dynamic vascular responses, we performed venous occlusion-reperfusion experiments by applying pressure to the upper arm with monitoring protocol 1 (Fig. 4a–g). The protocol consisted of continuous monitoring of the thenar vasculature at baseline (0–60 s), during venous occlusion (60–260 s, 80 mmHg cuff pressure), and during reperfusion (260–430 s). The results provide valuable insights into endothelial function, a critical indicator of various cardiovascular risk factors 46,47.

Multi-depth photoacoustic imaging revealed distinct haemodynamic responses across tissue layers during the protocol (Fig. 4b–d). The imaging results revealed a significant elevation in signal amplitude during occlusion relative to baseline, suggesting an increase in hemoglobin concentrations across all vascular layers. This phenomenon can be attributed to the obstruction of venous outflow while arterial inflow remained constant. Spatiotemporal analysis revealed depth-dependent patterns in both hemoglobin concentration (Fig. 4e) and oxygen saturation (Fig. 4f). The papillary dermis (PD) presented the most pronounced increase in hemoglobin (49%) and oxygen desaturation (41%) during occlusion, whereas the reticular dermis (RD) presented only moderate changes (an ~21% increase and 20% decrease, respectively). Interestingly, the subcutaneous tissue (ST) demonstrated relatively stable hemoglobin levels (2–3% increase) but increased oxygen saturation (13%). The observed increase in hemoglobin concentration alongside a decrease in oxygen saturation can be attributed to the restricted transport of deoxygenated blood from the peripheral vessels back to the lungs, as blood accumulates while the tissues continue to consume oxygen during occlusion. The more pronounced response of the PD relative to the RD likely reflects the greater density of capillaries in the PD, which serve as crucial exchange sites for oxygen and nutrients to epidermal cells. The relatively modest response within the ST suggests the engagement of complex oxygen redistribution mechanisms across tissue depths.

Vessel-specific analysis (Fig. 4g) revealed different responses depending on vessel type and size. The venule (V2, 87 μm) demonstrated the largest diameter changes (~62%) during occlusion, peaking at ~180 s, whereas the arteriole (V1, 69 μm) showed similar increases in diameter (51%). Larger vessels exhibited progressively smaller changes, with the deepest arteries (V4, 826 μm) showing minimal dilation (~7%), reflecting size-dependent vascular compliance. These multiparameter observations align with previous findings while reflecting the unprecedented resolution of our system for visualizing depth-specific microvascular dynamics 48,49.

Heat-induced hyperemia experiment
To investigate microvascular responses to thermal challenges, we performed cold-to-warm transition experiments on the palm (Fig. 4h–n). The protocol involved immersing the hand in cold water (10°C) followed by gradual warming to 33°C over 590 s, enabling continuous monitoring of temperature-induced haemodynamic responses. Time-lapse dual-wavelength imaging (Fig. 4i–k) captured progressive vascular responses across three phases: cold baseline (0 s), thermal stimulation (250 s), and sustained hyperemia (590 s). Unlike venous occlusion—which induced uniform vessel dilation with increased oxygenation across all layers—thermal stimulation elicited striking depth-dependent patterns. Quantitative analysis (Fig. 4l,m) revealed that the papillary dermis (PD) exhibited decreased hemoglobin concentration (−15%) and oxygen saturation (-20%), whereas deeper layers demonstrated substantial increases in both parameters (RD: hemoglobin +42%, oxygen saturation +21%; ST: hemoglobin +29%, oxygen saturation +26%). Vessel-specific tracking (Fig. 4n) revealed uniform vasodilation across vessel types (+35 to +53%).

The observed paradoxical haemodynamic response in the papillary dermis—characterized by simultaneous reductions in blood volume and oxygenation despite widespread vasodilation—point to the potential activation of arteriovenous (AV) shunts. These AV anastomoses, located within the papillary dermis, may preferentially open during thermal stimulation, effectively redirecting blood flow from arterioles to venules while bypassing the dense capillary networks in superficial layers. This mechanism aligns with established thermoregulatory strategies that optimize heat dissipation at the skin surface.

Notably, haemodynamic patterns observed in this study are consistent with prior findings using benchtop high-frequency photoacoustic imaging systems 50. However, our flexible fiber-optic imaging approach uniquely enables high-resolution tracking of vascular responses across extended tissue depths and diverse vessel types in vivo. To definitively confirm the involvement of AV shunts in these complex microvascular dynamics, further validation using complementary techniques—such as functional ultrasound, laser Doppler flowmetry, or direct anatomical imaging—will be essential.

High-intensity exercise reveals complex microcirculation dynamics
To extend our investigation to more demanding conditions, we developed a probe integrated with a handlebar for high-intensity cycling exercise (Fig. 5i). The protocol included a 280 s baseline period (0–280 s), an 840 s cycling period (280–1120 s), and a 600 s recovery period (1120–1720 s). The integrated probe design ensured stable contact during vigorous motion, whereas the ultrasound coupling gel maintained consistent imaging conditions despite the presence of exercise-induced movement. Photoacoustic imaging revealed distinct vascular patterns across the exercise phases (Fig. 5j–l), with the baseline state (t=40 s) showing a normal vessel distribution, the exercise period (t=880 s) demonstrating significant vascular adaptation, and the recovery phase (t=1600 s) exhibiting a gradual return to the patterns observed at baseline. High-intensity exercise elicited more pronounced microcirculatory adaptations than free motion did, with temporal analysis revealing that the peak heart rate corresponded with decreased rather than increased skin blood concentration, indicating greater blood redistribution.

Depth-resolved analysis (Fig. 5m,n) demonstrated layer-specific responses: during the exercise process, the PD showed a rapid decrease in oxygenation (27%) with a simultaneous reduction in the hemoglobin concentration (7%). The RD exhibited subtle increases in both oxygenation (3%) and blood concentration (4%), suggesting minimal involvement in the oxygen exchange processes. The ST displayed a distinctive pattern of decreased oxygenation (25%) coupled with increased hemoglobin concentration (14%), which is consistent with exercise-induced arterial constriction.

Unlike transcutaneous oximetry, which provides only single-point, indirect measurements of tissue oxygenation, our photoacoustic system enables simultaneous monitoring of blood concentration and oxygenation across multiple tissue layers with high spatial and temporal resolution. The advantages of this system are evidenced by the results of our vessel-specific analysis (Fig. 5o,p), which revealed different vascular adaptations during high-intensity exercise: the arteriole (V6, 86 μm) demonstrated up to 19% constriction, whereas the venule (V5, 83 μm) showed 32% dilation, and vessels (V7, 268 μm; V8, 740 μm) exhibited consistent constriction patterns (20% and 8%, respectively). These detailed microvascular dynamics, combined with layer-specific haemodynamic response, significantly exceeded the sensitivity of transcutaneous measurements (7% decrease in pO₂). The temporal correlation between vascular responses and heart rate dynamics captured rapid blood oxygen fluctuations during exercise transitions, which were particularly pronounced during heart rate elevation phases, followed by quick stabilization during steady-state exercise. These dynamic patterns, typically undetectable with conventional technologies, provide unprecedented insights into exercise-induced vascular adaptation mechanisms.

Methods
Fiber-optic ultrasound sensor
The sensor was constructed on the basis of a single-frequency, single-polarization fiber laser built in an active, rare-earth-doped optical fiber (EY-305, Coractive, Inc.) with dual wavelength-matched Bragg gratings (see photo in Fig. 1f). The laser architecture features two precisely engineered 3-mm Bragg reflectors that provide optical feedback, created with a phasemask (period: 1062.2 nm, Ibsen Photonics) under controlled UV exposure from an excimer laser (Coherent, Compex Pro 110F, 40 mJ, 30 Hz). This configuration generates a highly polarization-selective resonant spectrum. When pumped by a custom-designed 980-nm low-noise semiconductor laser, the cavity maintains single-polarized laser operation. Ultrasound-induced perturbations modulate the laser frequency, which is detected through a self-delayed heterodyne detection scheme (more parameters in the Supplementary Note S1 and Supplementary Table S5).

Sensor calibration and characterization
We performed a frequency response calibration of the fiber sensor using photoacoustic signals. The ultrasonic source was generated by a 532 nm pulsed laser (Pulse width: 5.2 ns) inducing the PDMS-carbon powder composite layer coated on the end face of the optical fiber. We conducted ultrasonic pressure calibration using a calibrated needle hydrophone (NH0200, Precision Acoustics). Initial sound pressure calibration measurements were obtained 1 mm from the ultrasonic source using the hydrophone, with systematic optimization of the transmitting and receiving angles. The ultrasonic amplitude spectrum density H(Ω) was analyzed in conjunction with the hydrophone’s known responsivity (SH(Ω), 48 mV/MPa over 30 MHz) to determine the pressure spectral density P(Ω) = H(Ω)/SH(Ω). Next, we assessed the acoustic response of the fiber sensor by positioning it orthogonally to the incident ultrasound waves and recorded the acoustically induced laser phase variations. The sensor was rotated in 10° increments to record these data shown in Fig. 1b. Finally, its sensitivity was received shown in Fig. 1e.

MOBILE imaging system configuration
For photoacoustic excitation, we utilized a Q-switched Nd:YAG laser (Dawa-200, Beamtech) with dual wavelengths of 532 and 1064 nm, a pulse width of 5.2 ns and 5.7 ns, a repetition rate of 20 Hz. The initial spot size of the laser beam was 6 mm, which we expanded to a 2.5-cm-diameter illumination spot with a beam diffuser (DG10-120, Thorlabs). The optical fluence at 532 nm was maintained at 6.5 mJ/cm², significantly below the American National Standards Institute (ANSI) safety limit of 20 mJ/cm². Similarly, the fluence at 1064 nm was maintained at 12.9 mJ/cm², also well under the ANSI threshold of 100 mJ/cm² (Details in Supplementary Table S3).

Sensor array for dynamic imaging
We developed an 8-element fiber optic sensor array (Supplementary Fig. S4) utilizing wavelength and time division multiplexing for enhanced imaging speed in dynamic microvascular imaging. The array elements operate at eight distinct wavelengths (1542.12–1547.72 nm, 0.8 nm interval) corresponding to standard DWDM communication channels. The multiplexed optical signals undergo uniform amplification through a customized erbium-doped fiber amplifier to achieve consistent channel power levels (~23 dBm). The amplified signals are processed through a self-coherent interference pathway and systematically transmitted to the photodetectors for photoelectric conversion. Finally, these electrical signals were simultaneously collected by an 8-channel data acquisition card and demodulated into PA signals, resulting in an imaging speed of 10 s per frame.

Performance characterization of MOBILE
Spatial resolution: Black-dyed microspheres (10 μm diameter) were employed to assess the spatial resolution of the system (Supplementary Note S3a and Supplementary Fig. S9a–d). The sample preparation protocol consisted of the following: First, a dissolved agar solution was poured into a mould and allowed to solidify. A centrifuged microsphere suspension was subsequently carefully deposited onto the solidified agar substrate. A final agar layer was then overlaid to immobilize the microspheres, creating a three-layer agar block with microspheres embedded in the central plane. In this way, we ensured a uniform planar distribution of the microspheres, allowing calibration of the resolution across multiple depths. Following microsphere imaging acquisition, we analyzed the particles at depths ranging from 2 mm to 15 mm relative to the surface of the fiber-optic sensor surface. Lateral and axial resolution metrics were obtained through envelope detection of the point-spread functions, and the resulting depth-dependent resolution profile is presented in Fig. 1c.

Image depth: The penetration capacity of the photoacoustic system was evaluated using pencil graphite arrays embedded within chicken breast tissue (Supplementary Note S3a and Supplementary Fig. S9k–m). A 3D-printed chamber was used to stably accommodate the chicken breast to a depth of 30 mm and enable precise parallel insertion of eight 0.5-mm-diameter pieces of pencil graphite at 3 mm vertical intervals. Depth-dependent signal-to-noise ratio (SNR) metrics, as shown in Fig. 1d, were derived from reconstructed photoacoustic images of the pieces of pencil lead, in which the noise amplitudes were quantified from the root mean square (r.m.s.) of the background noise and the signal amplitudes were determined by the peak photoacoustic intensities of the reconstructions of the pencil graphite.

Image reconstruction and processing
We implemented a dual speed-of-sound (SoS) back-projection algorithm using the MATLAB k-wave toolbox for image reconstruction, which significantly reduced imaging artefacts and improved visualization of perpendicular vessels (detailed in Supplementary Note S2). For quantitative assessment, we generate spatiotemporal heat maps to analyze dynamic changes in the vascular network. Firstly, to ensure the accuracy of the statistical results, all spatiotemporal maps presented in Figs. 4 and 5 of main text were derived from the reconstructed images data without contrast enhancement. Secondly, the region of interest (ROI), indicated by orange dashed line in Figs. 4 and 5, was used for calculation. Thirdly, the absolute values of dual-wavelength (1064 nm and 532 nm) photoacoustic signals were superimposing within ROI across each depth layer to generate a preliminary spatiotemporal map. For example, the depth layers of Fig. 4b correspond exactly to those in Fig. 4e. Simultaneously, the preliminary map of S factor was obtained by calculating as S = I₁₀₆₄/I₅₃₂ within ROI across each depth layer, where I₁₀₆₄ and I₅₃₂ denote the absolute values of 1064 nm and 532 nm photoacoustic amplitudes, and the S factor is proportional to blood oxygen. Then, a moving average filter (with a kernel size of 100 μm along the depth direction and 30 s along the time direction) was applied to both of PA amplitude and S factor spatiotemporal maps to reduce the temporal and spatial fluctuations. Finally, the spatiotemporal map of PA amplitude changes and relative changes in blood oxygenation (S factor change) were both normalized respectively to its baseline (defined as the average value of the first ten seconds) to derive the temporal dynamics for each layer.

Vessel diameter measurements are conducted using the full-width-at-half-maximum (FWHM) method on the reconstructed images, with multiple measurements taken along each vessel segment of interest for statistical reliability. The specific steps are as follow: extract the envelope curve perpendicular to the target vessel and normalize to the maximum values of all curves. Then take the FWHM of each envelope curve as the diameter of the target vessel.

To improve the visualizations, we employed multi-modal encoded processing pipelines, incorporating Hessian-based Frangi vesselness filters for contrast enhancement. For human skin imaging applications, we implement a surface flattening algorithm to correct for surface curvature, facilitating more accurate vessel depth measurements. Frequency encoding separates signals into two bands (0–30 MHz and 30–80 MHz), enabling differentiation between vessels of different sizes. Depth encoding employs a red-to-green color transition to represent vessel depth change. Angular encoding reflects the vessel orientation information, showing large angle vessel in red and small angle vessel in blue. The final dual-wavelength-merged images were produced through sequential processing, including straightening, aligning, and color-coded fusion (detailed processing protocols are provided in Supplementary Note S3a and Supplementary Fig. S8).

Animal imaging protocol
We used 10-week-old male BALB/c mice (Guangdong Zhiyuan Biomedical Technology Co., Ltd., China) weighing 30 g for brain imaging. Before imaging, each mouse was positioned on a temperature-controlled cushion and anaesthetized with 1.5% vaporized isoflurane. Pharmaceutical-grade ophthalmic ointment was applied to cover the eyes of the mice. We subsequently removed the hair on the head using clippers and depilatory cream, followed by opening the scalp and removing the skull using a handheld drill. The mouse was then secured on a mouse stand to immobilize the head and minimize movement during photoacoustic imaging.

We used 7-week-old male SD rats (Guangdong Zhiyuan Biomedical Technology Co., Ltd., China) weighing 250 g for kidney imaging. The rats were first anaesthetized with 1.5% vaporized isoflurane, placed supine on a temperature-controlled cushion, and dissected after shaving. A 30-mm skin incision was made along the midline from 15 mm below the sternum towards the genitals. A piece of gauze was placed over the drape and attached lightly to the muscle layer with hemostat forceps on each side of the incision to allow access to the kidney. The left kidney was chosen for dissection, as the right kidney is adjacent to the liver and portal vein, which can be easily injured during dissection. This study did not involve long-term housing of mice, as the mice were purchased from the relevant commercial company and euthanasia was performed immediately after the experiment. All procedures were conducted in “Guiding Principles in the Care and Use of Animals” (GB/T 35892-2018, China) and were approved by the Laboratory Animal Ethics Committee of Guangzhou Huateng Biomedical Technology (IACUC: C202312-10).

Subcutaneous vessel imaging protocol
The human imaging experiments were conducted in accordance with a protocol approved by the Ethics Committee of Jinan University (Approval Number: JNUKY-2023-0151, n=9 healthy volunteers). Total nine healthy adult male and female volunteers, aged from 22 to 28 years, participated in the study. Sex and gender were not taken into consideration in this experimental design and all participants were randomly selected. Written informed consent was obtained from each participant in accordance with the approved protocol. To ensure safety from laser exposure, all participants were equipped with safety glasses throughout the experiment. The participants were seated comfortably with their arms extended and positioned at heart level in a room maintained at standard temperature. For imaging of human subcutaneous vessels using dual-wavelength illumination, the system was applied to the fingers, palms, and arms of the volunteers. Prior to imaging, ultrasound gel was applied to improve image quality. The participants were then asked to position the targeted imaging area beneath the imaging apparatus.

Protocol for the dynamic monitoring of microcirculatory responses
For haemodynamic monitoring in response to cuff occlusion, a blood pressure cuff was secured around the right upper arm of each participant and inflated to 80 mmHg to induce venous occlusion while maintaining normal blood pressure conditions. The region of interest for these experiments was the thenar area of the palm. Baseline images were taken at rest before initiating a 200 s period of venous occlusion. Immediately after imaging, the cuff pressure was quickly released. This was followed by a 170 s resting phase, allowing time for the blood vessels to return to their normal state before proceeding with further vascular imaging.

For the heat-induced hyperemia response experiment, the palms of the volunteers were placed in a water tank containing a hole in the top, with the region of interest for imaging maintained in direct contact with the water surface and aligned perpendicular to the fiber-optic sensor. The water temperature was initially set to 10°C and subsequently increased to 33°C over a period of 590 s through controlled heating. Throughout this imaging protocol, the volunteers were asked to keep their palms as stable as possible to ensure consistent skin contact with the water surface and minimize motion artefacts during data acquisition.

Free motion/cycling monitoring
The handheld circumferential scanning probe primarily consists of three parts: a probe shell, the probe core assembly, and a drive motor (See in Supplementary Fig. S15). The probe core represents the critical functional module, integrating three precision-engineered elements: fiber optic bundle apertures for light transmission, mirror slots containing reflective optical elements, and an optical fiber sensor unit mounted on a motor-driven rotational bracket. The excitation light emitted from the fiber bundle is primarily reflected at the mirror interface before illuminating the target imaging area. The optical fiber sensor component, rigidly affixed to the rotating bracket coupled to the motor shaft, achieves circumferential scanning through controlled rotational displacement.

For low-intensity free motion, continuous photoacoustic imaging monitoring was achieved by having the volunteers directly grasp the imaging probe shell and align the palm target imaging area with the excitation light irradiation zone. During the entire imaging monitoring process, the volunteer’s palm maintained close contact with the imaging probe shell by ultrasound glue to reduce artefacts caused by shaking during movement.

To enable real-time monitoring during cycling motion, the conventional handlebar grip of an exercise bicycle was systematically redesigned. The cylindrical section of the probe shell was ergonomically substituted for the original handle grip structure. Through precise mechanical integration, the probe core assembly was embedded within the handlebar-style shell, thereby achieving seamless sensor integration with the cycling apparatus. This structural modification preserves the full rotational freedom of the handlebar while maintaining continuous optical coupling during dynamic motion.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript introduces a highly innovative fibre-optic–transducer–based photoacoustic imaging system that leverages acousto-optic phase modulation and heterodyne interferometry to achieve broadband (0.3–80 MHz), omnidirectional ultrasound detection. The system demonstrates high-resolution vascular imaging in phantoms, small animals, and humans. While the results are very interesting, the manuscript quality can be improved by providing more elaborations and experimental details, as listed in the following.\n1. The key innovation of this work lies in the fibre-optic–based ultrasound transducer, which is claimed to provide omnidirectional detection with wide bandwidth. However, the rationale underlying both properties remains vague. From a hardware perspective, compared with previously reported optical resonant sensors such as Fabry–Pérot cavity detectors, what are the fundamental design differences and technical takeaways in this work?\n2. The authors state that the sensing area of a single fibre-laser transducer is ~300 times smaller than that of conventional piezoelectric transducers. Under such conditions, how is the field of view not compromised in this system? What specific factors or design features compensate for the reduced sensing aperture and ensure sufficient coverage for wide-field imaging?\n3. A major concern with the presentation of this work is the absence of images of the system and experimental setup. Although Supplementary Fig. 13 includes two photos, they do not provide sufficient details about the imaging probe. In addition, photos and schematics of the experimental setup used for animal studies should also be included to allow readers to better assess the practicality.\n4. The manuscript lacks several essential systems as a photoacoustic study. On the optical excitation side, key parameters such as duty cycle, average power, pulse energy, and laser spot distribution are not reported. On the ultrasound detection side, dynamic range, impulse response, and quantitative angular sensitivity measurements are missing. At the system level, critical information such as the imaging sampling rate and point spread function measurements (e.g., using microspheres at different depths) should be provided.\n5. The authors should provide additional details regarding the design rationale for each sensor module. Parameters such as fibre diameter, grating characteristics, and cladding materials can largely influence the field of view and detection sensitivity.\n6. In Fig. 1e, both theoretical calculation and experimental results show large fluctuations in sensitivity at high frequency range. The reviewer wonders about the origin of these fluctuations. In addition, the definition of sensitivity in this work should be explicitly stated, and the corresponding standard deviation should be provided to ensure the characterization is statistically meaningful.\n7. In Fig. 2, the mouse imaging experiments appear to have been conducted using a single excitation wavelength, whereas the later human imaging experiments employ dual-wavelength excitation. The authors should clarify the rationale for this discrepancy. In addition, the angle-encoded images should be more clearly explained: what additional information can be extracted from these images compared with conventional photoacoustic images?\n8. The authors state that the human experiments were conducted in compliance with safety standards. However, no quantitative characterization of the optical exposure is provided. The power density of the light delivered to the skin should be reported and explicitly compared with safety limits.\n9. In Fig. 3h, an “S factor” is introduced to reveal distinct oxygenation patterns at different tissue layers. But the manuscript does not define how this parameter is calculated. The authors should explain its definition and biological meanings.\n10. For the high-frequency microvasculature imaging results, the authors should clarify how they distinguish between true fine vascular structures and potential reconstruction artifacts. Were independent modalities used as ground truth for validation?\n11. For the spatiotemporal analysis in Figs 4 and 5, the region of interest used to calculate photoacoustic amplitude changes and oxygen saturation is not specified. Clear labeling of ROIs on photoacoustic images should be provided.\n12. In the heat-induced hyperthermia experiment, the authors state that temperature increase can activate arteriovenous shunts, thereby altering haemodynamic patterns. Additional clinical discussion should be provided along with a clearer explanation of how such vascular changes are manifested in the photoacoustic images.\n13. In the demo of photoacoustic imaging during exercise, motion artifacts are unavoidable and can arise from two main sources: first, relative movement between the probe and the skin; second, Bragg gratings are inherently sensitive to strain caused by deformation. The authors should provide experimental results illustrating the impact of these motion artifacts and discuss their influence on imaging performance.\n14. A major concern of the current wearable setup is the requirement for two separate light sources: one for photoacoustic excitation and the other for ultrasound detection. Neither of these sources can be easily integrated into the probe. Although the performance surpasses that of conventional piezoelectric-based systems, this requirement substantially increases the system form factor and limits the practicality of wearable applications.", "reviewer_2": "This is an excellent contribution, showing a new photoacoustic imaging approach capable of high resolution and real time imaging of a moving subject. The authors introduced miniaturized fiber-based photoacoustic imaging sensor array, presenting a compact and wearable platform for real-time photoacoustic imaging. The system achieves 40 µm resolution with 1 cm penetration depth, enabling stratified visualization of vascular responses from superficial to deep subcutaneous vessels. The platform holds significant promise for advancing cardiovascular assessment and critical care management by providing high-resolution, depth-resolved monitoring of microcirculatory function. I'd recommend acceptance after minor revision to address the following comments.\n1. The fiber based acoustic sensor and it's detection and imaging reconstruction method can be briefly introduced prior to discussing the results, as it's an important component and helpful to readers to appreciate the capability of the proposed system, which is better not to be placed entirely in the Supplemental Information.\n2. The authors present the acoustic responses of the sensors as a function of frequency and sensitivity. However, the use of logarithmic scales on both the x- and y-axes makes it difficult to interpret the device’s performance clearly. Presenting linear scales would provide a more intuitive understanding of the results (can be in the SI if necessary). Additionally, it would be valuable to include the 3 dB bandwidth of the device’s sensitivity with the corresponding center frequency.\n3. Could authors explain why using an active, rare-earth-doped optical fiber (EY-305, Coractive, Inc.)? if the activity is required for the system operation, please provide the emission spectrum of the fiber sensor, including its center wavelength and the full width at half maximum (FWHM), to better clarify the optical performance of the system.\n4. The MOBILE system is capable of 180° ultrasound detection, which enhances the signal-to-noise ratio (SNR) of imaging. However, as the device consists of a one-dimensional array detector, it can detect signals originating not only from the imaging plane but also from out-of-plane sources. Would this reduce the effective SNR of the reconstructed images due to blurring effects? The manuscript would be strengthened if the authors discuss some limitations of the proposed platform, e.g. discuss this issue if it matters and suggest possible strategies to mitigate or overcome such limitation.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Thank you for this insightful question. The omnidirectional and broadband capabilities of our sensor stem from two fundamental design principles that distinguish it from conventional optical ultrasound sensors.\na. Active laser cavity versus passive resonant cavity\nThe key distinction lies in how acoustic signals are amplified. Passive Fabry-Pérot cavity sensors use an external laser to interrogate a high-Q resonator. To achieve high sensitivity, they require high Q-factors (10⁶-10⁸), which necessitates precise wavelength locking between the external laser and cavity resonance. This approach faces an inherent trade-off between sensitivity and stability.\nOur active fibre laser cavity takes a fundamentally different approach. The fibre itself is the laser source, and acoustic pressure directly modulates the lasing process. Stimulated emission continuously amplifies the acoustic-induced phase modulation without relying on ultra-high Q-factors. Additionally, the self-contained laser architecture eliminates the need for external laser sources and wavelength locking systems, significantly simplifying the system and improving operational stability—particularly important for in vivo applications where environmental fluctuations can disrupt passive cavity wavelength alignment.\nA detailed response comparison is provided in Supplementary Note S5c and Figure S19, with a detailed description of the ultrasound detection mechanisms.\nb. Omnidirectional detection through cylindrical symmetry\nThe fibre's cylindrical geometry (62.5 μm diameter) is inherently symmetric in all radial directions, meaning it responds equally to acoustic waves arriving from any angle in the transverse plane. This enables 180° angular coverage without requiring mechanical scanning or complex sensor arrays. The miniaturized dimension—comparable to the acoustic wavelength at tens of MHz—also minimizes spatial averaging effects that would otherwise degrade high-frequency sensitivity. In contrast, many optical sensors employ planar membrane structures optimized for acoustic waves arriving perpendicular to the surface, resulting in limited angular acceptance and directional sensitivity. Experimental validation of our sensor's omnidirectional response is shown in Supplementary Figure S3c-d.\nWe have added detailed sensor characterization (Supplementary Note S1b and Figure S2), frequency response analysis (Supplementary Note S1c and Figure S3), and comprehensive comparison with state-of-the-art optical ultrasound sensors (Supplementary Note S5b and Tables S1-S2) to further clarify these technical distinctions. We have also incorporated relevant details into the first part of the results in the main text.\n2. The authors state that the sensing area of a single fibre-laser transducer is ~300 times smaller than that of conventional piezoelectric transducers. Under such conditions, how is the field of view not compromised in this system? What specific factors or design features compensate for the reduced sensing aperture and ensure sufficient coverage for wide-field imaging?\nResponse:\nThank you for this important question. The relationship between sensor size and field of view in our system may appear counterintuitive, but it reflects a fundamental principle of photoacoustic computed tomography (PACT) [1, 2].\na. Field of view is determined by synthetic aperture\nIn PACT, the field of view is not limited by the physical sensing area of an individual transducer. Instead, it is determined by the synthetic aperture formed through scanning or array configuration. The imaging principle works as follows: the fibre sensor scans linearly across the sample, acquiring photoacoustic signals at multiple positions. For each acoustic source, signals detected at different sensor positions arrive with characteristic time delays determined by acoustic propagation distances. By coherently synthesizing these time-delayed signals through back-projection reconstruction, we recover the spatial distribution of acoustic sources. Therefore, the field of view in this synthetic aperture approach is determined by: (1) the scanning range, which defines the lateral coverage, and (2) the angular acceptance of each sensor, which determines the depth range that can be effectively imaged. (Supplementary Figure S5)\nb. Smaller sensors enable larger angular acceptance\nCritically, our miniaturized sensor provides a key advantage: smaller sensors offer wider angular acceptance. Spatial averaging effects scale with sensor dimensions—a sensor large compared to the acoustic wavelength exhibits directional sensitivity with narrow acceptance angle, whereas a sensor comparable to or smaller than the wavelength responds uniformly to acoustic waves from different directions. Our fibre sensor (62.5 μm cladding diameter, with 7 μm core diameter) is significantly smaller than the acoustic wavelength at the center frequency (~20 MHz, corresponding to ~75 μm in water), enabling near-omnidirectional detection with 180° angular coverage in the transverse plane (Supplementary Figure S3c-d). This wide angular acceptance translates to a large effective aperture for tomographic reconstruction, enabling a field of view of 10 × 10 mm²—significantly larger than the physical sensor dimension.\nIn contrast, conventional piezoelectric transducers with larger sensing areas (typically 0.5-2 mm diameter) exhibit limited angular acceptance, requiring more complex array configurations or mechanical scanning schemes to achieve comparable coverage. Our approach demonstrates that miniaturization, when combined with synthetic aperture imaging, actually enhances rather than compromises the field of view. We have added detailed in (Supplementary Figure S6)\nReferences\n[1] Chao Tian, Kang Shen, Wende Dong, Fei Gao, Kun Wang, Jiao Li, Songde Liu, Ting Feng, Chengbo Liu, Changhui Li, Meng Yang, Sheng Wang, and Jie Tian, \"Image reconstruction from photoacoustic projections,\" Photonics Insights, R06 (2024).\n[2] Murad Omar, Juan Aguirre, and Vasilis Ntziachristos, \"Optoacoustic mesoscopy for biomedicine,\" Nature Biomedical Engineering 3, 354-370 (2019).\n3. A major concern with the presentation of this work is the absence of images of the system and experimental setup. Although Supplementary Fig. 13 includes two photos, they do not provide sufficient details about the imaging probe. In addition, photos and schematics of the experimental setup used for animal studies should also be included to allow readers to better assess the practicality.\nResponse:\nWe have significantly expanded the visual documentation of our system and experimental setups in the revised manuscript.\na. System overview and imaging configurations\nFigure 1f in the main text presents the complete system schematic with two imaging configurations, including Protocol 1 (Linear scanning) with fibre sensor positioned above the target through a water tank interface, suitable for anesthetized animals, and stationary human subjects, and Protocol 2 (Rotational scanning with handheld probe), with compact handheld probe with integrated water chamber, enabling unrestricted monitoring during natural physiological activities and dynamic movements.\nSupplementary Figure S10: Complete experimental setup for mouse brain imaging, showing water tank configuration, fibre sensor positioning, laser illumination geometry, and animal mounting platform.\nSupplementary Figure S12: Experimental setup for human forearm imaging, demonstrating water coupling interface, sensor scanning mechanism, and subject positioning.\nSupplementary Figure S15: Detailed design of the handheld rotational scanning probe.\nb. Additional technical details\nSupplementary Note S3b: Animal imaging protocols, including anesthesia procedures, surgical preparation, and imaging parameters.\nSupplementary Note S3c: Human subject imaging protocols, including skin preparation, water coupling procedures, and safety considerations.\nSupplementary Note S4a: Technical specifications of the rotational scanning probe, including mechanical design, water chamber configuration, and data acquisition integration.\nThese additions provide complete information to assess the system's practicality and reproducibility. Hoping it can adequately address the reviewer's concerns.\n4. The manuscript lacks several essential systems as a photoacoustic study. On the optical excitation side, key parameters such as duty cycle, average power, pulse energy, and laser spot distribution are not reported. On the ultrasound detection side, dynamic range, impulse response, and quantitative angular sensitivity measurements are missing. At the system level, critical information such as the imaging sampling rate and point spread function measurements (e.g., using microspheres at different depths) should be provided.\n5. The authors should provide additional details regarding the design rationale for each sensor module. Parameters such as fibre diameter, grating characteristics, and cladding materials can largely influence the field of view and detection sensitivity.\nResponse to Questions 4 and 5:\nWe have added Supplementary Figure S2 summarizing the performance characterization of fibre sensor, Supplementary Figure S9 summarizing the performance characterization of phantom imaging, Supplementary Table S3 summarizing the key optical excitation specifications for both wavelengths used in this study, Supplementary Table S4 summarizing the ultrasound detection specifications and imaging performances, and Supplementary Table S5 detailing the fibre sensor design parameters.\nHere, the optical excitation parameters (Supplementary Table S3) were selected based on established photoacoustic imaging practices and ANSI safety standards. The pulse energy and spot size were optimized to balance sufficient photoacoustic signal generation with substantial safety margins. For ultrasound detection (Supplementary Table S4-S5), the fibre sensor design leverages mature fibre-optic telecommunication components to ensure cost-effectiveness and reliability. The grating length primarily affects the integrated length along the y-axis shown in Supplementary Figure S5. The cladding material of the optical fibre is essentially identical to the core (both being fused quartz) in terms of acoustic impedance. However, there is a significant difference in acoustic impedance between the fibre and water. As a result, these factors primarily influence the acoustic response of the optical fibre. To optimize the acoustic response, the fibre cladding diameter was deliberately reduced from the standard 125 µm to 62.5 µm through chemical etching to extend the detection bandwidth to 80 MHz—the smaller dimension minimizes spatial averaging effects and enables detection of higher-frequency ultrasound components essential for achieving 40 µm axial resolution. The experimental results presented here correspond to the resonant spectrum of a bare fibre (including the cladding) of erbium-ytterbium co-doped fibre (EY305) after coating removal. In future work, we will consider the use of cladding materials to achieve acoustic impedance matching with biological tissues, thereby further improving the ultrasonic detection performance of the sensor.\nThe operating wavelength (~1550 nm), pump configuration (980 nm), grating parameters (3 mm length, >99% reflectivity), and signal acquisition electronics (200 MSa/s sampling rate) were selected from commercially available telecommunication-grade components, facilitating seamless system integration and cost control while maintaining high performance.\nThese comprehensive specifications are now documented in the Methods section and Supplementary Tables S3-S5, with experimental validation provided in Supplementary Figures S2, S3, S9, and related notes.\n6. In Fig. 1e, both theoretical calculation and experimental results show large fluctuations in sensitivity at high frequency range. The reviewer wonders about the origin of these fluctuations. In addition, the definition of sensitivity in this work should be explicitly stated, and the corresponding standard deviation should be provided to ensure the characterization is statistically meaningful.\nResponse:\nThank you for this insightful question. We address the three concerns regarding sensitivity fluctuations, definition, and statistical validation below.\na. Physical origin of high-frequency fluctuations\nThe sensitivity fluctuations at high frequencies originate from acoustic resonance modes within the fibre structure. The acoustic impedance mismatch between silica fibre (~13 MRayl) and the surrounding water medium (~1.5 MRayl) induces resonant vibrations when ultrasound waves interact with the fibre, analogous to the ringing effect in piezoelectric transducers.\nWe performed finite element simulations (COMSOL Multiphysics) to quantitatively analyze this phenomenon. The results confirm that the two prominent sensitivity peaks at ~42 MHz and ~60 MHz correspond to the TR₂₁ torsional-radial mode and R₀₁ radial breathing mode, respectively (Supplementary Figure S3). The simulation accurately reproduces the experimental sensitivity spectrum, validating the physical mechanism. Detailed modal analysis and simulation parameters are provided in the Supplementary Note S1c section (“Theoretical analysis and numerical simulation”).\nb. Definition of sensitivity\nSensitivity is defined as the frequency-dependent acoustic-optic conversion efficiency, quantified as:\nlaser\nacoustic\nΔ𝑓\nwhere is the laser frequency mo𝑆d(u𝑓la)t=ion (in kHz) and is the applied acoustic\nlaser 𝑃 acoustic\npressure (in Pa). The unit of sensitivity is kHz/Pa. This metric directly characterizes the sensor's\nΔ𝑓 𝑃\nability to transduce ultrasound pressure into optical frequency shifts, which are demodulated through self-delayed heterodyne detection.\nc. Statistical validation\nTo ensure statistical rigor, we performed repeated measurements (n = 12) across the entire bandwidth (0.3-80 MHz) using calibrated piezoelectric transducers as reference sources. The experimental data in Figure 1e represent mean sensitivity values, with shaded regions indicating standard deviation (SD). The good agreement between theoretical predictions and experimental measurements (Supplementary Figure S2b), including resonance features, validates both the physical model and measurement methodology.\nThese statistical analyses are now explicitly included in Supplementary Figure S2 and the Methods section.\n7. In Fig. 2, the mouse imaging experiments appear to have been conducted using a single excitation wavelength, whereas the later human imaging experiments employ dual-wavelength excitation. The authors should clarify the rationale for this discrepancy. In addition, the angle-encoded images should be more clearly explained: what additional information can be extracted from these images compared with conventional photoacoustic images?\nResponse:\nThank you for these important questions regarding wavelength selection and the functional significance of angle-encoded imaging.\na. Rationale for wavelength selection\nThe mouse brain imaging (Figure 2) initially used single-wavelength (1064 nm) excitation to validate anatomical accuracy against MRI angiography, as near-infrared light provides superior penetration in brain tissue. To maintain consistency with human experiments and demonstrate the system's full capability, we have now added dual-wavelength mouse brain imaging data (Supplementary Figure S11) in the revised manuscript, showcasing the complementary advantages: 532 nm enhances superficial microvessel contrast, while 1064 nm enables deeper penetration.\nb. Angular encoding: additional information beyond conventional imaging\nThe angle-encoded visualization (Fig. 2d-e) directly addresses a fundamental limitation of conventional compact photoacoustic systems: the inability to detect steeply oriented penetrating vessels due to restricted angular acceptance (±40° for typical piezoelectric linear arrays). Our fibre sensor's 165° angular acceptance enables detection of vessels oriented up to 82.5°. This capability is critical for microcirculatory assessment because penetrating vessels — such as cortical penetrating arterioles in the brain and interlobular arterioles in the kidney — propagate perpendicular to the tissue surface and play essential roles in delivering oxygen and nutrients to metabolically active deep tissues (neurons, glomeruli, and renal tubules). Dysfunction of these vessels is implicated in severe pathologies, including cerebral infarction and renal ischemia. Traditional linear probes would miss more than half of these perpendicularly oriented vessels, fundamentally limiting their utility for microvascular diagnostics. The section “Small-animal imaging” has been revised for clarification.\n8. The authors state that the human experiments were conducted in compliance with safety standards. However, no quantitative characterization of the optical exposure is provided. The power density of the light delivered to the skin should be reported and explicitly compared with safety limits.\nResponse:\nWe have provided comprehensive quantitative characterization of optical exposure with explicit comparison to ANSI Z136.1-2022 safety standards [1]. Our system operates with substantial safety margins: at 532 nm, the fluence of 6.5 mJ/cm² represents only 32.5% of the maximum permissible exposure (MPE: 20 mJ/cm², safety margin: 3.1×); at 1064 nm, the fluence of 12.9 mJ/cm² corresponds to 12.9% of the MPE (100 mJ/cm², safety margin: 7.8×). The average power densities (130 mW/cm² at 532 nm and 258 mW/cm² at 1064 nm, 20 Hz repetition rate) are both far below the continuous-wave MPE of 400 mW/cm² at 532 nm and 2000 mW/cm² at 1064 nm for skin exposure (see Methods and Supplementary Table S3). All human experiments were approved by the Jinan University Ethics Committee (Approval Number: JNUKY-2023-0151) with informed consent, and no adverse effects were reported.\nReferences\n[1] Laser Institute of America. American National Standard for Safe Use of Lasers (ANSI Z136.1-2022). Available from: https://webstore.ansi.org/standards/lia/ansiz1362022.\n9. In Fig. 3h, an “S factor” is introduced to reveal distinct oxygenation patterns at different tissue layers. But the manuscript does not define how this parameter is calculated. The authors should explain its definition and biological meanings.\nResponse:\nThe S factor is defined as the ratio of photoacoustic signal intensities at the two excitation wavelengths: , where and represent the PA amplitudes at 532 nm and 1064 nm, respectively (now added to Methods). This parameter serves as a relative oxygenation 𝑆 = 𝐼1064/𝐼532 𝐼532 𝐼1064 indicator based on the distinct absorption characteristics of hemoglobin: At 532 nm, oxyhemoglobin (HbO₂) and deoxyhemoglobin (Hb) exhibit nearly level absorption coefficients ( ≈ 22.48 mm⁻¹ for HbO₂ and 18.66 mm⁻¹ for Hb), approximating an isosbestic point where 𝜇𝑎 photoacoustic signals are relatively insensitive to oxygenation variations. In contrast, at 1064 nm, HbO₂ shows significantly higher absorption ( ≈ 0.45 mm⁻¹) compared to Hb ( ≈ 0.2 mm⁻¹), enabling oxygenation-dependent contrast [1-5]. Consequently, higher S values indicate higher 𝜇𝑎 𝜇𝑎 relative oxygenation. We emphasize that S factor should be interpreted as a relative metric rather than absolute oxygen saturation, as wavelength-dependent scattering and depth-dependent light attenuation introduce confounding factors. However, it remains valuable for comparative analysis within similar tissue types and depths, enabling detection of oxygenation differences between anatomical regions (e.g., palm vs. forearm in Fig. 3h), temporal monitoring of physiological responses (e.g., exercise, occlusion), and discrimination between superficial arterial-rich vessels (higher S) and deeper venous vessels (lower S). The observed differences in Fig. 3h are consistent with known physiology: the saturation of hemoglobin in dermal vessels was greater in acral skin of the extremities compared with proximal sites. In the finger there are arteriovenous anastomoses that directly connect arterioles to venules and are under high basal sympathetic vasoconstrictor drive [6].\nReferences\n[1] Mesradi M, Genoux A, Cuplov V, et al. Experimental and analytical comparative study of optical coefficient of fresh and frozen rat tissues. Journal of Biomedical Optics 18, 11-117010 (2013).\n[2] Bosschaart N, Edelman G, Aalders M, et al. A literature review and novel theoretical approach on the optical properties of whole blood. Lasers in medical science 29, 453-479 (2014).\n[3] Galiakhmetova D, Dremin V, Koviarov A, et al. Ultra-short laser pulses propagation through mouse head tissues: experimental and computational study. IEEE Journal of Selected Topics in Quantum Electronics 29,1-11 (2022).\n[4] Marcos-Vidal A, Vaquero J, Ripoll J. Optical properties of tissues in the near infrared: Their relevance for optical bioimaging. Cham: Springer International Publishing, 1-20 (2020).\n[5] Yoshida K, Nishidate I, Ishizuka T, et al. Multispectral imaging of absorption and scattering properties of in vivo exposed rat brain using a digital red-green-blue camera. Journal of Biomedical Optics 20, 051026-051026 (2015).\n[6] Thorn C, Matcher S, Meglinski I, Shore A. Is mean blood saturation a useful marker of tissue oxygenation? Am J Physiol-Heart C 296, H1289-H1295 (2009).\n10. For the high-frequency microvasculature imaging results, the authors should clarify how they distinguish between true fine vascular structures and potential reconstruction artifacts. Were independent modalities used as ground truth for validation?\nResponse:\nThank you for this critical question. We distinguish true vascular structures from reconstruction artifacts through three complementary approaches:\n(1) Morphological characterization: Reconstruction artifacts typically arise from acoustic velocity mismatch, limited-view aperture effects, and motion-induced inconsistencies. Our system minimizes these through dual-sound-speed correction (Supplementary Figure S7) and 165° angular acceptance. Critically, artifacts exhibit characteristic morphological signatures (e.g., streaking, blurring) and lack physiological responsiveness to stimuli, whereas true vessels display coherent dynamic changes during functional challenges.\n(2) Multi-modal validation: We performed parallel imaging of mouse brain vasculature using 9.4T MRI angiography as ground truth (Supplementary Figure S18). Quantitative comparison of representative vessels in the hippocampal region shows excellent agreement in diameter measurements, with matched branching patterns and anatomical distributions, confirming that high-frequency signals originate from genuine vascular structures.\n(3) Physiological validation: For human skin microvasculature, we validated vascular authenticity through dynamic functional challenges—brachial artery occlusion induced progressive signal reduction followed by reactive hyperemia, thermal stimulation produced vasodilation, and exercise revealed increased perfusion—with all responses spatially localized to anatomically appropriate vessels and following expected temporal dynamics.\nThe spatial distribution of S factor values revealed distinct skin regions, including the palm, dorsal forearm, and fingertip, and effectively captured the decrease in oxygenation changes during arterial occlusion-reperfusion cycles. These experimental results are in agreement with existing reports and well-documented physiological phenomena. Additionally, we performed co-localized transcutaneous oxygen tension (TcPO₂) measurements using a clinical monitor (TCM4, Radiometer) to validate the physiological relevance of our S factor-based oxygenation mapping (Figure 5p). Importantly, reconstruction artifacts would not exhibit such coherent spatiotemporal patterns or correlate with independent physiological measurements. These multi-faceted validations—combining anatomical correspondence with MRI, functional responsiveness to physiological perturbations, and correlation with clinical oxygenation measurements—collectively confirm that our high-frequency microvascular signals reflect true hemodynamic structures rather than imaging artifacts.\n11. For the spatiotemporal analysis in Figs 4 and 5, the region of interest used to calculate photoacoustic amplitude changes and oxygen saturation is not specified. Clear labeling of ROIs on photoacoustic images should be provided.\nResponse:\nThank you for this suggestion. We have added explicit ROI labeling in the revised manuscript. The regions of interest are indicated by orange dashed lines in Figures 4-5. More statistical analysis details are added in Supplementary Information S2c.\n12. In the heat-induced hyperthermia experiment, the authors state that temperature increase can activate arteriovenous shunts, thereby altering haemodynamic patterns. Additional clinical discussion should be provided along with a clearer explanation of how such vascular changes are manifested in the photoacoustic images.\nResponse:\nOur photoacoustic images reveal that thermal stimulation (warming from cold to near body temperature) induces distinctive vascular responses: while deeper vessels in the reticular dermis exhibit dilation similar to venous occlusion, the superficial papillary dermis (PD) layer shows decreased PA signal intensity and reduced S factor values (Figure 4l-m). This pattern is consistent with activation of arteriovenous (AV) shunts—direct vascular connections abundant in acral skin that allow blood to bypass nutritive capillaries and flow directly into venous circulation for thermoregulation. When AV shunts open, blood flow is redirected away from superficial capillaries toward deeper venous drainage, resulting in reduced oxygen extraction in the papillary dermis and lower local oxygenation signals despite overall increased blood volume. This thermoregulatory mechanism has clinical relevance for detecting microcirculatory dysfunction in peripheral vascular diseases. While this interpretation aligns with established physiology and our imaging findings [1], we acknowledge it requires further validation through complementary modalities (e.g., functional ultrasound, laser Doppler flowmetry). We have revised the manuscript to clarify this mechanism and discuss its clinical significance (See the revised “Heat-induced hyperaemia experiment” section).\nReferences\n[1] Schwarz M, Buehler A, Aguirre J, Ntziachristos V. Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo. J Biophotonics 9, 55-60 (2016).\n13. In the demo of photoacoustic imaging during exercise, motion artifacts are unavoidable and can arise from two main sources: first, relative movement between the probe and the skin; second, Bragg gratings are inherently sensitive to strain caused by deformation. The authors should provide experimental results illustrating the impact of these motion artifacts and discuss their influence on imaging performance.\nResponse:\nThank you for this important observation. Motion artifacts in our system arise from two sources:\n(a) For probe-skin relative movement, we implemented a stabilized handheld design with a protective window that prevents direct fibre-skin contact, thereby minimizing mechanical coupling and relative motion. Despite these measures, residual position shifts inevitably occur during dynamic monitoring. To address this, we employed a cross-correlation-based motion correction algorithm (detailed in Supplementary Note S4c and Fig. S17) that registers each frame to the first image by detecting the maximum cross-correlation peak. After correction, the residual displacement is reduced from >200 to <50 µm, enabling consistent tracking of individual vessels throughout the monitoring period.\n(b) Strain-induced FBG wavelength shifts from fibre deformation during motion. However, these changes are all low-frequency effects (typically below kHz). For the latter, given that the transfer function of our interferometric demodulation device is |G|=2sin(Ωτ/2), which has a filtering effect on DC or extremely low frequencies, we have further applied high-pass filtering (>0.3 MHz) to remove low-frequency influences. This approach effectively eliminates quasi-static strain drift [1] while preserving photoacoustic signals, thus not affecting the normal operation of the sensor, which can also be observed from the motion imaging (see Supplementary Note S4c).\nReferences\n[1] Liang, Y, Fu, W, Li, Q, et al. Optical-resolution functional gastrointestinal photoacoustic endoscopy based on optical heterodyne detection of ultrasound. Nature Communications 13, 7604 (2022).\n14. A major concern of the current wearable setup is the requirement for two separate light sources: one for photoacoustic excitation and the other for ultrasound detection. Neither of these sources can be easily integrated into the probe. Although the performance surpasses that of conventional piezoelectric-based systems, this requirement substantially increases the system form factor and limits the practicality of wearable applications.\nResponse:\nThank you for this critical assessment. We acknowledge that the current system is portable but not yet fully wearable. The compact fibre-optic sensor enables flexible, lightweight probe designs. However, the pulsed excitation laser (532/1064 nm) remains the primary bottleneck, limiting the system to tethered operation, while the sensor laser is already compact and readily integrable. Emerging technologies such as high-power VCSEL arrays and compact pulsed laser diodes offer promising pathways toward miniaturization [1, 2]. In the near term, the current portable configuration is well-suited for bedside monitoring, intraoperative assessment, and rehabilitation tracking. We have revised the Discussion and conclusion section to acknowledge this limitation and outline future miniaturization strategies toward fully wearable photoacoustic imaging systems.\nReferences\n[1] Gao X, Chen X, Hu H, et al. A photoacoustic patch for three-dimensional imaging of hemoglobin and core temperature. Nature Communications 13, 7757 (2022).\n2] Jin H, Zheng Z, Cui, Z.et al.A flexible optoacoustic blood ‘stethoscope’ for noninvasive multiparametric cardiovascular monitoring.Nature Communications14, 4692 (2023).\n\nResponse to Reviewer 2:\n1. The fibre based acoustic sensor and it's detection and imaging reconstruction method can be briefly introduced prior to discussing the results, as it's an important component and helpful to readers to appreciate the capability of the proposed system, which is better not to be placed entirely in the Supplemental Information.\nResponse:\nThank you for this valuable suggestion. We have substantially expanded the description of the fibre-optic sensor and image reconstruction methodology in the main text (Results section, Methods section, Supplementary Note S1 and S2). The revised manuscript now includes: (1) sensor array fabrication and acoustic characterization (sensitivity, directivity, bandwidth); (2) heterodyne interferometric detection principle; and (3) time-reversal-based image reconstruction algorithm with experimental validation.\n2. The authors present the acoustic responses of the sensors as a function of frequency and sensitivity. However, the use of logarithmic scales on both the x- and y-axes makes it difficult to interpret the device’s performance clearly. Presenting linear scales would provide a more intuitive understanding of the results (can be in the SI if necessary). Additionally, it would be valuable to include the 3 dB bandwidth of the device’s sensitivity with the corresponding center frequency.\nResponse:\nWe have replotted the sensitivity curve with standard deviations in Figure 1e (a linear scale form in Supplementary Figure S2b), which provides a more intuitive visualization and measurement reproducibility of the sensor's acoustic response (Supplementary Figure S2). However, we note that the fibre sensor exhibits multiple resonance peaks across the frequency spectrum due to the acoustic impedance mismatch. Therefore, conventional 3 dB bandwidth characterization may not be adequate for this complex acoustic response. Instead, we have quantified the system's performance using point spread function (PSF) analysis and spatial resolution measurements (supplementary Figure S9), which more accurately reflect the sensor's imaging capability across different scales. The angular response uniformity is also studied and provided in Supplementary Figure S3.\n3. Could authors explain why using an active, rare-earth-doped optical fibre (EY-305, Coractive, Inc.)? if the activity is required for the system operation, please provide the emission spectrum of the fibre sensor, including its center wavelength and the full width at half maximum (FWHM), to better clarify the optical performance of the system.\nResponse:\nThe rare-earth-doped active fibre enables the integration of the laser source and acoustic sensor into a single device by forming a laser resonant cavity within the fibre itself. This integrated design offers two key advantages: (1) it provides intrinsically low-noise laser emission, eliminating the need for external laser sources and associated coupling losses; and (2) it produces significantly larger phase shifts in response to acoustic perturbations due to the intracavity amplification effect, thereby enhancing acoustic sensing sensitivity. We added detailed descriptions in Supplementary Note S5c.\nBy precisely controlling the grating inscription depth, the fibre sensor operates as a single-polarization, single-longitudinal-mode laser. The emission spectrum is shown in Supplementary Note S1a and Figure S1b, with a center wavelength of ~1550 nm and FWHM of <0.1 nm, confirming stable single-mode operation essential for high-sensitivity heterodyne detection.\n4. The MOBILE system is capable of 180° ultrasound detection, which enhances the signal-to-noise ratio (SNR) of imaging. However, as the device consists of a one-dimensional array detector, it can detect signals originating not only from the imaging plane but also from out-of-plane sources. Would this reduce the effective SNR of the reconstructed images due to blurring effects? The manuscript would be strengthened if the authors discuss some limitations of the proposed platform, e.g. discuss this issue if it matters and suggest possible strategies to mitigate or overcome such limitation.\nResponse:\nThank you for this insightful question. The MOBILE system employs a linear fibre sensor for 2D imaging with integral projection within a ~3 mm-thick detection imaging plane, with negligible out-of-plane signal interference (Supplementary Note S2, Figure S5, and also the following two reference papers).\nThe system is optimized for high-speed 2D hemodynamic monitoring rather than 3D volumetric imaging.\nFor 3D imaging, strategies include rotational scanning with tomographic reconstruction, acoustic focusing elements, or curved fibre arrays for depth sectioning. These extensions maintain fibre-based detection advantages—high sensitivity, large angular coverage, and flexibility. We have addressed this in the Discussion and Conclusion section.\nReferences\n[1] Zohar O, Ahiad R, Yoav H, et al. Hand-Held Optoacoustic System for the Localization of Mid-Depth Blood Vessels. Photonics 9, 907 (2022).\n[2] Grün H, Berer T, Felbermayer K, et al. Integrating Detectors for Photoacoustic Imaging. Femtosecond-Scale Optics, (2011).\n\nResponse to Reviewer 3:\nWe sincerely thank Reviewer #3 for participating in the peer review process and for their valuable contribution to evaluating our manuscript. We appreciate the time and effort invested in this collaborative review."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed the reviewer’s comments comprehensively. The reviewer has two minor remaining suggestions:\n1. Because the wide angular acceptance is a central advantage of this work, the reviewer suggests that the authors include a quantitative comparison with the typical angular acceptance performance of mainstream piezoelectric transducers.\n2. Although several photos of the experimental setups have been provided, high-resolution images of the fiber sensor itself are still missing. The reviewer recommends adding several detailed photos to improve clarity for readers.", "reviewer_2": "I am satisfied with the authors' responses and revision and recommend acceptance of the manuscript for publication.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We appreciate the reviewers' suggestions and have added a quantitative comparison of the typical angular acceptance of mainstream piezoelectric transducers in Supplementary Table S2. This comparison includes sensor type and receiving angle, as shown in the table below with red color.\nSupplementary Table S2. Performance of piezoelectric and optical sensors employed in photoacoustic microvasculature imaging.\nImage depth\nDetection Axial Lateral\nSize Bandwidth\n(Scattering\nTransducer Angle resolution resolution\n(µm2) (MHz)\nmimics/in\n(°) (µm) (µm)\nvivo)\n4.5 18\n(10-180 (10-180\nFocused 1.5 mm\n7×106 10-180\nLiNbO [1] (human skin)\n3 (NA: 0.45) 8.6 29.6\n(10-120 (10-120\nMHz) MHz)\n14 mm\n21 (sample)\nTransparent\n3.1×107 15-45 40 144\nLiNbO [2]\n3 (NA: 0.18) 6.5 mm\n(human skin)\nFocused\n3.3 mm\n52\npiezoelectric (sample)\n2.8×107 32-67 15 45\n（V214-BB- (NA: 0.44)\n0.7 mm (rat)\nRM）[3]\n2.5 mm\nFocused\n49 (sample)\n2×107 0.1-35 —— 90\npiezoelectric\n(NA: 0.41) 1 mm (human\n[4]\nskin)\nPolyvinylidene\ndifluoride 4mm\n9.5×105 0.3-40 —— 30 40\n(PVDF) films\n(human skin)\n[5]\n15 mm\nPlanar Fabry-\n3215 0.1-30 20 45 60\nPerot [6-8]\n(human skin)\n25 mm\n(sample)\nThis work 2.1×104 0.3-80 180 40 33\n10 mm\n(human skin)\nReferences\n1. Aguirre, J. et al. Precision assessment of label-free psoriasis biomarkers with ultra-broadband optoacoustic mesoscopy. Nat. Biomed. Eng. 1, 68 (2017).\n2. Cho, S. et al. An ultrasensitive and broadband transparent ultrasound transducer for ultrasound and photoacoustic imaging in-vivo. Nat. Commun. 15, 1444 (2024).\n3. Zhang, H. F., Maslov, K., Stoica, G. & Wang, L. V. Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging. Nat. Biotechnol. 24, 848-851 (2006).\n4. Bost, W., Lemor, R. & Fournelle, M. Optoacoustic Imaging of Subcutaneous Microvasculature With a Class one Laser. IEEE T. Med. Imaging 33, 1900-1904 (2014).\n5. Subochev, P. V. et al. Ultrawideband high density polymer-based spherical array for real-time functional optoacoustic micro-angiography. Light: Science & Applications 14, 239, (2025).\n6. Zhang, E., Laufer, J. & Beard, P. Backward-mode multiwavelength photoacoustic scanner using a planar Fabry-Perot polymer film ultrasound sensor for high-resolution three-dimensional imaging of biological tissues. Appl. Optics 47, 561-577 (2008).\n7. Cox, B. T. & Beard, P. C. The frequency-dependent directivity of a planar fabry-perot polymer film ultrasound sensor. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control 54, 394-404 (2007).\n8. Huynh, N. T. et al. A fast all-optical 3D photoacoustic scanner for clinical vascular imaging. Nat. Biomed. Eng. 9, 638-655 (2025).\n2. Although several photos of the experimental setups have been provided, high-resolution images of the fiber sensor itself are still missing. The reviewer recommends adding several detailed photos to improve clarity for readers\nResponse:\nThanks for the reviewers' suggestion. We have added a high-resolution photo of the fibre optic sensor in Figure 1f of main text, comparing with a ruler featuring standard graduations.\nFigure 1f. System schematic showing fibre sensor photo and two imaging configurations.\n\nResponse to Reviewer 2:\nWe sincerely thank Reviewer #2 for participating in the peer review process and for their valuable contribution to evaluating our manuscript. We appreciate the time and effort invested in this collaborative review.\n\nResponse to Reviewer 3:\nWe sincerely thank Reviewer #3 for participating in the peer review process and for their valuable contribution to evaluating our manuscript. We appreciate the time and effort invested in this collaborative review."}]

Decision letter