Photoacoustic (PA) imaging has the potential to deliver non-invasive diagnostic information. However, skin tone differences bias PA target visualization, as the elevated optical absorption of melanated skin decreases optical fluence within the imaging plane and increases the presence of acoustic clutter. This paper demonstrates that short-lag spatial coherence (SLSC) beamforming mitigates this bias. PA data from the forearm of 18 volunteers were acquired with 750-, 810-, and 870-nm wavelengths. Skin tones ranging from light to dark were objectively quantified using the individual typology angle (ITA$°$). The signal-to-noise ratio (SNR) of the radial artery (RA) and surrounding clutter were measured. Clutter was minimal (e.g., −16 dB relative to the RA) with lighter skin tones and increased to −8 dB with darker tones, which compromised RA visualization in conventional PA images. SLSC beamforming achieved a median SNR improvement of 3.8 dB, resulting in better RA visualization for all skin tones.

Photoacoustic imaging (PAI) combines optical contrast with ultrasound spatial resolution and can be obtained up to a depth of a few centimeters. Hand-held PAI systems using linear array usually operate in reflection mode using a dark-field illumination scheme, where the optical fiber output is attached to both sides of the elevation plane (short-axis) of the transducer. More recently, bright-field strategies where the optical illumination is coaxial with acoustic detection have been proposed to overcome some limitations of the standard dark-field approach. In this paper, a novel multiangle long-axis lateral illumination is proposed. Monte Carlo simulations were conducted to evaluate light delivery for three different illumination schemes: bright-field, standard dark-field, and long-axis lateral illumination. Long-axis lateral illumination showed remarkable improvement in light delivery for targets with a width smaller than the transducer lateral dimension. A prototype was developed to experimentally demonstrate the feasibility of the proposed approach. In this device, the fiber bundle terminal ends are attached to both sides of the transducer’s long-axis and the illumination angle of each fiber bundle can be independently controlled. The final PA image is obtained by the coherent sum of subframes acquired using different angles. The prototype was experimentally evaluated by taking images from a phantom, a mouse abdomen, forearm, and index finger of a volunteer. The system provided light delivery enhancement taking advantage of the geometry of the target, achieving sufficient signal-to-noise ratio at clinically relevant depths.

Background/Objectives: Magnetic nanoparticles (MNPs) have gained attention in theranostics for their ability to combine diagnostic imaging and therapeutic capabilities in a single platform, enhancing targeted treatment and monitoring. Surface coatings are essential for stabilizing MNPs, improving biocompatibility, and preventing oxidation that could compromise their functionality. Natural rubber latex (NRL) offers a promising coating alternative due to its biocompatibility and stability-enhancing properties. While NRL-coated MNPs have shown potential in applications such as magnetic resonance imaging, their effectiveness in theranostics, particularly magnetic hyperthermia (MH) and photoacoustic imaging (PAI), remains underexplored. Methods: In this study, iron oxide nanoparticles were synthesized via coprecipitation, using NRL as the coating agent. The samples were labeled by NRL amount used during synthesis: NRL-100 for 100 μL and NRL-400 for 400 μL. Results: Characterization results showed that NRL-100 and NRL-400 samples exhibited improved stability with zeta potentials of −27 mV and −30 mV, respectively and higher saturation magnetization values of 79 emu/g and 88 emu/g of Fe₃O₄. Building on these findings, we evaluated the performance of these nanoparticles in biomedical applications, including magnetomotive ultrasound (MMUS), PAI, and MH. NRL-100 and NRL-400 samples showed greater displacements and higher contrast in MMUS than uncoated samples (5, 8, and 9 µm) at 0.5 wt%. In addition, NRL-coated samples demonstrated an improved signal-to-noise ratio (SNR) in PAI. SNR values were 24.72 (0.51), 31.44 (0.44), and 33.81 (0.46) dB for the phantoms containing uncoated MNPs, NRL-100, and NRL-400, respectively. Calorimetric measurements for MH confirmed the potential of NRL-coated MNPs as efficient heat-generating agents, showing values of 43 and 40 W/g for NRL-100 and NRL-400, respectively. Conclusions: Overall, NRL-coated MNPs showed great promise as contrast agents in MMUS and PAI imaging, as well as in MH applications.

Short-lag spatial coherence (SLSC) beamforming of photoacoustic signals reduces acoustic clutter and enhances the contrast of underlying signals of interest. However, the original SLSC imaging algorithm is also known to be computationally expensive to implement. CohereNet, a custom deep neural network (DNN), was previously introduced to address the computational complexity of SLSC beamforming when applied to ultrasound data. Although it is conceivable that CohereNet can be translated to photoacoustic data, this translation is challenged by differences in data patterns and imaging depths when compared to ultrasound data, and it requires a similar diversity of photoacoustic training data to that present in ultrasound training data. Therefore, we propose to translate CohereNet to photoacoustic imaging after taking advantage of the diversity of signal-to-noise ratios (SNRs) available with transcutaneous in vivo data containing various levels of acoustic clutter. Raw channel data were acquired from the distal forearm of 18 volunteers with a variety of skin constitutive pigmentation, with 12 volunteers designated for training, 3 for validation, and the remaining 3 for testing. Time-delayed kernels and corresponding spatial coherence functions were computed and utilized as DNN training inputs and outputs, respectively. The correlation between standard central processing unit (CPU) SLSC and DNN SLSC images in the test set were 0.76, 0.78, and 0.84 when acquired with 750 nm, 810 nm, and 870 nm wavelengths, respectively. In addition, a mean SNR improvement of 2.5 dB was achieved with DNN SLSC imaging (relative to CPU SLSC imaging), due to the smoother coherence functions created with CohereNet. Results highlight the versatility of CohereNet, particularly when translating from ultrasound to photoacoustic data after appropriate steps are taken to achieve success, with no evidence of overfitting to training data.

Short-lag spatial coherence beamforming (SLSC) has shown promise in improving the signal-to-noise ratio (SNR) of photoacoustic (PA) images acquired under conditions of low optical fluence. However, the performance of this technique has not yet been evaluated with LED-based PA imaging (PAI). Therefore, the objective of this study was to compare the resulting image quality when applying SLSC and a conventional amplitude-based (FFT) beamformer. The influence of both LED and laser illumination was investigated using the same PAI system on a tissue-mimicking phantom and in ex vivo experiments. In both experimental conditions and illumination strategies, the SLSC method exhibited superior performance compared to FFT. Lowering the LED PAI frame rate, by increasing frame averaging, resulted in more significant SNR improvement for amplitude-based PAI compared to SLSC. For example, in the ex vivo experiment, the SNR values with SLSC exhibited enhancements of 13.6 dB and 11.1 dB for LED and laser illumination at 10 Hz, respectively. Meanwhile, at a frame rate of 0.25 Hz, the improvements were less pronounced, specifically 11.2 dB and 7.4 dB for LED and laser illumination, respectively. In conclusion, our results demonstrate that SLSC can improve SNR of LED-based PAI, particularly in conditions of low-SNR.