Three-dimensional bimodal photoacoustic/US imaging provided volumetric and multiparametric information about morphologic and physiologic features of the human foot, potentially useful in diagnosing... Background Monitoring the microcirculation in human feet is crucial in assessing peripheral vascular diseases, such as diabetic foot. However, conventional imaging modalities are more focused on di...

Functional imaging of microvascular dynamics in extremities delivers intuitive information for early detection, diagnosis, and prognosis of vascular diseases. High-resolution and high-speed photoacoustic microscopy (PAM) visualizes and measures multiparametric information of microvessel networks in vivo such as morphology, flow, oxygen saturation, and metabolic rate. Here, we demonstrate high-resolution photoacoustic monitoring of vascular dynamics in human fingers. We photoacoustically monitored the position displacement of blood vessels associated with arterial pulsation in human fingers. Then, during and after arterial occlusion, we photoacoustically quantified oxygen consumption and blood perfusion in the fingertips. The results demonstrate that high-resolution functional PAM could be a vital tool in peripheral vascular examination for measuring heart rate, oxygen consumption, and/or blood perfusion.

Dual-mode photoacoustic/ultrasound endoscopy (ePAUS) is a promising tool for preclinical and clinical interventions. To be clinically useful, ePAUS must deliver high-performance ultrasound imaging comparable to commercial systems and maintain high photoacoustic imaging performance at long working distances. This requires a transducer with an intact physical aperture and coaxial alignment of acoustic and optical beams within the probe, a challenging integration task. We present a high-performance ePAUS probe with a miniaturized, optically transparent ultrasonic transducer (TUT) called ePAUS-TUT. The 1.8-mm-diameter probe, fitting into standard endoscopic channels, aligns acoustic and optical beams efficiently, achieving commercial-level ultrasound and high-resolution photoacoustic imaging over long distances. These imaging capabilities were validated through in vivo imaging of a rat’s rectum and a pig’s esophagus. The ePAUS-TUT system substantially enhances feasibility and potential for clinical applications.

Mid-infrared photoacoustic microscopy can capture biochemical information without staining. However, the long mid-infrared optical wavelengths make the spatial resolution of photoacoustic microscopy significantly poorer than that of conventional confocal fluorescence microscopy. Here, we demonstrate an explainable deep learning-based unsupervised inter-domain transformation of low-resolution unlabeled mid-infrared photoacoustic microscopy images into confocal-like virtually fluorescence-stained high-resolution images. The explainable deep learning-based framework is proposed for this transformation, wherein an unsupervised generative adversarial network is primarily employed and then a saliency constraint is added for better explainability. We validate the performance of explainable deep learning-based mid-infrared photoacoustic microscopy by identifying cell nuclei and filamentous actins in cultured human cardiac fibroblasts and matching them with the corresponding CFM images. The XDL ensures similar saliency between the two domains, making the transformation process more stable and more reliable than existing networks. Our XDL-MIR-PAM enables label-free high-resolution duplexed cellular imaging, which can significantly benefit many research avenues in cell biology.

Photoacoustic microscopy (PAM) is used to visualize blood vessels and to monitor their time-dependent changes. Photoplethysmography (PPG) measures hemodynamic time-series changes such as heart rate. However, PPG’s limited visual access to the dynamic changes of blood vessels has prohibited further understanding of hemodynamics. Here, we propose a novel, fully integrated PAM and photoplethysmography (PAM-PPG) system to understand hemodynamic features in detail. Using the PAM-PPG system, we simultaneously acquire vascular images (by PAM) and changes in the blood volume (by PPG) from human fingers. Next, we determine the heart rate from changes in the PA signals, which match well with the PPG signals. These changes can be measured if the blood flow is not blocked. From the results, we believe that PAM-PPG could be a useful clinical tool in various clinical fields such as cardiology and endocrinology.

Mobile and wearable healthcare electronics are widely used for measuring bio-signals using various fusion sensors that employ photoplethysmograms, cameras, microphones, ultrasound (US) sensors, and accelerometers. However, the consumer demand for small form factors has significantly increased as the integration of multiple sensors is difficult in small mobile or wearable devices. This study proposes two novel opto-US sensors, namely (1) a wearable photoplethysmography (PPG)-US device and (2) a PPG sensor built-in mobile smartphone with a US sensor, seamlessly integrated using a transparent ultrasound transducer (TUT). The TUT exhibits a center frequency of 6 MHz with a 50% bandwidth and 82% optical transparency in visible and near-infrared regions. We developed an integrated wearable PPG-US device to demonstrate its feasibility and coupled the TUT sensor with a smartphone. We measured the heart rates optically and acoustically in human subjects and quantified the oxygen saturation optically by passing light through the TUT. The proposed proof-of-concept is a novel sensor fusion for mobile and wearable devices that require a small form factor and aim to improve digital healthcare. The results of this study can form the basis for innovative developments in sensor-based high-tech industrial applications, such as automobiles, robots, and drones, in addition to healthcare applications.