An Adjustable Dark-Field Acoustic-Resolution Photoacoustic Imaging System with Fiber Bundle-Based Illumination

Performance evaluation of mesoscopic photoacoustic imaging

Photoacoustic mesoscopy visualises vascular architecture at high-resolution up to ~3 mm depth. Despite promise in preclinical and clinical imaging studies, with applications in oncology and dermatology, the accuracy and precision of photoacoustic mesoscopy is not well established. Here, we evaluate a commercial photoacoustic mesoscopy system for imaging vascular structures. Typical artefact types are first highlighted and limitations due to non-isotropic illumination and detection are evaluated with respect to rotation, angularity, and depth of the target. Then, using tailored phantoms and mouse models, we investigate system precision, showing coefficients of variation (COV) between repeated scans [short term (1 h): COV= 1.2%; long term (25 days): COV= 9.6%], from target repositioning (without: COV=1.2%, with: COV=4.1%), or from varying in vivo user experience (experienced: COV=15.9%, unexperienced: COV=20.2%). Our findings show robustness of the technique, but also underscore general challenges of limited-view photoacoustic systems in accurately imaging vessel-like structures, thereby guiding users when interpreting biologically-relevant information.

Visible CCD Camera-Guided Photoacoustic Imaging System for Precise Navigation during Functional Rat Brain Imaging

In photoacoustic (PA) imaging, tissue absorbs specific wavelengths of light. The absorbed energy results in thermal expansion that generates ultrasound waves that are reconstructed into images. Existing commercial PA imaging systems for preclinical brain imaging are limited by imprecise positioning capabilities and inflexible user interfaces. We introduce a new visible charge-coupled device (CCD) camera-guided photoacoustic imaging (ViCPAI) system that integrates an ultrasound (US) transducer and a data acquisition platform with a CCD camera for positioning. The CCD camera accurately positions the US probe at the measurement location. The programmable MATLAB-based platform has an intuitive user interface. In vitro carbon fiber and in vivo animal experiments were performed to investigate the precise positioning and imaging capabilities of the ViCPAI system. We demonstrated real-time capturing of bilateral cerebral hemodynamic changes during (1) forelimb electrical stimulation under normal conditions, (2) forelimb stimulation after right brain focal photothrombotic ischemia (PTI) stroke, and (3) progression of KCl-induced cortical spreading depression (CSD). The ViCPAI system accurately located target areas and achieved reproducible positioning, which is crucial in animal and clinical experiments. In animal experiments, the ViCPAI system was used to investigate bilateral cerebral cortex responses to left forelimb electrical stimulation before and after stroke, showing that the CBV and SO₂ in the right primary somatosensory cortex of the forelimb (S1FL) region were significantly changed by left forelimb electrical stimulation before stroke. No CBV or SO₂ changes were observed in the bilateral cortex in the S1FL area in response to left forelimb electrical stimulation after stroke. While monitoring CSD progression, the ViCPAI system accurately locates the S1FL area and returns to the same position after the probe moves, demonstrating reproducible positioning and reducing positioning errors. The ViCPAI system utilizes the real-time precise positioning capability of CCD cameras to overcome various challenges in preclinical and clinical studies.

Revisiting the cerebral hemodynamics of awake, freely moving rats with repeated ketamine self-administration using a miniature photoacoustic imaging system

SIGNIFICANCE

Revealing the dynamic associations between brain functions and behaviors is a significant challenge in neurotechnology, especially for awake subjects. Imaging cerebral hemodynamics in awake animal models is important because the collected data more realistically reflect human disease states.

AIM

We previously reported a miniature head-mounted scanning photoacoustic imaging (hmPAI) system. In the present study, we utilized this system to investigate the effects of ketamine on the cerebral hemodynamics of normal rats and rats subjected to prolonged ketamine self-administration.

APPROACH

The cortical superior sagittal sinus (SSS) was continuously monitored. The full-width at half-maximum (FWHM) of the photoacoustic (PA) A-line signal was used as an indicator of the SSS diameter, and the number of pixels in PA B-scan images was used to investigate changes in the cerebral blood volume (CBV).

RESULTS

We observed a significantly higher FWHM (blood vessel diameter) and CBV in normal rats injected with ketamine than in normal rats injected with saline. For rats subjected to prolonged ketamine self-administration, no significant changes in either the blood vessel diameter or CBV were observed.

CONCLUSIONS

The lack of significant change in prolonged ketamine-exposed rats was potentially due to an increased ketamine tolerance. Our device can reliably detect changes in the dilation of cortical blood vessels and the CBV. This study validates the utility of the developed hmPAI system in an awake, freely moving rat model for behavioral, cognitive, and preclinical cerebral disease studies.

Machine Learning-Based Diagnosis in Laser Resonance Frequency Analysis for Implant Stability of Orthopedic Pedicle Screws

Evaluation of the initial stability of implants is essential to reduce the number of implant failures of pedicle screws after orthopedic surgeries. Laser resonance frequency analysis (L-RFA) has been recently proposed as a viable diagnostic scheme in this regard. In a previous study, L-RFA was used to demonstrate the diagnosis of implant stability of monoaxial screws with a fixed head. However, polyaxial screws with movable heads are also frequently used in practice. In this paper, we clarify the characteristics of the laser-induced vibrational spectra of polyaxial screws which are required for making L-RFA diagnoses of implant stability. In addition, a novel analysis scheme of a vibrational spectrum using L-RFA based on machine learning is demonstrated and proposed. The proposed machine learning-based diagnosis method demonstrates a highly accurate prediction of implant stability (peak torque) for polyaxial pedicle screws. This achievement will contribute an important analytical method for implant stability diagnosis using L-RFA for implants with moving parts and shapes used in various clinical situations.