The assessment of tissue chromophores at a volumetric scale is vital for an improved diagnosis and treatment of a large number of diseases. Spectral photoacoustic imaging (sPAI) co-registered with high-resolution ultrasound (US) is an innovative technology that has a great potential for clinical translation as it can assess the volumetric distribution of the tissue components. Conventionally, to detect and separate the chromophores from sPAI, an input of the expected tissue absorption spectra is required. However, in pathological conditions, the prediction of the absorption spectra is difficult as it can change with respect to the physiological state. Besides, this conventional approach can also be hampered due to spectral coloring, which is a prominent distortion effect that induces spectral changes at depth. Here, we are proposing a novel data-driven framework that can overcome all these limitations and provide an improved assessment of the tissue chromophores. We have developed a superpixel spectral unmixing (SPAX) approach that can detect the most and less prominent absorber spectra and their volumetric distribution without any user interactions. Within the SPAX framework, we have also implemented an advanced spectral coloring compensation approach by utilizing US image segmentation and Monte Carlo simulations, based on a predefined library of optical properties. The framework has been tested on tissue-mimicking phantoms and also on healthy animals. The obtained results show enhanced specificity and sensitivity for the detection of tissue chromophores. To our knowledge, this is a unique framework that accounts for the spectral coloring and provides automated detection of tissue spectral signatures at a volumetric scale, which can open many possibilities for translational research.

Magnesium (Mg) alloys possess unique properties that make them ideal for use as biodegradable implants in clinical applications. However, reports on the in vivo assessment of these alloys are insufficient. Thus, monitoring the degradation of Mg and its alloys in vivo is challenging due to the dynamic process of implant degradation and tissue regeneration. Most current works focus on structural remodeling, but functional assessment is crucial in providing information about physiological changes in tissues, which can be used as an early indicator of healing. Here, we report continuous wave near-infrared spectroscopy (CW NIRS), a non-invasive technique that is potentially helpful in assessing the implant-tissue dynamic interface in a rodent model. The purpose of this study was to investigate the effects on hemoglobin changes and tissue oxygen saturation (StO) after the implantation of Mg-alloy (WE43) and titanium (Ti) implants in rats' femurs using a multiwavelength optical probe. Additionally, the effect of changes in the skin on these parameters was evaluated. Lastly, combining NIRS with photoacoustic (PA) imaging provides a more reliable assessment of tissue parameters, which is further correlated with principal component analysis.

Characterizations based on anatomically realistic phantoms are highly effective to perform accurate technical validation of imaging systems. Specifically for photoacoustic imaging (PAI), although a variety of phantom models with simplified geometries are reported, an unmet need still exists to establish morphologically realistic heterogeneous pre-clinical phantoms. So the development of a mouse-mimicking phantom can reduce the use of animals for the validation and standardization studies of pre-clinical PAI systems and thus eventually translate the PAI technology to clinical research.

Liver fibrosis, a major global health issue, is marked by excessive collagen deposition that impairs liver function. Noninvasive methods for the direct visualization of collagen content are crucial for the early detection and monitoring of fibrosis progression. This study investigates the potential of spectral photoacoustic imaging (sPAI) to monitor collagen development in liver fibrosis. Utilizing a novel data-driven superpixel photoacoustic unmixing (SPAX) framework, we aimed to distinguish collagen presence and evaluate its correlation with fibrosis progression. We employed an established diethylnitrosamine (DEN) model in rats to study liver fibrosis over various time points. Our results revealed a significant correlation between increased collagen photoacoustic signal intensity and advanced fibrosis stages. Collagen abundance maps displayed dynamic changes throughout fibrosis progression. These findings underscore the potential of sPAI for the noninvasive monitoring of collagen dynamics and fibrosis severity assessment. This research advances the development of noninvasive diagnostic tools and personalized management strategies for liver fibrosis.

Fibrillar collagen accumulation emerges as a promising biomarker in several diseases, such as desmoplastic tumors and unstable atherosclerotic plaque. Gold nanorods (GNRs) hold great potential as contrast agents in high-resolution, biomedically safe, and non-invasive photoacoustic imaging (PAI). This study presents the design and characterization of a specialized imaging tool which exploits GNR assisted targeted photoacoustic imaging that is tailored for the identification of fibrillar collagen. In addition to the photoacoustic characterization of collagen in the NIR 1 and 2 regions, we demonstrate the detailed steps of conjugating a decoy to GNRs. This study serves as a proof of concept, that demonstrates that conjugated collagenase-1 (MMP-1) generates a distinct and collagen-specific photoacoustic signal, facilitating real-time visualization in the wavelength range of 700-970 nm (NIR I). As most of the reported studies utilized the endogenous contrast of collagen in the NIR II wavelength that has major limitations to perform deep tissue imaging, the approach that we are proposing is unique and it highlights the promise of MMP-1 decoy-functionalized GNRs as novel contrast agents for photoacoustic imaging of collagen in the NIR 1 region. To our knowledge this is the first time functionalized GNRs are optimized for the detection of fibrillar collagen and utilized in the field of non-invasive photoacoustic imaging that can facilitate a better prognosis of desmoplastic tumors and broken atherosclerotic plaques.