Dear Colleagues,

Photoacoustic imaging (PAI) gained significant attention from the biomedical community by displaying rich optical contrast information of deep biological tissue with high spatial resolution. For example, the optical absorption of hemoglobin molecules allows PAI to generate label-free images of blood vasculature, associated functional oxygen saturation, blood flow, and blood volume. Such multiparametric vascular information alone has attracted several pre-clinical and clinical applications in diagnosing vascular diseases, cancer detection, tissue metabolism, and monitoring brain activity. Further molecular imaging strategies using contrast agents have been developed to improve the sensitivity and specificity of PAI for disease detection. Since ultrasound and PAI share the same detection platform, conventional ultrasound systems can be easily adapted to display dual-modality anatomical ultrasound and functional/molecular photoacoustic information of the deep tissue. Like ultrasound, PAI systems are non-ionizing, non-invasive, portable, low-cost, and can be realized in various form factors to suit different clinical applications. This includes photoacoustic microscopy (PAM) for imaging superficial tissue depths with micron-scale spatial resolution, photoacoustic endoscopy (PAE) for imaging internal organs at scalable spatial resolution and imaging depth, and photoacoustic tomography (PAT) for deep tissue imaging with ultrasonic spatial resolution. In recent years, PAI has been translated to clinical applications such as cancer detection of breast, prostate, and ovaries; imaging primary melanoma and melanoma metastasis; detecting circulating melanoma tumor cells, monitoring Chron’s disease activity, arthritis, muscular dystrophy, and tissue metabolism. This Special Issue encompasses a broad range of such emerging clinical applications of PAI, including wearable and point-of-care imaging, and the role of machine- and deep learning-based artificial intelligence for further enhancing the performance of PAI in the clinic.

Dr. Sri-Rajasekhar Kothapalli
Guest Editor

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• Early detection and monitoring of cancer, arthritis, metabolic, vascular, and neuro diseases
• Molecular imaging strategies with immediate potential for clinical translation
• Image-guided surgeries
• Neonatal brain imaging
• Point-of-care sensing or imaging
• Machine and deep learning methods
• Low-cost diagnostic PAI systems integrating components such as light-emitting diodes, laser diodes, and ultrasound devices, and miniaturized scanners
• Durable and stable phantoms for routine clinical validation
• Image reconstruction and signal processing algorithms
• Novel multimodal systems integrating PAI (e.g., combined PAI and fluorescence imaging device)