Biomedical photoacoustic imaging

By Paul C. Beard. Interface Focus, 2011

2,049 citations recorded by the source corpus.

Photoacoustic (PA) imaging, also called optoacoustic imaging, is a new biomedical imaging modality based on the use of laser-generated ultrasound that has emerged over the last decade. It is a hybrid modality, combining the high-contrast and spectroscopic-based specificity of optical imaging with the high spatial resolution of ultrasound imaging. In essence, a PA image can be regarded as an ultrasound image in which the contrast depends not on the mechanical and elastic properties of the tissue, but its optical properties, specifically optical absorption. As a consequence, it offers greater specificity than conventional ultrasound imaging with the ability to detect haemoglobin, lipids, water and other light-absorbing chomophores, but with greater penetration depth than purely optical imaging modalities that rely on ballistic photons. As well as visualizing anatomical structures such as the microvasculature, it can also provide functional information in the form of blood oxygenation, blood flow and temperature. All of this can be achieved over a wide range of length scales from micrometres to centimetres with scalable spatial resolution. These attributes lend PA imaging to a wide variety of applications in clinical medicine, preclinical research and basic biology for studying cancer, cardiovascular disease, abnormalities of the microcirculation and other conditions. With the emergence of a variety of truly compelling in vivo images obtained by a number of groups around the world in the last 2–3 years, the technique has come of age and the promise of PA imaging is now beginning to be realized. Recent highlights include the demonstration of whole-body small-animal imaging, the first demonstrations of molecular imaging, the introduction of new microscopy modes and the first steps towards clinical breast imaging being taken as well as a myriad of in vivo preclinical imaging studies. In this article, the underlying physical principles of the technique, its practical implementation, and a range of clinical and preclinical applications are reviewed.

Subfields: Biomedical Engineering, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/bce87ec88b2f2a14d414a9e331f1640ac3e722b7

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In Biomedical Engineering

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Solving inverse problems using data-driven models (2019, background): “Beard (2011), ‘Biomedical photoacoustic imaging’, Interface Focus 1, 602–631.”
Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography (2017, methodology): “The US sensing is then modeled as a linear operator M acting on the pressure field p(r, t) restricted to the boundary of the computational domain and a finite time window (see [3], [36] for details on measurement systems):”
Fully Dense UNet for 2-D Sparse Photoacoustic Tomography Artifact Removal (2018, background): “Grüneisen coefficient describing the conversion efficiency from heat energy to pressure [2].”
Photoacoustic tomography of blood oxygenation: A mini review (2018, methodology): “Various methods have been explored to further improve PAT’s performance in resolution, contrast, imaging speed, and penetration depth [1,29,31,45].”
Contrast agents for molecular photoacoustic imaging (2016, background): “For example, when operating in the ‘nearinfrared (NIR) window’ (620 – 950 nm), tomographic PAI can reach a penetration depth of several centimeters with a resolution of the order of a few 100 μm, scaling to < 100 μm resolution for shallower (<1 cm) penetration depths.(3) PAI is currently one of the ”
A review of clinical photoacoustic imaging: Current and future trends (2019, methodology): “Addressing the limited view drawback [11] by using ring detectors that can be switched between 2D and 3D modes, eight out of nine breast cancer lesions were accurately detected using high spatial (255 μm) and temporal resolution images.”
Quantitative spectroscopic photoacoustic imaging: a review. (2012, methodology): “The key to this method is part (2), finding a solution to”