Another decade of photoacoustic imaging

Das, Dhiman; Sharma, Arunima; Rajendran, Praveenbalaji; Pramanik, Manojit

doi:10.1088/1361-6560/abd669

Cited by 105 publications

(67 citation statements)

References 314 publications

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“…By applying acoustic (usually ultrasonic) detectors to receive acoustic waves and scanning the PA generation zone, it is possible to obtain an optical absorbing image of the material through a specific image reconstruction algorithm. This technique is known as PA (or optoacoustic) imaging and has found wide application in biotissue studies and in vivo small animal studies [8,9]. Examples include visualizing blood vessels [10,11], imaging tissue tumours [12,13], determining blood hemoglobin (HbR) [14] and deoxyhemoglobin (HbO) [15] levels as well as oxygen saturation [16,17] and oxygen metabolism [15,18].…”

Section: Pai Technique and Its Categoriesmentioning

confidence: 99%

Recent Technical Progression in Photoacoustic Imaging—Towards Using Contrast Agents and Multimodal Techniques

Zhao

Myllylä

2021

Applied Sciences

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For combining optical and ultrasonic imaging methodologies, photoacoustic imaging (PAI) is the most important and successful hybrid technique, which has greatly contributed to biomedical research and applications. Its theoretical background is based on the photoacoustic effect, whereby a modulated or pulsed light is emitted into tissue, which selectively absorbs the optical energy of the light at optical wavelengths. This energy produces a fast thermal expansion in the illuminated tissue, generating pressure waves (or photoacoustic waves) that can be detected by ultrasonic transducers. Research has shown that optical absorption spectroscopy offers high optical sensitivity and contrast for ingredient determination, for example, while ultrasound has demonstrated good spatial resolution in biomedical imaging. Photoacoustic imaging combines these advantages, i.e., high contrast through optical absorption and high spatial resolution due to the low scattering of ultrasound in tissue. In this review, we focus on advances made in PAI in the last five years and present categories and key devices used in PAI techniques. In particular, we highlight the continuously increasing imaging depth achieved by PAI, particularly when using exogenous reagents. Finally, we discuss the potential of combining PAI with other imaging techniques.

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Section: Pai Technique and Its Categoriesmentioning

confidence: 99%

Recent Technical Progression in Photoacoustic Imaging—Towards Using Contrast Agents and Multimodal Techniques

Zhao

Myllylä

2021

Applied Sciences

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“…In the recent decade, photoacoustic tomography (PAT, also referred to as optoacoustic tomography or thermoacoustic tomography) has emerged as one of the fastest-growing imaging technologies and has become an enabling tool in many fundamental and translational studies, particularly for early cancer diagnosis, functional brain imaging, drug delivery monitoring, and interventional procedure guidance. 1 The imaging process in PAT typically starts with a short laser pulse that illuminates biological tissue. As the excitation photons propagate through the tissue, some are absorbed by endogenous or exogenous biomolecules, and their energy is partially or completely converted into heat and thus a transient temperature rise, through nonradiative relaxation of excited molecules [ Fig.…”

Section: Introductionmentioning

confidence: 99%

Perspective on fast-evolving photoacoustic tomography

Yao

Wang

2021

J. Biomed. Opt.

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: Significance: Acoustically detecting the rich optical absorption contrast in biological tissues, photoacoustic tomography (PAT) seamlessly bridges the functional and molecular sensitivity of optical excitation with the deep penetration and high scalability of ultrasound detection. As a result of continuous technological innovations and commercial development, PAT has been playing an increasingly important role in life sciences and patient care, including functional brain imaging, smart drug delivery, early cancer diagnosis, and interventional therapy guidance. Aim: Built on our 2016 tutorial article that focused on the principles and implementations of PAT, this perspective aims to provide an update on the exciting technical advances in PAT. Approach: This perspective focuses on the recent PAT innovations in volumetric deep-tissue imaging, high-speed wide-field microscopic imaging, high-sensitivity optical ultrasound detection, and machine-learning enhanced image reconstruction and data processing. Representative applications are introduced to demonstrate these enabling technical breakthroughs in biomedical research. Conclusions: We conclude the perspective by discussing the future development of PAT technologies.

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“…The hybrid imaging modality of photoacoustic tomography (PAT) combines optical excitation and ultrasound detection to achieve an unparalleled balance of spatial resolution, penetration depth, and imaging speed. [1][2][3] PAT relies on the photoacoustic effect, by which the absorption of excitation light by endogenous or exogenous chromophores causes a transient temperature rise that generates a pressure rise proportional to the optical absorption. 1,4 This rapid pressure rise propagates through the tissue as ultrasound waves that are detected by an external ultrasound transducer or transducer array.…”

Section: Introductionmentioning

confidence: 99%

Sounding out the hidden data: A concise review of deep learning in photoacoustic imaging

DiSpirito

Pramanik

et al. 2021

Exp Biol Med (Maywood)

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The rapidly evolving field of photoacoustic tomography utilizes endogenous chromophores to extract both functional and structural information from deep within tissues. It is this power to perform precise quantitative measurements in vivo—with endogenous or exogenous contrast —that makes photoacoustic tomography highly promising for clinical translation in functional brain imaging, early cancer detection, real-time surgical guidance, and the visualization of dynamic drug responses. Considering photoacoustic tomography has benefited from numerous engineering innovations, it is of no surprise that many of photoacoustic tomography’s current cutting-edge developments incorporate advances from the equally novel field of artificial intelligence. More specifically, alongside the growth and prevalence of graphical processing unit capabilities within recent years has emerged an offshoot of artificial intelligence known as deep learning. Rooted in the solid foundation of signal processing, deep learning typically utilizes a method of optimization known as gradient descent to minimize a loss function and update model parameters. There are already a number of innovative efforts in photoacoustic tomography utilizing deep learning techniques for a variety of purposes, including resolution enhancement, reconstruction artifact removal, undersampling correction, and improved quantification. Most of these efforts have proven to be highly promising in addressing long-standing technical obstacles where traditional solutions either completely fail or make only incremental progress. This concise review focuses on the history of applied artificial intelligence in photoacoustic tomography, presents recent advances at this multifaceted intersection of fields, and outlines the most exciting advances that will likely propagate into promising future innovations.

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Another decade of photoacoustic imaging

Cited by 105 publications

References 314 publications

Recent Technical Progression in Photoacoustic Imaging—Towards Using Contrast Agents and Multimodal Techniques

Recent Technical Progression in Photoacoustic Imaging—Towards Using Contrast Agents and Multimodal Techniques

Perspective on fast-evolving photoacoustic tomography

Sounding out the hidden data: A concise review of deep learning in photoacoustic imaging

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