LED-Based Photoacoustic Imaging for Guiding Peripheral Minimally Invasive Procedures

Mackle, Eleanor C.; Maneas, Efthymios; Xia, Wenfeng; West, Simeon J.; Desjardins, Adrien E.

doi:10.1007/978-981-15-3984-8_13

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…In recent years, there have been advancements in solid-state device technology leading to the development of laser diodes (LD) and light-emitting diodes (LED), which are suitable for PAI [ 20 , 21 , 22 ]. High power LEDs have shown potential in PAI-based superficial and sub-surface (skin and <10 mm imaging depth) imaging in both preclinical and clinical applications [ 23 , 24 , 25 , 26 , 27 , 28 ]. LED-PAI is portable, affordable, and energy-efficient, for that reason it may have an easy clinical acceptance.…”

Section: Introductionmentioning

confidence: 99%

Oxygen Saturation Imaging Using LED-Based Photoacoustic System

Bulsink

Singh²,

Xavierselvan

et al. 2021

Sensors

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Oxygen saturation imaging has potential in several preclinical and clinical applications. Dual-wavelength LED array-based photoacoustic oxygen saturation imaging can be an affordable solution in this case. For the translation of this technology, there is a need to improve its accuracy and validate it against ground truth methods. We propose a fluence compensated oxygen saturation imaging method, utilizing structural information from the ultrasound image, and prior knowledge of the optical properties of the tissue with a Monte-Carlo based light propagation model for the dual-wavelength LED array configuration. We then validate the proposed method with oximeter measurements in tissue-mimicking phantoms. Further, we demonstrate in vivo imaging on small animal and a human subject. We conclude that the proposed oxygen saturation imaging can be used to image tissue at a depth of 6–8 mm in both preclinical and clinical applications.

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Section: Introductionmentioning

confidence: 99%

Oxygen Saturation Imaging Using LED-Based Photoacoustic System

Bulsink

Singh²,

Xavierselvan

et al. 2021

Sensors

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“… 9 , 46 In addition, SLSC beamforming improves the quality of photoacoustic signals acquired with low laser energies, 52 which is advantageous because the use of low laser energies can help to ensure laser safety. Miniaturized low-energy light delivery systems (such as pulsed laser diodes 52 – 54 or light-emitting diodes 55 ) are additionally beneficial for portability in the operating room and increasing frame rates when compared with

-switched lasers. Therefore, we are interested in exploring capabilities and limitations of SLSC beamforming with regard to low-energy light sources.…”

Section: Introductionmentioning

confidence: 99%

GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions

González

Bell

2020

J. Biomed. Opt.

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Significance: Photoacoustic-based visual servoing is a promising technique for surgical tool tip tracking and automated visualization of photoacoustic targets during interventional procedures. However, one outstanding challenge has been the reliability of obtaining segmentations using low-energy light sources that operate within existing laser safety limits. Aim: We developed the first known graphical processing unit (GPU)-based real-time implementation of short-lag spatial coherence (SLSC) beamforming for photoacoustic imaging and applied this real-time algorithm to improve signal segmentation during photoacoustic-based visual servoing with low-energy lasers. Approach: A 1-mm-core-diameter optical fiber was inserted into ex vivo bovine tissue. Photoacoustic-based visual servoing was implemented as the fiber was manually displaced by a translation stage, which provided ground truth measurements of the fiber displacement. GPU-SLSC results were compared with a central processing unit (CPU)-SLSC approach and an amplitude-based delay-and-sum (DAS) beamforming approach. Performance was additionally evaluated with in vivo cardiac data. Results: The GPU-SLSC implementation achieved frame rates up to 41.2 Hz, representing a factor of 348 speedup when compared with offline CPU-SLSC. In addition, GPU-SLSC successfully recovered low-energy signals (i.e., ≤268 μJ) with mean ± standard deviation of signal-to-noise ratios of 11.2 AE 2.4 (compared with 3.5 AE 0.8 with conventional DAS beamforming). When energies were lower than the safety limit for skin (i.e., 394.6 μJ for 900-nm wavelength laser light), the median and interquartile range (IQR) of visual servoing tracking errors obtained with GPU-SLSC were 0.64 and 0.52 mm, respectively (which were lower than the median and IQR obtained with DAS by 1.39 and 8.45 mm, respectively). GPU-SLSC additionally reduced the percentage of failed segmentations when applied to in vivo cardiac data. Conclusions: Results are promising for the use of low-energy, miniaturized lasers to perform GPU-SLSC photoacoustic-based visual servoing in the operating room with laser pulse repetition frequencies as high as 41.2 Hz.

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