Comparison of acoustic shock waves generated by micro and nanosecond lasers for a smart laser surgery system

Kenhagho, Hervé Nguendon; Rauter, Georg; Guzman, Raphael; Cattin, Philippe C.; Zam, Azhar

doi:10.1117/12.2290094

Cited by 3 publications

(3 citation statements)

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“…at the moment of the formation of the breakdown plasma and the formation of the cavitation area [11]. The practical application of these results is closely related to medicine and laser surgery as lasers with femto-and nanosecond pulse duration often used in these areas [12,13].…”

Section: Introductionmentioning

confidence: 98%

Case Report: Investigation of the Time Evolution of Optical Breakdown Plasma During Irradiation of Aqueous Solutions of Fe Nanoparticles

et al. 2021

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The time sweeps of images of optical breakdown plasma flashes under irradiation of aqueous solutions of Fe nanoparticles with Nd: YAG laser radiation (λ = 1,064 nm, τ = 10 ns, ν = 10 kHz, ε = 2 mJ) are studied. It is shown that the sizes of plasma flares, the plasma glow intensity, and the time to reach the maximum intensity are concentrated around certain values. So, for example, the values of 30 μm are most typical for the maximum size of flares. The maximum luminescence is usually reached in 3–4 ns. It is found that at initial stage of optical breakdown process the water-vapor boundary moves at typical speed of 11 km/s and have maximum and minimum values at 15 and 4 km/s respectively. It is assumed in this work that such a distribution may be associated with the initiation of breakdown on nanoparticles located in different places of the laser radiation waist.

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Section: Introductionmentioning

confidence: 98%

Case Report: Investigation of the Time Evolution of Optical Breakdown Plasma During Irradiation of Aqueous Solutions of Fe Nanoparticles

et al. 2021

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“…When the tissue is exposed to microsecond pulsed Er:YAG laser light, the water in the tissue heats up, vaporizes, and the expansion causes micro-explosions that ablate a small part of the tissue [8]. This process emits an acoustic wave that is captured by a transducer [9].…”

Section: Introductionmentioning

confidence: 99%

Bone Ablation Depth Estimation From Er:YAG Laser-Generated Acoustic Waves

et al. 2022

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Using a laser for cutting bones instead of the traditional saws has been shown to improve a patient's healing process. Additionally, the laser has the potential to reduce the collateral damage to the surrounding tissue if appropriately applied. This can be achieved by building additional sensing elements besides the laser itself into an endoscope. To this end, we use a microsecond pulsed Erbium-doped Yttrium Aluminium Garnet (Er:YAG) laser to cut bones. During ablation, each pulse emits an acoustic shock wave that is captured by an air-coupled transducer. In our research, we use the data from these acoustic waves to predict the depth of the cut during the ablation process. We use a Neural Network (NN) to approximate the depth, where we use one or multiple consecutive measurements of acoustic waves. The NN outperforms the base-line method that assumes a constant ablation rate with each pulse to predict the depth. The results are evaluated and compared against the ground-truth depth measurements from Optical Coherence Tomography (OCT) images that measure the depth in realtime during the ablation process.

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“…This process takes place in microseconds and builds up pressure that is released in a series of micro-explosions. The explosions ablate a small portion of the tissue [10], creating an acoustic wave [11]. A transducer can then measure the resulting acoustic wave.…”

mentioning

confidence: 99%

Deep-Learning Approach for Tissue Classification Using Acoustic Waves During Ablation With an Er:YAG Laser

Seppi¹,

Huck

Kenhagho

et al. 2021

IEEE Access

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We acknowledge the funding of the Werner Siemens Foundation through the MIRCALE (Minimally Invasive Robot-Assisted Computer-guided LaserosteotomE) project. ABSTRACT Today's mechanical tools for bone cutting (osteotomy) lead to mechanical trauma that prolong the healing process. Medical device manufacturers continuously strive to improve their tools to minimize such trauma. One example of such a new tool and procedure is minimally invasive surgery with laser as the cutting element. This setup allows for tissue ablation using laser light instead of mechanical tools, which reduces the post-surgery healing time. During surgery, a reliable feedback system is crucial to avoid collateral damage to the surrounding tissues. Therefore, we propose a tissue classification method that analyzes the acoustic waves produced during laser ablation and show its applicability in an ex-vivo experiment. The ablation process with a microsecond pulsed Erbium-doped Yttrium Aluminium Garnet (Er:YAG) laser produces acoustic waves that we captured with an air-coupled transducer. Consequently, we used these captured waves to classify five porcine tissue types: hard bone, soft bone, muscle, fat, and skin tissue. For automated tissue classification of the measured acoustic waves, we propose three Neural Network (NN) approaches: A Fully-connected Neural Network (FcNN), a one-dimensional Convolutional Neural Network (CNN), and a Recurrent Neural Network (RNN). The time-and the frequency-dependent parts of the measured waves' pressure variation were used as separate inputs to train and validate the designed NNs. In a final step, we used Grad-CAM to find the frequencies' activation map and conclude that the low frequencies are the most important ones for this classification task. In our experiments, we achieved an accuracy of 100 % for the five tissue types for all the proposed NNs. We tested the different classifiers for their robustness and concluded that using frequency-dependent data together with a FcNN is the most robust approach.

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Comparison of acoustic shock waves generated by micro and nanosecond lasers for a smart laser surgery system

Cited by 3 publications

References 11 publications

Case Report: Investigation of the Time Evolution of Optical Breakdown Plasma During Irradiation of Aqueous Solutions of Fe Nanoparticles

Case Report: Investigation of the Time Evolution of Optical Breakdown Plasma During Irradiation of Aqueous Solutions of Fe Nanoparticles

Bone Ablation Depth Estimation From Er:YAG Laser-Generated Acoustic Waves

Deep-Learning Approach for Tissue Classification Using Acoustic Waves During Ablation With an Er:YAG Laser

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