LIBS for Smart Laserosteotomy

Over the past several years laserosteotomes have become a generally accepted device in various surgical applications. In laserosteotomy, the type of tissue being cut has to be identified, otherwise critical structures of the body under or near the focal spot of the laser beam are prone to inadvertently ablation. Laser-Induced Breakdown Spectroscopy (LIBS) is a potential tool for detecting the type and properties of the ablating tissue. This study examines the applicability of LIBS as a potential technique to differentiate bone from surrounding soft tissue (fat, muscle and bone marrow). Moreover, LIBS has been evaluated to detect the bone carbonization during the ablation process. In these experiments, fresh porcine femur tissues were used as samples. A beam of a nanosecond frequency-doubled Nd:YAG laser was used to ablate the tissue samples and generate the plasma. The plasma light emitted from the ablated spot, which corresponds to the recombination spectra of ionized atoms and molecules, was collected with a collection optic (including a reflective light collector and a UV-enhanced fiber optic) and was sent to an Echelle spectrometer to resolve the atomic composition of the ablated sample. Several spectra from different points of different samples of each group were collected. Then, to determine the elemental composition of the ablated tissues, the atomic emissions in the recorded LIBS spectra of all classes were compared to known spectra of atoms available in the NIST atomic emission database. Afterward, Discrimination Function Analysis (DFA) was employed to classify different groups of the samples. Finally, the Receiver Operating Characteristic (ROC) was performed, and the Area Under Curve (AUC) were calculated. Differences in the recorded spectra of the results are potentially enabled a real-time tissue classification in smart laserosteotomy

Optical Feedback Mechanism for Minimally Invasive Laserosteotome

Laserosteotomy has become a generally accepted method in surgical applications. However, the method still suffers from a lack of information about the type of tissue currently being ablated. Therefore, critical structures of the body near the focal spot of the laser beam are prone to inadvertent ablation. This issue can be solved by connecting the laserosteotome to an optical detection setup, which can differentiate various types of tissues, especially bone from soft connective tissues. This study examines the applicability of laser-induced breakdown spectroscopy (LIBS) as a potential technique to differentiate bone from surrounding soft tissue (fat and muscle). Additionally, the efficiency of the developed system to detect laser-induced thermal effects on the bone (dehydration and carbonization) has been investigated. In this experiment, fresh porcine femur bone, muscle, and fat were used. The beam of frequency-doubled Nd:YAG laser with nanoseconds pulse duration was used to ablate the tissue samples and generate the plasma. The plasma light emitted from the ablated spot, which is associated with the recombination spectra of ionized atoms and molecules, was collected with an optical fiber and sent to an Echelle spectrometer for resolving the atomic composition of the ablated sample. The results showed that LIBS is capable to differentiate between tissues and also detect laser-induced thermal damages with high accuracy

All fiber-based LIBS feedback system for endoscopic laser surgery

There has been a particular interest to use laser-induced breakdown spectroscopy (LIBS) as a feedback mechanism for laser surgeries in the past decade 1-6. However, none of the mentioned setups 1-6 is suitable for endoscopic applications due to their bulky free-space configurations. In minimally nvasive surgeries, the major challenge is to integrate ablating laser waveguides and also all sensors inside the narrow channel of the endoscope. In this paper, we present a LIBS setup, which uses a multimode silica fiber for both delivering the inducing laser pulse and collecting the plasma emission light through the endoscope. The fiber-based LIBS setup consists of a frequency-doubled Q-switched Nd:YAG laser (Q-smart 450, Quantel, 532 nm, 5 ns, 60 mJ, 1 Hz), a cleaved large-core silica fiber (1.5 m-long, 1500 um-core, 0.39-NA, 70 mm-bending radius), and an in-house Echelle spectrometer (See Fig. 1). A 75 cm plano-convex laser line lens (Thorlabs, LA1978-YAG) was used to couple the laser beam into a multimode step-index silica fiber. Such a long focal length convex lens was used to avoid breakdown process in air. Moreover, the input face of the fiber was placed at 1 cm behind the focal point to maintain the laser power density below the damage threshold of the fiber. Two tight focusing lenses were placed in front of the fiber end face to collimate the highly divergent laser beam and refocus it onto the sample surface. The light emitted from the microplasma generated at the surface of the sample (bone and its surrounding soft tissues) was collected by the same optics and directed to the spectrometer for characterization. The performance of the developed fiber-based LIBS setup for classification of different tissues has been investigated and compared with the free-space LIBS. The feedback provided by this fiber-based LIBS setup can be used in minimally invasive laserosteotomies in order to stop the laser before causing any collateral damage to surrounding tissues. References [1] F. Yueh, H. Zheng, J.P. Singh, S. Burgess, Preliminary evaluation of laser-induced breakdown spectroscopy for tissue classification, Spectrochim. Acta B 64 (2009) 1059-1067. [2] R. Kanawade, F. Mehari, C. Knipfer, M. Rohde, K. Tangermann-Gerk, et al., Pilot study of laser induced breakdown spectroscopy for tissue differentiation by monitoring the plume created during laser surgery-An approach on a feedback Laser control mechanism, Spectrochim. Acta B 87 (2013) 175-181. [3] K. Henn, G.G. Gubaidullin, J. Bongartz, J. Wahrburg, H. Roth, et al., A spectroscopic approach to monitor the cut processing in pulsed laser osteotomy, Lasers Med. Sci. 28 (2013) 87-92. [4] H. Huang, L.-M. Yang, S. Bai, J. Liu, Smart surgical tool, J. Biomed. Opt. 20 (2015) 028001. [5] R.K. Gill, Z.J. Smith, C. Lee, S. Wachsmann-Hogiu, The effects of laser repetition rate on femtosecond laser ablation of dry bone: a thermal and LIBS study, J. Biophotonics 9 (2016) 171-180. [6] H. Abbasi, G. Rauter, R. Guzman, P.C. Cattin, A. Zam, Laser-induced breakdown spectroscopy as a potential tool for auto carbonization detection in laserosteotomy, J. Biomed. Opt. 23 (2018) 071206

Toward finding the best machine learning classifier for LIBS-based tissue differentiation

Lasers have become generally accepted devices in surgical applications, especially as a cutting tool, for cutting both soft and hard tissues including bone (laserosteotomy). It has been shown that applying lasers in osteotomy have important advantages over mechanical tools, including faster healing, more precise cut and functional cutting geometries as well as less trauma [1, 2]. However, the ability of detecting the type of tissue that being cut during surgery can extend the application and safety of laserosteotomes in practice. As a result, the laser could be stopped automatically in case of cutting a tissue that should be preserved. Authors have previously demonstrated that laser-induced breakdown spectroscopy (LIBS) is a potential candidate to differentiate surrounding soft tissue from the bone in ex vivo condition [3]. In the current study, different machine learning classifiers were examined to find the best possible method to differentiate bone from soft tissues based on LIBS data. These methods include decision tree, K Nearest Neighbor (KNN), linear and quadratic Support Vector Machine (SVM) as well as linear and quadratic discriminant analysis. All classifiers were applied on LIBS data obtained from bone, muscle, and fat tissues using an Nd:YAG laser and an Echelle spectrometer. Confusion matrix and Receiver Operating Characteristic (ROC) curve were obtained for each classifier afterwards. Moreover, in order to estimate the model's performance on new data and also to protect the model against overfitting, cross-validation was applied. All mentioned examinations were performed with MATLAB (R2017b)

Design and implementation of a compact high-throughput echelle spectrometer using off-the-shelf off-axis parabolic mirrors for analysis of biological samples by LIBS (Conference Presentation)

This work presents the development of an Echelle spectrometer that is optimized for the characterization of laser-driven plasma emission of biological samples for application in smart laser surgery systems. Despite the compact (portable) and cost-efficient design of the developed spectrometer, it allows analyzing the spectrum of a plasma emitted from bone, and its surrounding soft tissues (bone marrow, muscle, and fat) in nearly the same way as a full-sized Echelle spectrometer as used in commercial laser-induced breakdown spectroscopy (LIBS) systems. Most of the commercially available Echelle spectrometers on the market use a long focal length on-axis mirror to have a reasonable F number (which defines the optical throughput of the system) and low aberration. While a long focal length requires less tilting of the mirror than a shorter focal length (the higher the tilt angle, the higher the aberration), a long focal length increases the system size and decreases sensitivity (i.e., less optical throughput). In this work, a parabolic 90o off-axis mirror with a focal length of 152.4 mm and a diameter of 50.8 mm, which leads to an F-number of 3, has been used. This low F-number provides a high optical throughput compared to other similar commercial Echelle spectrometers with F-numbers of 10 or more [1-5]. Since most of the important peaks in biological tissue are in the interval of 240 to 840 nm [6], the design was done by using off-the-shelf aluminum mirrors with a UV-enhanced coating for both collimating and focusing purposes to cover this range with sub-Angstrom resolution. Both collimating and focusing mirrors were chosen with the same radius of curvature and declination angle (opposite direction) to cancel the coma. In this antiparallel configuration, the second parabolic mirror largely eliminates the aberrations from the first one. Moreover, we positioned the Echelle grating under the condition of quasi-Littrow design to have high diffraction efficiency with an off-axis angle in the horizontal plane. A ruled reflection grating with dispersion perpendicular to that of the Echelle grating was utilized as a cross dispenser (order separator) after the Echelle grating to distinguish the overlapping diffraction harmonics. The spectrometer has been connected to a gated ICCD to measure time-resolved spectra. The developed spectrometer was installed on a 3-tier utility cart, the inducing laser (Q-switched Nd:YAG) for LIBS was placed on the middle tier, and the last tier was dedicated for calibration instruments (a NIST traceable balanced Deuterium-Halogen light source for intensity calibration, and some gas/vapor spectral lamps including Mercury-Argon, Argon, Neon, and Krypton for wavelength calibration). The portability feature of this LIBS setup provides a remarkable value for testing and characterizing different biological samples on-site. This is a great capability especially if the target sample has the potential of being contagious. This setup is meant to be used for so-called smart laser osteotomies, i.e., the osteotome will be able to identify the type of the tissue being cut through the feedback provided by LIBS [6-8]

Highly flexible fiber delivery of a high peak power nanosecond Nd:YAG laser beam for flexiscopic applications

Minimally invasive laser surgeries that require the use of a flexible endoscope (flexiscope) could benefit from high-energy nanosecond laser pulses delivered through fibers for real-time tissue characterization and phenotyping. The damage threshold of the fiber's glass material limits the maximum amount of deliverable peak power. To transmit high-energy pulses without damaging the fiber material, large-diameter fibers are typically used, leading to a limited bending radius. Moreover, in a large-core fiber, self-focusing can damage the fiber even if the tip remains intact. In this work, we tested a fused-end fiber bundle combined with a beam shaper capable of delivering more than 20 MW (>100 mJ/5 ns). The fiber bundle was tested over more than eight hours of operation, with different bending radiuses down to 15 mm. The results demonstrate, to the best of our knowledge, the highest peak power delivered through a flexible fiber, for a frequency-doubled Q-switched Nd:YAG laser

Machine learning-based method for linearization and error compensation of an absolute rotary encoder

The main objective of this work is to develop a miniaturized, high accuracy, single-turn absolute, rotary encoder called ASTRAS360. Its measurement principle is based on capturing an image that uniquely identifies the rotation angle. To evaluate this angle, the image first has to be classified into its sector based on its color, and only then can the angle be regressed. In-spired by machine learning, we built a calibration setup, able to generate labeled training data automatically. We used these training data to test, characterize, and compare several machine learning algorithms for the classification and the regression. In an additional experiment, we also characterized the tolerance of our rotary encoder to eccentric mounting. Our findings demonstrate that various algorithms can perform these tasks with high accuracy and reliability; furthermore, providing extra-inputs (e.g. rotation direction) allows the machine learning algorithms to compensate for the mechanical imperfections of the rotary encoder.Comment: This paper was submitted for publication to Measurement (Elsevier) on the 7th July 202

Proof of concept of a novel absolute rotary encoder

Rotary encoders are used in many applications that require monitoring or controlling mechanical systems such as robots. Typically, small rotary encoders have poor resolution; this is unfortunate for applications such as robotics in medical surgery procedures. For example, in an articulated robotic endoscope, miniaturization is mandatory and, when automation is desired, high accuracy to track the shape and pose of the device is required; small (few millimeters) and accurate (few hundred arcsec) rotary encoders are thus needed. Previously, we introduced a novel concept of a miniaturizable angular sensor, called ASTRAS (Angular Sensor for TRAcking System). This was presented as a basic element of a tracking system for articulated endoscopes. The principle of measurement of ASTRAS is based on processing a shadow image cast by a shadow mask onto an image sensor. The characterization of the first prototype of ASTRAS was very promising, however, its angular range of about ±30 degrees was too limiting for many practical applications. In this work, we present an extension of the concept mentioned above to a rotary encoder that can measure one full rotation of 360 degrees thus the name is ASTRAS360. Its working principle bases on encoding the shadow image using colored light to distinguish different angular sectors. The identification of the sector corresponds to a coarse angular measurement, which is afterward refined using the same technique as in ASTRAS. We implemented this concept, realizing a prototype and an algorithm to calculate the angle from the shadow image. The experiments demonstrated the validity of this concept and showed encouraging results with a precision of ∼0.6 arcsec and 6σ-resolution of 3.6 arcsec corresponding to 19 bits

Plasma plume expansion dynamics in nanosecond Nd:YAG laserosteotome

In minimal invasive laser osteotomy precise information about the ablation process can be obtained with LIBS in order to avoid carbonization, or cutting of wrong types of tissue. Therefore, the collecting fiber for LIBS needs to be optimally placed in narrow cavities in the endoscope. To determine this optimal placement, the plasma plume expansion dynamics in ablation of bone tissue by the second harmonic of a nanosecond Nd:YAG laser at 532 nm has been studied. The laserinduced plasma plume was monitored in different time delays, from one nanosecond up to one hundred microseconds. Measurements were performed using high-speed gated illumination imaging. The expansion features were studied using illumination of the overall visible emission by using a gated intensified charged coupled device (ICCD). The camera was capable of having a minimum gate width (Optical FWHM) of 3 ns and the timing resolution (minimum temporal shift of the gate) of 10 ps. The imaging data were used to generate position-time data of the luminous plasma-front. Moreover, the velocity of the plasma plume expansion was studied based on the time-resolved intensity data. By knowing the plasma plume profile over time, the optimum position (axial distance from the laser spot) of the collecting fiber and optimal time delay (to have the best signal to noise ratio) in spatial-resolved and time-resolved laser-induced breakdown spectroscopy (LIBS) can be determined. Additionally, the function of plasma plume expansion could be used to study the shock wave of the plasma plume

Laser-induced breakdown spectroscopy as a potential tool for autocarbonization detection in laserosteotomy

In laserosteotomy, it is vital to avoid thermal damage of the surrounding tissue, such as carbonization, since carbonization does not only deteriorate the ablation efficiency but also prolongs the healing process. The state-of-the-art method to avoid carbonization is irrigation systems; however, it is difficult to determine the desired flow rate of the air and cooling water based on previous experiments without online monitoring of the bone surface. Lack of such feedback during the ablation process can cause carbonization in case of a possible error in the irrigation system or slow down the cutting process when irrigating with too much cooling water. The aim of this paper is to examine laser-induced breakdown spectroscopy as a potential tool for autocarbonization detection in laserosteotomy. By monitoring the laser-driven plasma generated during nanosecond pulse ablation of porcine bone samples, carbonization is hypothesized to be detectable. For this, the collected spectra were analyzed based on variation of a specific pair of emission line ratios in both groups of samples: normal and carbonized bone. The results confirmed a high accuracy of over 95% in classifying normal and carbonized bone