Tissue discrimination by uncorrected autofluorescence spectra: a proof-of-principle study for tissue-specific laser surgery

Real-time closed-loop tissue-specific laser osteotomy using deep-learning-assisted optical coherence tomography

This article presents a real-time noninvasive method for detecting bone and bone marrow in laser osteotomy. This is the first optical coherence tomography (OCT) implementation as an online feedback system for laser osteotomy. A deep-learning model has been trained to identify tissue types during laser ablation with a test accuracy of 96.28 %. For the hole ablation experiments, the average maximum depth of perforation and volume loss was 0.216 mm and 0.077 mm³, respectively. The contactless nature of OCT with the reported performance shows that it is becoming more feasible to utilize it as a real-time feedback system for laser osteotomy.

Analysis of muscle tissue in vivo using fiber-optic autofluorescence and diffuse reflectance spectroscopy

SIGNIFICANCE

Current methods for analyzing pathological muscle tissue are time consuming and rarely quantitative, and they involve invasive biopsies. Faster and less invasive diagnosis of muscle disease may be achievable using marker-free in vivo optical sensing methods.

AIM

It was speculated that changes in the biochemical composition and structure of muscle associated with pathology could be measured quantitatively using visible wavelength optical spectroscopy techniques enabling automated classification.

APPROACH

A fiber-optic autofluorescence (AF) and diffuse reflectance (DR) spectroscopy device was manufactured. The device and data processing techniques based on principal component analysis were validated using in situ measurements on healthy skeletal and cardiac muscle. These methods were then applied to two mouse models of genetic muscle disease: a type 1 neurofibromatosis (NF1) limb-mesenchyme knockout (Nf1Prx1  -  /  -  ) and a muscular dystrophy mouse (mdx).

RESULTS

Healthy skeletal and cardiac muscle specimens were separable using AF and DR with receiver operator curve areas (ROC-AUC) of >0.79. AF and DR analyses showed optically separable changes in Nf1Prx1  -  /  -   quadriceps muscle (ROC-AUC >0.97) with no differences detected in the heart (ROC-AUC <0.67), which does not undergo gene deletion in this model. Changes in AF spectra in mdx muscle were seen between the 3 week and 10 week time points (ROC-AUC = 0.96) and were not seen in the wild-type controls (ROC-AUC = 0.58).

CONCLUSION

These findings support the utility of in vivo fiber-optic AF and DR spectroscopy for the assessment of muscle tissue. This report highlights that there is considerable scope to develop this marker-free optical technology for preclinical muscle research and for diagnostic assessment of clinical myopathies and dystrophies.

Functional Micro-/Nanomaterials for Multiplexed Biodetection

When analyzing biological phenomena and processes, multiplexed biodetection has many advantages over single-factor biodetection and is highly relevant to both human health issues and advancements in the life sciences. However, many key problems with current multiplexed biodetection strategies remain unresolved. Herein, the main issues are analyzed and summarized: 1) generating sufficient signal to label targets, 2) improving the signal-to-noise ratio to ensure total detection sensitivity, and 3) simplifying the detection process to reduce the time and labor costs of multiple target detection. Then, available solutions made possible by designing and controlling the properties of micro- and nanomaterials are introduced. The aim is to emphasize the role that micro-/nanomaterials can play in the improvement of multiplexed biodetection strategies. Through analyzing existing problems, introducing state-of-the-art developments regarding relevant materials, and discussing future directions of the field, it is hopeful to help promote necessary developments in multiplexed biodetection and associated scientific research.

Halide perovskite nanocrystals for multiphoton applications

Halide perovskite nanocrystals (NCs) are a unique class of NCs with novel properties distinct from those of traditional semiconductor NCs. These exceptional properties of defect tolerance, large absorption coefficients, high brightness, and narrow emission linewidths stem from their atypical band structure. Their facile synthesis and broad colour tunability have attracted widespread interest for application in light emitting devices and lasers. One fledging niche area is the field of multiphoton excited emission where their giant nonlinear optical action cross-sections are highly favorable for imaging applications. This Frontier article examines the state-of-the-art in perovskite NCs for multiphoton applications from the materials science and physics perspectives that include their synthesis and nonlinear optical characterization. Opportunities and challenges of these exceptional NCs as potential fluorescent labels for multiphoton deep tissue microscopy are also highlighted.

Combined Nd:YAG and Er:YAG lasers for real-time closed-loop tissue-specific laser osteotomy

A novel real-time and non-destructive method for differentiating soft from hard tissue in laser osteotomy has been introduced and tested in a closed-loop fashion. Two laser beams were combined: a low energy frequency-doubled nanosecond Nd:YAG for detecting the type of tissue, and a high energy microsecond Er:YAG for ablating bone. The working principle is based on adjusting the energy of the Nd:YAG laser until it is low enough to create a microplasma in the hard tissue only (different energies are required to create plasma in different tissue types). Analyzing the light emitted from the generated microplasma enables real-time feedback to a shutter that prevents the Er:YAG laser from ablating the soft tissue.

Machine learning classification of human joint tissue from diffuse reflectance spectroscopy data

Objective: To assess if incorporation of DRS sensing into real-time robotic surgery systems has merit. DRS as a technology is relatively simple, cost-effective and provides a non-contact approach to tissue differentiation. Methods: Supervised machine learning analysis of diffuse reflectance spectra was performed to classify human joint tissue that was collected from surgical procedures. Results: We have used supervised machine learning in the classification of a DRS human joint tissue data set and achieved classification accuracy in excess of 99%. Sensitivity for the various classes were; cartilage 99.7%, subchondral 99.2%, meniscus 100% and cancellous 100%. Full wavelength range is required for maximum classification accuracy. The wavelength resolution must be larger than 8nm. A SNR better than 10:1 was required to achieve a classification accuracy greater than 50%. The 800-900nm wavelength range gave the greatest accuracy amongst those investigated Conclusion: DRS is a viable method for differentiating human joint tissue and has the potential to be incorporated into robotic orthopaedic surgery.

Compatibility of CO2 laser surgery and fluorescence detection in head and neck cancer cells

BACKGROUND

Surgical treatment of cancer requires tumor excision with emphasis on function preservation which is achieved in (early stage) laryngeal cancer by transoral carbon dioxide (CO₂ ) laser surgery. Whereas conventional laser surgery is restricted by the surgeon's visual recognition of tumor tissue, new approaches based on fluorescence-guided surgery (FGS) improve the detection of the tumor and its margin. However, it is unclear whether fluorophores are compatible with high-power laser application or whether precision is compromised by laser-induced bleaching of the dye.

METHODS

We applied topology-controlled 3D laser resection of fluorescent tumors cell in vitro and laser-induced autofluorescence analysis ex vivo.

RESULTS

Laser-induced bleaching of fluorescent dyes in the visible and near-infrared light spectrum (650-900 nm) ranges below the resolution range of operation microscopes. Furthermore, specific fluorescent signals in an FGS mouse model is 10⁴ higher than laser-induced autofluorescence in mouse tissue.

CONCLUSION

Laser-induced lateral photobleaching is negligible indicating a path forward for fluorescence-guided laser surgery in head and neck cancer.

Autofluorescence spectroscopy for nerve-sparing laser surgery of the head and neck-the influence of laser-tissue interaction

The use of remote optical feedback systems represents a promising approach for minimally invasive, nerve-sparing laser surgery. Autofluorescence properties can be exploited for a fast, robust identification of nervous tissue. With regard to the crucial step towards clinical application, the impact of laser ablation on optical properties in the vicinity of structures of the head and neck has not been investigated up to now. We acquired 24,298 autofluorescence spectra from 135 tissue samples (nine ex vivo tissue types from 15 bisected pig heads) both before and after ER:YAG laser ablation. Sensitivities, specificities, and area under curve(AUC) values for each tissue pair as well as the confusion matrix were statistically calculated for pre-ablation and post-ablation autofluorescence spectra using principal component analysis (PCA), quadratic discriminant analysis (QDA), and receiver operating characteristics (ROC). The confusion matrix indicated a highly successful tissue discrimination rate before laser exposure, with an average classification error of 5.2%. The clinically relevant tissue pairs nerve/cancellous bone and nerve/salivary gland yielded an AUC of 100% each. After laser ablation, tissue discrimination was feasible with an average classification accuracy of 92.1% (average classification error 7.9%). The identification of nerve versus cancellous bone and salivary gland performed very well with an AUC of 100 and 99%, respectively. Nerve-sparing laser surgery in the area of the head and neck by means of an autofluorescence-based feedback system is feasible even after ER-YAG laser-tissue interactions. These results represent a crucial step for the development of a clinically applicable feedback tool for laser surgery interventions in the oral and maxillofacial region.

Non-linear imaging and characterization of atherosclerotic arterial tissue using combined SHG and FLIM microscopy

Atherosclerosis is one of the leading causes of death in the Western World and its characterization is extremely interesting from the diagnostic point of view. Here, we employed combined SHG-FLIM microscopy to characterize arterial tissue with atherosclerosis. The shorter mean fluorescence lifetime measured within plaque depositions (1260 ± 80 ps) with respect to normal arterial wall (1480 ± 100 ps) allowed discriminating collagen from lipids. SHG measurements and image analysis demonstrated that the normal arterial wall has a more anisotropic Aspect Ratio (0.37 ± 0.02) with respect to plaque depositions (0.61 ± 0.02) and that the correlation length can be used for discriminating collagen fibre bundles (2.0 ± 0.6 µm) from cholesterol depositions (4.1 ± 0.6 µm). The presented method has the potential to find place in a clinical setting as well as to be applied in vivo in the near future. Graphic composition of SHG and FLIM images representing normal arterial wall and plaque depositions.

Laser induced breakdown spectroscopy for bone and cartilage differentiation - ex vivo study as a prospect for a laser surgery feedback mechanism

Laser surgery enables for very accurate, fast and clean modeling of tissue. The specific and controlled cutting and ablation of tissue, however, remains a central challenge in the field of clinical laser applications. The lack of information on what kind of tissue is being ablated at the bottom of the cut may lead to iatrogenic damage of structures that were meant to be preserved. One such example is the shaping or removal of diseased cartilaginous and bone tissue in the temporomandibular joint (TMJ). Diseases of the TMJ can induce deformation and perforation of the cartilaginous discus articularis, as well as alterations to the cartilaginous surface of the condyle or even the bone itself. This may result in restrictions of movement and pain. The aim of a surgical intervention ranges from specific ablation and shaping of diseased cartilage, bone or synovial tissues to extensive removal of TMJ structures. One approach to differentiate between these tissues is to use Laser Induced Breakdown Spectroscopy (LIBS). The ultimate goal is a LIBS guided feedback control system for surgical laser systems that enables real-time tissue identification for tissue specific ablation. In the presented study, the authors focused on the LIBS based differentiation between cartilage tissue and cortical bone tissue using an ex-vivo pig model.