Nerve detection using optical spectroscopy, an evaluation in four different models: In human and swine, in-vivo, and post mortem

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Optimal endobronchial tool sizes for targeting lung lesions based on 3D modeling

Background For patients with suspicious lung lesions found on chest x-ray or CT, endo/trans- bronchial biopsy of the lung is the preferred method for obtaining a diagnosis. With the addition of new screening programs, a higher number of patients will require diagnostic biopsy which will prove even more challenging due to the small size of lesions found with screening. There are many endobronchial tools available on the market today and a wide range of new tools under investigation to improve diagnostic yield. However, there is little information available about the optimal tool size required to reach the majority of lesions, especially peripheral ones. In this manuscript we investigate the percentage of lesions that can be reached for various diameter tools if the tools remain inside the airways (i.e. endobronchial biopsy) and the distance a tool must travel “off-road” (or outside of the airways) to reach all lesions. Methods and findings To further understand the distribution of lung lesions with respect to airway sizes and distances from the airways, six 3D models of the lung were generated. The airways were modeled at two different respiratory phases (inspiration and expiration). Three sets of 1,000 lesions were randomly distributed throughout the lung for each respiratory phase. The simulations showed that the percentage of reachable lesions decreases with increasing tool diameter and decreasing lesion diameter. A 1mm diameter tool will reach <25% of 1cm lesions if it remains inside the airways. To reach all 1cm lesions this 1mm tool would have to navigate through the parenchyma up to 8.5mm. CT scans of 21 patient lesions confirm these results reasonably well. Conclusions The smaller the tool diameter the more likely it will be able to reach a lung lesion, whether it be for diagnostic biopsy, ablation, or resection. However, even a 1mm tool is not small enough to reach the majority of small (1-2cm) lesions. Therefore, it is necessary for endobronchial tools to be able to navigate through the parenchyma to reach the majority of lesions.Medical Instruments & Bio-Inspired Technolog

In vivo nerve identification in head and neck surgery using diffuse reflectance spectroscopy

Background: Careful identification of nerves during head and neck surgery is essential to prevent nerve damage. Currently, nerves are identified based on anatomy and appearance, optionally combined with electromyography (EMG). In challenging cases, nerve damage is reported in up to 50%. Recently, optical techniques, like diffuse reflectance spectroscopy (DRS) and fluorescence spectroscopy (FS) show potential to improve nerve identification. Methods: 212 intra-operative DRS/FS measurements were performed. Small nerve branches (1-3 mm), on near-nerve adipose tissue, muscle and subcutaneous fat were measured during 11 surgical procedures. Tissue identification was based on quantified concentrations of optical absorbers and scattering parameters. Results: Clinically comprehensive parameters showed significant differences (<0.05) between the tissues. Classification using k-Nearest Neighbor resulted in 100% sensitivity and a specificity of 83% (accuracy 91%), for the identification of nerve against surrounding tissues. Conclusions: DRS/FS is a potentially useful intraoperative tool for identification of nerves from adjacent tissues. Level of Evidence: Observational proof of principle study.Medical Instruments & Bio-Inspired Technolog

Nerve detection with optical spectroscopy for regional anesthesia procedures

BACKGROUND: Regional anesthesia has several advantages over general anesthesia but requires accurate needle placement to be effective. To achieve accurate placement, a needle equipped with optical fibers that allows tissue discrimination at the needle tip based on optical spectroscopy is proposed. This study investigates the sensitivity and specificity with which this optical needle can discriminate nerves from the surrounding tissues making use of different classification methods. METHODS: Diffuse reflectance spectra were acquired from 1563 different locations from 19 human cadavers in the wavelength range of 400–1710 nm; measured tissue types included fascicular tissue of the nerve, muscle, sliding fat and subcutaneous fat. Physiological parameters of the tissues were derived from the measured spectra and part of the data was directly compared to histology. Various classification methods were then applied to the derived parameter dataset to determine the accuracy with which fascicular tissue of the nerve can be discriminated from the surrounding tissues. RESULTS: From the parameters determined from the measured spectra of the various tissues surrounding the nerve, fat content, blood content, beta-carotene content and scattering were most distinctive when comparing fascicular and non-fascicular tissue. Support Vector Machine classification with a combination of feature selections performed best in discriminating fascicular nerve tissue from the surrounding tissues with a sensitivity and specificity around 90 %. CONCLUSIONS: This study showed that spectral tissue sensing, based on diffuse reflectance spectroscopy at the needle tip, is a promising technique to discriminate fascicular tissue of the nerve from the surrounding tissues. The technique may therefore improve accurate needle placement near the nerve which is necessary for effective nerve blocks in regional anesthesia

Depiction of how to calculate the off-road distance.

<p>The lesion is indicated by the red circle.</p

Percentage of lesions within reach of different sized tools if the tool remains inside the airways.

<p>Colors indicate the three simulated models (1- red, 2 –blue, 3 –green) and the type of line represents the targeted lesion diameter; black and gray are the CT data for lesions of 0.7–1.3cm and 1.7–2.3cm diameter respectively.</p

Distance a tool must travel off-road to reach a lesion in simulated model 1.

<p>The lines represent the average and standard deviations of the model. The black dots are the lesions measured from the CT scans.</p

Simulated airway model at expiration showing 2mm lesions as spheres distributed randomly throughout the lung.

<p>The different colored lesions represent the 3 repeated models (white = model 1; pink = model 2; yellow = model 3). Images were created in ParaView 4.3.1.</p