Objective: Detecting the cancerous growth margin and achieving a negative margin is one of the challenges that surgeons face during cancer procedures. A smart electrosurgical knife with integrated optical fibers has been designed previously to enable real-time use of diffuse reflectance spectroscopy for intraoperative margin assessment. In this paper, the thermal effect of the electrosurgical knife on tissue sensing is investigated. Methods: Porcine tissues and phantoms were used to investigate the performance of the smart electrosurgical knife after electrosurgery. The fat-to-water content ratio (F/W-ratio) served as the discriminative parameter for distinguishing tissues and tissue mimicking phantoms with varying fat content. The F/W-ratio of tissues and phantoms was measured with the smart electrosurgical knife before and after 14 minutes of electrosurgery. Additionally, a layered porcine tissue and phantom were sliced and measured from top to bottom with the smart electrosurgical knife. Results: Mapping the thermal activity of the electrosurgical knife's electrode during animal tissue electrosurgery revealed temperatures exceeding 400 °C. Electrosurgery for 14 minutes had no impact on the device's accurate detection of the F/W-ratio. The smart electrosurgical knife enables real-time tissue detection and predicts the fat content of the next layer from 4 mm ahead. Conclusion: The design of the smart electrosurgical knife outlined in this paper demonstrates its potential utility for tissue detection during electrosurgery. Significance: In the future, the smart electrosurgical knife could be a valuable intraoperative margin assessment tool, aiding surgeons in detecting tumor borders and achieving negative margins.

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Deep learning-based object detectors, while offering exceptional performance, are data-dependent and can suffer from generalization issues. In this work, we investigated deep neural networks for detecting people and medical instruments for the vision-based workflow analysis system inside Catheterization Laboratories (Cath Labs). The central problem explored in this paper is the fact that the performance of the detector can degrade drastically if it is trained and tested on data from different Cath Labs. Our research aimed to investigate the underlying causes of this specific performance degradation and find solutions to mitigate this issue. We employed the YOLOv8 object detector and created datasets from clinical procedures recorded at Reinier de Graaf Hospital (RdGG) and Philips Best Campus, supplemented with publicly accessible images. Through a series of experiments complemented by data visualization, we discovered that the performance degradation primarily stems from data distribution shifts in the feature space. Notably, the object detector trained on non-sensitive online images can generalize to unseen Cath Labs, outperforming the model trained on a procedure recording from a different Cath Lab. The detector trained on the online images achieved an [email protected] of 0.517 on the RdGG dataset. Furthermore, by switching to the most suitable camera for each object in the Cath Lab, the multi-camera system can further improve the detection performance significantly. An aggregated L-camera [email protected] of 0.679 is achieved for single-object classes on the RdGG dataset.

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Our research highlights the potential of Diffuse Reflectance Spectroscopy (DRS) in detecting cortical breaches during pedicle screw placement. We propose a sideways-looking fiber-optic probe, integrating diffuse light emission with both forward and sideways light collection. Experiments on an optical tissue phantom validate the probe’s potential to distinguish bone tissues and provide real-time guidance for spine surgery. Our findings prove that DRS with diffuse emission can detect perpendicular breaches, and demonstrate how the integration of a 45^◦ slanted fiber coated with gold enables parallel breach detection, advancing spine surgery by allowing for accurate pedicle screw placement.

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Diffuse Reflectance Spectroscopy (DRS) can provide tissue feedback for pedicle screw placement in spine surgery, yet the integration of fiber optics into the tip of the pedicle probe, a device used to pierce through bone, is challenging, since the optical probing depth and signal-to-noise ratio (SNR) are affected negatively compared to those of a blunt DRS probe. Through Monte Carlo simulations and optical phantom experiments, we show how differences in the shape of the instrument tip influence the acquired spectrum. Our findings demonstrate that a single bevel with an angle of 30∘ offers a solution to anticipate cortical breaches during pedicle screw placement. Compared to a blunt probe, the optical probing depth and SNR of a cone tip are reduced by 50%. The single bevel tip excels with 75% of the optical probing depth and a SNR remaining at approximately ⅔, facilitating the construction of a surgical instrument with integrated DRS.@en

In this paper, we aim to design an automatic camera pose estimation pipeline for clinical spaces such as catheterization laboratories. Our proposed pipeline exploits Scaled-YOLOv4 to detect fixed objects. We adopt the self-supervised key-point detector SuperPoint in combination with SuperGlue, a keypoint matching technique based on graph neural networks. Thus, we match key-points on input images with annotated reference points. Reference points are chosen on fixed objects in the scene, such as corners of door posts or windows. The point-correspondences between the image coordinates and the 3D coordinates are applied to the Perspective-n-Point algorithm to estimate the pose of each camera. Compared with other camera pose estimation methods, the proposed pipeline does not require the construction of 3D point-cloud model of the scene or placing a polyhedron object in the scene before each required calibration. Using videos from real procedures, we show that the pipeline can estimate the camera pose with high accuracy.@en

Introduction: Anastomotic leakage after gastrointestinal surgery has a high impact on patient's quality of life and its origin is associated with inadequate perfusion. Imaging photoplethysmography (iPPG) is a noninvasive imaging technique that measures blood-volume changes in the microvascular tissue bed and detects changes in tissue perfusion. Materials and methods: Intraoperative iPPG imaging was performed in 29 patients undergoing an open segment resection of the small intestine or colon. During each surgery, imaging was performed on fully perfused (true positives) and ischemic intestines (true negatives) and the anastomosis (unknowns). Imaging consisted of a 30-s video from which perfusion maps were extracted, providing detailed information about blood flow within the intestine microvasculature. To detect the predictive capabilities of iPPG, true positive and true negative perfusion conditions were used to develop two different perfusion classification methods. Results: iPPG-derived perfusion parameters were highly correlated with perfusion—perfused or ischemic—in intestinal tissues. A perfusion confidence map distinguished perfused and ischemic intestinal tissues with 96% sensitivity and 86% specificity. Anastomosis images were scored as adequately perfused in 86% of cases and 14% inconclusive. The cubic-Support Vector Machine achieved 90.9% accuracy and an area under the curve of 96%. No anastomosis-related postoperative complications were encountered in this study. Conclusions: This study shows that noninvasive intraoperative iPPG is suitable for the objective assessment of small intestine and colon anastomotic perfusion. In addition, two perfusion classification methods were developed, providing the first step in an intestinal perfusion prediction model.

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Accuracy in spinal fusion varies greatly depending on the experience of the physician. Real-time tissue feedback with diffuse reflectance spectroscopy has been shown to provide cortical breach detection using a conventional probe with two parallel fibers. In this study, Monte Carlo simulations and optical phantom experiments were conducted to investigate how angulation of the emitting fiber affects the probed volume to allow for the detection of acute breaches. Difference in intensity magnitude between cancellous and cortical spectra increased with the fiber angle, suggesting that outward angulated fibers are beneficial in acute breach scenarios. Proximity to the cortical bone could be detected best with fibers angulated at θf = 45° for impending breaches between θp = 0° and θp = 45°. An orthopedic surgical device comprising a third fiber perpendicular to the device axis could thus cover the full impending breach range from θp = 0° to θp = 90°.

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Background: Neurosurgical procedures are complex and require years of training and experience. Traditional training on human cadavers is expensive, requires facilities and planning, and raises ethical concerns. Therefore, the use of anthropomorphic phantoms could be an excellent substitute. The aim of the study was to design and develop a patient-specific 3D-skull and brain model with realistic CT-attenuation suitable for conventional and augmented reality (AR)-navigated neurosurgical simulations. Methods: The radiodensity of materials considered for the skull and brain phantoms were investigated using cone beam CT (CBCT) and compared to the radiodensities of the human skull and brain. The mechanical properties of the materials considered were tested in the laboratory and subsequently evaluated by clinically active neurosurgeons. Optimization of the phantom for the intended purposes was performed in a feedback cycle of tests and improvements. Results: The skull, including a complete representation of the nasal cavity and skull base, was 3D printed using polylactic acid with calcium carbonate. The brain was cast using a mixture of water and coolant, with 4 wt% polyvinyl alcohol and 0.1 wt% barium sulfate, in a mold obtained from segmentation of CBCT and T1 weighted MR images from a cadaver. The experiments revealed that the radiodensities of the skull and brain phantoms were 547 and 38 Hounsfield units (HU), as compared to real skull bone and brain tissues with values of around 1300 and 30 HU, respectively. As for the mechanical properties testing, the brain phantom exhibited a similar elasticity to real brain tissue. The phantom was subsequently evaluated by neurosurgeons in simulations of endonasal skull-base surgery, brain biopsies, and external ventricular drain (EVD) placement and found to fulfill the requirements of a surgical phantom. Conclusions: A realistic and CT-compatible anthropomorphic head phantom was designed and successfully used for simulated augmented reality-led neurosurgical procedures. The anatomic details of the skull base and brain were realistically reproduced. This phantom can easily be manufactured and used for surgical training at a low cost. @en

During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice.

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Glial tumors grow diffusely in the brain. Survival is correlated to the extent of tumor removal, but tumor borders are often invisible. Resection beyond the borders as defined by conventional methods may further improve prognosis. In this proof-of-concept study, we evaluate diffuse reflectance spectroscopy (DRS) for discrimination between glial tumors and normal brain ex vivo. DRS spectra and histology were acquired from 22 tumor samples and nine brain tissue samples retrieved from 30 patients. The content of biological chromophores and scattering features were estimated by fitting a model derived from diffusion theory to the DRS spectra. DRS parameters differed significantly between tumor and normal brain tissue. Classification using random forest yielded a sensitivity and specificity for the detection of low-grade gliomas of 82.0% and 82.7%, respectively, and the area under curve (AUC) was 0.91. Applied in a hand-held probe or biopsy needle, DRS has the potential to provide intra-operative tissue analysis.

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Emerging intraoperative tumor margin assessment techniques require the development of more complex and reliable organ phantoms to assess the performance of the technique before its translation into the clinic. In this work, electrically conductive tissue-mimicking materials (TMMs) based on fat, water and agar/gelatin were produced with tunable optical properties. The composition of the phantoms allowed for the assessment of tumor margins using diffuse reflectance spectroscopy, as the fat/water ratio served as a discriminating factor between the healthy and malignant tissue. Moreover, the possibility of using polyvinyl alcohol (PVA) or transglutaminase in combination with fat, water and gelatin for developing TMMs was studied. The diffuse spectral response of the developed phantom materials had a good match with the spectral response of porcine muscle and adipose tissue, as well as in vitro human breast tissue. Using the developed recipe, anatomically relevant heterogeneous breast phantoms representing the optical properties of different layers of the human breast were fabricated using 3D-printed molds. These TMMs can be used for further development of phantoms applicable for simulating the realistic breast conserving surgery workflow in order to evaluate the intraoperative optical-based tumor margin assessment techniques during electrosurgery.

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Surgical excision is the golden standard for treatment of intestinal tumors. In this surgical procedure, inadequate perfusion of the anastomosis can lead to postoperative complications, such as anastomotic leakages. Imaging photoplethysmography (iPPG) can potentially provide objective and real-time feedback of the perfusion status of tissues. This feasibility study aims to evaluate an iPPG acquisition system during intestinal surgeries to detect the perfusion levels of the microvasculature tissue bed in different perfusion conditions. This feasibility study assesses three patients that underwent resection of a portion of the small intestine. Data was acquired from fully perfused, non-perfused and anastomosis parts of the intestine during different phases of the surgical procedure. Strategies for limiting motion and noise during acquisition were implemented. iPPG perfusion maps were successfully extracted from the intestine microvasculature, demonstrating that iPPG can be successfully used for detecting perturbations and perfusion changes in intestinal tissues during surgery. This study provides proof of concept for iPPG to detect changes in organ perfusion levels.

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Introduction: Disposable instruments in healthcare have led to a significant increase of medical waste. The aim of this study is to validate the recycling of disposable Zamak laryngoscope blades into new medical products by using a new ‘all-in-one’ affordable reprocessing setup as alternative for die-casting.
Methods: An “all-in-one” casting set-up was designed and built. Laryngoscope blades, recovered from two hospitals, were disinfected, melted and casted into dog-bones and into new instrument parts. The quality of the casted material was evaluated using X-ray fluorescence spectrometry. The mechanical properties were obtained by assessing the Ultimate Tensile Strength (UTS) and tensile tests.
Results: A recovery of 93% Zamak was obtained using a melting temperature of 420 0C for three hours. The XRF Spectro data showed higher Zinc and silicon concentrations when compared with Virgin Zamak. The dog-bones tests resulted in an average UTS, Yield Strength (YS) and Young’s Modulus (YM) of 236 ±61 (MPa), 70 ±43 and 9 ±3, respectively, representing 82%, 103% and 64% of the UTS, YS and YM of standard Zamak. Functional instrument parts with extensions and inner chambers were casted with a maximal shrinkage percentage of 1±1%.
Discussion: This study demonstrates that the created “all-in-one” reprocessing method can process contaminated disposable Zamak laryngoscope blades into new raw base material and new instrument parts. Although material and surface properties can deteriorate, reprocessed Zamak still has sufficient mechanical properties and can be used to cast complex parts with sufficient dimensional tolerances and minimal shrinkage.
Conclusion: A circular micro reprocessing method was designed and used to turn disposed laryngoscope blades into new basis material and semi-finished products. Follow up studies are needed to scale and optimize this process towards a functional alternative for die casting. It should be further investigated how this process can contribute to further medical waste reduction and a circular healthcare economy.@en

The most important prognostic factor for the survival of advanced-stage epithelial ovarian cancer (EOC) is the completeness of cytoreductive surgery (CRS). Therefore, an intraoperative technique to detect microscopic tumors would be of great value. The aim of this pilot study is to assess the feasibility of near-infrared hyperspectral imaging (HSI) for EOC detection in ex vivo tissue samples. Images were collected during CRS in 11 patients in the wavelength range of 665–975 nm, and processed by calibration, normalization, and noise filtering. A linear support vector machine (SVM) was employed to classify healthy and tumorous tissue (defined as >50% tumor cells). Classifier performance was evaluated using leave-one-out cross-validation. Images of 26 tissue samples from 10 patients were included, containing 26,446 data points that were matched to histopathology. Tumorous tissue could be classified with an area under the curve of 0.83, a sensitivity of 0.81, a specificity of 0.70, and Matthew’s correlation coefficient of 0.41. This study paves the way to in vivo and intraoperative use of HSI during CRS. Hyperspectral imaging can scan a whole tissue surface in a fast and non-contact way. Our pilot study demonstrates that HSI and SVM learning can be used to discriminate EOC from surrounding tissue. @en

Introduction: Steering light is relevant to many medical applications that require tissue illumination, sensing, or modification. To control the propagation direction of light beams, a great variety of innovative fiber-optic medical devices have been designed. Areas covered: This review provides a comprehensive overview of the patent literature on light beam control in fiber-optic medical devices. The Web of Science Derwent Innovation Index database was scanned, and 81 patents on fiber-optic devices published in the last 20 years (2001–2021) were retrieved and categorized based on the working principle to steer light (refraction/reflection, scattering, diffraction) and the design strategy that was employed (within fiber, at fiber end, outside fiber). Expert opinion: Patents describing medical devices were found for all categories, except for generating diffraction at the fiber end surface. The insight in the different designs reveals that there are still several opportunities to design innovative devices that can collect light at an angle off-axis, reduce the angular distribution of light, or split light into multiple beams.

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Distinguishing the diseased breast tissue from the healthy tissue is a sorely challenging task for the surgeons during breast conserving surgery (BCS) as both tissues own relatively similar visual and haptic characteristics. It has been shown that diffused reflectance spectroscopy (DRS) has the potential to be used as a real-time tumor margin detection technique during BCS. In this research, an electrosurgical knife is equipped with fiber-based DRS sensing to provide the surgeon with real-time oncological guidance during BCS. To prevent overheating of the fibers, they were placed inside quartz tubes which were mounted on the electrosurgical knife. The effect of using quartz tubes and debris formation during electrosurgery on the DRS measurements on porcine tissue was investigated. Furthermore to investigate the performance of the new device, a heterogeneous breast phantom representing optical properties and anatomical shape of the real breast was developed. The new device was then used to cut through the phantom’s layers to assess the performance of the new knife while cutting. Finally, a BCS was performed on the phantom using the new knife without receiving visual and haptic feedback from the tissue. The results show that both using the quartz tubes and the formed debris do not have a significant effect on the DRS output. Moreover, the DRS outputs obtained during cutting the layered phantom showed the transition between the layers clearly, demonstrating that the cutting effect on the phantom tissue does not significantly affect the measurements . The X-ray images from the phantom before and after BCS using the new device confirmed the complete resection of the tumors from the breast phantom. The results indicate that the electrosurgical knife equipped with DRS is a promising technique for simultaneously distinguishing and cutting the tissue, and assessing real-time tumor margins during BCS.

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Establishing adequate resection margins during colorectal cancer surgery is challenging. Currently, in up to 30% of the cases the tumor is not completely removed, which emphasizes the lack of a real-time tissue discrimination tool that can assess resection margins up to multiple millimeters in depth. Therefore, we propose to combine spectral data from diffuse reflectance spectroscopy (DRS) with spatial information from ultrasound (US) imaging to evaluate multi-layered tissue structures. First, measurements with animal tissue were performed to evaluate the feasibility of the concept. The phantoms consisted of muscle and fat layers, with a varying top layer thickness of 0-10 mm. DRS spectra of 250 locations were obtained and corresponding US images were acquired. DRS features were extracted using the wavelet transform. US features were extracted based on the graph theory and first-order gradient. Using a regression analysis and combined DRS and US features, the top layer thickness was estimated with an error of up to 0.48 mm. The tissue types of the first and second layers were classified with accuracies of 0.95 and 0.99 respectively, using a support vector machine model.

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Background: Although the incidence of positive resection margins in breast-conserving surgery has decreased, both incomplete resection and unnecessary large resections still occur. This is especially the case in the surgical treatment of ductal carcinoma in situ (DCIS). Diffuse reflectance spectroscopy (DRS), an optical technology based on light tissue interactions, can potentially characterize tissue during surgery thereby guiding the surgeon intraoperatively. DRS has shown to be able to discriminate pure healthy breast tissue from pure invasive carcinoma (IC) but limited research has been done on (1) the actual optical characteristics of DCIS and (2) the ability of DRS to characterize measurements that are a mixture of tissue types. Methods: In this study, DRS spectra were acquired from 107 breast specimens from 107 patients with proven IC and/or DCIS (1488 measurement locations). With a generalized estimating equation model, the differences between the DRS spectra of locations with DCIS and IC and only healthy tissue were compared to see if there were significant differences between these spectra. Subsequently, different classification models were developed to be able to predict if the DRS spectrum of a measurement location represented a measurement location with “healthy” or “malignant” tissue. In the development and testing of the models, different definitions for “healthy” and “malignant” were used. This allowed varying the level of homogeneity in the train and test data. Results: It was found that the optical characteristics of IC and DCIS were similar. Regarding the classification of tissue with a mixture of tissue types, it was found that using mixed measurement locations in the development of the classification models did not tremendously improve the accuracy of the classification of other measurement locations with a mixture of tissue types. The evaluated classification models were able to classify measurement locations with > 5% malignant cells with a Matthews correlation coefficient of 0.41 or 0.40. Some models showed better sensitivity whereas others had better specificity. Conclusion: The results suggest that DRS has the potential to detect malignant tissue, including DCIS, in healthy breast tissue and could thus be helpful for surgical guidance.

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Peripheral Artery Diseases (PAD) are caused by the occlusions of arteries in the peripheral locations of the circulatory system. The severity of PAD is usually assessed using the Ankle Brachial Index (ABI) and the Ultrasound Doppler. Non-contact Photoplethysmography (PPG) imaging is a recent emerging technology capable of monitoring skin perfusion. Using an off-The-shelf camera and a light source, is possible to remotely detect the dynamic changes in blood volume in the skin and derive a map correlated to the blood perfusion. The aim of this study is the evaluation of a PPG imaging system (iPPG) for the assessment of Peripheral Arterial Diseases. Reduced blood flow is simulated on 21 volunteers by increasing the pressure in a pressure cuff. For each volunteer, measurements with iPPG, ultrasound, Laser Speckle Contrast Analysis (LASCA) and ABI were acquired. Our experiments show that iPPG can detect reduced perfusion levels, and correlates well with the other measurement systems.

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OBJECTIVE The aim of this study was to evaluate the accuracy (deviation from the target or intended path) and efficacy (insertion time) of an augmented reality surgical navigation (ARSN) system for insertion of biopsy needles and external ventricular drains (EVDs), two common neurosurgical procedures that require high precision. METHODS The hybrid operating room-based ARSN system, comprising a robotic C-arm with intraoperative conebeam CT (CBCT) and integrated video tracking of the patient and instruments using nonobtrusive adhesive optical markers, was used. A 3D-printed skull phantom with a realistic gelatinous brain model containing air-filled ventricles and 2-mm spherical biopsy targets was obtained. After initial CBCT acquisition for target registration and planning, ARSN was used for 30 cranial biopsies and 10 EVD insertions. Needle positions were verified by CBCT. RESULTS The mean accuracy of the biopsy needle insertions (n = 30) was 0.8 mm ± 0.43 mm. The median path length was 39 mm (range 16-104 mm) and did not correlate to accuracy (p = 0.15). The median device insertion time was 149 seconds (range 87-233 seconds). The mean accuracy for the EVD insertions (n = 10) was 2.9 mm ± 0.8 mm at the tip with a 0.7° ± 0.5° angular deviation compared with the planned path, and the median insertion time was 188 seconds (range 135-400 seconds). CONCLUSIONS This study demonstrated that ARSN can be used for navigation of percutaneous cranial biopsies and EVDs with high accuracy and efficacy.

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