503 results found
Nazarian S, Gkouzionis I, Murphy J, et al., 2024, Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment, International Journal of Surgery, ISSN: 1743-9159
Background: Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and poorer survival. We investigated diffuse reflectance spectroscopy (DRS) to distinguish tumour and non-tumour tissue in ex vivo colorectal specimens, to aid margin assessment and provide augmented visual maps to the surgeon in real-time.Methods: Patients undergoing elective colorectal cancer resection surgery at a London-based hospital were prospectively recruited. A hand-held DRS probe was used on the surface of freshly resected ex vivo colorectal tissue. Spectral data was acquired for tumour and non-tumour tissue. Binary classification was achieved using conventional machine learning classifiers and a convolutional neural network (CNN), which were evaluated in terms of sensitivity, specificity, accuracy and the area under the curve.Results: A total of 7692 mean spectra were obtained for tumour and non-tumour colorectal tissue. The CNN-based classifier was the best performing machine learning algorithm, when compared to contrastive approaches, for differentiating tumour and non-tumour colorectal tissue, with an overall diagnostic accuracy of 90.8% and area under the curve of 96.8%. Live on-screen classification of tissue type was achieved using a graduated colourmap.Conclusion: A high diagnostic accuracy for a DRS probe and tracking system to differentiate ex vivo tumour and non-tumour colorectal tissue in real-time with on-screen visual feedback was highlighted by this study. Further in vivo studies are needed to ensure integration into a surgical workflow.
Huang B, Hu Y, Nguyen A, et al., 2023, Detecting the sensing area of a laparoscopic probe in minimally invasive cancer surgery, MICCAI 2023, Publisher: Springer Nature Switzerland, Pages: 260-270, ISSN: 0302-9743
In surgical oncology, it is challenging for surgeons to identify lymph nodes and completely resect cancer even with pre-operative imaging systems like PET and CT, because of the lack of reliable intraoperative visualization tools. Endoscopic radio-guided cancer detection and resection has recently been evaluated whereby a novel tethered laparoscopic gamma detector is used to localize a preoperatively injected radiotracer. This can both enhance the endoscopic imaging and complement preoperative nuclear imaging data. However, gamma activity visualization is challenging to present to the operator because the probe is non-imaging and it does not visibly indicate the activity origination on the tissue surface. Initial failed attempts used segmentation or geometric methods, but led to the discovery that it could be resolved by leveraging high-dimensional image features and probe position information. To demonstrate the effectiveness of this solution, we designed and implemented a simple regression network that successfully addressed the problem. To further validate the proposed solution, we acquired and publicly released two datasets captured using a custom-designed, portable stereo laparoscope system. Through intensive experimentation, we demonstrated that our method can successfully and effectively detect the sensing area, establishing a new performance benchmark. Code and data are available at https://github.com/br0202/Sensing_area_detection.git.
Kedrzycki M, Elson D, Leff D, 2023, Guidance in breast-conserving surgery: tumour localization versus identification, British Journal of Surgery, Vol: 110, Pages: 920-922, ISSN: 0007-1323
In breast-conserving surgery (BCS), the tumour is removed with the goal of preserving as much healthy breast tissue as possible. Breast conservation comes with a risk of positive resection margins, an independent predictor of ipsilateral tumour recurrence, necessitating reoperation1. Contemporary data from the UK Get it Right First Time1 suggest high average reoperation rates of around 19 %. Current tumour localization techniques can only guide surgeons to the tumour epicentre, but fail to provide identification of the boundary between tumour and normal tissue. Imaging techniques, such as intraoperative ultrasonography (IOUS), intraoperative MRI (iMRI) or fluorescence-guided surgery (FGS), enable visualization of the tumour in its entirety and may provide improved operative precision2–5.
Qi J, Tatla T, Nissanka-Jayasuriya E, et al., 2023, Surgical polarimetric endoscopy for the detection of laryngeal cancer, Nature Biomedical Engineering, Vol: 7, Pages: 971-985, ISSN: 2157-846X
The standard-of-care for the detection of laryngeal pathologies involves distinguishing suspicious lesions from surrounding healthy tissue via contrasts in colour and texture captured by white-light endoscopy. However, the technique is insufficiently sensitive and thus leads to unsatisfactory rates of false negatives. Here, we show that laryngeal lesions can be better detected in real time by taking advantage of differences in the light-polarization properties of cancer and healthy tissues. By measuring differences in polarized-light reflectance, the technique, which we named ‘surgical polarimetric endoscopy’ (SPE), generates about one-order-of-magnitude greater contrast than white-light endoscopy, and hence allows for the better discrimination of cancerous lesions, as we show with patients diagnosed with squamous cell carcinoma. Polarimetric imaging of excised and stained slices of laryngeal tissue with SPE indicated that changes in the retardance of polarized light can be largely attributed to architectural features of the tissue. We also assessed SPE to aid routine transoral laser surgery for the removal of a cancerous lesion, indicating that SPE can complement white-light endoscopy for the detection of laryngeal cancer.
Gkouzionis I, Zhong Y, Nazarian S, et al., 2023, A YOLOv5-based network for the detection of a diffuse reflectance spectroscopy probe to aid surgical guidance in gastrointestinal cancer surgery, International Journal of Computer Assisted Radiology and Surgery, Vol: 19, ISSN: 1861-6410
PURPOSE: A positive circumferential resection margin (CRM) for oesophageal and gastric carcinoma is associated with local recurrence and poorer long-term survival. Diffuse reflectance spectroscopy (DRS) is a non-invasive technology able to distinguish tissue type based on spectral data. The aim of this study was to develop a deep learning-based method for DRS probe detection and tracking to aid classification of tumour and non-tumour gastrointestinal (GI) tissue in real time. METHODS: Data collected from both ex vivo human tissue specimen and sold tissue phantoms were used for the training and retrospective validation of the developed neural network framework. Specifically, a neural network based on the You Only Look Once (YOLO) v5 network was developed to accurately detect and track the tip of the DRS probe on video data acquired during an ex vivo clinical study. RESULTS: Different metrics were used to analyse the performance of the proposed probe detection and tracking framework, such as precision, recall, mAP 0.5, and Euclidean distance. Overall, the developed framework achieved a 93% precision at 23 FPS for probe detection, while the average Euclidean distance error was 4.90 pixels. CONCLUSION: The use of a deep learning approach for markerless DRS probe detection and tracking system could pave the way for real-time classification of GI tissue to aid margin assessment in cancer resection surgery and has potential to be applied in routine surgical practice.
Qi J, Tatla T, Nissanka-Jayasuriya E, et al., 2023, Publisher Correction: Surgical polarimetric endoscopy for the detection of laryngeal cancer., Nature Biomedical Engineering, Vol: 7, Pages: 1-1, ISSN: 2157-846X
Kedrzycki M, Leiloglou M, Shankthakumar D, et al., 2023, 5-ALA- induced Fluorescence for Tumor Visualization in Breast-conserving Surgery: Part 2 of the "GLOW" Study, 24th Annual Meeting of The American Society of Breast Surgeons (ASBrS), Publisher: SPRINGER, Pages: S475-S476, ISSN: 1068-9265
Kedrzycki M, Leiloglou M, Shankthakumar D, et al., 2023, Fluorescence and Multispectral Imaging in Breast-conserving Surgery - Proof of Concept Trial, 24th Annual Meeting of The American Society of Breast Surgeons (ASBrS), Publisher: SPRINGER, Pages: S447-S448, ISSN: 1068-9265
Shanthakumar D, Leiloglou M, Kelliher C, et al., 2023, A comparison of spectroscopy and imaging techniques utilizing spectrally resolved diffusely reflected light for intraoperative margin assessment in breast-conserving surgery: a systematic review and meta-analysis, Cancers, Vol: 15, ISSN: 2072-6694
Up to 19% of patients require re-excision surgery due to positive margins in breast-conserving surgery (BCS). Intraoperative margin assessment tools (IMAs) that incorporate tissue optical measurements could help reduce re-excision rates. This review focuses on methods that use and assess spectrally resolved diffusely reflected light for breast cancer detection in the intraoperative setting. Following PROSPERO registration (CRD42022356216), an electronic search was performed. The modalities searched for were diffuse reflectance spectroscopy (DRS), multispectral imaging (MSI), hyperspectral imaging (HSI), and spatial frequency domain imaging (SFDI). The inclusion criteria encompassed studies of human in vivo or ex vivo breast tissues, which presented data on accuracy. The exclusion criteria were contrast use, frozen samples, and other imaging adjuncts. 19 studies were selected following PRISMA guidelines. Studies were divided into point-based (spectroscopy) or whole field-of-view (imaging) techniques. A fixed-or random-effects model analysis generated pooled sensitivity/specificity for the different modalities, following heterogeneity calculations using the Q statistic. Overall, imaging-based techniques had better pooled sensitivity/specificity (0.90 (CI 0.76-1.03)/0.92 (CI 0.78-1.06)) compared with probe-based techniques (0.84 (CI 0.78-0.89)/0.85 (CI 0.79-0.91)). The use of spectrally resolved diffusely reflected light is a rapid, non-contact technique that confers accuracy in discriminating between normal and malignant breast tissue, and it constitutes a potential IMA tool.
Avila-Rencoret F, Mylonas G, Elson D, 2023, Robotic large-area optical biopsy imaging for automated detection of gastrointestinal cancers tested in tissue phantoms and ex vivo porcine bowel, Translational Biophotonics, Vol: 5, ISSN: 2627-1850
Gastrointestinal endoscopy is a subjective procedure that frequently requires tissue samples for diagnosis. Contact optical biopsy (OB) techniques have the aim of providing direct diagnosis of endoscopic areas without excising tissue samples but lack the wide-area coverage required for locating and resecting lesions. This article presents a large-area robotically deployed OB imaging platform for endoscopic detection of colorectal cancer as an add-on for conventional endoscopes. In vitro, in silicon colon phantoms, the platform achieves an optical resolution of 0.5 line pairs per millimeter, while resolving simulated cancer lesions down to 0.75 mm diameter across large-area images (55-103 cm2). Large-area OB images were generated in an ex vivo porcine colon. The platform allows centimeter-sized large-area OB imaging in vitro and ex vivo with submillimeter resolution, including automatic data segmentation of simulated cancer areas. The ability for robotic actuation and spectrum collection is also shown for ex vivo animal colon. If successful, this technology could widen access to user-independent high-quality endoscopy and early detection of gastrointestinal cancers.
Ford L, Chalau V, Naguleswaran A, et al., 2023, Feasibility Analysis of iEndoscope for Real-Time Data Driven Pathology Using Novel MS and Optical Technology, Mass Spectrometry and Advances in the Clinical Lab
Elson D, 2023, Minimally-invasive surgical application of multispectral and polarization resolved imaging, Advances in Optics for Biotechnology, Medicine and Surgery XVII
Nazarian S, Gkouzionis I, Darzi A, et al., 2023, Real-time Classification of Tumour and Non-tumour Colorectal Tissue using Diffuse Reflectance Spectroscopy to Aid Resection Margin Assessment, Digestive Diseases Week
Elson D, 2023, Endoscopic Polarization-Resolved Imaging, 3rd BIOAM-2023 workshop on Biophotonics and Optical Angular Momentum
Anichini G, Leiloglou M, Hu Z, et al., 2023, Intra-operative applications of optical imaging in neurosurgery: a developing field?, World Federation of Neurosurgical Societies
Anichini G, Hu Z, Gayo I, et al., 2023, Hyperspectral imaging for intra-operative characterisation of brain tumours, margins, and eloquent connectomes, World Federation of Neurosurgical Societies
Leiloglou M, Shanthakumar D, Gkouzionis I, et al., 2023, Investigation of multispectral imaging classification routines for intraoperative margin assessment in breast conserving surgery, European Conferences on Biomedical Optics
Gkouzionis I, Nazarian S, Patel N, et al., 2023, Diffuse reflectance spectroscopy for in-vivo stomach and oesophageal tissue classification during upper gastrointestinal cancer surgery, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XXI
Deng K, Huang B, Elson D, 2023, Deep Imitation Learning for Automated Drop-In Gamma Probe Manipulation, Hamlyn Symposium on Medical Robotics
Kedrzycki M, Leiloglou M, Shanthakumar D, et al., 2023, Fluorescence and Multispectral Imaging in Breast-conserving Surgery – Proof of Concept Trial, The American Society of Breast Surgeons 24th Annual Meeting
Kedrzycki M, Leiloglou M, Shanthakumar D, et al., 2023, 5-ALA-induced Fluorescence for Tumor Visualization in Breast-conserving Surgery: Part 2 of the “GLOW” Study, The American Society of Breast Surgeons 24th Annual Meeting
Shanthakumar D, Leiloglou M, Kelliher C, et al., 2023, Tissue optics for margin assessment in breast conserving surgery: Systematic review & meta-analysis, Association of Breast Surgery Conference
Shanthakumar D, Leiloglou M, Chalau V, et al., 2023, Intra-operative multispectral imaging for precision in breast conserving surgery, Association of Breast Surgery Conference
Gkouzionis I, Nazarian S, Darzi A, et al., 2023, Diffuse reflectance spectroscopy for tissue discrimination during in vivo upper gastrointestinal cancer surgery, European Conferences on Biomedical Opticsfd
Leiloglou M, Kedrzycki M, Chalau V, et al., 2023, 5-ALA induced fluorescence imaging for margin status identification during breast conserving surgery, Association of Breast Surgery Conference
Chon HTW, Kedrzycki M, Leiloglou M, et al., 2023, Fluorescence guided surgery imaging systems for breast cancer identification: A systematic review, Association of Breast Surgery Conference
Liu JTC, Bale G, Choe R, et al., 2023, Introduction to the Biophotonics Congress 2022 feature issue, Biomedical Optics Express, Vol: 14, Pages: 385-386, ISSN: 2156-7085
A feature issue is being presented by a team of guest editors containing papers based on studies presented at the Optica Biophotonics Congress: Biomedical Optics held on April 24–27, 2022 in Fort Lauderdale, Florida, USA.
Leiloglou M, Kedrzycki M, Shanthakumar D, et al., 2023, Fluorescence and multispectral imaging use for tumour identification in breast conserving surgery, Association of Breast Surgery Conference
Wang C, Cartucho J, Elson D, et al., 2022, Towards autonomous control of surgical instruments using adaptive-fusion tracking and robot self-calibration, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Publisher: IEEE, Pages: 2395-2401, ISSN: 2153-0858
The ability to track surgical instruments in realtime is crucial for autonomous Robotic Assisted Surgery (RAS). Recently, the fusion of visual and kinematic data has been proposed to track surgical instruments. However, these methods assume that both sensors are equally reliable, and cannot successfully handle cases where there are significant perturbations in one of the sensors' data. In this paper, we address this problem by proposing an enhanced fusion-based method. The main advantage of our method is that it can adjust fusion weights to adapt to sensor perturbations and failures. Another problem is that before performing an autonomous task, these robots have to be repetitively recalibrated by a human for each new patient to estimate the transformations between the different robotic arms. To address this problem, we propose a self-calibration algorithm that empowers the robot to autonomously calibrate the transformations by itself in the beginning of the surgery. We applied our fusion and selfcalibration algorithms for autonomous ultrasound tissue scanning and we showed that the robot achieved stable ultrasound imaging when using our method. Our performance evaluation shows that our proposed method outperforms the state-of-art both in normal and challenging situations.
Saebe A, Wiwatpanit T, Varatthan T, et al., 2022, Comparative study between the 3D‐liver spheroid models developed from HepG2 and immortalized hepatocyte‐like cells with primary hepatic stellate coculture for drug metabolism analysis and anticancer drug screening, Advanced Therapeutics, Vol: 6, Pages: 1-16, ISSN: 2366-3987
Liver spheroids may be the best alternative models for evaluating efficacy and toxicity of the new anticancer candidates and diagnostics for hepatocellular carcinoma (HCC). Here, novel 3D-liver spheroid models are constructed from human hepatoma cells (HepG2)/ immortalized human hepatocyte-like cells (imHCs) with primary hepatic stellate cells (HSCs) coculture using the ultralow attachment technique. Spheroid morphology, HSC distribution, metabolic activity, protein expressions, and drug penetration are evaluated. All developed 3D spheroid models exhibit in spherical shape with narrow size distribution, diameter between 639–743 (HepG2-10%HSC) and 519–631 (imHC-10%HSC) µm. Both imHC mono and coculture models significantly express normal liver biomarkers at the higher level than HepG2 models. While 3D-HepG2 models significantly exhibit HCC biomarkers at the higher level than imHC models. HepG2 and imHC spheroids express basal cytochrom P450 (CYP450) enzymes at different levels depending on cell types, culture period, and ratio of coculture. Their metabolic activities for dextromethorphan (CYP2D6) tolbutamide (CYP2C9) and midazolam (CYP3A4) are routinely evaluated. For midazolam metabolism, imHC models allow the detection of phase II metabolic enzymes (UGT2B4 and UGT2B7). The presence of HSC in HepG2-HSC model increases biological barrier for doxorubicin (DOX) penetration, and escalates IC50 of DOX from 61.4 to 127.2 µg mL−1.
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