Fluorescence guided surgery imaging systems for breast cancer identification: a systematic review.

Significance: Breast-conserving surgery (BCS) is limited by high rates of positive margins and re-operative interventions. Fluorescence-guided surgery seeks to detect the entire lesion in real time, thus guiding the surgeons to remove all the tumor at the index procedure. Aim: Our aim was to identify the optimal combination of a camera system and fluorophore for fluorescence-guided BCS. Approach: A systematic review of medical databases using the terms "fluorescence," "breast cancer," "surgery," and "fluorescence imaging" was performed. Cameras were compared using the ratio between the fluorescent signal from the tumor compared to background fluorescence, as well as diagnostic accuracy measures, such as sensitivity, specificity, and positive predictive value. Results: Twenty-one studies identified 14 camera systems using nine different fluorophores. Twelve cameras worked in the infrared spectrum. Ten studies reported on the difference in strength of the fluorescence signal between cancer and normal tissue, with results ranging from 1.72 to 4.7. In addition, nine studies reported on whether any tumor remained in the resection cavity (5.4% to 32.5%). To date, only three studies used the fluorescent signal for guidance during real BCS. Diagnostic accuracy ranged from 63% to 98% sensitivity, 32% to 97% specificity, and 75% to 100% positive predictive value. Conclusion: In this systematic review, all the studies reported a clinically significant difference in signal between the tumor and normal tissue using various camera/fluorophore combinations. However, given the heterogeneity in protocols, including camera setup, fluorophore studied, data acquisition, and reporting structure, it was impossible to determine the optimal camera and fluorophore combination for use in BCS. It would be beneficial to develop a standardized reporting structure using similar metrics to provide necessary data for a comparison between camera systems.

Novel Techniques in Microscopy: introduction to the feature issue.

The editors introduce the feature issue on "Novel Techniques in Microscopy," which was the topic of a symposium held on April 24-27, 2023, in Vancouver, BC. This symposium was part of the Optics in the Life Sciences Congress.

Monoclonal Antibodies for Targeted Fluorescence-Guided Surgery: A Review of Applicability across Multiple Solid Tumors.

This study aims to review the status of the clinical use of monoclonal antibodies (mAbs) that have completed or are in ongoing clinical trials for targeted fluorescence-guided surgery (T-FGS) for the intraoperative identification of the tumor margins of extra-hematological solid tumors. For each of them, the targeted antigen, the mAb generic/commercial name and format, and clinical indications are presented, together with utility, doses, and the timing of administration. Based on the current scientific evidence in humans, the top three mAbs that could be prepared in a GMP-compliant bank ready to be delivered for surgical purposes are proposed to speed up the translation to the operating room and produce a few readily available "off-the-shelf" injectable fluorescent probes for safer and more effective solid tumor resection.

Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment.

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. The authors 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 were 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.

A YOLOv5-based network for the detection of a diffuse reflectance spectroscopy probe to aid surgical guidance in gastrointestinal cancer surgery.

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.

Suppression of Ah Receptor (AhR) increases the aggressiveness of TNBC cells and 11-Cl-BBQ-activated AhR inhibits their growth.

Triple-negative breast cancer (TNBC) represents around 15% of the 2.26 million breast cancers diagnosed worldwide annually and has the worst outcome. Despite recent therapeutic advances, there remains a lack of targeted therapies for this breast cancer subtype. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor with biological roles in regulating development, xenobiotic metabolism, cell cycle progression and cell death. AhR activation by select ligands can promote tumor suppression in multiple cancer types. AhR can negatively regulate the activity of different oncogenic signaling pathways and can directly upregulate tumor suppressor genes such as p27Kip1. To determine the role of AhR in TNBC, we generated AhR-deficient cancer cells and investigated the impact of AhR loss on TNBC cell growth phenotypes. We found that AhR-deficient MDA-MB-468 TNBC cells have increased proliferation and formed significantly more colonies compared to AhR expressing cells. These cells without AhR expression grew aggressively in vivo. To determine the molecular targets driving this phenotype, we performed transcriptomic profiling in AhR expressing and AhR knockout MDA-MB-468 cells and identified tyrosine receptor kinases, as well as other genes involved in proliferation, survival and clonogenicity that are repressed by AhR. In order to determine therapeutic targeting of AhR in TNBC, we investigated the anti-cancer effects of the novel AhR ligand 11-chloro-7H-benzimidazo[2,1-a]benzo[de]iso-quinolin-7-one (11-Cl-BBQ), which belongs to a class of high affinity, rapidly metabolized AhR ligands called benzimidazoisoquinolines (BBQs). 11-Cl-BBQ induced AhR-dependent cancer cell-selective growth inhibition and strongly inhibited colony formation in TNBC cells.

Induction of Aryl Hydrocarbon Receptor-Mediated Cancer Cell-Selective Apoptosis in Triple-Negative Breast Cancer Cells by a High-Affinity Benzimidazoisoquinoline.

Triple-negative breast cancer (TNBC) remains a disease with a paucity of targeted treatment opportunities. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that is involved in a wide range of physiological processes, including the sensing of xenobiotics, immune function, development, and differentiation. Different small-molecule AhR ligands drive strikingly varied cellular and organismal responses. In certain cancers, AhR activation by select small molecules induces cell cycle arrest or apoptosis via activation of tumor-suppressive transcriptional programs. AhR is expressed in triple-negative breast cancers, presenting a tractable therapeutic opportunity. Here, we identify a novel ligand of the aryl hydrocarbon receptor that potently and selectively induces cell death in triple-negative breast cancer cells and TNBC stem cells via the AhR. Importantly, we found that this compound, Analog 523, exhibits minimal cytotoxicity against multiple normal human primary cells. Analog 523 represents a high-affinity AhR ligand with potential for future clinical translation as an anticancer agent.

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.

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.

Tumor-Suppressive Functions of the Aryl Hydrocarbon Receptor (AhR) and AhR as a Therapeutic Target in Cancer.

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor involved in regulating a wide range of biological responses. A diverse array of xenobiotics and endogenous small molecules bind to the receptor and drive unique phenotypic responses. Due in part to its role in mediating toxic responses to environmental pollutants, AhR activation has not been traditionally viewed as a viable therapeutic approach. Nonetheless, the expression and activation of AhR can inhibit the proliferation, migration, and survival of cancer cells, and many clinically approved drugs transcriptionally activate AhR. Identification of novel select modulators of AhR-regulated transcription that promote tumor suppression is an active area of investigation. The development of AhR-targeted anticancer agents requires a thorough understanding of the molecular mechanisms driving tumor suppression. Here, we summarized the tumor-suppressive mechanisms regulated by AhR with an emphasis on the endogenous functions of the receptor in opposing carcinogenesis. In multiple different cancer models, the deletion of AhR promotes increased tumorigenesis, but a precise understanding of the molecular cues and the genetic targets of AhR involved in this process is lacking. The intent of this review was to synthesize the evidence supporting AhR-dependent tumor suppression and distill insights for development of AhR-targeted cancer therapeutics.

Surgical polarimetric endoscopy for the detection of laryngeal cancer.

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 retardance and depolarization, 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 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.

Introduction to the Biophotonics Congress 2022 feature issue.

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.

11-Cl-BBQ, a select modulator of AhR-regulated transcription, suppresses lung cancer cell growth via activation of p53 and p27Kip1.

Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor and functions as a tumour suppressor in different cancer models. In the present study, we report detailed characterization of 11-chloro-7H-benzimidazo[2,1-a]benzo[de]iso-quinolin-7-one (11-Cl-BBQ) as a select modulator of AhR-regulated transcription (SMAhRT) with anti-cancer actions. Treatment of lung cancer cells with 11-Cl-BBQ induced potent and sustained AhR-dependent anti-proliferative effects by promoting G1 phase cell cycle arrest. Investigation of 11-Cl-BBQ-induced transcription in H460 cells with or without the AhR expression by RNA-sequencing revealed activation of p53 signalling. In addition, 11-Cl-BBQ suppressed multiple pathways involved in DNA replication and increased expression of cyclin-dependent kinase inhibitors, including p27Kip1 , in an AhR-dependent manner. CRISPR/Cas9 knockout of individual genes revealed the requirement for both p53 and p27Kip1 for the AhR-mediated anti-proliferative effects. Our results identify 11-Cl-BBQ as a potential lung cancer therapeutic, highlight the feasibility of targeting AhR and provide important mechanistic insights into AhR-mediated-anticancer actions.

Real-time Tracking and Classification of Tumor and Nontumor Tissue in Upper Gastrointestinal Cancers Using Diffuse Reflectance Spectroscopy for Resection Margin Assessment.

Importance: Cancers of the upper gastrointestinal tract remain a major contributor to the global cancer burden. The accurate mapping of tumor margins is of particular importance for curative cancer resection and improvement in overall survival. Current mapping techniques preclude a full resection margin assessment in real time. Objective: To evaluate whether diffuse reflectance spectroscopy (DRS) on gastric and esophageal cancer specimens can differentiate tissue types and provide real-time feedback to the operator. Design, Setting, and Participants: This was a prospective ex vivo validation study. Patients undergoing esophageal or gastric cancer resection were prospectively recruited into the study between July 2020 and July 2021 at Hammersmith Hospital in London, United Kingdom. Tissue specimens were included for patients undergoing elective surgery for either esophageal carcinoma (adenocarcinoma or squamous cell carcinoma) or gastric adenocarcinoma. Exposures: A handheld DRS probe and tracking system was used on freshly resected ex vivo tissue to obtain spectral data. Binary classification, following histopathological validation, was performed using 4 supervised machine learning classifiers. Main Outcomes and Measures: Data were divided into training and testing sets using a stratified 5-fold cross-validation method. Machine learning classifiers were evaluated in terms of sensitivity, specificity, overall accuracy, and the area under the curve. Results: Of 34 included patients, 22 (65%) were male, and the median (range) age was 68 (35-89) years. A total of 14 097 mean spectra for normal and cancerous tissue were collected. For normal vs cancer tissue, the machine learning classifier achieved a mean (SD) overall diagnostic accuracy of 93.86% (0.66) for stomach tissue and 96.22% (0.50) for esophageal tissue and achieved a mean (SD) sensitivity and specificity of 91.31% (1.5) and 95.13% (0.8), respectively, for stomach tissue and of 94.60% (0.9) and 97.28% (0.6) for esophagus tissue. Real-time tissue tracking and classification was achieved and presented live on screen. Conclusions and Relevance: This study provides ex vivo validation of the DRS technology for real-time differentiation of gastric and esophageal cancer from healthy tissue using machine learning with high accuracy. As such, it is a step toward the development of a real-time in vivo tumor mapping tool for esophageal and gastric cancers that can aid decision-making of resection margins intraoperatively.

Simultaneous Depth Estimation and Surgical Tool Segmentation in Laparoscopic Images.

Surgical instrument segmentation and depth estimation are crucial steps to improve autonomy in robotic surgery. Most recent works treat these problems separately, making the deployment challenging. In this paper, we propose a unified framework for depth estimation and surgical tool segmentation in laparoscopic images. The network has an encoder-decoder architecture and comprises two branches for simultaneously performing depth estimation and segmentation. To train the network end to end, we propose a new multi-task loss function that effectively learns to estimate depth in an unsupervised manner, while requiring only semi-ground truth for surgical tool segmentation. We conducted extensive experiments on different datasets to validate these findings. The results showed that the end-to-end network successfully improved the state-of-the-art for both tasks while reducing the complexity during their deployment.

Self-supervised Monocular Depth Estimation with 3D Displacement Module for Laparoscopic Images.

We present a novel self-supervised training framework with 3D displacement (3DD) module for accurately estimating per-pixel depth maps from single laparoscopic images. Recently, several self-supervised learning based monocular depth estimation models have achieved good results on the KITTI dataset, under the hypothesis that the camera is dynamic and the objects are stationary, however this hypothesis is often reversed in the surgical setting (laparoscope is stationary, the surgical instruments and tissues are dynamic). Therefore, a 3DD module is proposed to establish the relation between frames instead of ego-motion estimation. In the 3DD module, a convolutional neural network (CNN) analyses source and target frames to predict the 3D displacement of a 3D point cloud from a target frame to a source frame in the coordinates of the camera. Since it is difficult to constrain the depth displacement from two 2D images, a novel depth consistency module is proposed to maintain depth consistency between displacement-updated depth and model-estimated depth to constrain 3D displacement effectively. Our proposed method achieves remarkable performance for monocular depth estimation on the Hamlyn surgical dataset and acquired ground truth depth maps, outperforming monodepth, monodepth2 and packnet models.

The cyclin-dependent kinase inhibitor p27Kip1 interacts with the aryl hydrocarbon receptor and negatively regulates its transcriptional activity.

p27Kip1 functions to coordinate cell cycle progression through the inhibition of cyclin-dependent kinase (CDK) complexes. p27Kip1 also exerts distinct activities beyond CDK-inhibition, including functioning as a transcriptional regulator. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor with diverse biological roles. The regulatory inputs that control AhR-mediated transcriptional responses are an active area of investigation. AhR was previously established as a direct regulator of p27Kip1 transcription. Here, we report the physical interaction of AhR and p27Kip1 and show that p27Kip1 expression negatively regulates AhR-mediated transcription. p27Kip1 knockout cells display increased AhR nuclear localisation and significantly higher expression of AhR target genes. This work thus identifies new regulatory cross-talk between p27Kip1 and AhR.

Leveraging a High-Throughput Screening Method to Identify Mechanisms of Individual Susceptibility Differences in a Genetically Diverse Zebrafish Model.

Understanding the mechanisms behind chemical susceptibility differences is key to protecting sensitive populations. However, elucidating gene-environment interactions (GxE) presents a daunting challenge. While mammalian models have proven useful, problems with scalability to an enormous chemical exposome and clinical translation faced by all models remain; therefore, alternatives are needed. Zebrafish (Danio rerio) have emerged as an excellent model for investigating GxE. This study used a combined bioinformatic and experimental approach to probe the mechanisms underlying chemical susceptibility differences in a genetically diverse zebrafish population. Starting from high-throughput screening (HTS) data, a genome-wide association study (GWAS) using embryonic fish exposed to 0.6 µM Abamectin revealed significantly different effects between individuals. A hypervariable region with two distinct alleles-one with G at the SNP locus (GG) and one with a T and the 16 bp deletion (TT)-associated with differential susceptibility was found. Sensitive fish had significantly lower sox7 expression. Due to their location and the observed expression differences, we hypothesized that these sequences differentially regulate sox7. A luciferase reporter gene assay was used to test if these sequences, alone, could lead to expression differences. The TT allele showed significantly lower expression than the GG allele in MCF-7 cells. To better understand the mechanism behind these expression differences, predicted transcription factor binding differences between individuals were compared in silico, and several putative binding differences were identified. EMSA was used to test for binding differences in whole embryo protein lysate to investigate these TF binding predictions. We confirmed that the GG sequence is bound to protein in zebrafish. Through a competition EMSA using an untagged oligo titration, we confirmed that the GG oligo had a higher binding affinity than the TT oligo, explaining the observed expression differences. This study identified differential susceptibility to chemical exposure in a genetically diverse population, then identified a plausible mechanism behind those differences from a genetic to molecular level. Thus, an HTS-compatible zebrafish model is valuable and adaptable in identifying GxE mechanisms behind susceptibility differences to chemical exposure.

Polarization-based smoke removal method for surgical images.

Smoke generated during surgery affects tissue visibility and degrades image quality, affecting surgical decisions and limiting further image processing and analysis. Polarization is a fundamental property of light and polarization-resolved imaging has been studied and applied to general visibility restoration scenarios such as for smog or mist removal or in underwater environments. However, there is no related research or application for surgical smoke removal. Due to differences between surgical smoke and general haze scenarios, we propose an alternative imaging degradation model by redefining the form of the transmission parameters. The analysis of the propagation of polarized light interacting with the mixed medium of smoke and tissue is proposed to realize polarization-based smoke removal (visibility restoration). Theoretical analysis and observation of experimental data shows that the cross-polarized channel data generated by multiple scattering is less affected by smoke compared to the co-polarized channel. The polarization difference calculation for different color channels can estimate the model transmission parameters and reconstruct the image with restored visibility. Qualitative and quantitative comparison with alternative methods show that the polarization-based image smoke-removal method can effectively reduce the degradation of biomedical images caused by surgical smoke and partially restore the original degree of polarization of the samples.