Real-Time Visualization of Tissue Surface Biochemical Features Derived From Fluorescence Lifetime Measurements

Dual excitation spectral autofluorescence lifetime and reflectance imaging for fast macroscopic characterization of tissues

Advancements in optical imaging techniques have revolutionized the field of biomedical research, allowing for the comprehensive characterization of tissues and their underlying biological processes. Yet, there is still a lack of tools to provide quantitative and objective characterization of tissues that can aid clinical assessment in vivo to enhance diagnostic and therapeutic interventions. Here, we present a clinically viable fiber-based imaging system combining time-resolved spectrofluorimetry and reflectance spectroscopy to achieve fast multiparametric macroscopic characterization of tissues. An essential feature of the setup is its ability to perform dual wavelength excitation in combination with recording time-resolved fluorescence data in several spectral intervals. Initial validation of this bimodal system was carried out in freshly resected human colorectal cancer specimens, where we demonstrated the ability of the system to differentiate normal from malignant tissues based on their autofluorescence and reflectance properties. To further highlight the complementarity of autofluorescence and reflectance measurements and demonstrate viability in a clinically relevant scenario, we also collected in vivo data from the skin of a volunteer. Altogether, integration of these modalities in a single platform can offer multidimensional characterization of tissues, thus facilitating a deeper understanding of biological processes and potentially advancing diagnostic and therapeutic approaches in various medical applications.

Point Projection Mapping System for Tracking, Registering, Labeling, and Validating Optical Tissue Measurements

The validation of newly developed optical tissue-sensing techniques for tumor detection during cancer surgery requires an accurate correlation with the histological results. Additionally, such an accurate correlation facilitates precise data labeling for developing high-performance machine learning tissue-classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with the histopathology results is proposed and validated on a case study. The proposed framework provides a more-robust and accurate method for the tracking and validation of optical tissue-sensing techniques, which saves time and resources compared to the available conventional techniques.

Anatomy-Specific Classification Model Using Label-Free FLIm to Aid Intraoperative Surgical Guidance of Head and Neck Cancer

Intraoperative identification of head and neck cancer tissue is essential to achieve complete tumor resection and mitigate tumor recurrence. Mesoscopic fluorescence lifetime imaging (FLIm) of intrinsic tissue fluorophores emission has demonstrated the potential to demarcate the extent of the tumor in patients undergoing surgical procedures of the oral cavity and the oropharynx. Here, we report FLIm-based classification methods using standard machine learning models that account for the diverse anatomical and biochemical composition across the head and neck anatomy to improve tumor region identification. Three anatomy-specific binary classification models were developed (i.e., "base of tongue," "palatine tonsil," and "oral tongue"). FLIm data from patients (N = 85) undergoing upper aerodigestive oncologic surgery were used to train and validate the classification models using a leave-one-patient-out cross-validation method. These models were evaluated for two classification tasks: (1) to discriminate between healthy and cancer tissue, and (2) to apply the binary classification model trained on healthy and cancer to discriminate dysplasia through transfer learning. This approach achieved superior classification performance compared to models that are anatomy-agnostic; specifically, a ROC-AUC of 0.94 was for the first task and 0.92 for the second. Furthermore, the model demonstrated detection of dysplasia, highlighting the generalization of the FLIm-based classifier. Current findings demonstrate that a classifier that accounts for tumor location can improve the ability to accurately identify surgical margins and underscore FLIm's potential as a tool for surgical guidance in head and neck cancer patients, including those subjects of robotic surgery.

Handheld wide-field fluorescence lifetime imaging system based on a distally mounted SPAD array

In this work a handheld Fluorescent Lifetime IMaging (FLIM) system based on a distally mounted < 2 mm² 128 × 120 single photon avalanche diode (SPAD) array operating over a > 1 m long wired interface is demonstrated. The head of the system is ∼4.5 cm x 4.5 cm x 4.5 cm making it suitable for hand-held ex vivo applications. This is, to the best of the authors' knowledge, the first example of a SPAD array mounted on the distal end of a handheld FLIM system in this manner. All existing systems to date use a fibre to collect and relay fluorescent light to detectors at the proximal end of the system. This has clear potential biological and biomedical applications. To demonstrate this, the system is used to provide contrast between regions of differing tissue composition in ovine kidney samples, and between healthy and stressed or damaged plant leaves. Additionally, FLIM videos are provided showing that frame rates of > 1 Hz are achievable. It is thus an important step in realising an in vivo miniaturized chip-on-tip FLIM endoscopy system.

In vivo characterization of the human glioblastoma infiltrative edge with label-free intraoperative fluorescence lifetime imaging

Challenges in identifying a glioblastoma's infiltrative edge during neurosurgical procedures result in rapid recurrence. A label-free fluorescence lifetime imaging (FLIm) device was used to evaluate glioblastoma's infiltrative edge in vivo in 15 patients (89 samples). FLIm data were analyzed according to tumor cell density, infiltrating tissue type (gray and white matter), and diagnosis history (new or recurrent). Infiltrations in white matter from new glioblastomas showed decreasing lifetimes and a spectral red shift with increasing tumor cell density. Areas of high versus low tumor cell density were separated through a linear discriminant analysis with a ROC-AUC=0.74. Current results support the feasibility of intraoperative FLIm for real-time in vivo brain measurements and encourage refinement to predict glioblastoma infiltrative edge, underscoring the ability of FLIm to optimize neurosurgical outcomes.

Multimodal fluorescence lifetime imaging and optical coherence tomography for longitudinal monitoring of tissue-engineered cartilage maturation in a preclinical implantation model

Significance

Cartilage tissue engineering is a promising strategy for effective curative therapies for treatment of osteoarthritis. However, tissue engineers depend predominantly on time-consuming, expensive, and destructive techniques as quality control to monitor the maturation of engineered cartilage. This practice can be impractical for large-scale biomanufacturing and prevents spatial and temporal monitoring of tissue growth, which is critical for the fabrication of clinically relevant-sized cartilage constructs. Nondestructive multimodal imaging techniques combining fluorescence lifetime imaging (FLIm) and optical coherence tomography (OCT) hold great potential to address this challenge.

Aim

The feasibility of using multimodal FLIm-OCT for nondestructive, spatial, and temporal monitoring of self-assembled cartilage tissue maturation in a preclinical mouse model is investigated.

Approach

Self-assembled cartilage constructs were developed for 4 weeks in vitro followed by 4 weeks of in vivo maturation in nude mice. Sterile and nondestructive in situ multispectral FLIm and OCT imaging were carried out at multiple time points ( t = 2 , 4, and 8 weeks) during tissue development. FLIm and 3D volumetric OCT images were reconstructed and used for the analysis of tissue biochemical homogeneity, morphology, and structural integrity. A biochemical homogeneity index was computed to characterize nonhomogeneous tissue growth at different time points. OCT images were validated against histology.

Results

FLIm detects heterogenous extracellular matrix (ECM) growth of tissue-engineered cartilage. The outer edge of the tissue construct exhibited longer fluorescence lifetime in 375 to 410 and 450 to 485 nm spectral channels, indicating increase in collagen content. Significant ( p < 0.05 ) decrease of construct homogeneity index was observed between t = 2 weeks and t = 4 weeks. Both FLIm and OCT images revealed defects (voids) at the center of the tissue construct during in vitro culture ( t = 2 and 4 weeks). Cyst formation during in vivo culture was detected by OCT and confirmed with histology.

Conclusions

The ability of multimodal FLIm-OCT to nondestructively monitor the heterogenous growth of engineered tissue constructs in situ is demonstrated. Spatial and temporal variation of construct ECM component was detected by FLIm. OCT reveals structural defects (voids and cysts). This multimodal approach has great potential to replace costly destructive tests in the manufacturing of tissue-engineered medical products, facilitating their clinical translation.

Non-destructive, continuous monitoring of biochemical, mechanical, and structural maturation in engineered tissue

Regulatory guidelines for tissue engineered products require stringent characterization during production and necessitate the development of novel, non-destructive methods to quantify key functional parameters for clinical translation. Traditional assessments of engineered tissues are destructive, expensive, and time consuming. Here, we introduce a non-destructive, inexpensive, and rapid sampling and analysis system that can continuously monitor the mechanical, biochemical, and structural properties of a single sample over extended periods of time. The label-free system combines the imaging modalities of fluorescent lifetime imaging and ultrasound backscatter microscopy through a fiber-based interface for sterile monitoring of tissue quality. We tested the multimodal system using tissue engineered articular cartilage as an experimental model. We identified strong correlations between optical and destructive testing. Combining FLIm and UBM results, we created a novel statistical model of tissue homogeneity that can be applied to tissue engineered constructs prior to implantation. Continuous monitoring of engineered tissues with this non-destructive system has the potential for in-process monitoring of tissue engineered products, reducing costs and improving quality controls in research, manufacturing, and clinical applications.

Intraoperative delineation of p16+ oropharyngeal carcinoma of unknown primary origin with fluorescence lifetime imaging: Preliminary report

BACKGROUND

This study evaluated whether fluorescence lifetime imaging (FLIm), coupled with standard diagnostic workups, could enhance primary lesion detection in patients with p16+ head and neck squamous cell carcinoma of the unknown primary (HNSCCUP).

METHODS

FLIm was integrated into transoral robotic surgery to acquire optical data on six HNSCCUP patients' oropharyngeal tissues. An additional 55-patient FLIm dataset, comprising conventional primary tumors, trained a machine learning classifier; the output predicted the presence and location of HNSCCUP for the six patients. Validation was performed using histopathology.

RESULTS

Among the six HNSCCUP patients, p16+ occult primary was surgically identified in three patients, whereas three patients ultimately had no identifiable primary site in the oropharynx. FLIm correctly detected HNSCCUP in all three patients (ROC-AUC: 0.90 ± 0.06), and correctly predicted benign oropharyngeal tissue for the remaining three patients. The mean sensitivity was 95% ± 3.5%, and specificity 89% ± 12.7%.

CONCLUSIONS

FLIm may be a useful diagnostic adjunct for detecting HNSCCUP.

Fast Analysis of Time-Domain Fluorescence Lifetime Imaging via Extreme Learning Machine

We present a fast and accurate analytical method for fluorescence lifetime imaging microscopy (FLIM), using the extreme learning machine (ELM). We used extensive metrics to evaluate ELM and existing algorithms. First, we compared these algorithms using synthetic datasets. The results indicate that ELM can obtain higher fidelity, even in low-photon conditions. Afterwards, we used ELM to retrieve lifetime components from human prostate cancer cells loaded with gold nanosensors, showing that ELM also outperforms the iterative fitting and non-fitting algorithms. By comparing ELM with a computational efficient neural network, ELM achieves comparable accuracy with less training and inference time. As there is no back-propagation process for ELM during the training phase, the training speed is much higher than existing neural network approaches. The proposed strategy is promising for edge computing with online training.

Real-time molecular imaging of near-surface tissue using Raman spectroscopy

The steady progress in medical diagnosis and treatment of diseases largely hinges on the steady development and improvement of modern imaging modalities. Raman spectroscopy has attracted increasing attention for clinical applications as it is label-free, non-invasive, and delivers molecular fingerprinting information of a sample. In combination with fiber optic probes, it also allows easy access to different body parts of a patient. However, image acquisition with fiber optic probes is currently not possible. Here, we introduce a fiber optic probe-based Raman imaging system for the real-time molecular virtual reality data visualization of chemical boundaries on a computer screen and the physical world. The approach is developed around a computer vision-based positional tracking system in conjunction with photometric stereo and augmented and mixed chemical reality, enabling molecular imaging and direct visualization of molecular boundaries of three-dimensional surfaces. The proposed approach achieves a spatial resolution of 0.5 mm in the transverse plane and a topology resolution of 0.6 mm, with a spectral sampling frequency of 10 Hz, and can be used to image large tissue areas in a few minutes, making it highly suitable for clinical tissue-boundary demarcation. A variety of applications on biological samples, i.e., distribution of pharmaceutical compounds, brain-tumor phantom, and various types of sarcoma have been characterized, showing that the system enables rapid and intuitive assessment of molecular boundaries.

Mesoscopic fluorescence lifetime imaging: Fundamental principles, clinical applications and future directions

Fluorescence lifetime imaging (FLIm) is an optical spectroscopic imaging technique capable of real-time assessments of tissue properties in clinical settings. Label-free FLIm is sensitive to changes in tissue structure and biochemistry resulting from pathological conditions, thus providing optical contrast to identify and monitor the progression of disease. Technical and methodological advances over the last two decades have enabled the development of FLIm instrumentation for real-time, in situ, mesoscopic imaging compatible with standard clinical workflows. Herein, we review the fundamental working principles of mesoscopic FLIm, discuss the technical characteristics of current clinical FLIm instrumentation, highlight the most commonly used analytical methods to interpret fluorescence lifetime data and discuss the recent applications of FLIm in surgical oncology and cardiovascular diagnostics. Finally, we conclude with an outlook on the future directions of clinical FLIm.

Intraoperative Mapping of Parathyroid Glands Using Fluorescence Lifetime Imaging

BACKGROUND

Hypoparathyroidism is a common complication following thyroidectomy. There is a need for technology to aid surgeons in identifying the parathyroid glands. In contrast to near infrared technologies, fluorescence lifetime imaging (FLIm) is not affected by ambient light and may be valuable in identifying parathyroid tissue, but has never been evaluated in this capacity.

METHODS

We used FLIm to measure the UV induced (355 nm) time-resolved autofluorescence signatures (average lifetimes in 3 spectral emission channels) of thyroid, parathyroid, lymphoid and adipose tissue in 21 patients undergoing thyroid and parathyroid surgery. The Mann-Whitney U test was used to assess the ability of FLIm to discriminate normocellular parathyroid from each of the other tissues. Various machine learning classifiers (random forests, neural network, support vector machine) were then evaluated to recognize parathyroid through a leave-one-out cross-validation.

RESULTS

Statistically significant differences in average lifetime were observed between parathyroid and each of the other tissue types in spectral channels 2 and 3 respectively. The largest change was observed between adipose tissue and parathyroid (P < 0.001), while less pronounced but still significant changes were observed when comparing parathyroid with lymphoid tissue (P < 0.05) and thyroid (P < 0.01). A random forest classifier trained on average lifetimes was found to detect parathyroid tissue with 100% sensitivity and 93% specificity at the acquisition run level.

CONCLUSION

We found that FLIm derived parameters can distinguish the parathyroid glands and other adjacent tissue types and has promise in scanning the surgical field to identify parathyroid tissue in real-time.

Intraoperative Margin Assessment in Oral and Oropharyngeal Cancer Using Label-Free Fluorescence Lifetime Imaging and Machine Learning

OBJECTIVE

To demonstrate the diagnostic ability of label-free, point-scanning, fiber-based Fluorescence Lifetime Imaging (FLIm) as a means of intraoperative guidance during oral and oropharyngeal cancer removal surgery.

METHODS

FLIm point-measurements acquired from 53 patients (n = 67893 pre-resection in vivo, n = 89695 post-resection ex vivo) undergoing oral or oropharyngeal cancer removal surgery were used for analysis. Discrimination of healthy tissue and cancer was investigated using various FLIm-derived parameter sets and classifiers (Support Vector Machine, Random Forests, CNN). Classifier output for the acquired set of point-measurements was visualized through an interpolation-based approach to generate a probabilistic heatmap of cancer within the surgical field. Classifier output for dysplasia at the resection margins was also investigated.

RESULTS

Statistically significant change (P 0.01) between healthy and cancer was observed in vivo for the acquired FLIm signal parameters (e.g., average lifetime) linked with metabolic activity. Superior classification was achieved at the tissue region level using the Random Forests method (ROC-AUC: 0.88). Classifier output for dysplasia (% probability of cancer) was observed to lie between that of cancer and healthy tissue, highlighting FLIm's ability to distinguish various conditions.

CONCLUSION

The developed approach demonstrates the potential of FLIm for fast, reliable intraoperative margin assessment without the need for contrast agents.

SIGNIFICANCE

Fiber-based FLIm has the potential to be used as a diagnostic tool during cancer resection surgery, including Transoral Robotic Surgery (TORS), helping ensure complete resections and improve the survival rate of oral and oropharyngeal cancer patients.

The Role of Suspension Array Technology in Rapid Detection of Foodborne Pollutants: Applications and Future Challenges

Food safety is an important livelihood issue, which has always been focused attention by countries and governments all over the world. As food supply chains are becoming global, food quality control is essential for consumer protection as well as for the food industry. In recent years, a great part of food analysis is carried out using new techniques for rapid detection. As the first biochip technology that has been approved by the Food and Drug Administration (FDA), there is an increasing interest in suspension array technology (SAT) for food and environmental analysis with advantages of rapidity, high accuracy, sensitivity, and throughput. Therefore, it is important for researchers to understand the development and application of this technology in food industry. Herein, we summarized the principle and composition of SAT and its application in food safety monitoring. The utility of SAT in detection of foodborne microorganisms, residues of agricultural and veterinary drugs, genetically modified food and allergens in recent years is elaborated, and the further development direction of SAT is envisaged.

FLImBrush: dynamic visualization of intraoperative free-hand fiber-based fluorescence lifetime imaging

A free-hand scanning approach to medical imaging allows for flexible, lightweight probes to image intricate anatomies for modalities such as fluorescence lifetime imaging (FLIm), optical coherence tomography (OCT) and ultrasound. While very promising, this approach faces several key challenges including tissue motion during imaging, varying lighting conditions in the surgical field, and sparse sampling of the tissue surface. These challenges limit the coregistration accuracy and interpretability of the acquired imaging data. Here we report FLImBrush as a robust method for the localization and visualization of intraoperative free-hand fiber optic fluorescence lifetime imaging (FLIm). FLImBrush builds upon an existing method while employing deep learning-based image segmentation, block-matching based motion correction, and interpolation-based visualization to address the aforementioned challenges. Current results demonstrate that FLImBrush can provide accurate localization of FLIm point-measurements while producing interpretable and complete visualizations of FLIm data acquired from a tissue surface. Each of the main processing steps was shown to be capable of real-time processing (> 30 frames per second), highlighting the feasibility of FLImBrush for intraoperative imaging and surgical guidance. Current findings show the feasibility of integrating FLImBrush into a range of surgical applications including cancer margins assessment during head and neck surgery.

Development of a Robust Autofluorescence Lifetime Sensing Method for Use in an Endoscopic Application

Endoscopic autofluorescence lifetime imaging is a promising technique for making quantitative and non-invasive diagnoses of abnormal tissue. However, motion artifacts caused by vibration in the direction perpendicular to the tissue surface in a body makes clinical diagnosis difficult. Thus, this paper proposes a robust autofluorescence lifetime sensing technique with a lens tracking system based on a laser beam spot analysis. Our optical setup can be easily mounted on the head of an endoscope. The variation in distance between the optical system and the target surface is tracked by the change in the spot size of the laser beam captured by the camera, and the lens actuator is feedback-controlled to suppress motion artifacts. The experimental results show that, when using a lens tracking system, the standard deviation of fluorescence lifetime is dramatically reduced. Furthermore, the validity of the proposed method is experimentally confirmed by using a bio-mimicking phantom that replicates the shape, optical parameters, and chemical component distribution of the cancerous tissue.

Real-time diagnosis and visualization of tumor margins in excised breast specimens using fluorescence lifetime imaging and machine learning

Tumor-free surgical margins are critical in breast-conserving surgery. In up to 38% of the cases, however, patients undergo a second surgery since malignant cells are found at the margins of the excised resection specimen. Thus, advanced imaging tools are needed to ensure clear margins at the time of surgery. The objective of this study was to evaluate a random forest classifier that makes use of parameters derived from point-scanning label-free fluorescence lifetime imaging (FLIm) measurements of breast specimens as a means to diagnose tumor at the resection margins and to enable an intuitive visualization of a probabilistic classifier on tissue specimen. FLIm data from fresh lumpectomy and mastectomy specimens from 18 patients were used in this study. The supervised training was based on a previously developed registration technique between autofluorescence imaging data and cross-sectional histology slides. A pathologist's histology annotations provide the ground truth to distinguish between adipose, fibrous, and tumor tissue. Current results demonstrate the ability of this approach to classify the tumor with 89% sensitivity and 93% specificity and to rapidly (∼ 20 frames per second) overlay the probabilistic classifier overlaid on excised breast specimens using an intuitive color scheme. Furthermore, we show an iterative imaging refinement that allows surgeons to switch between rapid scans with a customized, low spatial resolution to quickly cover the specimen and slower scans with enhanced resolution (400 μm per point measurement) in suspicious regions where more details are required. In summary, this technique provides high diagnostic prediction accuracy, rapid acquisition, adaptive resolution, nondestructive probing, and facile interpretation of images, thus holding potential for clinical breast imaging based on label-free FLIm.

Real-time augmented reality for delineation of surgical margins during neurosurgery using autofluorescence lifetime contrast

Current clinical brain imaging techniques used for surgical planning of tumor resection lack intraoperative and real-time feedback; hence surgeons ultimately rely on subjective evaluation to identify tumor areas and margins. We report a fluorescence lifetime imaging (FLIm) instrument (excitation: 355 nm; emission spectral bands: 390/40 nm, 470/28 nm, 542/50 nm and 629/53 nm) that integrates with surgical microscopes to provide real-time intraoperative augmentation of the surgical field of view with fluorescent derived parameters encoding diagnostic information. We show the functionality and safety features of this instrument during neurosurgical procedures in patients undergoing craniotomy for the resection of brain tumors and/or tissue with radiation damage. We demonstrate in three case studies the ability of this instrument to resolve distinct tissue types and pathology including cortex, white matter, tumor and radiation-induced necrosis. In particular, two patients with effects of radiation-induced necrosis exhibited longer fluorescence lifetimes and increased optical redox ratio on the necrotic tissue with respect to non-affected cortex, and an oligodendroglioma resected from a third patient reported shorter fluorescence lifetime and a decrease in optical redox ratio than the surrounding white matter. These results encourage the use of FLIm as a label-free and non-invasive intraoperative tool for neurosurgical guidance.

Fluorescence imaging reversion using spatially variant deconvolution

Fluorescence imaging opens new possibilities for intraoperative guidance and early cancer detection, in particular when using agents that target specific disease features. Nevertheless, photon scattering in tissue degrades image quality and leads to ambiguity in fluorescence image interpretation and challenges clinical translation. We introduce the concept of capturing the spatially-dependent impulse response of an image and investigate Spatially Adaptive Impulse Response Correction (SAIRC), a method that is proposed for improving the accuracy and sensitivity achieved. Unlike classical methods that presume a homogeneous spatial distribution of optical properties in tissue, SAIRC explicitly measures the optical heterogeneity in tissues. This information allows, for the first time, the application of spatially-dependent deconvolution to correct the fluorescence images captured in relation to their modification by photon scatter. Using experimental measurements from phantoms and animals, we investigate the improvement in resolution and quantification over non-corrected images. We discuss how the proposed method is essential for maximizing the performance of fluorescence molecular imaging in the clinic.

Fluorescence lifetime imaging for intraoperative cancer delineation in transoral robotic surgery

This study evaluates the potential for fluorescence lifetime imaging (FLIm) to enhance intraoperative decisionmaking during robotic-assisted surgery of oropharyngeal cancer. Using a custom built FLIm instrument integrated with the da Vinci robotic surgical platform, we first demonstrate that cancer in epithelial tissue diagnosed by histopathology can be differentiated from surrounding healthy epithelial tissue imaged in vivo prior to cancer resection and ex vivo on the excised specimen. Second, we study the fluorescence properties of tissue imaged in vivo at surgical resection margins (tumor bed). Fluorescence lifetimes and spectral intensity ratios were calculated for three spectral channels, producing a set of six FLIm parameters. Current results from 10 patients undergoing TORS procedures demonstrate that healthy epithelium can be resolved from cancer (P < .001) for at least one FLIm parameter. We also showed that a multiparameter linear discriminant analysis approach provides superior discrimination to individual FLIm parameters for tissue imaged both in vivo and ex vivo. Overall, this study highlights the potential for FLIm to be developed into a diagnostic tool for clinical cancer applications of the oropharynx. This technique could help to circumvent the issues posed by the lack of tactile feedback associated with robotic surgical platforms to better enable cancer delineation.

Raman ChemLighter: Fiber optic Raman probe imaging in combination with augmented chemical reality

Raman spectroscopy using fiber optic probe combines non-contacted and label-free molecular fingerprinting with high mechanical flexibility for biomedical, clinical and industrial applications. Inherently, fiber optic Raman probes provide information from a single point only, and the acquisition of images is not straightforward. For many applications, it is highly crucial to determine the molecular distribution and provide imaging information of the sample. Here, we propose an approach for Raman imaging using a handheld fiber optic probe, which is built around computer vision-based assessment of positional information and simultaneous acquisition of spectroscopic information. By combining this implementation with real-time data processing and analysis, it is possible to create not only fiber-based Raman imaging but also an augmented chemical reality image of the molecular distribution of the sample surface in real-time. We experimentally demonstrated that using our approach, it is possible to determine and to distinguish borders of different bimolecular compounds in a short time. Because the method can be transferred to other optical probes and other spectroscopic techniques, it is expected that the implementation will have a large impact for clinical, biomedical and industrial applications.

Multispectral Depth-Resolved Fluorescence Lifetime Spectroscopy Using SPAD Array Detectors and Fiber Probes

Single Photon Avalanche Diode (SPAD) arrays are increasingly exploited and have demonstrated potential in biochemical and biomedical research, both for imaging and single-point spectroscopy applications. In this study, we explore the application of SPADs together with fiber-optic-based delivery and collection geometry to realize fast and simultaneous single-point time-, spectral-, and depth-resolved fluorescence measurements at 375 nm excitation light. Spectral information is encoded across the columns of the array through grating-based dispersion, while depth information is encoded across the rows thanks to a linear arrangement of probe collecting fibers. The initial characterization and validation were realized against layered fluorescent agarose-based phantoms. To verify the practicality and feasibility of this approach in biological specimens, we measured the fluorescence signature of formalin-fixed rabbit aorta samples derived from an animal model of atherosclerosis. The initial results demonstrate that this detection configuration can report fluorescence spectral and lifetime contrast originating at different depths within the specimens. We believe that our optical scheme, based on SPAD array detectors and fiber-optic probes, constitute a powerful and versatile approach for the deployment of multidimensional fluorescence spectroscopy in clinical applications where information from deeper tissue layers is important for diagnosis.

Non-destructive detection of matrix stabilization correlates with enhanced mechanical properties of self-assembled articular cartilage

Tissue engineers rely on expensive, time-consuming, and destructive techniques to monitor the composition, microstructure, and function of engineered tissue equivalents. A non-destructive solution to monitor tissue quality and maturation would greatly reduce costs and accelerate the development of tissue-engineered products. The objectives of this study were to (a) determine whether matrix stabilization with exogenous lysyl oxidase-like protein-2 (LOXL2) with recombinant hyaluronan and proteoglycan link protein-1 (LINK) would result in increased compressive and tensile properties in self-assembled articular cartilage constructs, (b) evaluate whether label-free, non-destructive fluorescence lifetime imaging (FLIm) could be used to infer changes in both biochemical composition and biomechanical properties, (c) form quantitative relationships between destructive and non-destructive measurements to determine whether the strength of these correlations is sufficient to replace destructive testing methods, and (d) determine whether support vector machine (SVM) learning can predict LOXL2-induced collagen crosslinking. The combination of exogenous LOXL2 and LINK proteins created a synergistic 4.9-fold increase in collagen crosslinking density and an 8.3-fold increase in tensile strength as compared with control (CTL). Compressive relaxation modulus was increased 5.9-fold with addition of LOXL2 and 3.4-fold with combined treatments over CTL. FLIm parameters had strong and significant correlations with tensile properties (R²  = 0.82; p < 0.001) and compressive properties (R²  = 0.59; p < 0.001). SVM learning based on FLIm-derived parameters was capable of automating tissue maturation assessment with a discriminant ability of 98.4%. These results showed marked improvements in mechanical properties with matrix stabilization and suggest that FLIm-based tools have great potential for the non-destructive assessment of tissue-engineered cartilage.

Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients

Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols.

Detection of glycosaminoglycan loss in articular cartilage by fluorescence lifetime imaging

Glycosaminoglycan (GAG) loss is an early marker of osteoarthritis, which is a clinical late stage disease that affects millions of people worldwide. The goal of our study was to evaluate the ability of a fiber-based fluorescence lifetime imaging (FLIm) technique to detect GAG loss in articular cartilage. Native bovine cartilage explants (n  =  20) were exposed to 0 (control), 0.5 (low), or 1  U  /  mL (high) concentrations of chondroitinase ABC (cABC) to create samples with different levels of GAG loss. FLIm assessment (excitation: 355 nm; detection: channel 1: 375 to 410 nm, channel 2: 450 to 485 nm, channel 3: 530 to 565 nm) was conducted on depth-resolved cross-sections of the cartilage sample. FLIm images, validated with histology, revealed that loss of GAG resulted in a decrease of fluorescence lifetime values in channel 2 (Δ  =  0.44  ns, p  <  0.05) and channel 3 (Δ  =  0.75  ns, p  <  0.01) compared to control samples (channel 2: 6.34 ns; channel 3: 5.22 ns). Fluorescence intensity ratio values were lower in channel 1 (37%, p  <  0.0001) and channel 2 (31% decrease, p  <  0.0001) and higher in channel 3 (23%, p  <  0.0001) relative to control samples. These results show that FLIm can detect the loss of GAG in articular cartilage and support further investigation into the feasibility of in vivo FLIm arthroscopy.

Lifetime-engineered NIR-II nanoparticles unlock multiplexed in vivo imaging

Deep tissue imaging in the second near-infrared (NIR-II) window holds great promise for physiological studies and biomedical applications^1-6. However, inhomogeneous signal attenuation in biological matter^7,8 hampers the application of multiple-wavelength NIR-II probes to multiplexed imaging. Here, we present lanthanide-doped NIR-II nanoparticles with engineered luminescence lifetimes for in vivo quantitative imaging using time-domain multiplexing. To achieve this, we have devised a systematic approach based on controlled energy relay that creates a tunable lifetime range spanning three orders of magnitude with a single emission band. We consistently resolve selected lifetimes from the NIR-II nanoparticle probes at depths of up to 8 mm in biological tissues, where the signal-to-noise ratio derived from intensity measurements drops below 1.5. We demonstrate that robust lifetime coding is independent of tissue penetration depth, and we apply in vivo multiplexing to identify tumour subtypes in living mice. Our results correlate well with standard ex vivo immunohistochemistry assays, suggesting that luminescence lifetime imaging could be used as a minimally invasive approach for disease diagnosis.

Label-free assessment of carotid artery biochemical composition using fiber-based fluorescence lifetime imaging

Novel diagnostic tools with the ability to monitor variations in biochemical composition and provide benchmark indicators of vascular tissue maturation are needed to create functional tissue replacements. We investigated the ability of fiber-based, label-free multispectral fluorescent lifetime imaging (FLIm) to quantify the anatomical variations in biochemical composition of native carotid arteries and validated these results against biochemical assays. FLIm-derived parameters in spectral band 415-455 nm correlated with tissue collagen content (R² = 0.64) and cell number (R² = 0.61) and in spectral band 465-553 nm strongly correlated with elastin content (R² = 0.89). These results suggest that FLIm holds great potential for assessing vascular tissue maturation and functional properties based on tissue autofluorescence.

Method for accurate registration of tissue autofluorescence imaging data with corresponding histology: a means for enhanced tumor margin assessment

An important step in establishing the diagnostic potential for emerging optical imaging techniques is accurate registration between imaging data and the corresponding tissue histopathology typically used as gold standard in clinical diagnostics. We present a method to precisely register data acquired with a point-scanning spectroscopic imaging technique from fresh surgical tissue specimen blocks with corresponding histological sections. Using a visible aiming beam to augment point-scanning multispectral time-resolved fluorescence spectroscopy on video images, we evaluate two different markers for the registration with histology: fiducial markers using a 405-nm CW laser and the tissue block's outer shape characteristics. We compare the registration performance with benchmark methods using either the fiducial markers or the outer shape characteristics alone to a hybrid method using both feature types. The hybrid method was found to perform best reaching an average error of 0.78±0.67  mm. This method provides a profound framework to validate diagnostical abilities of optical fiber-based techniques and furthermore enables the application of supervised machine learning techniques to automate tissue characterization.

Automated detection of breast cancer in resected specimens with fluorescence lifetime imaging

Re-excision rates for breast cancer lumpectomy procedures are currently nearly 25% due to surgeons relying on inaccurate or incomplete methods of evaluating specimen margins. The objective of this study was to determine if cancer could be automatically detected in breast specimens from mastectomy and lumpectomy procedures by a classification algorithm that incorporated parameters derived from fluorescence lifetime imaging (FLIm). This study generated a database of co-registered histologic sections and FLIm data from breast cancer specimens (N  =  20) and a support vector machine (SVM) classification algorithm able to automatically detect cancerous, fibrous, and adipose breast tissue. Classification accuracies were greater than 97% for automated detection of cancerous, fibrous, and adipose tissue from breast cancer specimens. The classification worked equally well for specimens scanned by hand or with a mechanical stage, demonstrating that the system could be used during surgery or on excised specimens. The ability of this technique to simply discriminate between cancerous and normal breast tissue, in particular to distinguish fibrous breast tissue from tumor, which is notoriously challenging for optical techniques, leads to the conclusion that FLIm has great potential to assess breast cancer margins. Identification of positive margins before waiting for complete histologic analysis could significantly reduce breast cancer re-excision rates.

Label-free optical imaging technologies for rapid translation and use during intraoperative surgical and tumor margin assessment

The biannual International Conference on Biophotonics was recently held on April 30 to May 1, 2017, in Fremantle, Western Australia. This continuing conference series brought together key opinion leaders in biophotonics to present their latest results and, importantly, to participate in discussions on the future of the field and what opportunities exist when we collectively work together for using biophotonics for biological discovery and medical applications. One session in this conference, entitled "Tumor Margin Identification: Critiquing Technologies," challenged invited speakers and attendees to review and critique representative label-free optical imaging technologies and their application for intraoperative assessment and guidance in surgical oncology. We are pleased to share a summary in this outlook paper, with the intent to motivate more research inquiry and investigations, to challenge these and other optical imaging modalities to evaluate and improve performance, to spur translation and adoption, and ultimately, to improve the care and outcomes of patients.

Rapid fluorescence lifetime estimation with modified phasor approach and Laguerre deconvolution: a comparative study

Fluorescence lifetime imaging has been shown to serve as a valuable tool for interrogating and diagnosis of biological tissue at a mesoscopic level. The ability to analyze fluorescence decay curves to extract lifetime values in real-time is crucial for clinical translation and applications such as tumor margin delineation or intracoronary imaging of atherosclerotic plaques. In this work, we compare the performance of two popular non-parametric (fit-free) methods for determining lifetime values from fluorescence decays in real-time-the Phasor approach and Laguerre deconvolution. We demonstrate results from simulated and experimental data to compare the accuracy and speed of both methods and their dependence on noise and model parameters.