Fibre-based fluorescence-lifetime imaging microscopy: a real-time biopsy guidance tool for suspected lung cancer.

Lung cancer is the most common cause of cancer-related deaths worldwide. Early detection improves outcomes, however, existing sampling techniques are associated with suboptimal diagnostic yield and procedure-related complications. Autofluorescence-based fluorescence-lifetime imaging microscopy (FLIM), a technique which measures endogenous fluorophore decay rates, may aid identification of optimal biopsy sites in suspected lung cancer. Our fibre-based fluorescence-lifetime imaging system, utilising 488 nm excitation, which is deliverable via existing diagnostic platforms, enables real-time visualisation and lifetime analysis of distal alveolar lung structure. We evaluated the diagnostic accuracy of the fibre-based fluorescence-lifetime imaging system to detect changes in fluorescence lifetime in freshly resected ex vivo lung cancer and adjacent healthy tissue as a first step towards future translation. The study compares paired non-small cell lung cancer (NSCLC) and non-cancerous tissues with gold standard diagnostic pathology to assess the performance of the technique. Paired NSCLC and non-cancerous lung tissues were obtained from thoracic resection patients (N=21). A clinically compatible 488 nm fluorescence-lifetime endomicroscopy platform was used to acquire simultaneous fluorescence intensity and lifetime images. Fluorescence lifetimes were calculated using a computationally-lightweight, rapid lifetime determination method. Fluorescence lifetime was significantly reduced in ex vivo lung cancer, compared with non-cancerous lung tissue [mean ± standard deviation (SD), 1.79±0.40 vs. 2.15±0.26 ns, P<0.0001], and fluorescence intensity images demonstrated distortion of alveolar elastin autofluorescence structure. Fibre-based fluorescence-lifetime imaging demonstrated good performance characteristics for distinguishing lung cancer, from adjacent non-cancerous tissue, with 81.0% sensitivity and 71.4% specificity. Our novel fibre-based fluorescence-lifetime imaging system, which enables label-free imaging and quantitative lifetime analysis, discriminates ex vivo lung cancer from adjacent healthy tissue. This minimally invasive technique has potential to be translated as a real-time biopsy guidance tool, capable of optimising diagnostic accuracy in lung cancer.

A Novel Fit-Flexible Fluorescence Soft Imager: Tri-Sensing of Intensity, Fall-Time, and Life Profile.

Time-resolved fluorescence imaging techniques, like confocal fluorescence lifetime imaging microscopy, are powerful photonic instrumentation tools of modern science with diverse applications, including: biology, medicine, and chemistry. However, complexities of the systems, both at specimen and device levels, cause difficulties in quantifying soft biomarkers. To address the problems, we first aim to understand and model the underlying photophysics of fluorescence decay curves. For this purpose, we provide a set of mathematical functions, called "life models", fittable with the real temporal recordings of histogram of photon counts. For each model, an equivalent electrical circuit, called a "life circuit", is derived for explaining the whole process. In confocal endomicroscopy, the components of excitation laser, specimen, and fluorescence-emission signal as the histogram of photon counts are modelled by a power source, network of resistor-inductor-capacitor circuitry, and multimetre, respectively. We then design a novel pixel-level temporal classification algorithm, called a "fit-flexible approach", where qualities of "intensity", "fall-time", and "life profile" are identified for each point. A model selection mechanism is used at each pixel to flexibly choose the best representative life model based on a proposed Misfit-percent metric. A two-dimensional arrangement of the quantified information detects some kind of structural information. This approach showed a potential of separating microbeads from lung tissue, distinguishing the tri-sensing from conventional methods. We alleviated by 7% the error of the Misfit-percent for recovering the histograms on real samples than the best state-of-the-art competitor. Codes are available online.

Combined fluorescence lifetime and surface topographical imaging of biological tissue.

In this work a combined fluorescence lifetime and surface topographical imaging system is demonstrated. Based around a 126 × 192 time resolved single photon avalanche diode (SPAD) array operating in time correlated single-photon counting (TCSPC) mode, both the fluorescence lifetime and time of flight (ToF) can be calculated on a pixel by pixel basis. Initial tests on fluorescent samples show it is able to provide 4 mm resolution in distance and 0.4 ns resolution in lifetime. This combined modality has potential biomedical applications such as surgical guidance, endoscopy, and diagnostic imaging. The system is demonstrated on both ovine and human pulmonary tissue samples, where it offers excellent fluorescence lifetime contrast whilst also giving a measure of the distance to the sample surface.

Applications of machine learning in time-domain fluorescence lifetime imaging: a review.

Many medical imaging modalities have benefited from recent advances in Machine Learning (ML), specifically in deep learning, such as neural networks. Computers can be trained to investigate and enhance medical imaging methods without using valuable human resources. In recent years, Fluorescence Lifetime Imaging (FLIm) has received increasing attention from the ML community. FLIm goes beyond conventional spectral imaging, providing additional lifetime information, and could lead to optical histopathology supporting real-time diagnostics. However, most current studies do not use the full potential of machine/deep learning models. As a developing image modality, FLIm data are not easily obtainable, which, coupled with an absence of standardisation, is pushing back the research to develop models which could advance automated diagnosis and help promote FLIm. In this paper, we describe recent developments that improve FLIm image quality, specifically time-domain systems, and we summarise sensing, signal-to-noise analysis and the advances in registration and low-level tracking. We review the two main applications of ML for FLIm: lifetime estimation and image analysis through classification and segmentation. We suggest a course of action to improve the quality of ML studies applied to FLIm. Our final goal is to promote FLIm and attract more ML practitioners to explore the potential of lifetime imaging.

Development of a high-speed line-scanning fluorescence lifetime imaging microscope for biological imaging.

We report the development of a novel line-scanning microscope capable of acquiring high-speed time-correlated single-photon counting (TCSPC)-based fluorescence lifetime imaging microscopy (FLIM) imaging. The system consists of a laser-line focus, which is optically conjugated to a 1024 × 8 single-photon avalanche diode (SPAD)-based line-imaging complementary metal-oxide semiconductor (CMOS), with 23.78 µm pixel pitch at 49.31% fill factor. Incorporation of on-chip histogramming on the line-sensor enables acquisition rates 33 times faster than our previously reported bespoke high-speed FLIM platforms. We demonstrate the imaging capability of the high-speed FLIM platform in a number of biological applications.

Deep learning-assisted co-registration of full-spectral autofluorescence lifetime microscopic images with H&E-stained histology images.

Autofluorescence lifetime images reveal unique characteristics of endogenous fluorescence in biological samples. Comprehensive understanding and clinical diagnosis rely on co-registration with the gold standard, histology images, which is extremely challenging due to the difference of both images. Here, we show an unsupervised image-to-image translation network that significantly improves the success of the co-registration using a conventional optimisation-based regression network, applicable to autofluorescence lifetime images at different emission wavelengths. A preliminary blind comparison by experienced researchers shows the superiority of our method on co-registration. The results also indicate that the approach is applicable to various image formats, like fluorescence in-tensity images. With the registration, stitching outcomes illustrate the distinct differences of the spectral lifetime across an unstained tissue, enabling macro-level rapid visual identification of lung cancer and cellular-level characterisation of cell variants and common types. The approach could be effortlessly extended to lifetime images beyond this range and other staining technologies.

Fast and Robust Single-Exponential Decay Recovery From Noisy Fluorescence Lifetime Imaging.

Fluorescence lifetime imaging is a valuable technique for probing characteristics of wide ranging samples and sensing of the molecular environment. However, the desire to measure faster and reduce effects such as photo bleaching in optical photon-count measurements for lifetime estimation lead to inevitable effects of convolution with the instrument response functions and noise, causing a degradation of the lifetime accuracy and precision. To tackle the problem, this paper presents a robust and computationally efficient framework for recovering fluorophore sample decay from the histogram of photon-count arrivals modelled as a decaying single-exponential function. In the proposed approach, the temporal histogram data is first decomposed into multiple bins via an adaptive multi-bin signal representation. Then, at each level of the multi-resolution temporal space, decay information including both the amplitude and the lifetime of a single-exponential function is rapidly decoded based on a novel statistical estimator. Ultimately, a game-theoretic model consisting of two players in an "amplitude-lifetime" game is constructed to be able to robustly recover optimal fluorescence decay signal from a set of fused multi-bin estimates. In addition to theoretical demonstrations, the efficiency of the proposed framework is experimentally shown on both synthesised and real data in different imaging circumstances. On a challenging low photon-count regime, our approach achieves about 28% improvement in bias than the best competing method. On real images, the proposed method processes data on average around 63 times faster than the gold standard least squares fit. Implementation codes are available to researchers.

Full spectrum fluorescence lifetime imaging with 0.5 nm spectral and 50 ps temporal resolution.

The use of optical techniques to interrogate wide ranging samples from semiconductors to biological tissue for rapid analysis and diagnostics has gained wide adoption over the past decades. The desire to collect ever more spatially, spectrally and temporally detailed optical signatures for sample characterization has specifically driven a sharp rise in new optical microscopy technologies. Here we present a high-speed optical scanning microscope capable of capturing time resolved images across 512 spectral and 32 time channels in a single acquisition with the potential for ~0.2 frames per second (256 × 256 image pixels). Each pixel in the resulting images contains a detailed data cube for the study of diverse time resolved light driven phenomena. This is enabled by integration of system control electronics and on-chip processing which overcomes the challenges presented by high data volume and low imaging speed, often bottlenecks in previous systems.

Time-correlated single photon Raman spectroscopy at megahertz repetition rates.

Significant improvements in time-correlated single photon counting (TCSPC) Raman spectroscopy acquisition times can be achieved through exploitation of megahertz (MHz) laser repetition rates. We have developed a TCSPC Raman spectroscopy system based on a high peak power (>40W) pulsed laser, a high pulse repetition rate (40 MHz), a custom f/1.5 spectrometer, and a 512 spectral channel × 16 time bin single photon avalanche diode line sensor. We report millisecond Raman spectrum acquisition times, a peak Raman count rate of 104 kcps, and a linewidth aggregated count rate of 440 kcps with a diamond sample. This represents a three-order-of-magnitude increase in measured Raman count rate in comparison with a 104 kHz pulsed laser operating at 300 W and a four-order-of-magnitude increase over a 0.1 W pulsed laser operating at 40 MHz. A Raman-to-fluorescence ratio of 4.76 is achieved with a sesame oil sample at a 20 MHz repetition rate. Achieving high count rates and Raman-to-fluorescence ratios unlocks the potential of combined Raman/fluorescence lifetime spectroscopy for imaging and other short acquisition time applications.

Solitary pulmonary nodule imaging approaches and the role of optical fibre-based technologies.

Solitary pulmonary nodules (SPNs) are a clinical challenge, given there is no single clinical sign or radiological feature that definitively identifies a benign from a malignant SPN. The early detection of lung cancer has a huge impact on survival outcome. Consequently, there is great interest in the prompt diagnosis, and treatment of malignant SPNs. Current diagnostic pathways involve endobronchial/transthoracic tissue biopsies or radiological surveillance, which can be associated with suboptimal diagnostic yield, healthcare costs and patient anxiety. Cutting-edge technologies are needed to disrupt and improve, existing care pathways. Optical fibre-based techniques, which can be delivered via the working channel of a bronchoscope or via transthoracic needle, may deliver advanced diagnostic capabilities in patients with SPNs. Optical endomicroscopy, an autofluorescence-based imaging technique, demonstrates abnormal alveolar structure in SPNs in vivo Alternative optical fingerprinting approaches, such as time-resolved fluorescence spectroscopy and fluorescence-lifetime imaging microscopy, have shown promise in discriminating lung cancer from surrounding healthy tissue. Whilst fibre-based Raman spectroscopy has enabled real-time characterisation of SPNs in vivo Fibre-based technologies have the potential to enable in situ characterisation and real-time microscopic imaging of SPNs, which could aid immediate treatment decisions in patients with SPNs. This review discusses advances in current imaging modalities for evaluating SPNs, including computed tomography (CT) and positron emission tomography-CT. It explores the emergence of optical fibre-based technologies, and discusses their potential role in patients with SPNs and suspected lung cancer.

Deep Learning in ex-vivo Lung Cancer Discrimination using Fluorescence Lifetime Endomicroscopic Images.

Fluorescence lifetime is effective in discriminating cancerous tissue from normal tissue, but conventional discrimination methods are primarily based on statistical approaches in collaboration with prior knowledge. This paper investigates the application of deep convolutional neural networks (CNNs) for automatic differentiation of ex-vivo human lung cancer via fluorescence lifetime imaging. Around 70,000 fluorescence images from ex-vivo lung tissue of 14 patients were collected by a custom fibre-based fluorescence lifetime imaging endomicroscope. Five state-of-the-art CNN models, namely ResNet, ResNeXt, Inception, Xception, and DenseNet, were trained and tested to derive quantitative results using accuracy, precision, recall, and the area under receiver operating characteristic curve (AUC) as the metrics. The CNNs were firstly evaluated on lifetime images. Since fluorescence lifetime is independent of intensity, further experiments were conducted by stacking intensity and lifetime images together as the input to the CNNs. As the original CNNs were implemented for RGB images, two strategies were applied. One was retaining the CNNs by putting intensity and lifetime images in two different channels and leaving the remaining channel blank. The other was adapting the CNNs for two-channel input. Quantitative results demonstrate that the selected CNNs are considerably superior to conventional machine learning algorithms. Combining intensity and lifetime images introduces noticeable performance gain compared with using lifetime images alone. In addition, the CNNs with intensity-lifetime RGB image is comparable to the modified two-channel CNNs with intensity-lifetime two-channel input for accuracy and AUC, but significantly better for precision and recall.

Immune responses to a HSV-2 polynucleotide immunotherapy COR-1 in HSV-2 positive subjects: A randomized double blinded phase I/IIa trial.

BACKGROUND: Genital herpes simplex infection affects more than 500 million people worldwide. We have previously shown that COR-1, a therapeutic HSV-2 polynucleotide vaccine candidate, is safe and well tolerated in healthy subjects. OBJECTIVE: Here, we present a single center double-blind placebo-controlled, randomized phase I/IIa trial of COR-1 in HSV-2 positive subjects in which we assessed safety and tolerability as primary endpoints, and immunogenicity and therapeutic efficacy as exploratory endpoints. METHODS: Forty-four HSV-2+ subjects confirmed by positive serology or pathology, and positive qPCR during baseline shedding, with a recurrent genital HSV-2 history of at least 12 months including three to nine reported lesions in 12 months prior to screening, aged 18 to 50 years females and males with given written informed consent, were randomized into two groups. Three immunizations at 4-week intervals and one booster immunization at 6 months, each of 1 mg COR-1 DNA or placebo, were administered intradermally as two injections of 500 µg each to either one forearm or both forearms. RESULTS: No serious adverse events, life-threatening events or deaths occurred throughout the study. As expected, HSV-2 infected subjects displayed gD2-specific antibody titers prior to immunization. COR-1 was associated with a reduction in viral shedding after booster administration compared with baseline. CONCLUSIONS: This study confirms the previously demonstrated safety of COR-1 in humans and indicates a potential for use of COR-1 as a therapy to reduce viral shedding in HSV-2 infected subjects.

DNA Vaccine Encoding HPV16 Oncogenes E6 and E7 Induces Potent Cell-mediated and Humoral Immunity Which Protects in Tumor Challenge and Drives E7-expressing Skin Graft Rejection.

We have previously shown that a novel DNA vaccine technology of codon optimization and the addition of ubiquitin sequences enhanced immunogenicity of a herpes simplex virus 2 polynucleotide vaccine in mice, and induced cell-mediated immunity when administered in humans at relatively low doses of naked DNA. We here show that a new polynucleotide vaccine using the same technology and encoding a fusion protein of the E6 and E7 oncogenes of high-risk human papillomavirus type 16 (HPV16) is immunogenic in mice. This vaccine induces long-lasting humoral and cell-mediated immunity and protects mice from establishment of HPV16-E7-expressing tumors. In addition, it suppresses growth of readily established tumors and shows enhanced efficacy when combined with immune checkpoint blockade targeted at PD-L1. This vaccine also facilitates rejection of HPV16-E7-expressing skin grafts that demonstrate epidermal hyperplasia with characteristics of cervical and vulvar intraepithelial neoplasia. Clinical studies evaluating the efficacy of this vaccine in patients with HPV16 premalignancies are planned.

An escalating dose study to assess the safety, tolerability and immunogenicity of a Herpes Simplex Virus DNA vaccine, COR-1.

This paper describes a single site, open-label Phase I clinical trial evaluating the safety, tolerability and immunogenicity in healthy volunteers of a herpes simplex polynucleotide vaccine that has previously been shown to enhance immunogenicity and protect against lethal herpes simplex virus type 2 (HSV-2) challenge in mice. Five escalating doses of the vaccine, COR-1, were given by intradermal injection to HSV-1 and 2 seronegative healthy individuals. COR-1 was found to be safe and well-tolerated; the only vaccine-related adverse events were mild. While vaccine-induced antibody responses were not detectable, cell-mediated immune responses to HSV-specific peptide groups were identified in 19 of the 20 subjects who completed the study, and local inflammation at the immunisation site was observed. This study indicates COR-1 has potential to be used as a therapeutic vaccine for HSV-2 infection.

Antibiotic-free production of a herpes simplex virus 2 DNA vaccine in a high yield cGMP process.

Two DNA vaccine plasmids encoding Herpes simplex virus type 2 (HSV-2) glycoprotein D, NTC8485-O2-gD2 and NTC8485-O2-UgD2tr, were produced at large scale under current good manufacturing practice (cGMP) for use in a Phase I human clinical trial. These DNA vaccines incorporate the regulatory agency compliant, minimal, antibiotic-free (AF) NTC8485 mammalian expression vector. Plasmid yields of>1 g/L were achieved using the HyperGRO™ fed-batch fermentation process, with successful scale up from 10 L process development scale to 320 L culture volume for cGMP production. The DNA vaccines were purified using a low residence time, high shear lysis process and AIRMIX(TM) technology, followed by chromatographic purification. This combination of optimized plasmid vector, high yield upstream production, and efficient downstream purification resulted in purified HSV-2 DNA vaccines with>99% total supercoiled plasmid, ≤ 0.2% RNA, ≤ 0.1% host cell genomic DNA, and ≤ 0.1 endotoxin units per mg.