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

Unveiling intracellular phase separation: advances in optical imaging of biomolecular condensates

Intracellular biomolecular condensates, which form via phase separation, display a highly organized ultrastructure and complex properties. Recent advances in optical imaging techniques, including super-resolution microscopy and innovative microscopic methods that leverage the intrinsic properties of the molecules observed, have transcended the limitations of conventional microscopies. These advances facilitate the exploration of condensates at finer scales and in greater detail. The deployment of these emerging but sophisticated imaging tools allows for precise observations of the multiphasic organization and physicochemical properties of these condensates, shedding light on their functions in cellular processes. In this review, we highlight recent progress in methodological innovations and their profound implications for understanding the organization and dynamics of intracellular biomolecular condensates.

Deformable multi-modal image registration for the correlation between optical measurements and histology images

Significance

The accurate correlation between optical measurements and pathology relies on precise image registration, often hindered by deformations in histology images. We investigate an automated multi-modal image registration method using deep learning to align breast specimen images with corresponding histology images.

Aim

We aim to explore the effectiveness of an automated image registration technique based on deep learning principles for aligning breast specimen images with histology images acquired through different modalities, addressing challenges posed by intensity variations and structural differences.

Approach

Unsupervised and supervised learning approaches, employing the VoxelMorph model, were examined using a dataset featuring manually registered images as ground truth.

Results

Evaluation metrics, including Dice scores and mutual information, demonstrate that the unsupervised model exceeds the supervised (and manual) approaches significantly, achieving superior image alignment. The findings highlight the efficacy of automated registration in enhancing the validation of optical technologies by reducing human errors associated with manual registration processes.

Conclusions

This automated registration technique offers promising potential to enhance the validation of optical technologies by minimizing human-induced errors and inconsistencies associated with manual image registration processes, thereby improving the accuracy of correlating optical measurements with pathology labels.

Live Microscopy of Multicellular Spheroids with the Multimodal Near-Infrared Nanoparticles Reveals Differences in Oxygenation Gradients

Assessment of hypoxia, nutrients, metabolite gradients, and other hallmarks of the tumor microenvironment within 3D multicellular spheroid and organoid models represents a challenging analytical task. Here, we report red/near-infrared (NIR) emitting cell staining with O2-sensitive nanoparticles, which enable measurements of spheroid oxygenation on a conventional fluorescence microscope. Nanosensor probes, termed "MMIR" (multimodal infrared), incorporate an NIR O2-sensitive metalloporphyrin (PtTPTBPF) and deep red aza-BODIPY reference dyes within a biocompatible polymer shell, allowing for oxygen gradient quantification via fluorescence ratio and phosphorescence lifetime readouts. We optimized staining techniques and evaluated the nanosensor probe characteristics and cytotoxicity. Subsequently, we applied nanosensors to the live spheroid models based on HCT116, DPSCs, and SKOV3 cells, at rest, and treated with drugs affecting cell respiration. We found that the growth medium viscosity, spheroid size, and formation method influenced spheroid oxygenation. Some spheroids produced from HCT116 and dental pulp stem cells exhibited "inverted" oxygenation gradients, with higher core oxygen levels than the periphery. This contrasted with the frequently encountered "normal" gradient of hypoxia toward the core caused by diffusion. Further microscopy analysis of spheroids with an "inverted" gradient demonstrated metabolic stratification of cells within spheroids: thus, autofluorescence FLIM of NAD(P)H indicated the formation of a glycolytic core and localization of OxPhos-active cells at the periphery. Collectively, we demonstrate a strong potential of NIR-emitting ratiometric nanosensors for advanced microscopy studies targeting live and quantitative real-time monitoring of cell metabolism and hypoxia in complex 3D tissue models.

Pioglitazone Phases and Metabolic Effects in Nanoparticle-Treated Cells Analyzed via Rapid Visualization of FLIM Images

Fluorescence lifetime imaging microscopy (FLIM) has proven to be a useful method for analyzing various aspects of material science and biology, like the supramolecular organization of (slightly) fluorescent compounds or the metabolic activity in non-labeled cells; in particular, FLIM phasor analysis (phasor-FLIM) has the potential for an intuitive representation of complex fluorescence decays and therefore of the analyzed properties. Here we present and make available tools to fully exploit this potential, in particular by coding via hue, saturation, and intensity the phasor positions and their weights both in the phasor plot and in the microscope image. We apply these tools to analyze FLIM data acquired via two-photon microscopy to visualize: (i) different phases of the drug pioglitazone (PGZ) in solutions and/or crystals, (ii) the position in the phasor plot of non-labelled poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs), and (iii) the effect of PGZ or PGZ-containing NPs on the metabolism of insulinoma (INS-1 E) model cells. PGZ is recognized for its efficacy in addressing insulin resistance and hyperglycemia in type 2 diabetes mellitus, and polymeric nanoparticles offer versatile platforms for drug delivery due to their biocompatibility and controlled release kinetics. This study lays the foundation for a better understanding via phasor-FLIM of the organization and effects of drugs, in particular, PGZ, within NPs, aiming at better control of encapsulation and pharmacokinetics, and potentially at novel anti-diabetics theragnostic nanotools.

The realization of medical devices for precision surgery - development and implementation of 'stop-and-go' imaging technologies

INTRODUCTION

Surgery and biomedical imaging encompass a big share of the medical-device market. The ever-mounting demand for precision surgery has driven the integration of these two into the field of image-guided surgery. A key-question herein is how imaging modalities can guide the surgical decision-making process. Through performance-based design, chemists, engineers, and doctors need to build a bridge between imaging technologies and surgical challenges.

AREAS-COVERED

This perspective article highlights the complementary nature between the technological design of an image-guidance modality and the type of procedure performed. The specific roles of the involved professionals, imaging technologies, and surgical indications are addressed.

EXPERT-OPINION

Molecular-image-guided surgery has the potential to advance pre-, intra- and post-operative tissue characterization. To achieve this, surgeons need the access to well-designed indication-specific chemical-agents and detection modalities. Hereby, some technologies stimulate exploration ('go'), while others stimulate caution ('stop'). However, failing to adequately address the indication-specific needs rises the risk of incorrect tool employment and sub-optimal surgical performance. Therefore, besides the availability of new technologies, market growth is highly dependent on the practical nature and impact on real-life clinical care. While urology currently takes the lead in the widespread implementation of image-guidance technologies, the topic is generic and its popularity spreads rapidly within surgical oncology.

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32[Formula: see text]32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

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.

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.

Emerging clinical applications in oncology for non-invasive multi- and hyperspectral imaging of cell and tissue autofluorescence

Hyperspectral and multispectral imaging of cell and tissue autofluorescence is an emerging technology in which fluorescence imaging is applied to biological materials across multiple spectral channels. This produces a stack of images where each matched pixel contains information about the sample's spectral properties at that location. This allows precise collection of molecularly specific data from a broad range of native fluorophores. Importantly, complex information, directly reflective of biological status, is collected without staining and tissues can be characterised in situ, without biopsy. For oncology, this can spare the collection of biopsies from sensitive regions and enable accurate tumour mapping. For in vivo tumour analysis, the greatest focus has been on oral cancer, whereas for ex vivo assessment head-and-neck cancers along with colon cancer have been the most studied, followed by oral and eye cancer. This review details the scope and progress of research undertaken towards clinical translation in oncology.

Pulse-sampling fluorescence lifetime imaging: evaluation of photon economy

This Letter presents an experimental study comparing the photon rate and photon economy of pulse sampling fluorescence lifetime imaging (PS-FLIm) with the conventional time-correlated single photon counting (TCSPC) technique. We found that PS-FLIm has a significantly higher photon detection rate (200 MHz) compared with TCSPC (2-8 MHz) but lower photon economy (4-5 versus 1-1.3). The main factor contributing to the lower photon economy in PS-FLIm is laser pulse variability. These results demonstrate that PS-FLIm offers 25× faster imaging speed than TCSPC while maintaining room light rejection in clinical settings. This makes PS-FLIm a robust technique for clinical applications.

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.

Intraoperative detection of IDH-mutant glioma using fluorescence lifetime imaging

Identifying isocitrate dehydrogenase (IDH)-mutation and glioma subtype during surgery instead of days later can aid in modifying tumor resection strategies for better survival outcomes. We report intraoperative identification of IDH-mutant glioma (N = 12 patients) with a clinically compatible fluorescence lifetime imaging (FLIm) device (excitation: 355 nm; emission spectral bands: 390/40 nm, 470/28 nm, 542/50 nm). The fluorescence-derived parameters were analyzed to study the optical contrast between IDH-mutant tumors and surrounding brain tissue. IDH-mutant oligodendrogliomas exhibited shorter lifetimes (3.3 ± 0.1 ns) than IDH-mutant astrocytomas (4.1 ± 0.1 ns). Both IDH-mutant glioma subtypes had shorter lifetimes than white matter (4.6 ± 0.4 ns) but had comparable lifetimes to cortex. Lifetimes also increased with malignancy grade within IDH-mutant oligodendrogliomas (grade 2: 2.96 ± 0.08 ns, grade 3: 3.4 ± 0.3 ns) but not within IDH-mutant astrocytomas. The current results support the feasibility of FLIm as a surgical adjuvant for identifying IDH-mutant glioma tissue.

Clinical applications of non-invasive multi and hyperspectral imaging of cell and tissue autofluorescence beyond oncology

Hyperspectral and multispectral imaging of cell and tissue autofluorescence employs fluorescence imaging, without exogenous fluorophores, across multiple excitation/emission combinations (spectral channels). This produces an image stack where each pixel (matched by location) contains unique information about the sample's spectral properties. Analysis of this data enables access to a rich, molecularly specific data set from a broad range of cell-native fluorophores (autofluorophores) directly reflective of biochemical status, without use of fixation or stains. This non-invasive, non-destructive technology has great potential to spare the collection of biopsies from sensitive regions. As both staining and biopsy may be impossible, or undesirable, depending on the context, this technology great diagnostic potential for clinical decision making. The main research focus has been on the identification of neoplastic tissues. However, advances have been made in diverse applications-including ophthalmology, cardiovascular health, neurology, infection, assisted reproduction technology and organ transplantation.

The power of super-resolution microscopy in modern biomedical science

Super-resolution microscopy (SRM) technology that breaks the diffraction limit has revolutionized the field of cell biology since its appearance, which enables researchers to visualize cellular structures with nanometric resolution, multiple colors and single-molecule sensitivity. With the flourishing development of hardware and the availability of novel fluorescent probes, the impact of SRM has already gone beyond cell biology and extended to nanomedicine, material science and nanotechnology, and remarkably boosted important breakthroughs in these fields. In this review, we will mainly highlight the power of SRM in modern biomedical science, discussing how these SRM techniques revolutionize the way we understand cell structures, biomaterials assembly and how assembled biomaterials interact with cellular organelles, and finally their promotion to the clinical pre-diagnosis. Moreover, we also provide an outlook on the current technical challenges and future improvement direction of SRM. We hope this review can provide useful information, inspire new ideas and propel the development both from the perspective of SRM techniques and from the perspective of SRM's applications.

The application of optical technology in the diagnosis and therapy of oxidative stress-mediated hepatic ischemia-reperfusion injury

Hepatic ischemia-reperfusion injury (HIRI) is defined as liver tissue damage and cell death caused by reperfusion during liver transplantation or hepatectomy. Oxidative stress is one of the important mechanisms of HIRI. Studies have shown that the incidence of HIRI is very high, however, the number of patients who can get timely and efficient treatment is small. The reason is not hard to explain that invasive ways of detection and lack of timely of diagnostic methods. Hence, a new detection method is urgently needed in clinic application. Reactive oxygen species (ROS), which are markers of oxidative stress in the liver, could be detected by optical imaging and offer timely and effective non-invasive diagnosis and monitoring. Optical imaging could become the most potential tool of diagnosis of HIRI in the future. In addition, optical technology can also be used in disease treatment. It found that optical therapy has the function of anti-oxidative stress. Consequently, it has possibility to treat HIRI caused by oxidative stress. In this review, we mainly summarized the application and prospect of optical techniques in oxidative stress-induced by HIRI.

Multi-Photon Microscopy

In this series of papers on light microscopy imaging, we have covered the fundamentals of microscopy, super-resolution microscopy, and lightsheet microscopy. This last review covers multi-photon microscopy with a brief reference to intravital imaging and Brainbow labeling. Multi-photon microscopy is often referred to as two-photon microscopy. Indeed, using two-photon microscopy is by far the most common way of imaging thick tissues; however, it is theoretically possible to use a higher number of photons, and three-photon microscopy is possible. Therefore, this review is titled "multi-photon microscopy." Another term for describing multi-photon microscopy is "non-linear" microscopy because fluorescence intensity at the focal spot depends upon the average squared intensity rather than the squared average intensity; hence, non-linear optics (NLO) is an alternative name for multi-photon microscopy. It is this non-linear relationship (or third exponential power in the case of three-photon excitation) that determines the axial optical sectioning capability of multi-photon imaging. In this paper, the necessity for two-photon or multi-photon imaging is explained, and the method of optical sectioning by multi-photon microscopy is described. Advice is also given on what fluorescent markers to use and other practical aspects of imaging thick tissues. The technique of Brainbow imaging is discussed. The review concludes with a description of intravital imaging of the mouse. © 2023 Wiley Periodicals LLC.

Detecting vulnerable carotid plaque and its component characteristics: Progress in related imaging techniques

Carotid atherosclerotic plaque rupture and thrombosis are independent risk factors for acute ischemic cerebrovascular disease. Timely identification of vulnerable plaque can help prevent stroke and provide evidence for clinical treatment. Advanced invasive and non-invasive imaging modalities such as computed tomography, magnetic resonance imaging, intravascular ultrasound, optical coherence tomography, and near-infrared spectroscopy can be employed to image and classify carotid atherosclerotic plaques to provide clinically relevant predictors used for patient risk stratification. This study compares existing clinical imaging methods, and the advantages and limitations of different imaging techniques for identifying vulnerable carotid plaque are reviewed to effectively prevent and treat cerebrovascular diseases.

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.

Autofluorescent Biomolecules in Diptera: From Structure to Metabolism and Behavior

Light-based phenomena in insects have long attracted researchers’ attention. Surface color distribution patterns are commonly used for taxonomical purposes, while optically-active structures from Coleoptera cuticle or Lepidoptera wings have inspired technological applications, such as biosensors and energy accumulation devices. In Diptera, besides optically-based phenomena, biomolecules able to fluoresce can act as markers of bio-metabolic, structural and behavioral features. Resilin or chitinous compounds, with their respective blue or green-to-red autofluorescence (AF), are commonly related to biomechanical and structural properties, helpful to clarify the mechanisms underlying substrate adhesion of ectoparasites’ leg appendages, or the antennal abilities in tuning sound detection. Metarhodopsin, a red fluorescing photoproduct of rhodopsin, allows to investigate visual mechanisms, whereas NAD(P)H and flavins, commonly relatable to energy metabolism, favor the investigation of sperm vitality. Lipofuscins are AF biomarkers of aging, as well as pteridines, which, similarly to kynurenines, are also exploited in metabolic investigations. Beside the knowledge available in Drosophila melanogaster, a widely used model to study also human disorder and disease mechanisms, here we review optically-based studies in other dipteran species, including mosquitoes and fruit flies, discussing future perspectives for targeted studies with various practical applications, including pest and vector control.

Two-Photon Fluorescence Microscopy and Applications in Angiogenesis and Related Molecular Events

The role of angiogenesis in health and disease have gained considerable momentum in recent years. Visualizing angiogenic patterns and associated events of surrounding vascular beds in response to therapeutic and laboratory-grade biomolecules have become a commonplace in regenerative medicine and the biosciences. To aid imaging investigations in angiogenesis, the two-photon excitation fluorescence microscopy (2PEF), or multiphoton fluorescence microscopy is increasingly utilized in scientific investigations. The 2PEF microscope confers several distinct imaging advantages over other fluorescence excitation microscopy techniques - for the observation of in-depth, three-dimensional vascularity in a variety of tissue formats, including fixed tissue specimens and in vivo vasculature in live specimens. Understanding morphological and subcellular changes that occur in cells and tissues during angiogenesis will provide insights to behavioral responses in diseased states, advance the engineering of physiologically-relevant tissue models and provide biochemical clues for the design of therapeutic strategies. We review the applicability and limitations of the 2PEF microscope on the biophysical and molecular-level signatures of angiogenesis in various tissue models. Imaging techniques and strategies for best practices in 2PEF microscopy will be reviewed.

Looking for a perfect match: multimodal combinations of Raman spectroscopy for biomedical applications

Raman spectroscopy has shown very promising results in medical diagnostics by providing label-free and highly specific molecular information of pathological tissue ex vivo and in vivo. Nevertheless, the high specificity of Raman spectroscopy comes at a price, i.e., low acquisition rate, no direct access to depth information, and limited sampling areas. However, a similar case regarding advantages and disadvantages can also be made for other highly regarded optical modalities, such as optical coherence tomography, autofluorescence imaging and fluorescence spectroscopy, fluorescence lifetime microscopy, second-harmonic generation, and others. While in these modalities the acquisition speed is significantly higher, they have no or only limited molecular specificity and are only sensitive to a small group of molecules. It can be safely stated that a single modality provides only a limited view on a specific aspect of a biological specimen and cannot assess the entire complexity of a sample. To solve this issue, multimodal optical systems, which combine different optical modalities tailored to a particular need, become more and more common in translational research and will be indispensable diagnostic tools in clinical pathology in the near future. These systems can assess different and partially complementary aspects of a sample and provide a distinct set of independent biomarkers. Here, we want to give an overview on the development of multimodal systems that use RS in combination with other optical modalities to improve the diagnostic performance.