Biology subjects

Intes, X.

Publications and source records attributed to Intes, X..

17 recordsLinked to original sources

bioRxiv2025

Depth-Resolved Macroscopic Fluorescence Lifetime Imaging via High-Spatial-Frequency Structured Illumination

SignificanceMacroscopic Fluorescence Lifetime Imaging (MFLI) is a powerful, non-invasive imaging modality that offers robust, physiologically relevant contrast largely independent of fluorophore concentration, excitation intensity, and tissue signal attenuation. However, accurately determining the depth of signal origin remains challenging, potentially leading to ambiguity in biological interpretation. Here, we present a novel optical correction method that effectively eliminates surface signal bias, such as that from skin in preclinical imaging, without the need for chemical clearance. This advancement supports the robust applicability of MFLI in translational research. AimEstablishment of a High Spatial Frequency-Fluorescence Lifetime Imaging (HSF-FLI) framework to selectively isolate subsurface fluorescence (deeper signals) from surface fluorescence, while preserving the accuracy of lifetime estimation. ApproachA modulation transfer function (MTF) that relates spatial frequency to penetration depth was derived using Monte Carlo eXtreme (MCX) simulations (for physics-based modeling) and validated with agar-based capillary phantoms on a time-gated ICCD-DMD system. Depth-independent fluorescence was decomposed into surface and subsurface components through structured three-phase sinusoidal illumination, and nonlinear least squares fitting was applied to recover lifetime or lifetime based parameters maps. HSF-FLI was demonstrated in vivo in mouse models bearing tumor xenogratfs and was cross validated with ex vivo measurements. ResultsWe extensively characterized the performance of High Spatial Frequency-Fluorescence Lifetime Imaging (HSF-FLI) through simulations and tissue-mimicking phantoms. The approach was further validated in vivo by assessing drug delivery in preclinical models using MFLI-FRET (Forster Resonance Energy Transfer). ConclusionBy coupling structured illumination with physics-based depth modeling, HSF-FLI delivers accurate, depth-selective lifetime readouts, setting the stage for robust and fast FLI implementation in translational studies.

bioengineering↗

bioRxiv2025

Real-Time Wide-Field Fluorescence Lifetime Imaging via Single-Snapshot Acquisition for Biomedical Applications

Fluorescence lifetime imaging (FLI) is a powerful tool for investigating molecular processes, microenvironmental parameters, and molecular interactions across tissue to (sub-)cellular levels. Despite its established value in numerous biomedical applications, conventional FLI techniques are hindered by long acquisition times. This limitation restricts their use in real-time scenarios, such as monitoring fast biological processes, studying live organisms, and in environments that require rapid imaging and immediate inference, such as clinical image-guided interventions. Here, we present a novel FLI approach that combines a large-format time-gated SPAD array with dual-gate acquisition capability, alongside a rapid lifetime determination algorithm. This integration allows for real-time fluorescence lifetime estimation through single-snapshot acquisitions, eliminating the need for traditional, time-consuming time-resolved data collection. We demonstrate the scalability and versatility of this method by achieving real-time FLI across challenging biomedical applications, ranging from capturing fast neural dynamics at the microscopic scale, performing multimodal 3D volumetric FLI of tumor organoids at the mesoscopic scale, to macroscale FLI in both direct and highly scattering regimes. Furthermore, we validate its utility in fluorescence lifetime-guided surgical procedures using tissue-mimicking phantoms. Overall, this new methodology significantly enhances the temporal and spatial capabilities of FLI, opening the door to the assessment of fast dynamic biomedical signals. It also enables the seamless integration of FLI into clinical workflows, particularly in applications like fluorescence-guided surgery.

bioengineering↗

bioRxiv2024

A Novel Technique for Fluorescence Lifetime Tomography

Fluorescence lifetime imaging has emerged as a powerful tool for quantitatively assessing the molecular environment of live tissues in vivo. While fluorescence lifetime microscopy (FLIM) is a mature field, achieving effective 3D imaging in deep tissues has remained a significant challenge due to high scattering. In this study, we present a deep neural network-based approach, referred to as AUTO-FLI, which enables both 3D intensity and quantitative lifetime reconstructions at centimeters depth. This Deep Learning (DL)-based method incorporates an in silico framework to accurately generate fluorescence lifetime data for training and validation. The performance of this novel DL model is further validated with experimental data acquired on an anatomically accurate mouse-mimicking phantom. The results demonstrate that AUTO-FLI can provide precise 3D quantitative estimates of both intensity and lifetime distributions in highly scattering media. This method holds great promise for fluorescence lifetime-based molecular imaging at both the mesoscopic and macroscopic scales, with potential applications for pre-clinical translational research and fluorescence-guided surgery.

bioengineering↗

bioRxiv2024

Fluorescence Lifetime Imaging for quantification of targeted drug delivery in varying tumor microenvironments

RationaleTrastuzumab (TZM) is a monoclonal antibody that targets the human epidermal growth factor receptor (HER2) and is clinically used for the treatment of HER2-positive breast tumors. However, the tumor microenvironment can limit the access of TZM to the HER2 targets across the whole tumor and thereby compromise TZMs therapeutic efficacy. An imaging methodology that can non-invasively quantify the binding of TZM-HER2, which is required for therapeutic action, and distribution within tumors with varying tumor microenvironments is much needed. MethodsWe performed near-infrared (NIR) fluorescence lifetime (FLI) Forster Resonance Energy Transfer (FRET) to measure TZM-HER2 binding, using in vitro microscopy and in vivo widefield macroscopy, in HER2 overexpressing breast and ovarian cancer cells and tumor xenografts, respectively. Immunohistochemistry was used to validate in vivo imaging results. ResultsNIR FLI FRET in vitro microscopy data show variations in intracellular distribution of bound TZM in HER2-positive breast AU565 and AU565 tumor-passaged XTM cell lines in comparison to SKOV-3 ovarian cancer cells. Macroscopy FLI (MFLI) FRET in vivo imaging data show that SKOV-3 tumors display reduced TZM binding compared to AU565 and XTM tumors, as validated by ex vivo immunohistochemistry. Moreover, AU565/XTM and SKOV-3 tumor xenografts display different amounts and distributions of TME components, such as collagen and vascularity. Therefore, these results suggest that SKOV-3 tumors are refractory to TZM delivery due to their disrupted vasculature and increased collagen content. ConclusionOur study demonstrates that FLI is a powerful analytical tool to monitor the delivery of antibody drug tumor both in cell cultures and in vivo live systems. Especially, MFLI FRET is a unique imaging modality that can directly quantify target engagement with potential to elucidate the role of the TME in drug delivery efficacy in intact live tumor xenografts.

cancer biology↗

bioRxiv2023

in vivo quantitative FRET small animal imaging: intensity versus lifetime-based FRET

Forster Resonance Energy Transfer (FRET) microscopy is used in numerous biophysical and biomedical applications to monitor inter- and intramolecular interactions and conformational changes in the 2-10 nm range. FRET is currently being extended to in vivo optical imaging, its main application being in quantifying drug-target engagement or drug release in animal models of cancer using organic dye or nanoparticle-labeled probes. Herein, we compared FRET quantification using intensity-based FRET (sensitized emission FRET analysis with the 3-cube approach using an IVIS imager) and macroscopic fluorescence lifetime (MFLI) FRET using a custom system using a time-gated ICCD, for small animal optical in vivo imaging. The analytical expressions and experimental protocols required to quantify the product fD E of the FRET efficiency E and the fraction of donor molecules involved in FRET, fD, are described in detail for both methodologies. Dynamic in vivo FRET quantification of transferrin receptor-transferrin binding was acquired in live intact nude mice upon intravenous injection of near infrared-labeled transferrin FRET pair and benchmarked against in vitro FRET using hybridized oligonucleotides. Even though both in vivo imaging techniques provided similar dynamic trends for receptor-ligand engagement, we demonstrate that MFLI FRET has significant advantages. Whereas the sensitized emission FRET approach using the IVIS imager required 9 measurements (6 of which are used for calibration) acquired from three mice, MFLI FRET needed only one measurement collected from a single mouse, although a control mouse might be needed in a more general situation. Based on our study, MFLI therefore represents the method of choice for longitudinal preclinical FRET studies such as that of targeted drug delivery in intact, live mice. WHY IT MATTERSFRET measurements in live animals open a unique window into drug-target interaction monitoring, by sensing the close proximity between a donor and acceptor-labeled molecular probes. To perform these measurements, a 3-cube fluorescent intensity measurement strategy can be adopted, as is common for in vitro FRET microscopy studies. However, it is challenging to translate this already cumbersome approach to in vivo small animal imaging. Here, we compare this standard approach, for which we provide a revised analytical framework, to a conceptually much simpler and more powerful one based on fluorescence lifetime measurements. Our results demonstrate that the technical challenge of in vivo fluorescence lifetime macroscopic imaging is well worth surmounting to obtain quantitative, whole-animal information regarding molecular drug-target engagement.

biophysics↗

bioRxiv2022

Characterization of fluorescence lifetime of organic fluorophores for molecular imaging in the SWIR window

SignificanceFluorescence lifetime imaging in the short-wave infrared (SWIR) is expected to enable high resolution multiplexed molecular imaging in highly scattering tissue. AimTo characterize the brightness and fluorescence lifetime of commercially available organic SWIR fluorophores and benchmark them against the tail emission of conventional NIR-excited probes. ApproachCharacterization was performed through our established Time-domain Mesoscopic Fluorescence Molecular Tomography (TD-MFMT) system integrated around a TCSPC-SPAD array. Brightness and fluorescence lifetime was measured for NIR and SWIR probes above 1000 nm. Simultaneous probe imaging was then performed to assess their potential for multiplexed studies. ResultsNIR probes outperformed SWIR probes in brightness while the mean fluorescence lifetimes of the SWIR probes were extremely short. The phantom study demonstrated the feasibility of lifetime multiplexing in the SWIR window with both NIR and SWIR probes. ConclusionsLong tail emission of NIR probes outperformed the SWIR probes in brightness beyond 1000 nm. Fluorescence lifetime was readily detectable in the SWIR window, where the SWIR probes showed shorter lifetimes compared to the NIR probes. We demonstrate the feasibility of lifetime multiplexing in the SWIR window, which paves the way for in vivo multiplexed studies of intact tissues at improved resolution.

bioengineering↗

bioRxiv2021

In vitro and in vivo NIR Fluorescence Lifetime Imaging with a time-gated SPAD camera

Near-infrared (NIR) fluorescence lifetime imaging (FLI) provides a unique contrast mechanism to monitor biological parameters and molecular events in vivo. Single-photon avalanche photodiode (SPAD) cameras have been recently demonstrated in FLI microscopy (FLIM) applications, but their suitability for in vivo macroscopic FLI (MFLI) in deep tissues remains to be demonstrated. Herein, we report in vivo NIR MFLI measurement with SwissSPAD2, a large time-gated SPAD camera. We first benchmark its performance in well-controlled in vitro experiments, ranging from monitoring environmental effects on fluorescence lifetime, to quantifying Forster Resonant Energy Transfer (FRET) between dyes. Next, we use it for in vivo studies of target-drug engagement in live and intact tumor xenografts using FRET. Information obtained with SwissSPAD2 was successfully compared to that obtained with a gated-ICCD camera, using two different approaches. Our results demonstrate that SPAD cameras offer a powerful technology for in vivo preclinical applications in the NIR window.

bioengineering↗

bioRxiv2021

Efference information flow during skill acquisition mediates its interaction with medical simulation technology

Despite substantial progress towards establishing virtual reality (VR) simulators as a replacement for physical ones for skill training, its effect on the brain network during skill acquisition has not been well addressed. In this study, we employed portable optical neuroimaging technology and Granger causality approach to uncover the impact of the two medical simulation technologies on the directed functional brain network of the subjects with two different skill levels. The mobile brain-behavior relantionship was evaluated using functional near-infrared spectroscopy (fNIRS) while right-handed subjects performed well-established fundamentals of laparoscopic surgery (FLS) pattern cutting task. A multiple regression path analysis found that the cognitive-action information flow from the right prefrontal cortex to the supplementary motor area statistically significantly predicted the FLS task performance. Here, the skill level (expert vs novice) affected the cognitive-action information flow from the right prefrontal cortex and the efference copy information flow from the left primary motor cortex via supplementary motor area as hub to the cognitive-perception at the left prefrontal cortex, i.e., the action-preception link. The simulation technology (physical vs VR simulator) affected solely the cognitive-action information flow from the right prefrontal cortex to the left primary motor cortex; however, the interaction between the medical simulation technology) and the skill level affected the efference information flow from the left primary motor cortex to the right prefrontal cortex and from the supplementary motor area to the left prefrontal cortex. These discriminative findings are crucial since our VR simulator had face and construct validity. Therefore, our study highlighted the importance of efference information flow within the framework of the perception-action cycle when comparing medical simulation technology for visuomotor skill acquisition.

neuroscience↗

bioRxiv2021

Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator

Functional brain connectivity using functional near-infrared spectroscopy (fNIRS) during a pattern cutting (PC) task was investigated in physical and virtual simulators. 14 right-handed novice medical students were recruited and divided into separate cohorts for physical (N=8) and virtual (N=6) PC training. Functional brain connectivity measured were based on wavelet coherence (WCOH) from task-related oxygenated hemoglobin (HBO2) changes from baseline at left and right prefrontal cortex (LPFC, RPFC), left and right primary motor cortex (LPMC, RPMC), and supplementary motor area (SMA). HBO2 changes within the neurovascular frequency band (0.01-0.07Hz) from long-separation channels were used to compute average inter-regional WCOH metrics during the PC task. The coefficient of variation (CoV) of WCOH metrics and PC performance metrics were compared. WCOH metrics from short-separation fNIRS time-series were separately compared. Partial eta squared effect size (Bonferroni correction) between the physical versus virtual simulator cohorts was found to be highest for LPMC-RPMC connectivity. Also, the percent change in magnitude-squared WCOH metric was statistically (p<0.05) different for LPMC-RPMC connectivity between the physical and the virtual simulator cohorts. Percent change in WCOH metrics from extracerebral sources was not different at the 5% significance level. Also, higher CoV for both LPMC-RPMC magnitude-squared WCOH metric and PC performance metrics were found in physical than a virtual simulator. We conclude that interhemispheric connectivity of the primary motor cortex is the distinguishing functional brain connectivity feature between the physical versus the virtual simulator cohorts. Brain-behavior relationship based on CoV between the LPMC-RPMC magnitude-squared WCOH metric and the FLS PC performance metric provided novel insights into the neuroergonomics of the physical and virtual simulators that is crucial for validating Virtual Reality technology.

neuroscience↗

bioRxiv2020

Accelerating Monte Carlo modeling of structured-light based diffuse optical imaging via "photon sharing"

The increasing use of spatially-modulated imaging and single-pixel detection techniques demands computationally efficient methods for light transport modeling. Herein, we report an easy-to-implement yet significantly more efficient Monte Carlo (MC) method for simultaneously simulating spatially modulated illumination and detection patterns accurately in 3-D complex domains. We have implemented this accelerated algorithm, named "photon sharing", in our open-source MC simulators, reporting 13.6x and 5.5x speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used for accelerating the solving of inverse problems in spatially-modulated imaging systems by building Jaco-bians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement. https://doi.org/10.1101/2020.02.16.951590

biophysics↗

bioRxiv2020

Deep Learning Enhanced Hyperspectral Fluorescence Lifetime Imaging

Acquiring dense high-dimensional optical data in biological applications remains a challenge due to the very low levels of light typically encountered. Single pixel imaging methodologies enable improved detection efficiency in such conditions but are still limited by relatively slow acquisition times. Here, we propose a Deep Learning framework, NetFLICS-CR, which enables fast hyperspectral lifetime imaging for in vivo applications at enhanced resolution, acquisition and processing speeds, without the need of experimental training datasets. NetFLICS-CR reconstructs intensity and lifetime images at 128x128 pixels over 16 spectral channels while reducing the current acquisition times from [~]2.5 hours at 50% compression to [~]3 minutes at 99% compression when using a single-pixel Hyperspectral Macroscopic Fluorescence Lifetime Imaging (HMFLI) system. The potential of the technique is demonstrated in silico, in vitro and in vivo through the monitoring of receptor-ligand interactions in mice liver and bladder and further imaging of intracellular drug delivery of the clinical drug Trastuzumab in live animals bearing HER2-positive breast tumor xenografts.

biophysics↗

bioRxiv2019

Multiplexed Non-invasive in vivo Imaging to Assess Metabolism and Receptor Engagement in Tumor Xenografts

Following an ever-increased focus on personalized medicine, there is a continuing need to develop preclinical molecular imaging modalities to guide the development and optimization of targeted therapies. To date, non-invasive quantitative imaging modalities that can comprehensively assess simultaneous cellular drug delivery efficacy and therapeutic response are lacking. In this regard, Near-Infrared (NIR) Macroscopic Fluorescence Lifetime Forster Resonance Energy Transfer (MFLI-FRET) imaging offers a unique method to robustly quantify receptor-ligand engagement in vivo and subsequent intracellular internalization, which is critical to assess the delivery efficacy of targeted therapeutics. However, implementation of multiplexing optical imaging with FRET in vivo is challenging to achieve due to spectral crowding and cross-contamination. Herein, we report on a strategy that relies on a dark quencher that enables simultaneous assessment of receptor-ligand engagement and tumor metabolism in intact live mice. First, we establish that IRDye QC-1 (QC-1) is an effective NIR dark acceptor for the FRET-induced quenching of donor Alexa Fluor 700 (AF700) using in vitro NIR FLI microscopy and in vivo wide-field MFLI imaging. Second, we report on simultaneous in vivo imaging of the metabolic probe IRDye 800CW 2-deoxyglucose (2-DG) and MFLI-FRET imaging of NIR-labeled transferrin FRET pair (Tf-AF700/Tf-QC-1) uptake in tumors. Such multiplexed imaging revealed an inverse relationship between 2-DG uptake and Tf intracellular delivery, suggesting that 2-DG signal may predict the efficacy of intracellular targeted delivery. Overall, our methodology enables for the first time simultaneous non-invasive monitoring of intracellular drug delivery and metabolic response in preclinical studies.

bioengineering↗

bioRxiv2019

Spectral and lifetime fluorescence unmixing via deep learning

Hyperspectral Fluorescence Lifetime Imaging allows for the simultaneous acquisition of spectrally resolved temporal fluorescence emission decays. In turn, the acquired rich multidimensional data set enables simultaneous imaging of multiple fluorescent species for a comprehensive molecular assessment of biotissues. However, to enable quantitative imaging, inherent spectral overlap between the considered fluorescent probes and potential bleed-through must be taken into account. Such task is performed via either spectral or lifetime unmixing, typically independently. Herein, we present UNMIX-ME (unmix multiple emissions), a deep learning-based fluorescence unmixing routine, capable of quantitative fluorophore unmixing by simultaneously using both spectral and temporal signatures. UNMIX-ME was trained and validated using an in silico framework replicating the data acquisition process of a compressive hyperspectral fluorescent lifetime imaging platform (HMFLI). It was benchmarked against a conventional LSQ method for both tri and quadri-exponential simulated samples. Last, UNMIX-MEs potential was assessed for NIR FRET in vitro and in vivo for small animal experimental data.

bioengineering↗

bioRxiv2019

High-Resolution Tomographic Analysis of in vitro 3D Glioblastoma Tumor Model under Long-Term Drug Treatment

Glioblastoma multiforme (GBM) is an extremely lethal type of brain tumor as it frequently develops therapeutic resistance over months of chemotherapy cycles. Hence, there is a critical need to provide relevant biological systems to guide the development of new potent personalized drugs but also efficient methodologies that enable personalized prediction of various therapeutic regimens for enhanced patient prognosis. Towards this goal, we report on the development of i) an appropriate in vitro model that mimics the 3D tumor microenvironment and ii) a companion imaging modality that enables to assess this in vitro model in its entirety. More precisely, we developed an integrated platform of bio-printing in vitro 3D GBM models and mesoscopic imaging to monitor tumor growth and invasion along with long-term drug treatment. The newly-developed in vitro 3D model contains tumor spheroids made of patient-derived glioma stem cells with a fluorescent reporter and vascular channels for drug perfusion. The imaging of these thick tissue constructs was performed using our second-Generation Mesoscopic Fluorescence Molecular Tomography (2GMFMT) imaging system which delivered 3D reconstruction of the fluidic channels and the GBM spheroids over the course of pre- and post-drug treatment (up to 70 days). The 2D measurements collected via 2GMFMT was comparable to existing imaging modalities, but 2GMFMT enabled non-sacrificial volumetric monitoring that provided a unique insgiht into the GBM spheroid growth and drug response. Overall, our integrated platform provides customizable in vitro model systems combined with an efficient long-term non-sacrificial imaging for the volumetric change of tumor mass, thus has a great potential in profoundly affecting the drug pipeline for a vast array of pathologies as well as for guiding personalized therapeutic regimen.

bioengineering↗

bioRxiv2019

Ultra-fast fit-free analysis of complex fluorescence lifetime imaging via deep learning

Fluorescence lifetime imaging (FLI) provides unique quantitative information in biomedical and molecular biology studies, but relies on complex data fitting techniques to derive the quantities of interest. Herein, we propose a novel fit-free approach in FLI image formation that is based on Deep Learning (DL) to quantify complex fluorescence decays simultaneously over a whole image and at ultra-fast speeds. Our deep neural network (DNN), named FLI-Net, is designed and model-based trained to provide all lifetime-based parameters that are typically employed in the field. We demonstrate the accuracy and generalizability of FLI-Net by performing quantitative microscopic and preclinical experimental lifetime-based studies across the visible and NIR spectra, as well as across the two main data acquisition technologies. Our results demonstrate that FLI-Net is well suited to quantify complex fluorescence lifetimes, accurately, in real time in cells and intact animals without any parameter settings. Hence, it paves the way to reproducible and quantitative lifetime studies at unprecedented speeds, for improved dissemination and impact of FLI in many important biomedical applications, especially in clinical settings.

bioengineering↗

bioRxiv2018

In vitro and in vivo phasor analysis of stoichiometry and pharmacokinetics using near-infrared dyes

1We introduce a simple new approach for time-resolved multiplexed analysis of complex systems using near-infrared (NIR) dyes, applicable to in vitro and in vivo studies. We first show that fast and precise in vitro quantification of NIR fluorophores lifetime and stoichiometry can be done using phasor analysis, a computationally efficient and user-friendly representation of complex fluorescence intensity decays obtained with pulsed laser excitation. We apply this approach to the study of binding equilibria by Forster resonant energy transfer (FRET), using two different model systems: primary/secondary antibody binding in vitro and ligand/receptor binding in cell cultures. We then extend our demonstration to dynamic imaging of the pharmacokinetics of transferrin binding to the transferrin receptor in live mice, elucidating the kinetic of differential transferrin accumulation in specific organs, straightforwardly differentiating specific from non-specific binding. Our method, implemented in a freely-available software package, has all the advantages of time-resolved NIR imaging, including better tissue penetration and background-free imaging, but simplifies and considerably speeds up data processing and interpretation, while remaining quantitative. These advances make this method attractive and of broad applicability for in vitro and in vivo molecular imaging, and could be extended to applications as diverse as image guided-surgery or optical tomography.

bioengineering↗

bioRxiv2017

Quantitative Imaging of Receptor-Ligand Engagement in Intact Live Animals

Maintaining an intact tumor environment is critical for quantitation of receptor-ligand engagement in a targeted drug development pipeline. However, measuring receptor-ligand engagement in vivo and non-invasively in preclinical settings is extremely challenging. We found that quantitation of intracellular receptor-ligand binding can be achieved using whole-body macroscopic lifetime-based Forster Resonance Energy Transfer (FRET) imaging in intact, live animals bearing tumor xenografts. We determined that FRET levels report on ligand binding to transferrin receptors conversely to raw fluorescence intensity. We then established that FRET levels in heterogeneous tumors correlate with intracellular ligand binding but strikingly, not with ubiquitously used ex vivo receptor expression assessment. Hence, MFLI-FRET provides a direct measurement of systemic delivery, target availability and intracellular drug delivery in intact animals. Here, we have used MFLI to measure FRET longitudinally in intact animals for the first time. MFLI-FRET is well-suited for guiding the development of targeted drug therapy in heterogeneous intact, live small animals.

cancer biology↗