We present a learning-enabled lens-free microscope for quantitative analysis of cell cultures. Leveraging the advances of recent years in learning algorithms, we developed a suite of neural networks that detect, quantify and track the cells. The detection algorithm locates the cells. The quantification algorithm, measures different cell metrics directly from cell phase image patches centred on the cells detections. Measured features include among others: cell morphology (dry mass, thickness, aspect ratio, ...) and local neighbourhood (density, contact surface, …). Finally, the tracking algorithm predicts the position of a given cell at next time point, making it possible to monitor a cell across time. To train these models we designed a semi-automated pipeline able to generate a supervised training datasets of up to millions of cells. The measurements obtained from the proposed method open up for modelling the cell cultures and providing biological insights.
We present a diffraction-phase and fluorescence 3D microscope as novel bimodal imaging technique, which provides simultaneous phase and multi-color epi-fluorescence acquisitions of living multicellular samples. The instrument consists of an LED-array to acquire intensity images at different illumination angles and an epifluorescence setup for fluorescence excitation. The 3D sample’s optical properties are reconstructed using the beam propagation method embedded inside a deep learning framework. To obtain the fluorescence reconstructions, we developed a novel incoherent model that takes into account the heterogeneous refractive indexes of the scattering sample. We validated the technique on long-term acquisitions of mouse embryos and 3D liver organoids under physiological conditions.
One of the directions of development in quantitative phase imaging is to provide the capability to reconstruct the phase or preferably refractive index (RI) distribution within thick, highly scattering samples. This direction coincides with current trends in biology, where three-dimensional (3D) organoids are currently replacing standard 2D cultures as more physiological models for tissue growth and organ formation in a dish. The biological complexity of these 3D structures makes the imaging and RI reconstruction particularly challenging, and thus calibration as well as validation structures are important and sought-after tools in instrumentation development. For this reason, in this work, we present the full preparation and measurement procedure for organoid phantoms printed with two-photon polymerization along with the method to obtain the ground truth of the object structure independently of RI reconstruction errors and artifacts.
Cellular heterogeneity is the hallmark of many cancers, referring to the co-existence of different phenotypes with very distinct biological behaviours in single isolates. Automatically detecting single-cell heterogeneity is therefore critical, and can provide important information on cancer initiation. We present a clustering algorithm that allows identifying heterogeneity in cell culture from time-lapses of lensless microscopic images. A preliminary segmentation and tracking pipeline extract quantitative features (morphology, motility and reproduction cycle) for each cell. An unsupervised learning algorithm then clusters the time-series of the cell tracks measurements, in two steps. We validate our approach on co-cultures of mixed cells lines, and on murine fibroblasts isolated from genetically modified mice, where the modified genome promotes the establishment of cancers and heterogeneous cell morphologies and behaviours
Significance: Multi-laboratory initiatives are essential in performance assessment and standardization—crucial for bringing biophotonics to mature clinical use—to establish protocols and develop reference tissue phantoms that all will allow universal instrument comparison.
Aim: The largest multi-laboratory comparison of performance assessment in near-infrared diffuse optics is presented, involving 28 instruments and 12 institutions on a total of eight experiments based on three consolidated protocols (BIP, MEDPHOT, and NEUROPT) as implemented on three kits of tissue phantoms. A total of 20 synthetic indicators were extracted from the dataset, some of them defined here anew.
Approach: The exercise stems from the Innovative Training Network BitMap funded by the European Commission and expanded to include other European laboratories. A large variety of diffuse optics instruments were considered, based on different approaches (time domain/frequency domain/continuous wave), at various stages of maturity and designed for different applications (e.g., oximetry, spectroscopy, and imaging).
Results: This study highlights a substantial difference in hardware performances (e.g., nine decades in responsivity, four decades in dark count rate, and one decade in temporal resolution). Agreement in the estimates of homogeneous optical properties was within 12% of the median value for half of the systems, with a temporal stability of <5 % over 1 h, and day-to-day reproducibility of <3 % . Other tests encompassed linearity, crosstalk, uncertainty, and detection of optical inhomogeneities.
Conclusions: This extensive multi-laboratory exercise provides a detailed assessment of near-infrared Diffuse optical instruments and can be used for reference grading. The dataset—available soon in an open data repository—can be evaluated in multiple ways, for instance, to compare different analysis tools or study the impact of hardware implementations.
We present a CNN-based quantification pipeline for the imaging and analysis of adherent cell cultures. The imaging part features two CNNs dedicated to lens-free microscopy performing accelerated holographic reconstruction and phase unwrapping. The analysis part features CNNs estimating several cellular metrics. These CNNs maps phase image into 2D quantitative representations of cell positions and measurements. The outputs images are processed by a local maxima algorithm to obtain a list of cell measurements. Here, we discuss the performance and limitations of this CNN-based quantification pipeline. The advantage is the fast processing time, i.e. the analysis of ~10.000 cells in 10 seconds.
KEYWORDS: 3D image processing, Tomography, Live cell imaging, Diffraction, 3D modeling, 3D acquisition, Beam propagation method, 3D metrology, Spatial resolution, Scattering
Intensity diffraction tomography (IDT) is a 3D phase imaging technique that enables the reconstruction of the refractive indexes (RIs) and absorption of a sample. IDT targets biological imaging in a label-free manner using the optical variation within the sample and multiple tilted imaging to reconstruct the 3D map of RIs. However, standard IDT techniques reveal several drawbacks in terms of limited field of view and feasibility of imaging living samples in time-lapse conditions. We focused on time-lapse imaging of large sample (>100µm) without the need of large NA objective or immersion oil.
The challenge created by the absence of the phase information (intensity only measurements) as well as the limited illumination angle (low NA due to low magnification) has been solved using a Beam Propagation Method (BPM) embedded inside a deep leaning framework, that we call “physical neural network”. This network layers are encoding the 3D optical representation of the sample. Besides, we included in the forward model the effect of the spherical aberration introduced by the optical interfaces, which gave a strong impact on measurements under oblique illumination in terms of 3D spatial resolution.
Using this framework, we achieved 3D reconstructions of mouse embryos (>100µm) in time-lapse conditions over 7 days, observing the intrinsic embryonic development from single cell (low-scattering sample) to the blastocyst level (highly scattering sample). Such time-lapse yields quantitative information on the development and viability of embryos in view of the sub-cellular imaging capacities. Our technology opens up novel opportunities for 3D live cell imaging of whole organoids in time-lapse.
Optical diffraction tomography allows retrieving the 3D refractive index in a non-invasive and label-free manner. A sample is illuminated from various angles and the intensity of the diffracted light is recorded. The light wave can be calculated layer after layer and the inverse problem is usually solved using a gradient descent based algorithm.
Here we propose a solution to solve the inverse problem using a neural network where the weights of each layer are the unknown refractive index of the object. Importantly, the matrix product between each layers is replaced by the physics of light propagation.
Performance assessment and standardization are indispensable for instruments of clinical relevance in general and clinical instrumentation based on photon migration/diffuse optics in particular. In this direction, a multi-laboratory exercise was initiated with the aim of assessing and comparing their performances. 29 diffuse optical instruments belonging to 11 partner institutions of a European level Marie Curie Consortium BitMap1 were considered for this exercise. The enrolled instruments covered different approaches (continuous wave, CW; frequency domain, FD; time domain, TD and spatial frequency domain imaging, SFDI) and applications (e.g. mammography, oximetry, functional imaging, tissue spectroscopy). 10 different tests from 3 well-accepted protocols, namely, the MEDPHOT2 , the BIP3 , and the nEUROPt4 protocols were chosen for the exercise and the necessary phantoms kits were circulated across labs and institutions enrolled in the study. A brief outline of the methodology of the exercise is presented here. Mainly, the design of some of the synthetic descriptors, (single numeric values used to summarize the result of a test and facilitate comparison between instruments) for some of the tests will be discussed.. Future actions of the exercise aim at deploying these measurements onto an open data repository and investigating common analysis tools for the whole dataset.
We designed a particularly simple, compact and robust microscope for phase and fluorescent imaging. The phase-contrast image is reconstructed from a single, approximately 100 µm defocused image with an algorithm based on a constrained optimization of Fresnel diffraction model. Fluorescence image is recorded in-focus. No mechanical movement of neither sample nor objective or any other part of the system is needed to change between the phase-contrast and fluorescence modality. The change of focus between phase (out-of-focus) and fluorescence (in-focus) imaging is achieved with chromatic aberration specifically enhanced by the optical design of our system. Our microscope is sufficiently compact (10x10x10 cm^3) to fit into a standard biological incubator. The simple and robust design reduces the vibration and the drift of the sample. The absence of motorized components makes the system robust and resistant to the humid conditions inside the biological incubator. These aspects greatly facilitate the long-time observation of cell cultures.
We can observe a thousand of cells in parallel in a single field of view (1mm^2) with resolution down to 2 µm. We show FUCCI marked HeLa cell culture observed over three days directly in the incubator. FUCCI (fluorescence ubiquitination cell-cycle indicator), is a genetically encoded, two-colour (red and green), indicator of the progression through the cell cycle: the cells in G1 phase show red fluorescence nuclei while the cells in S, G2 and M phase display green fluorescence within the nuclei.
We use phase images for segmentation and tracking of the individual cells which allows us to determine the level of fluorescence in each cell in the green and red fluorescence channel. We compare the obtained statistics with the data from flow cytometer acquired at the end of the observation. We show that we can produce a statistically relevant time-resolved measurement of a cell population while keeping access to the individual cells.
Research is continuously developing imaging methods to better understand the structure and function of biological systems. In this paper, we describe our work to develop lens-free microscopy as a novel mean to observe and quantify cells in 2D and 3D cell culture conditions.
At first, we developed a lens-free video microscope based on multiple wavelength acquisitions to perform time-lapse 2D imaging of dense cell culture inside the incubator. We demonstrated that novel phase retrieval techniques enable imaging thin cell samples with high concentration (~15000 cells over a large field of view of 29.4 mm2). The experimental data can next be further analyzed with existing cell profiling and tracking algorithms. As an example, we showed that a 7 days acquisition of a culture of HeLa cells leads to a dataset featuring 2.106 cell point measurements and 104 cell cycle tracks.
Recently, we extended our work to the video-microscopy of 3D organoids culture. We showed the capability of lens-free microscopy to perform 3D+time acquisitions of 3D organoids culture. To our knowledge, our technique is the only one able to reconstruct very large volumes of 3D cell culture (~5 mm3) by phase contrast imaging. This new mean of microscopy allowed us to observe a broad range of phenomena present in 3D environments, e.g. self-organizations, displacement of large clusters, merging and interconnection over long distances (>1 mm). In addition, this 3D microscope can capture the interactions of single cells and organoids with their 3D environment, e.g. traction forces generated by large cell aggregates over long distances, up to 1.5 mm.
Overall, lens-free microscopy techniques favor ease of use and label-free experimentations as well as time-lapse acquisitions of large datasets. Importantly, we consider that these lens-free microscopy technique can thus expand the repertoire of phenomena that can be studied within 2D and 3D organoids cultures.
Lens-free microscopy aims at recovering sample image from diffraction measurements. The acquisitions are usually processed with an inverse problem approach to retrieve the sample image (phase and absorption). The perfect reconstruction of the sample image is however difficult to achieve. Mostly because of the lack of phase information in the recording process. Recently, deep learning has been used to circumvent this challenge. Convolutional neural networks can be applied to the reconstructed image as a single pass to improve e.g. the signal-to noise ratio or the spatial resolution. Here as an alternative, we propose to alternate between the two classes of algorithms, between the inverse problem approach and the data driven approach. In doing so we intend to improve the reconstruction results but also and importantly try to address the concerns associated with the use of deep learning, namely the generalization and hallucination problems. To demonstrate the applicability of our novel approach we choose to address the case of floating cells sample acquired by means of lens-free microscopy. This is a challenging case with a lot of phase wrapping artifacts that has never been solved using inverse problem approaches only. We demonstrate that our approach is successful in performing the phase unwrapping and that it can next be applied to a very different cell sample, namely the cultures of adherent mammalian cell lines.
Lens-free microscopy aims at recovering sample image from diffraction measurements. The acquisitions are usually processed with an inverse problem approach. Recently, deep learning has been used to further improve phase retrieval results. Here, we propose to alternate iteratively between the two algorithms, to improve the reconstruction results without losing data fidelity. We validated this method for the phase image recovery of floating cells sample at large density acquired by means of lens-free microscopy. This is a challenging case with a lot of phase wrapping artefacts that has never been successfully solved using inverse problem approaches only.
We designed a simple, compact and robust microscope for phase and fluorescent imaging. No mechanical movement of neither sample nor objective or any other part of the system is needed to change between the phase-contrast and fluorescence modality. We can observe a thousand cells in parallel in a single field of view with resolution down to 2 µm. We demonstrate the system on a FUCCI marked HeLa cell culture observed over several days directly in the standard incubator. We compare the obtained statistics to the flow cytometer data and show that we can produce a statistically relevant time-resolved measurement
Lens-Free microscopy aims at recovering an observed object such as cell cultures from its diffraction measurements. Diffraction acquisitions are processed with an inverse problem approach to recover optical path difference (OPD) images of the object. Phase unwrapping issue is solved here by using a convolutional neural network (CNN) trained on simulations. The procedure was applied successfully on a neuron cells culture video acquisition.
Performance assessment of instruments is a growing demand in the diffuse optics community and there is a definite need to get together to address this issue. Within the EU Network BITMAP1, we initiated a campaign for the performance evaluation of 10 diffuse optical instrumentation from 7 partner institutions adopting a set of 3 well accepted, standardized protocols. A preliminary analysis of the outcome along with future perspectives will be presented.
Open Data philosophy is becoming more popular among scientists. Open Data approach aims to transform science by making high-quality and well-documented scientific data open to everybody in order to promote collaboration and transparency. In diffuse optical and near-infrared spectroscopy community, a large measurement dataset collected with state-of-the-art instrumentation applied on well-defined phantoms is still missing. Within that context, several European labs from BitMap network1 have collected diffuse optical data on standard phantoms involving the largest set of diffuse optics instruments published until now. In this work, we present a running project on the open dataset and associated reporting tools.
Diffuse optical tomography (DOT) estimates the optical properties inside a turbid medium by injecting light from the surface and measuring the reflected photons. In time-resolved technology, since to perform DOT reconstruction at time domain is too computationally expensive, datatypes are used instead. Temporal windows are the most used datatypes but until now just w(t) = tne−pt forms could be computed fast. In this work, we propose a new method to compute efficiently a larger set of window datatypes. The results show that with these new windows (1) the localization of inclusions deeper than 2.5 cm is improved and (2) the absorption quantification is ameliorated at all inclusion depths.
Quantitative phase imaging (QPI) allows the monitoring of adherent cell cultures continuously over long time periods and it delivers an image of the cell with pixel intensities corresponding to the optical path difference (OPD). These images can be processed to quantify several cellular features. In particular, cell OPD measurements allows the estimation of the cell dry mass, an important metric to study cell mass and growth kinetics.
If the ability of QPI to provide phase-contrast images of cells is taken for granted, the accuracy and the precision of QPI cell OPD measurements can still be questioned. Indeed, the reported QPI cell measurements have not yet been assessed with any reference method (e.g. microfluidic resonators). And there is a lack of independent experimental comparison and validation which can hinder the acceptance of QPI in the realms of live-cell mass profiling.
With the aim of filling this gap, here we compare three different methods: digital holographic microscopy, quadriwave lateral sheering interferometry and lens-free microscopy (not yet established as a QPI technique). The experimental design is based on the inter-modality comparisons of OPD measurements performed over several tens of cells. To ensure consistency, we performed OPD measurements on a fixed cell culture the same day on the same location. Importantly, the statistical analysis of these measurements allowed us to estimate the precision of QPI cell OPD measurements without any reference material. In addition, we have evaluated the influence of the post-processing steps (baseline subtraction, cell segmentation) on the precision of QPI cell measurements.
We propose a simple and compact microscope combining phase imaging with fluorescence. This compact setup can be easily inserted in a standard biological incubator and allows observation of cellular cultures over several days. Phase image of the sample is reconstructed from a single, slightly (~50 μm) defocused image taken under semi-coherent illumination. Fluorescence in-focus image is recorded in epi-fluorescence geometry. The phase and fluorescence images are taken sequentially using a single CMOS camera. No mechanical movement of neither sample nor objective is required to change the imaging modality. The only change is the wavelength of illumination and excitation light for phase and fluorescence imaging, respectively. The slight defocus needed for phase imaging is achieved due to specifically introduced chromatic aberration in the imaging system.
We present dual modality time-lapse movies of cellular cultures observed over several days in physiological conditions inside an incubator. A field-of-view of 3 mm2 allows observation up to thousands of cells with micro-meter spatial resolution in quasi-simultaneous phase and fluorescence mode. We believe that the simplicity, small dimensions, ease-of-use and low cost of the system make it a useful tool for biological research
We present our implementation of lens-free video microscopy setup for the monitoring of adherent cell cultures. We use a multi-wavelength LED illumination together with a dedicated holographic reconstruction algorithm that allows for an efficient removal of twin images from the reconstructed phase image for densities up to those of confluent cell cultures (>500 cells/mm2). We thereby demonstrate that lens-free video microscopy, with a large field of view (~30 mm2) can enable us to capture the images of thousands of cells simultaneously and directly inside the incubator. It is then possible to trace and quantify single cells along several cell cycles. We thus prove that lens-free microscopy is a quantitative phase imaging technique enabling estimation of several metrics at the single cell level as a function of time, for example the area, dry mass, maximum thickness, major axis length and aspect ratio of each cell. Combined with cell tracking, it is then possible to extract important parameters such as the initial cell dry mass (just after cell division), the final cell dry mass (just before cell division), the average cell growth rate, and the cell cycle duration. As an example, we discuss the monitoring of a HeLa cell cultures which provided us with a data-set featuring more than 10 000 cell cycle tracks and more than 2x106 cell morphological measurements in a single time-lapse.
We present a simple and compact phase imaging microscope for long-term observation of non-absorbing biological samples such as unstained cells in nutritive media. The phase image is obtained from a single defocused image taken with a standard wide-field microscope. Using a semi-coherent light source allows us to computationally re-focus image post-acquisition and recover both phase and transmission of the complex specimen. The simplicity of the system reduces both the cost and its physical size and allows a long-term observation of samples directly in a standard biological incubator. The low cost of the system can contribute to the democratization of science by allowing to perform complex long-term biological experiments to the laboratories with constrained budget. In this proceeding we present several results taken with our prototype and discuss the possibilities and limitations of our system.
We introduce a label-free technique based on lens-free microscopy to perform cell counting and cell viability assay. Without the use of any labelling, the discrimination between alive and dead cells is obtained by analyzing the cells on the basis of their holographic signature. We have assessed this novel technique by comparing the obtained results in terms of viability and cell counting against automatic optical counting and trypan blue staining as reference methods. The lensfree measurements agree very well with the reference techniques up to ~30.106 cells/ml. We found a coefficient of determination R2 of 0.99 and a slope of 1.01 for the viability measurements (N=84 CHO cell samples).
The cytology of the cerebrospinal fluid is traditionally performed by an operator (physician, biologist) by means of a conventional light microscope. The operator visually counts the leukocytes (white blood cells) present in a sample of cerebrospinal fluid (10 μl). It is a tedious job and the result is operator-dependent. Here in order to circumvent the limitations of manual counting, we approach the question of numeration of erythrocytes and leukocytes for the cytological diagnosis of meningitis by means of lens-free microscopy. In a first step, a prospective counts of leukocytes was performed by five different operators using conventional optical microscopy. The visual counting yielded an overall 16.7% misclassification of 72 cerebrospinal fluid specimens in meningitis/non-meningitis categories using a 10 leukocyte/μL cut-off. In a second step, the lens-free microscopy algorithm was adapted step-by-step for counting cerebrospinal fluid cells and discriminating leukocytes from erythrocytes. The optimization of the automatic lens-free counting was based on the prospective analysis of 215 cerebrospinal fluid specimens. The optimized algorithm yielded a 100% sensitivity and a 86% specificity compared to confirmed diagnostics. In a third step, a blind lens-free microscopic analysis of 116 cerebrospinal fluid specimens, including six cases of microbiology confirmed infectious meningitis, yielded a 100% sensitivity and a 79% specificity. Adapted lens-free microscopy is thus emerging as an operator-independent technique for the rapid numeration of leukocytes and erythrocytes in cerebrospinal fluid. In particular, this technique is well suited to the rapid diagnosis of meningitis at point-of-care laboratories.
To evaluated capabilities of multispectral TD-DOT systems in reflection geometry, we
performed a measurement campaign on multimaterial composition phantoms. Results show correct
composition gradation of inclusions but still lack absolute accuracy.
Pathologist examination of tissue slides provides insightful information about a patient’s disease. Traditional analysis of tissue slides is performed under a binocular microscope, which requires staining of the sample and delays the examination. We present a simple cost-effective lensfree imaging method to record 2–4μm resolution wide-field (10 mm2 to 6 cm2) images of unstained tissue slides. The sample processing time is reduced as there is no need for staining. A wide field of view (10 mm2) lensfree hologram is recorded in a single shot and the image is reconstructed in 2s providing a very fast acquisition chain. The acquisition is multispectral, i.e. multiple holograms are recorded simultaneously at three different wavelengths, and a dedicated holographic reconstruction algorithm is used to retrieve both amplitude and phase. Whole tissue slides imaging is obtained by recording 130 holograms with X-Y translation stages and by computing the mosaic of a 25 x 25 mm2 reconstructed image. The reconstructed phase provides a phase-contrast-like image of the unstained specimen, revealing structures of healthy and diseased tissue. Slides from various organs can be reconstructed, e.g. lung, colon, ganglion, etc. To our knowledge, our method is the first technique that enables fast wide-field lensfree imaging of such unlabeled dense samples. This technique is much cheaper and compact than a conventional phase contrast microscope and could be made portable. In sum, we present a new methodology that could quickly provide useful information when a rapid diagnosis is needed, such as tumor margin identification on frozen section biopsies during surgery.
The noninvasive assessment of flap viability in autologous reconstruction surgery is still an unmet clinical need. To cope with this problem, we developed a proof-of-principle fully automatized setup for fast time-gated diffuse optical tomography exploiting Mellin–Laplace transform to obtain three-dimensional tomographic reconstructions of oxy- and deoxy-hemoglobin concentrations. We applied this method to perform preclinical tests on rats inducing total venous occlusion in the cutaneous abdominal flaps. Notwithstanding the use of just four source-detector couples, we could detect a spatially localized increase of deoxyhemoglobin following the occlusion (up to 550 μM in 54 min). Such capability to image spatio-temporal evolution of blood perfusion is a key issue for the noninvasive monitoring of flap viability.
Intraoperative fluorescence imaging in reflectance geometry is an attractive imaging modality as it allows to noninvasively monitor the fluorescence targeted tumors located below the tissue surface. Some drawbacks of this technique are the background fluorescence decreasing the contrast and absorption heterogeneities leading to misinterpretations concerning fluorescence concentrations. We propose a correction technique based on a laser line scanning illumination scheme. We scan the medium with the laser line and acquire, at each position of the line, both fluorescence and excitation images. We then use the finding that there is a relationship between the excitation intensity profile and the background fluorescence one to predict the amount of signal to subtract from the fluorescence images to get a better contrast. As the light absorption information is contained both in fluorescence and excitation images, this method also permits us to correct the effects of absorption heterogeneities. This technique has been validated on simulations and experimentally. Fluorescent inclusions are observed in several configurations at depths ranging from 1 mm to 1 cm. Results obtained with this technique are compared with those obtained with a classical wide-field detection scheme for contrast enhancement and with the fluorescence by an excitation ratio approach for absorption correction.
Near-infrared diffuse optical tomography (DOT) is a medical imaging which gives the distribution of the optical properties of biological tissues. To obtain endogenous chromophore features in the depth of a scattering medium, a multiwavelength/time-resolved (MW/TR) DOT setup was used. Reconstructions of the three-dimensional maps of chromophore concentrations of probed media were obtained by using a data processing technique which manages Mellin-Laplace Transforms of their MW/TR optical signals and those of a known reference medium. The point was to
put a constraint on the medium absorption coefficient by using a material basis composed of a given set of chromophores of known absorption spectra. Experimental measurements were conducted by injecting the light of a picosecond near-
infrared laser in the medium of interest and by collecting, for several wavelengths and multiple positions, the backscattered light via two fibers (with a source-detector separation of 15 mm) connected to fast-gated single-photon
avalanche diodes (SPAD) and coupled to a time-correlated single-photon counting (TCSPC) system. Validations of the method were performed in simulation in the same configuration as the experiments for different combination of chromophores. Evaluation of the technique in real conditions was investigated on liquid phantoms composed of an
homogenous background and a 10 mm depth inclusion formed of combination of intralipid and inks scanned at 30
positions and at three wavelengths. Both numerical and preliminary phantom experiments confirm the potential of this method to determine chromophore concentrations in the depth of biological tissues.
We conducted a preclinical assessment on young macaques aimed at detecting white matter lesions. We present the protocol we implemented to achieve the lesions detection using a bedside non-invasive optical-based Time-Resolved instrumentation we have optimized for this purpose. We validated the reconstructed 3D absorption map with co-registration of MRI data.
KEYWORDS: Detection and tracking algorithms, Video microscopy, Video, Image segmentation, Microscopes, Signal to noise ratio, Holography, Cell death, Time metrology, Reconstruction algorithms
In order to extend the analysis of the datasets produced by lensfree video microscopy we have implemented a cell tracking algorithm to combine and correlate cell motility to the previously devised metrics to quantify e.g. cell adhesion and spreading, cell division, and cell death. In this paper we present the assessment of these new methodology on experiments involving three different cell lines, namely 3T3 fibroblast cells, primary HUVEC cells and macrophage THP1 cells. We demonstrate that the good spatial resolution and the fast frame rate obtained with of our lensfree video microscope allows standard cell tracking algorithm to be computed. The results is the possibility to analyze thousands of cells successfully tracked over tens of hours. The results is the possibility to compare different cell cultures in terms of e.g. cell motility and cell confinement ration. Ultimately we managed to measure the doubling time at single cell level over a large number of N=235 cells tracked over two days.
We present a new setup for time-resolved diffuse optical tomography based on multiple source-detector acquisitions analysed by means of the Mellin-Laplace transform. The proposed setup has been used to perform pre-clinical measurements on rats in order to show its suitability for non-invasive assessment of flap viability.
We developed a new imaging tool that can help pathologists in recording wide-field images of tissue slides. We present a simple cost-effective lens-free imaging method to record 2-4μm resolution wide-field (10 mm2 - 6 cm2) images of stained and unstained tissue slides. To our knowledge, our method is the first technique that enables fast (less than 5 minutes) wide-field lens-free imaging of such dense samples. Multiple holograms are recorded with different wavelength illumination, and a multispectral algorithm is used to retrieve both amplitude and phase. Our method can be used to retrieve images of stained tissue slides. For such absorbing object, the useful information is included in the modulus of the reconstructed complex field. Our method can also be applied to retrieve images of unstained tissue slides, where the useful information is in the retrieved phase. This technique is much cheaper and compact than a conventional microscope and could be made portable. Moreover, it enables wide field unstained tissue slides imaging, which could quickly provide useful information, for example on frozen section biopsies, when a rapid diagnosis is needed during surgery.
There is a growing interest in imaging fluorescence contrast at depth within living tissues over wide fields of view and in real time. Most methods used to date to improve depth detection of fluorescence information involve acquisition of multiple images, postprocessing of the data using a light propagation model, and are capable of providing either depth-sectioned or tomographic fluorescence information. We introduce a method, termed masked detection of structured illumination, that allows the enhancement of fluorescence imaging at depth without postprocessing. This method relies on the scanning of a collimated beam onto a turbid medium and the physical masking of the point spread function on the detection arm before acquisition on a CCD camera. By preferentially collecting diffuse photons at a chosen source-detector range, this method enhances fluorescence information at depth and has the potential to form images without postprocessing and in real time.
Intraoperative fluorescence imaging in reflectance geometry is an attractive imaging modality to noninvasively monitor fluorescence-targeted tumors. In some situations, this kind of imaging suffers from poor resolution due to the diffusive nature of photons in tissue. The objective of the proposed technique is to tackle this limitation. It relies on the scanning of the medium with a laser line illumination and the acquisition of images at each position of excitation. The detection scheme proposed takes advantage of the stack of images acquired to enhance the resolution and the contrast of the final image. The experimental protocol is described to fully understand why we overpass the classical limits and validate the scheme on tissue-like phantoms and in vivo with a preliminary testing. The results are compared with those obtained with a classical wide-field illumination.
In order to increase sensitivity in the depth of diffusive media and to separate chromophores with distinct spectral signatures, we developed a method to process time-domain/multi-wavelength diffuse optical acquisitions: 3D Reconstructions of chromophore concentrations are performed with an algorithm based on the use of Mellin-Laplace Transform and material basis. A noise weighted data matching term is optimized by using the conjugated gradients method without expressing the Jacobian matrix of the system. As the algorithm uses reference measurements on a known medium, it does not require measurements or computations of the instrument response function of the system. Validations are performed in the reflectance geometry on a tissue-mimicking phantom composed of intralipid and black ink and a cylindrical blue dye inclusion with a radius of 4mm located at 15mm in depth. The optical tomography setup includes a laser whose picosecond pulses are injected via an optical fiber to the probed diffusive medium and the light collected by two fibers (located 15mm apart from the source), is sent to a Single-Photon Avalanche Diode (SPAD) connected to a Time-Correlated Single-Photon Counting (TCSPC) board. The source and two detectors scan the surface of the medium so as to provide 30 source-detector couples, 900 time-bins and 5 wavelength signals. 3D reconstructions performed on the black ink and blue dye materials on a mesh of around 10000 nodes show that we are able to detect, localize and determine the composition of the inclusion and the background.
Intraoperative fluorescence imaging in reflectance geometry (FRI) is an attractive imaging modality as it allows to noninvasively monitor the fluorescence targeted tumors located below the tissue surface. Some drawbacks of this technique are the background fluorescence decreasing the contrast and absorption heterogeneities leading to misinterpretations concerning fluorescence concentrations.
We presented a FRI technique relying on a laser line scanning instead of a uniform illumination. Here, we propose a correction technique based on this illumination scheme. We scan the medium with the laser line and acquire at each position of the line both fluorescence and excitation images. We then use the finding that there is a relationship between the excitation intensity profile and the background fluorescence one. This allows us to predict the amount of signal to subtract to the fluorescence images to get a better contrast. As the light absorption information is contained both in fluorescence and excitation images, this method also permits us to correct the effects of absorption heterogeneities, leading to a better accuracy for the detection.
This technique has been validated on simulations (with a Monte-Carlo code and with the diffusion approxi- mation using NIRFAST) and experimentally with tissue-like liquid phantoms with different levels of background fluorescence. Fluorescent inclusions are observed in several configurations at depths ranging from 1 mm to 1 cm. Results obtained with this technique are compared to those obtained with a more classical wide-field detection scheme for the contrast enhancement and to the fluorescence to excitation ratio approach for the absorption correction.
Fiber optic probes with a width limited to a few centimeters can enable diffuse optical tomography (DOT) in intern
organs like the prostate or facilitate the measurements on extern organs like the breast or the brain. We have recently
shown on 2D tomographic images that time-resolved measurements with a large dynamic range obtained with fast-gated
single-photon avalanche diodes (SPADs) could push forward the imaged depth range in a diffusive medium at short
source-detector separation compared with conventional non-gated approaches. In this work, we confirm these
performances with the first 3D tomographic images reconstructed with such a setup and processed with the Mellin-
Laplace transform. More precisely, we investigate the performance of hand-held probes with short interfiber distances in
terms of spatial resolution and specifically demonstrate the interest of having a compact probe design featuring small
source-detector separations. We compare the spatial resolution obtained with two probes having the same design but
different scale factors, the first one featuring only interfiber distances of 15 mm and the second one, 10 mm. We evaluate
experimentally the spatial resolution obtained with each probe on the setup with fast-gated SPADs for optical phantoms
featuring two absorbing inclusions positioned at different depths and conclude on the potential of short source-detector
separations for DOT.
KEYWORDS: High power microwaves, Photons, Sensors, 3D metrology, Cameras, Single photon detectors, 3D image reconstruction, Imaging systems, Reflectivity, Photomultipliers
We demonstrate the loss of depth sensitivity induced by the instrument response function on reflectance time-resolved
diffuse optical tomography through the comparison of 3 detection systems: on one hand a photomultiplier tube (PMT)
and a hybrid PMT coupled with a time-correlated single-photon counting card and on the other hand a high rate
intensified camera. We experimentally evaluate the depth sensitivity achieved for each detection module with an
absorbing inclusion embedded in a turbid medium. The different interfiber distances of 5, 10 and 15 mm are considered.
Finally, we determine a maximal depth reached for each detection system by using 3D tomographic reconstructions
based on the Mellin-Laplace transform.
We present experimental results of time-resolved reflectance diffuse optical tomography performed with fast-gated single-photon avalanche diodes (SPADs) and show an increased imaged depth range for a given acquisition time compared to the non gated mode.
We develop a time-resolved system coupled to a new analysis method based on Mellin Laplace Transforms to reconstruct absorption and diffusion map in depth for neonate brain imaging. Phantoms and ex-vivo result are presented.
We design a Time-Resolved (TR) instrumentation coupled with a reconstruction method based on Mellin-Laplace Transform (MLT) to accurately assess in depth absorption and diffusion maps of a cylindrical diffusive medium. To deal with experimental large TR dataset, MLT processing is handled without expressing the sensitivity matrix. Moreover an optimization of the TR probe geometry is performed to limit the number of measurements while keeping the sensitivity of the system. Simulations show how to optimize the probe geometry for specific inclusions depth given a background diffusing medium. These results lead to an experimental bench we use to perform experimental validations. This includes a femtosecond laser coupled with an HRI and a CCD camera.
Current methodologies for obtaining depth-sensitive contrast information from an optically diffusive medium involve complex hardware and software implementations. In turn, such methods typically lead to long acquisition and long reconstruction times, rendering them impractical for real-time use. In this work, we report preliminary proof-of-concept for a hardware-only method capable of providing depth sensitive contrast information without requiring post acquisition image reconstruction and with rapid acquisition. This method, termed Masked Detection of Structured Illumination (MDSI), relies on physically masking, in the detection arm, the point spread function from a collimated beam illuminating a diffusive medium, to isolate the contribution of the photon path lengths of interest. By continuously scanning and integrating the obtained images, MDSI allows, for the first time, optical depth sectioning of a diffusive medium without any processing.
Prostate cancer diagnosis is based on PSA rate measurement and ultrasound guided biopsy. Recently criticized for its lack of specificity, new approaches are currently investigated: MRI, elastography, TEP, NIRS and Time Resolved (TR) fluorescence tomography. The advantage of TR fluorescence tomography relies on its good complementarity with the standard ultrasound protocol and on the possible localization of prostate tumors marked by specific probes. After a first TR system based on a bulky titanium-sapphire laser, we designed a new one taking advantage of a more compact white pulsed laser (supercontinuum). The improved compactness is now fully compatible with clinical environment. The light, filtered by two linear variable filters to select a 770±20 nm window, is driven to the transrectal probe which also collects the fluorescence light emitted by the marker. The signal is detected by photomultipliers connected to TCSPC boards. A reconstruction algorithm based on intensities and time of flight allows a fast localization of the fluorophore. We compared the performances of the new white laser system to the previous titanium-sapphire on prostate mimicking phantoms. The laser power delivered on the phantom by the new laser appeared to be suitable to fluorescence measurements, just below cutaneous maximum permitted exposure. The new system allowed us to localize fluorescent inclusions of a fluorescent nanoemulsion at fixed positions inside a prostate mimicking phantom.
Intraoperative fluorescence imaging in reflectance geometry is an attractive imaging modality as it allows to
noninvasively monitor fluorescence targeted tumors located below the tissue surface. The drawbacks of this technique are the poor resolution in the axial and lateral directions due to multiple light scattering and background
fluorescence decreasing the contrast.
We propose a novel fluorescence imaging method based on laser line illumination in reflectance geometry. We
scan the medium with the laser line and acquire images at each position of the line. We then detect only single
stripes of each image located on the excitation line or farther from it. We can also subtract the surrounding
signal to the detected stripe, the optimal detection scheme depending on the depth of the object of interest. This
allows us to reduce the contribution of parasite signals such as background fluorescence or excitation leaks and
also enhances the resolution. These operations on the images can either be digitally done in post-processing or
can directly be hardware implemented, allowing our method to be integrated in a handheld device for real-time
use.
This technique has been validated with tissue-like liquid phantoms with different levels of background fluorescence. Fluorescent inclusions are observed in several configurations at depths ranging from 1 mm to 1 cm. Our
results are compared to those obtained with a more classical wide-field detection scheme. Finally, we propose
a setup to optically implement the masking detection that will dramatically fasten the detection scheme and
optimize the fluorescence light throughput of the system.
In the context of continuous wave fluorescence-enhanced diffuse optical tomography, we show that the reconstructed
fluorescence depends on the local diffusion coefficient and demonstrate that the a priori knowledge of specific optical
parameters may lead to the reconstruction of absolute quantification of the fluorophore distribution. In this context, we
point out the potentiality of a bimodal instrument coupling functional and morphological information to provide
knowledge of the distribution of optical parameters of internal organs. We show some quantitative results on simulated
and experimental data on phantoms and conclude suggesting the use of optical parameters atlases to achieve an absolute
quantification of fluorophore distribution in real contexts.
KEYWORDS: Bacteria, 3D image reconstruction, Thin films, Holograms, Holography, CMOS sensors, Sensors, Microlens, Imaging systems, Signal to noise ratio
Due to low light scattering, bacteria are difficult to detect using lensless imaging systems. In
order to detect individual bacteria, we report a method based on a thin wetting film imaging
that produces a micro-lens effect on top of each bacterium when the sample dries up. The
imaging using a high-end CMOS sensor is combined with an in-line holographic
reconstruction to improve positive detection rate up to 95% with micron-sized beads at high
density of ~103 objects/mm2. The system allows detecting from single bacterium to densely
packed objects (103 bacteria/μl) within 10μl sample. As an example, E.coli, Bacillus subtilis
and Bacillus thuringiensis, has been successfully detected with strong signal to noise ratio across a 24mm2 field of view.
This paper presents a tomograph for small animal fluorescence imaging. The compact and cost-effective system described in this article was designed to address the problem of tumor detection inside highly absorbent heterogeneous organs, such as lungs. To validate the tomograph's ability to detect cancerous nodules inside lungs, in vivo tumor growth was studied on seven cancerous mice bearing murine mammary tumors marked with Alexa Fluor 700. They were successively imaged 10, 12, and 14 days after the primary tumor implantation. The fluorescence maps were compared over this time period. As expected, the reconstructed fluorescence increases with the tumor growth stage.
We developed an endorectal time-resolved optical probe aiming at an early detection of prostate tumors targeted by
fluorescent markers. Optical fibers are embedded inside a clinical available ultrasound endorectal probe. Excitation light
is driven sequentially from a femtosecond laser (775 nm) into 6 source fibers. 4 detection fibers collect the medium
responses at the excitation and fluorescence wavelength (850 nm) by the mean of 4 photomultipliers associated with a 4
channel time-correlated single photon counting card.
We also developed the method to process the experimental data. This involves the numerical computation of the
forward model, the creation of robust features which are automatically correctly from numerous experimental possible
biases and the reconstruction of the inclusion by using the intensity and mean time of these features.
To evaluate our system performance, we acquired measurements of a 40 μL ICG inclusion (10 μmol.L-1) at
various lateral and depth locations in a phantom. Analysis of results showed we correctly reconstructed the
fluorophore for the lateral positions (16 mm range) and for a distance to the probe going up to 1.5 cm. Precision of
localization was found to be around 1 mm which complies well with precision specifications needed for the clinical
application.
Fluorescence imaging in diffusive media locates tumors tagged by injected fluorescent markers in NIR wave-lengths.
For deep embedded markers, natural autofluorescence of tissues comes to be a limiting factor to
tumor detection and accurate FDOT reconstructions. A spectroscopic approach coupled with Non-negative
Matrix Factorization source separation method is explored to discriminate fluorescence sources according to
their fluorescence spectra and remove unwanted autofluorescence. We successfully removed autofluorescence
from acquisitions on living mice with a single subcutaneous tumor or two capillary tubes inserted at different
depths.
The protocol for prostate cancer diagnosis, currently based on ultrasound guided biopsy, is limited by a lack of
relevance. To improve this protocol, a new approach was proposed combining optical and ultrasound measurements to
guide biopsy specifically to the tumors. Adding an optical measurement modality into an already existing ultrasound
probe is challenging as the overall size of the system should not exceed a given dimension so as to fit the operative
environment. Moreover, examination should not take more than 15 min to avoid any complication.
A combined ultrasound and optical endorectal probe was designed to comply with the constraints of the
sterilization protocols, the examination duration and required compactness. Therefore a totally innovative pulsed laser
source has been designed to meet compactness requirements while providing accurate time-resolved measurements. A
dedicated multi-channel photon counting system was optimized to decrease the examination duration. A fast
reconstruction method based on the analysis of the intensity and time of flight of the detected photons has been
associated to provide 3D localization of fluorescent dots almost immediately after acquisition.
The bi-modal probe was capable of withstanding the sterilization procedures. The performance of the compact
laser source has been shown at the same level as that of a standard laboratory Titane:Sapphire laser. The dedicated
photon counting solution was capable of acquiring optical data in less than one minute. To evaluate the overall
performance of the system in dealing with a realistic background signal, measurements and reconstructions were
conducted on prostate mimicking phantom and in vivo.
An instrument dedicated to the co-registration of optical and X-ray measurements is presented: specific acquisition
protocol and reconstruction software have been developed for carrying out fluorescence diffuse optical tomography in a
cylindrical geometry consistent with XCT. Actual animal geometry provided by the X-ray tomography is used to give
animal boundaries to the diffuse optical tomography reconstruction algorithm. To evaluate performances of this new
optical imaging system, experiments have been conducted on phantoms, mice with fluorescent capillaries, and finally on
mice bearing tumors. The fluorescence reconstructions are shown to be geometrically consistent with X-ray ones. We
determined that the sensibility limit of the system to detect fluorescence signal over intrinsic ones is 2 pmol for lungs
area and 5 pmol for the abdomen area.
Fluorescence imaging in diffusive media is an emerging imaging modality for medical applications that uses injected fluorescent markers that bind to specific targets, e.g., carcinoma. The region of interest is illuminated with near-IR light and the emitted back fluorescence is analyzed to localize the fluorescence sources. To investigate a thick medium, as the fluorescence signal decreases with the light travel distance, any disturbing signal, such as biological tissues intrinsic fluorescence (called autofluorescence) is a limiting factor. Several specific markers may also be simultaneously injected to bind to different molecules, and one may want to isolate each specific fluorescent signal from the others. To remove the unwanted fluorescence contributions or separate different specific markers, a spectroscopic approach is explored. The nonnegative matrix factorization (NMF) is the blind positive source separation method we chose. We run an original regularized NMF algorithm we developed on experimental data, and successfully obtain separated in vivo fluorescence spectra.
Finding a way to combine ultrasound and fluorescence optical imaging on an endorectal probe may improve early
detection of prostate cancer. A trans-rectal probe adapted to fluorescence diffuse optical tomography measurements was
developed by our team. This probe is based on a pulsed NIR laser source, an optical fiber network and a time-resolved
detection system. A reconstruction algorithm was used to help locate and quantify fluorescent prostate tumors.
In this study, two different kinds of time-resolved detectors are compared: High Rate Imaging system (HRI) and a
photon counting system. The HRI is based on an intensified multichannel plate and a CCD Camera. The temporal
resolution is obtained through a gating of the HRI. Despite a low temporal resolution (300ps), this system allows a
simultaneous acquisition of the signal from a large number of detection fibers. In the photon counting setup, 4
photomultipliers are connected to a Time Correlated Single Photon Counting (TCSPC) board, providing a better
temporal resolution (0.1 ps) at the expense of a limited number of detection fibers (4).
At last, we show that the limited number of detection fibers of the photon counting setup is enough for a good
localization and dramatically improves the overall acquisition time. The photon counting approach is then validated
through the localization of fluorescent inclusions in a prostate-mimicking phantom.
Fluorescence optical imaging use one or several (in multiplexing) injected fluorescent markers which specifically
bind to targeted compounds. Near infrared light illuminates the region of interest and the emitted fluorescence
is analyzed to localize fluorescence sources. A spectroscopic approach and a separation source method (Nonnegative
matrix factorization) are explored to separate different fluorescence sources and remove the unwanted
biological tissues autofluorescence. We present unmixing results on overlapping spectra of interest, and show
that autofluorescence removal improves Fluorescent Diffuse Optical Tomography.
It is well known that the reconstruction problem in fluorescence diffuse optical tomography is badly conditioned and
requires the knowledge of medium optical properties. Its principle is to measure the fluorescence light emerging at
different positions of the surface when the biological medium is excited with point sources. In this paper, we evaluate the
influence of the medium optical properties and the noise on the fluorescence reconstruction, and we introduce a new
regularized fluorescence reconstruction method using an a priori on contours. The fluorescence reconstruction
improvement is studied when using this method.
To increase prostate cancer diagnosis sensibility, we propose to add an optical modality to an US biopsy tool to localize
fluorophore marked tumors. Optical signals are acquired on a time-resolved acquisition chain composed by a 770 nm
femtosecond laser source and a four channels TCSPC device. The fluorescence concentration is reconstructed by using
intensity and mean time of flight acquired from each time-resolved source-detector signal. Validation experiments are
performed on a phantom mimicking prostate both on its optical and ultrasound properties with 10 μmol/L ICG 1 cm deep double fluorescent inclusions to simulate marked tumors. An exhaustive search algorithm succeeded in reconstructing the two distinct fluorescence dots with correct locations.
We present first results of a fluorescence optical diffusion tomography experiment coupled to a X-ray computed
tomography reconstruction. An instrument, dedicated to the co-registration of optical and X-ray measurements, has been
developed: specific acquisition protocol and reconstruction software have been developed for carrying out fluorescence
diffuse optical tomography in a cylindrical geometry consistent with X-ray tomography. Actual animal geometry
provided by the X-ray tomography is used to give animal boundaries to the diffuse optical tomography reconstruction
algorithm. Experiments have been conducted on sacrificed mice and fluorescence reconstructions have been evaluated
and are geometrically consistent with X-ray ones.
We present two major advances in preclinical fluorescence-enhanced diffuse optical tomography (fDOT) system and assess its performance. It is now possible to perform experiments without adaptation liquid or a glass plate over the animal, and our system is equipped with a filter wheel in order to discriminate two injected fluorophores. Evaluation carried out on characterization phantoms and in vivo on mice demonstrates enriched use of the system for biological studies on small animals.
Finding a way to combine ultrasound and fluorescence optical imaging on an endorectal probe may improve early detection of prostate cancer. The ultrasound provides morphological information about the prostate, while the optical system detects and locates fluorophore-marked tumors. A tissue-mimicking phantom, which is representative of prostate tissues both on its optical (absorption µa and diffusion µ) and its ultrasound properties, has been made by our team. A transrectal probe adapted to fluorescence diffuse optical tomography measurements was also developed. Measurements were taken on the prostate phantom with this probe based on a pulsed laser and a time-resolved detection system. A reconstruction algorithm was then used to help locate and quantify fluorescent inclusions of different concentrations at fixed depths.
A fluorescence diffuse optical tomography instrument including a dedicated reconstruction scheme which accounts for the
medium optical heterogeneities is presented. It allows non-contact measurements and does not require animal immersion in
an optical adaptation liquid.
Fluorescence Diffuse Optical Tomography is an optical non-invasive molecular technique for cancer imaging.
Depending on the accessibility of the organ two main geometries might be considered, reflection or transmission. We
will present first experimental and reconstruction comparison between these two geometries, on a laboratory time
resolved bench. Both acquisitions were made using a fluorophore inclusion positioned in a liquid phantom, with breast
comparable optical properties. We successfully reconstructed all fluorophore positions examined in both geometries.
Reflection geometry suffers of many drawbacks that we have to deal with. We will present all challenges it implies, and
also what are the advantages to use time resolved techniques in both geometries.
We present in vivo experiments conducted with a new fluorescence diffuse optical tomographic (fDOT) system on cancerous mice bearing mammary murine tumors. We first briefly present this new system that has been developed and its associated reconstruction method. Its main specificity is its ability to reconstruct the fluorescence yield even in heterogeneous and highly attenuating body regions such as lungs and to enable mouse inspection without immersion in optical index matching liquid (Intralipid and ink). Some phantom experiments validate the performance of this new system for heterogeneous media inspection. Its use for a mice study is then related. It consists in the follow-up of the lungs at different stages of tumor development after injection of RAFT-(cRGD)4-Alexa700. As expected, the reconstructed fluorescence increases along with the tumor stage. These results validate the use of our system for biological studies of small animals.
KEYWORDS: Luminescence, Tumors, Lung, 3D modeling, In vivo imaging, Geometrical optics, Reconstruction algorithms, Animal model studies, Liquids, Glasses
This paper presents in vivo experiments conducted on cancerous mice bearing mammary murine tumors. In order to
reconstruct the fluorescence yield even in highly attenuating and heterogeneous regions like lungs, we developed a fDOT
reconstruction method which at first corrects the light propagation model from optical heterogeneities by using the
transmitted excitation light measurements. The same approach is also designed to enable working without immersing the
mouse in adaptation liquid. The 3D fluorescence map is then reconstructed from the emitted signal of fluorescence and
from the corrected propagation model by an ART (Algebraic Reconstruction Technique) algorithm. The system ability to
reconstruct fluorescence distribution in presence of high attenuating objects has been validated on phantoms presenting a
fluorescent absorbent inclusion. A study was conducted on mice to follow up lungs at different stages of tumor
development. The mice were imaged after intravenous injection to the animal of a cancer specific fluorescent marker. A
control experiment was conducted in parallel on healthy mice to ensure that the multiple injections of fluorophore did not
induce parasite fluorescence distribution. These results validate our system performances for studying small animal lungs
tumor evolution. Detection and localization of the fluorophore fixations expresses the tumor development.
Fluorescence enhanced diffuse optical tomography (fDOT) is envisioned to be useful to collect functional information
from small animal models. For oncology applications, cancer-targeted fluorescent markers can be used as a surrogate of
the cancer activity.
We are developing a continuous wave fDOT bench intended to be integrated in systems dedicated to whole
body small animal fluorescence analyses. The focus is currently put on the reconstruction of non immersed small animals
imaged by a CCD camera. The reconstruction stage already corrects the tissue heterogeneity artifacts through the
computation of an optical heterogeneity map. We will show how this formalism coupled with the determination of the
animal boundaries performed by a laser scanner, can be used to manage non contact acquisitions. The time of
reconstruction for a 10 × 9 laser source positions, 45 × 40 detector elements and 14 × 11 × 14 mesh voxels is typically 10
minutes on a 3GHz PCs corresponding to the acquisition time allowing the two tasks to be performed in parallel.
The system is validated on an in vivo experiment performed on three healthy nude mice and a mouse bearing a
lung tumor at 10, 12 and 14 days after implantation allowing the follow up of the disease. The 3D fluorescence
reconstructions of this mouse are presented and the total fluorescence amounts are compared.
Optical imaging of fluorescent probes is an essential tool for investigation of molecular events in small animals for drug developments. In order to get localization and quantification information of fluorescent labels, CEA-LETI has developed efficient approaches in classical reflectance imaging as well as in diffuse optical tomographic imaging with continuous and temporal signals. This paper presents an overview of the different approaches investigated and their performances. High quality fluorescence reflectance imaging is obtained thanks to the development of an original "multiple wavelengths" system. The uniformity of the excitation light surface area is better than 15%. Combined with the use of adapted fluorescent probes, this system enables an accurate detection of pathological tissues, such as nodules, beneath the animal's observed area. Performances for the detection of ovarian nodules on a nude mouse are shown. In order to investigate deeper inside animals and get 3D localization, diffuse optical tomography systems are being developed for both slab and cylindrical geometries. For these two geometries, our reconstruction algorithms are based on analytical expression of light diffusion. Thanks to an accurate introduction of light/matter interaction process in the algorithms, high quality reconstructions of tumors in mice have been obtained. Reconstruction of lung tumors on mice are presented.
By the use of temporal diffuse optical imaging, localization and quantification performances can be improved at the price of a more sophisticated acquisition system and more elaborate information processing methods. Such a system based on a pulsed laser diode and a time correlated single photon counting system has been set up. Performances of this system for localization and quantification of fluorescent probes are presented.
Bone mineral density (BMD) and body composition estimates are commonly obtained by dual-energy X-ray absorptiometry measurements (DXA). Thanks to their high detection efficiency and good energy resolution at room temperature, semiconductor detectors are more and more utilized to discriminate energy channels for this application. Our purpose is to upgrade the measurements precision using this kind of detector. For a large range of patient morphologies, we simulate X-ray beam transmission measurements with realistic models of tube spectra, and investigate the opportunity offered by spectrometric detectors to cut the signal into n energy channels. By adjusting the channels boundaries, tube voltage and K-edge filtrations, we obtain the best configuration for a given type of patient according to a precision criterion. Furthermore, this configuration is found to be compatible with all the range of patients for BMD measurements. For this configuration, we validate our approach with experimental data acquired with a laboratory made CdZnTe detector.
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