Time-stretch Imaging Research Articles

Fourier-domain-compressed optical time-stretch quantitative phase imaging flow cytometry

Optical time-stretch (OTS) imaging flow cytometry offers a promising solution for high-throughput and high-precision cell analysis due to its capabilities of high-speed, high-quality, and continuous imaging. Compressed sensing (CS) makes it practically applicable by significantly reducing the data volume while maintaining its high-speed and high-quality imaging properties. To enrich the information of the images acquired with CS-equipped OTS imaging flow cytometry, in this work we propose and experimentally demonstrate Fourier-domain-compressed OTS quantitative phase imaging flow cytometry. It is capable of acquiring intensity and quantitative phase images of cells simultaneously from the compressed data. To evaluate the performance of our method, static microparticles and a corn root cross section are experimentally measured under various compression ratios. Furthermore, to show how our method can be applied in practice, we utilize it in the drug response analysis of breast cancer cells. Experimental results show that our method can acquire high-quality intensity and quantitative phase images of flowing cells at a flowing speed of 1 m/s and a compression ratio of 30%. Combined with machine-learning-based image analysis, it can distinguish drug-treated and drug-untreated cells with an accuracy of over 95%. We believe our method can facilitate cell analysis in both scientific research and clinical settings where both high-throughput and high-content cell analysis is required.

Optofluidic time-stretch imaging flow cytometry with a real-time storage rate beyond 5.9 GB/s.

Optofluidic time-stretch imaging flow cytometry (OTS-IFC) provides a suitable solution for high-precision cell analysis and high-sensitivity detection of rare cells due to its high-throughput and continuous image acquisition. However, transferring and storing continuous big data streams remains a challenge. In this study, we designed a high-speed streaming storage strategy to store OTS-IFC data in real-time, overcoming the imbalance between the fast generation speed in the data acquisition and processing subsystem and the comparatively slower storage speed in the transmission and storage subsystem. This strategy, utilizing an asynchronous buffer structure built on the producer-consumer model, optimizes memory usage for enhanced data throughput and stability. We evaluated the storage performance of the high-speed streaming storage strategy in ultra-large-scale blood cell imaging on a common commercial device. The experimental results show that it can provide a continuous data throughput of up to 5891 MB/s.

Principle and Recent Development in Photonic Time-Stretch Imaging

Inspiring development in optical imaging enables great applications in the science and engineering industry, especially in the medical imaging area. Photonic time-stretch imaging is one emerging innovation that attracted a wide range of attention due to its principle of one-to-one-to-one mapping among space-wavelength-time using dispersive medium both in spatial and time domains. The ultrafast imaging speed of the photonics time-stretch imaging technique achieves an ultrahigh frame rate of tens of millions of frames per second, which exceeds the traditional imaging methods in several orders of magnitudes. Additionally, regarding ultrafast optical signal processing, it can combine several other optical technologies, such as compressive sensing, nonlinear processing, and deep learning. In this paper, we review the principle and recent development of photonic time-stretch imaging and discuss the future trends.

Optical time-stretch imaging flow cytometry in the compressed domain.

Imaging flow cytometry based on optical time-stretch (OTS) imaging combined with a microfluidic chip attracts much attention in the large-scale single-cell analysis due to its high throughput, high precision, and label-free operation. Compressive sensing has been integrated into OTS imaging to relieve the pressure on the sampling and transmission of massive data. However, image decompression brings an extra overhead of computing power to the system, but does not generate additional information. In this work, we propose and demonstrate OTS imaging flow cytometry in the compressed domain. Specifically, we constructed a machine-learning network to analyze the cells without decompressing the images. The results show that our system enables high-quality imaging and high-accurate cell classification with an accuracy of over 99% at a compression ratio of 10%. This work provides a viable solution to the big data problem in OTS imaging flow cytometry, boosting its application in practice.

Cell damage evaluation by intelligent imaging flow cytometry.

Essential thrombocythemia (ET) is an uncommon situation in which the body produces too many platelets. This can cause blood clots anywhere in the body and results in various symptoms and even strokes or heart attacks. Removing excessive platelets using acoustofluidic methods receives extensive attention due to their high efficiency and high yield. While the damage to the remaining cells, such as erythrocytes and leukocytes is yet evaluated. Existing cell damage evaluation methods usually require cell staining, which are time-consuming and labor-intensive. In this paper, we investigate cell damage by optical time-stretch (OTS) imaging flow cytometry with high throughput and in a label-free manner. Specifically, we first image the erythrocytes and leukocytes sorted by acoustofluidic sorting chip with different acoustic wave powers and flowing speed using OTS imaging flow cytometry at a flowing speed up to 1 m/s. Then, we employ machine learning algorithms to extract biophysical phenotypic features from the cellular images, as well as to cluster and identify images. The results show that both the errors of the biophysical phenotypic features and the proportion of abnormal cells are within 10% in the undamaged cell groups, while the errors are much greater than 10% in the damaged cell groups, indicating that acoustofluidic sorting causes little damage to the cells within the appropriate acoustic power, agreeing well with clinical assays. Our method provides a novel approach for high-throughput and label-free cell damage evaluation in scientific research and clinical settings.

Label-free multiphoton imaging flow cytometry.

Label-free imaging flow cytometry is a powerful tool for biological and medical research as it overcomes technical challenges in conventional fluorescence-based imaging flow cytometry that predominantly relies on fluorescent labeling. To date, two distinct types of label-free imaging flow cytometry have been developed, namely optofluidic time-stretch quantitative phase imaging flow cytometry and stimulated Raman scattering (SRS) imaging flow cytometry. Unfortunately, these two methods are incapable of probing some important molecules such as starch and collagen. Here, we present another type of label-free imaging flow cytometry, namely multiphoton imaging flow cytometry, for visualizing starch and collagen in live cells with high throughput. Our multiphoton imaging flow cytometer is based on nonlinear optical imaging whose image contrast is provided by two optical nonlinear effects: four-wave mixing (FWM) and second-harmonic generation (SHG). It is composed of a microfluidic chip with an acoustic focuser, a lab-made laser scanning SHG-FWM microscope, and a high-speed image acquisition circuit to simultaneously acquire FWM and SHG images of flowing cells. As a result, it acquires FWM and SHG images (100 × 100 pixels) with a spatial resolution of 500 nm and a field of view of 50 μm × 50 μm at a high event rate of four to five events per second, corresponding to a high throughput of 560-700 kb/s, where the event is defined by the passage of a cell or a cell-like particle. To show the utility of our multiphoton imaging flow cytometer, we used it to characterize Chromochloris zofingiensis (NIES-2175), a unicellular green alga that has recently attracted attention from the industrial sector for its ability to efficiently produce valuable materials for bioplastics, food, and biofuel. Our statistical image analysis found that starch was distributed at the center of the cells at the early cell cycle stage and became delocalized at the later stage. Multiphoton imaging flow cytometry is expected to be an effective tool for statistical high-content studies of biological functions and optimizing the evolution of highly productive cell strains.

All-Optical Fourier-Domain-Compressed Time-Stretch Imaging with Low-Pass Filtering

Optical time-stretch (OTS) imaging has shown significant advantages in many applications, such as high-throughput cell screening, for its high frame rate and the capability of continuous image acquisition. Unfortunately, its application in practice is fundamentally limited by the pressure on data transmission and storage caused by the extreme throughput. Compressed sensing (CS) has been considered a promising approach to solve this problem by recovering the signal at a sampling rate significantly lower than the Nyquist sampling rate. However, the temporal stretch and compression processes, which are currently realized with two sections of dispersive media with complementary GVD, make the system complex and introduce notable power loss to the system, leading to a low signal-to-noise ratio (SNR). In this work, we propose and demonstrate all-optical Fourier-domain-compressed time-stretch imaging with low-pass filtering. Only one section of dispersive media is needed to temporal stretch the pulse, while the compression of the stretched pulses is achieved with low-pass-filtering after optical-electrical conversion. Therefore, the structure of the system is notably simplified, and the SNR or the quality of the images can be improved. The principle of this method is theoretically analyzed, and its performance is experimentally demonstrated. The results show that our system can image flowing cells at a high flowing speed of 1 m/s, with a spatial resolution of 2.19 μm on condition that the original data are compressed by 80%. Our method can boost the application of OTS imaging in the fields where high-throughput and real-time imaging is required.

Typing of acute leukemia by intelligent optical time-stretch imaging flow cytometry on a chip.

Acute leukemia (AL) is one of the top life-threatening diseases. Accurate typing of AL can significantly improve its prognosis. However, conventional methods for AL typing often require cell staining, which is time-consuming and labor-intensive. Furthermore, their performance is highly limited by the specificity and availability of fluorescent labels, which can hardly meet the requirements of AL typing in clinical settings. Here, we demonstrate AL typing by intelligent optical time-stretch (OTS) imaging flow cytometry on a microfluidic chip. Specifically, we employ OTS microscopy to capture the images of cells in clinical bone marrow samples with a spatial resolution of 780 nm at a high flowing speed of 1 m s-1 in a label-free manner. Then, to show the clinical utility of our method for which the features of clinical samples are diverse, we design and construct a deep convolutional neural network (CNN) to analyze the cellular images and determine the AL type of each sample. We measure 30 clinical samples composed of 7 acute lymphoblastic leukemia (ALL) samples, 17 acute myelogenous leukemia (AML) samples, and 6 samples from healthy donors, resulting in a total of 227 620 images acquired. Results show that our method can distinguish ALL and AML with an accuracy of 95.03%, which, to the best of our knowledge, is a record in label-free AL typing. In addition to AL typing, we believe that the high throughput, high accuracy, and label-free operation of our method make it a potential solution for cell analysis in scientific research and clinical settings.

An optimized PDMS microfluidic device for ultra-fast and high-throughput imaging flow cytometry.

Imaging flow cytometry (IFC) is a powerful tool for cell detection and analysis due to its high throughput and compatibility in image acquisition. Optical time-stretch (OTS) imaging is considered as one of the most promising imaging techniques for IFC because it can realize cell imaging at a flow speed of around 60 m s-1. However, existing PDMS-based microchannels cannot function at flow velocities higher than 10 m s-1; thus the capability of OTS-based IFC is significantly limited. To overcome the velocity barrier for PDMS-based microchannels, we proposed an optimized design of PDMS-based microchannels with reduced hydraulic resistance and 3D hydrodynamic focusing capability, which can drive fluids at an ultra-high flow velocity (of up to 40 m s-1) by using common syringe pumps. To verify the feasibility of our design, we fabricated and installed the microchannel in an OTS IFC system. The experimental results first proved that the proposed microchannel can support a stable flow velocity of up to 40 m s-1 without any leakage or damage. Then, we demonstrated that the OTS IFC is capable of imaging cells at a velocity of up to 40 m s-1 with good quality. To the best of our knowledge, it is the first time that IFC has achieved such a high flow velocity just by using a PDMS-glass chip. Moreover, high velocity can enhance the focusing of cells on the optical focal plane, increasing the number of detected cells and the throughput. This work provides a promising solution for IFC to fully release its capability of advanced imaging techniques by operating at an extremely high screening throughput.

Studying the efficacy of antiplatelet drugs on atherosclerosis by optofluidic imaging on a chip.

Vascular stenosis caused by atherosclerosis instigates activation and aggregation of platelets, eventually resulting in thrombus formation. Although antiplatelet drugs are commonly used to inhibit platelet activation and aggregation, they unfortunately cannot prevent recurrent thrombotic events in patients with atherosclerosis. This is partially due to the limited understanding of the efficacy of antiplatelet drugs in the complex hemodynamic environment of vascular stenosis. Conventional methods for evaluating the efficacy of antiplatelet drugs under stenosis either fail to simulate the hemodynamic environment of vascular stenosis characterized by high shear stress and recirculatory flow or lack spatial resolution in their analytical techniques to statistically identify and characterize platelet aggregates. Here we propose and experimentally demonstrate a method comprising an in vitro 3D stenosis microfluidic chip and an optical time-stretch quantitative phase imaging system for studying the efficacy of antiplatelet drugs under stenosis. Our method simulates the atherogenic flow environment of vascular stenosis while enabling high-resolution and statistical analysis of platelet aggregates. Using our method, we distinguished the efficacy of three antiplatelet drugs, acetylsalicylic acid (ASA), cangrelor, and eptifibatide, for inhibiting platelet aggregation induced by stenosis. Specifically, ASA failed to inhibit stenosis-induced platelet aggregation, while eptifibatide and cangrelor showed high and moderate efficacy, respectively. Furthermore, we demonstrated that the drugs tested also differed in their efficacy for inhibiting platelet aggregation synergistically induced by stenosis and agonists (e.g., adenosine diphosphate, and collagen). Taken together, our method is an effective tool for investigating the efficacy of antiplatelet drugs under vascular stenosis, which could assist the development of optimal pharmacologic strategies for patients with atherosclerosis.

Multiparameter Investigation of Diamond Plates with Optical Time-Stretch Quantitative Phase Imaging

Diamond is considered the ultimate semiconductor for its excellent physical and chemical properties, while the defects formed during the growth significantly limit the performance of diamond devices. Online monitoring and fixing is an effective method to minimize the defect density in diamond crystals. The existing methods fail to effectively investigate diamond crystals during growth due to the low frame rate or the limited variety of parameters. Here, we employ optical time-stretch quantitative phase imaging (OTS-QPI) to investigate the multiple parameters of diamond crystals synthesized in different situations. Specifically, we measure the morphological features, surface fluctuations, and refractive index distributions of diamond plates grown via chemical vapor deposition in different growth modes or via high-pressure high-temperature in doping with various concentrations of boron, respectively. The results indicate that the morphological features, surface fluctuations, and refractive index distributions acquired with OTS-QPI show an accuracy that agrees well with those captured by commercial devices, including a microscope, an optical profiler, and an ellipsometer. This work indicates that OTS-QPI can perform online measurements of multiple parameters of diamond crystals at a high speed and high accuracy, which can potentially be employed to increase the quality and yield rate of diamond devices.

Time-stretch-based multidimensional line-scan microscopy

Time-stretch tomography imaging with ultrahigh frame rate is a breathtaking optical imaging method for acquiring large data sets for detection and classification of rare events. However, mechanical scans of both x and y dimensions are required to obtain tomography imaging. Here we introduce an ultrafast multidimensional time-stretch imaging method, only by one-dimensional scan, a multidimensional imaging can be obtained. An entire row of surface and depth information for a reflective sample is encoded onto the amplitude and frequency of a spatially dispersed ultrafast chirped beam, respectively. The present multidimensional line-scan microscopy approaches an ultrafast imaging system with micron level positioning accuracy in depth, three-dimensional surface information acquisition and tomography capability, which aimed at emerging applications for optical coherence tomography (OCT), light detection and ranging (LIDAR) and hyperspectral imaging.

Understanding stenosis-induced platelet aggregation on a chip by high-speed optical imaging

Vascular stenosis is a pathological hallmark of atherosclerosis, the leading cause of cardiovascular diseases such as stroke and myocardial infarction. While stenosis-induced thrombus formation has been extensively studied using in vivo and in vitro vascular models, the transient and dynamic process of platelet aggregation remains unclear due to the lack of analytical tools with both high spatial and temporal resolution. Here we report spatiotemporally resolved observation of shear-induced platelet aggregation using an in vitro microfluidic stenosis model and an optical time-stretch imaging system. Specifically, we characterized the size, shape, and population of platelet aggregates at single-cell resolution every 20 min in the presence of different agonists in a 3D stenosis model. Our results indicate a significant enhancement in platelet aggregation when both stenosis and an agonist were present, thus suggesting a synergistic effect of atherogenic blood flow disturbance and circulating factors on platelet activation. In particular, platelets activated by thrombin receptor activator peptide 6 (TRAP-6) led to a broad-sized distribution of platelet aggregates with significantly large aggregates (>240 µm2 in area). These findings are expected to deepen our understanding of the mechanism behind stenosis-induced platelet aggregation and pave the way for development of better antithrombotic therapeutics.

Time-Stretch Imaging toward Auxiliary Diagnosis of COVID-19

Time-Stretch Imaging toward Auxiliary Diagnosis of COVID-19

A high-throughput label-free time-stretch acoustofluidic imaging cytometer for single-cell mechanotyping

Current circulating tumor cells (CTC) detection methods have to compromise between sensitivity and throughput. High-throughput imaging cytometer based on serial time-encoded amplified microscopy (STEAM) facilitates CTC detection at single-cell sensitivity from abundant cells. However, this method lacks the information to spot heterogeneity of cells with high morphological similarity. Researches on cell biophysical properties suggest cell mechanotyping can be an indicator of phenotypic heterogeneity to improve classification ability of STEAM cytometer. Here, we present a high-throughput label-free acoustofluidic imaging cytometer for single-cell mechanotyping based on STEAM and acoustofluidic technology. The generated acoustic resonance field translocates cells to different transversal exit positions under continuous flow according to their intrinsic biophysical properties. Such displacements are recorded with images simultaneously using STEAM cytometry at approximately 2000 cells/s. We experimentally verified that our method accounting for both cell images and acoustic displacements can improve mechanotyping accuracy by 12% upon image-based phenotyping method. This new acoustofluidic imaging cytometer facilitates high-accuracy and high-throughput imaging cytometry for single-cell CTC mechanotyping.

Analysis of signal detection configurations in optical time-stretch imaging.

Optical time-stretch (OTS) imaging is effective for observing ultra-fast dynamic events in real time by virtue of its capability of acquiring images with high spatial resolution at high speed. In different implementations of OTS imaging, different configurations of its signal detection, i.e. fiber-coupled and free-space detection schemes, are employed. In this research, we quantitatively analyze and compare the two detection configurations of OTS imaging in terms of sensitivity and image quality with the USAF-1951 resolution chart and diamond films, respectively, providing a valuable guidance for the system design of OTS imaging in diverse fields.

Ultrafast photonic time-stretch imaging using an optically transparent medium

A specially-designed optically transparent medium (OTM) is employed to map a pulse spectrum to a temporal waveform and utilize a single-pixel photodiode for detection at the MHz scale. We propose and demonstrate a feasible experimental arrangement for photonic time-stretch imaging (PTSI), composed of a compact OTM with a 200 × 180 × 10 mm volume, which results in 37 inner reflections and an 8.04 m propagation length of the light beam. The simulation results, realized by an optical pulse stretched from 40 fs to 2.4 ns, firmly verify the great potential for OTM-PTSI systems to be used in transient inspection and diagnosis applications.

Observing mode-dependent wavelength-to-time mapping in few-mode fibers using a single-photon detector array

Wavelength-to-time mapping (WTM)—stretching ultrashort optical pulses in a dispersive medium such that the instantaneous frequency becomes time-dependent—is usually performed using a single-mode fiber. In a number of applications, such as time-stretch imaging (TSI), the use of this single-mode fiber during WTM limits the achievable sampling rate and the imaging quality. Multimode fiber based WTM is a potential route to overcome this challenge and project a more diverse range of light patterns. Here, we demonstrate the use of a two-dimensional single-photon avalanche diode (SPAD) array to image, in a time-correlated single-photon counting (TCSPC) manner, the time- and wavelength-dependent arrival of different spatial modes in a few-mode fiber. We then use a TCSPC spectrometer with a one-dimensional SPAD array to record and calibrate the wavelength-dependent and mode-dependent WTM processes. The direct measurement of the WTM of the spatial modes opens a convenient route to estimate group velocity dispersion, differential mode delay, and the effective refractive index of different spatial modes. This is applicable to TSI and ultrafast optical imaging, as well as broader areas such as telecommunications.

Temporally interleaved optical time-stretch imaging

Optical time-stretch imaging has shown potential in diverse fields for its capability of acquiring images at high speed and high resolution. However, its wide application is hindered by the stringent requirement on the instrumentation hardware caused by the high-speed serial data stream. Here we demonstrate temporally interleaved optical time-stretch imaging that lowers the requirement without sacrificing the frame rate or spatial resolution by interleaving the high-speed data stream into multiple channels in the time domain. Its performance is validated with both a United States Air Force (USAF)-1951 resolution chart and a single-crystal diamond film. We achieve a 101 Mfps 1D scanning rate and 3 µm spatial resolution with only a 2.5 GS/s sampling rate by using a two-channel-interleaved system.

Virtual optofluidic time-stretch quantitative phase imaging

Optofluidic time-stretch quantitative phase imaging (OTS-QPI) is a potent tool for biomedical applications as it enables high-throughput QPI of numerous cells for large-scale single-cell analysis in a label-free manner. However, there are a few critical limitations that hinder OTS-QPI from being widely applied to diverse applications, such as its costly instrumentation and inherent phase-unwrapping errors. Here, to overcome the limitations, we present a QPI-free OTS-QPI method that generates “virtual” phase images from their corresponding bright-field images by using a deep neural network trained with numerous pairs of bright-field and phase images. Specifically, our trained generative adversarial network model generated virtual phase images with high similarity (structural similarity index >0.7) to their corresponding real phase images. This was also supported by our successful classification of various types of leukemia cells and white blood cells via their virtual phase images. The virtual OTS-QPI method is highly reliable and cost-effective and is therefore expected to enhance the applicability of OTS microscopy in diverse research areas, such as cancer biology, precision medicine, and green energy.