ABSTRACT
Stroke poses a significant global health threat, with millions affected annually, leading to substantial morbidity and mortality. Current stroke risk assessment for the general population relies on markers such as demographics, blood tests, and comorbidities. A minimally invasive, clinically scalable, and cost-effective way to directly measure cerebral blood flow presents an opportunity. This opportunity has potential to positively impact effective stroke risk assessment prevention and intervention. Physiological changes in the cerebral vascular system, particularly in response to carbon dioxide level changes and oxygen deprivation, such as during breath-holding, can offer insights into stroke risk assessment. However, existing methods for measuring cerebral perfusion reserve, such as blood flow and blood volume changes, are limited by either invasiveness or impracticality. Here, we propose a transcranial approach using speckle contrast optical spectroscopy (SCOS) to non-invasively monitor regional changes in brain blood flow and volume during breath-holding. Our study, conducted on 50 individuals classified into two groups (low-risk and higher-risk for stroke), shows significant differences in blood dynamic changes during breath-holding between the two groups, providing physiological insights for stroke risk assessment using a non-invasive quantification paradigm. Given its cost-effectiveness, scalability, portability, and simplicity, this laser-centric tool has significant potential in enhancing the pre-screening of stroke and mitigating strokes in the general population through early diagnosis and intervention.
ABSTRACT
The characteristics of subvisible particles (SbVPs) are critical quality attributes of injectable and ophthalmic solutions in pharmaceutical manufacturing. However, current compendial SbVP testing methods, namely the light obstruction method and the microscopic particle count method, are destructive and wasteful of target samples. In this study, we present the development of a non-destructive SbVP analyzer aiming to analyze SbVPs directly in drug product (DP) containers while keeping the samples intact. Custom sample housings are developed and incorporated into the analyzer to reduce optical aberrations introduced by the curvature of typical pharmaceutical DP sample containers. The analyzer integrates a light-sheet microscope structure and models the side scattering event from a particle with Mie scattering theory with refractive indices as prior information. Equivalent spherical particle size under assigned refractive index values is estimated, and the particle concentration is determined based on the number of scattering events and the volume sampled by the light sheet. The resulting analyzer's capability and performance to non-destructively analyze SbVPs in DP containers were evaluated using a series of polystyrene bead suspensions in ISO 2R and 6R vials. Our results and analysis show the particle analyzer is capable of directly detecting SbVPs from intact DP containers, sorting SbVPs into commonly used size bins (e.g. ≥ 2 µm, ≥ 5 µm, ≥ 10 µm, and ≥ 25 µm), and reliably quantifying SbVPs in the concentration range of 4.6e2 to 5.0e5 particle/mL with a margin of ± 15 % error based on a 90 % confidence interval.
ABSTRACT
Synthetic aperture radar (SAR) utilizes an aircraft-carried antenna to emit electromagnetic pulses and detect the returning echoes. As the aircraft travels across a designated area, it synthesizes a large virtual aperture to improve image resolution. Inspired by SAR, we introduce synthetic aperture ptycho-endoscopy (SAPE) for micro-endoscopic imaging beyond the diffraction limit. SAPE operates by hand-holding a lensless fiber bundle tip to record coherent diffraction patterns from specimens. The fiber cores at the distal tip modulate the diffracted wavefield within a confined area, emulating the role of the 'airborne antenna' in SAR. The handheld operation introduces positional shifts to the tip, analogous to the aircraft's movement. These shifts facilitate the acquisition of a ptychogram and synthesize a large virtual aperture extending beyond the bundle's physical limit. We mitigate the influences of hand motion and fiber bending through a low-rank spatiotemporal decomposition of the bundle's modulation profile. Our tests demonstrate the ability to resolve a 548-nm linewidth on a resolution target. The achieved space-bandwidth product is ~1.1 million effective pixels, representing a 36-fold increase compared to that of the original fiber bundle. Furthermore, SAPE's refocusing capability enables imaging over an extended depth of field exceeding 2 cm. The aperture synthesizing process in SAPE surpasses the diffraction limit set by the probe's maximum collection angle, opening new opportunities for both fiber-based and distal-chip endoscopy in applications such as medical diagnostics and industrial inspection.
ABSTRACT
Imaging three-dimensional microbial development and behavior over extended periods is crucial for advancing microbiological studies. Here, we introduce an upgraded ePetri dish system specifically designed for extended microbial culturing and 3D imaging, addressing the limitations of existing methods. Our approach includes a sealed growth chamber to enable long-term culturing, and a multi-step reconstruction algorithm that integrates 3D deconvolution, image filtering, ridge, and skeleton detection for detailed visualization of the hyphal network. The system effectively monitored the development of Aspergillus brasiliensis hyphae over a seven-day period, demonstrating the growth medium's stability within the chamber. The system's 3D imaging capability was validated in a volume of 5.5 mm × 4 mm × 0.5 mm, revealing a radial growth pattern of fungal hyphae. Additionally, we show that the system can identify potential filter failures that are undetectable with 2D imaging. With these capabilities, the upgraded ePetri dish represents a significant advancement in long-term 3D microbial imaging, promising new insights into microbial development and behavior across various microbiological research areas.
ABSTRACT
Computational imaging methods empower modern microscopes to produce high-resolution, large field-of-view, aberration-free images. Fourier ptychographic microscopy can increase the space-bandwidth product of conventional microscopy, but its iterative reconstruction methods are prone to parameter selection and tend to fail under excessive aberrations. Spatial Kramers-Kronig methods can analytically reconstruct complex fields, but is limited by aberration or providing extended resolution enhancement. Here, we present APIC, a closed-form method that weds the strengths of both methods while using only NA-matching and darkfield measurements. We establish an analytical phase retrieval framework which demonstrates the feasibility of analytically reconstructing the complex field associated with darkfield measurements. APIC can retrieve complex aberrations of an imaging system with no additional hardware and avoids iterative algorithms, requiring no human-designed convergence metrics while always obtaining a closed-form complex field solution. We experimentally demonstrate that APIC gives correct reconstruction results where Fourier ptychographic microscopy fails when constrained to the same number of measurements. APIC achieves 2.8 times faster computation using image tile size of 256 (length-wise), is robust against aberrations compared to Fourier ptychographic microscopy, and capable of addressing aberrations whose maximal phase difference exceeds 3.8π when using a NA 0.25 objective in experiment.
ABSTRACT
Significance: In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF noninvasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. Aim: Our study aims to introduce a compact speckle contrast optical spectroscopy device for noninvasive CBF measurements at long source-to-detector distances, offering cost-effectiveness, and scalability while tracking blood flow (BF) with remarkable sensitivity and temporal resolution. Approach: The wearable sensor module consists solely of a laser diode and a board camera. It can be easily placed on a subject's head to measure BF at a sampling rate of 80 Hz. Results: Compared to the single-fiber-based version, the proposed device achieved a signal gain of about 70 times, showed superior stability, reproducibility, and signal-to-noise ratio for measuring BF at long source-to-detector distances. The device can be distributed in multiple configurations around the head. Conclusions: Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing noninvasive cerebral monitoring technologies.
Subject(s)
Cerebrovascular Circulation , Equipment Design , Spectrum Analysis , Humans , Cerebrovascular Circulation/physiology , Spectrum Analysis/instrumentation , Cost-Benefit Analysis , Reproducibility of Results , Wearable Electronic Devices , Signal-To-Noise Ratio , Lasers , Brain/blood supply , Brain/diagnostic imaging , Brain/physiology , Laser Speckle Contrast Imaging/instrumentationABSTRACT
Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with stage I-III NSCLC followed for at least 5 years for the development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole-slide imaging. Three separate iterations were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. The DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish the eventual development of brain metastases with an accuracy of 87% (p < 0.0001) compared with an average of 57.3% by the four pathologists and appears to be particularly useful in predicting brain metastases in stage I patients. The DL algorithm appears to focus on a complex set of histologic features. DL-based algorithms using routine H&E-stained slides may identify patients who are likely to develop brain metastases from those who will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Subject(s)
Brain Neoplasms , Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Humans , Lung Neoplasms/pathology , Carcinoma, Non-Small-Cell Lung/pathology , Algorithms , PathologistsABSTRACT
In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution. The wearable hardware has a modular design approach consisting solely of a laser diode as the source and a meticulously selected board camera as the detector. They both can be easily placed on a subject's head to measure CBF with no additional optical elements. The SVS device can achieve a sampling rate of 80 Hz with minimal susceptibility to external disturbances. The device also achieves better SNR compared with traditional fiber-based SVS devices, capturing about 70 times more signal and showing superior stability and reproducibility. It is designed to be paired and distributed in multiple configurations around the head, and measure signals that exceed the quality of prior optical CBF measurement techniques. Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing non-invasive cerebral monitoring technologies.
ABSTRACT
Recently, speckle visibility spectroscopy (SVS) was non-invasively applied on the head to monitor cerebral blood flow. The technique, using a multi-pixel detecting device (e.g., camera), allows the detection of a larger number of speckles, increasing the proportion of light that is detected. Due to this increase, it is possible to collect light that has propagated deeper through the brain. As a direct consequence, cerebral blood flow can be monitored. However, isolating the cerebral blood flow from the other layers, such as the scalp or skull components, remains challenging. In this paper, we report our investigations on the depth-sensitivity of laser interferometry speckle visibility spectroscopy (iSVS). Specifically, we varied the depth of penetration of the laser light into the head by tuning the source-to-detector distance, and identified the transition point at which cerebral blood flow in humans and rabbits starts to be detected.
ABSTRACT
Diffusing wave spectroscopy (DWS) is a group of techniques used to measure the dynamics of a scattering medium in a non-invasive manner. DWS methods rely on detecting the speckle light field from the moving scattering medium and measuring the speckle decorrelation time to quantify the scattering medium's dynamics. For DWS, the signal-to-noise (SNR) is determined by the ratio between measured decorrelation time to the standard error of the measurement. This SNR is often low in certain applications because of high noise variances and low signal intensity, especially in biological applications with restricted exposure and emission levels. To address this photon-limited signal-to-noise ratio problem, we investigated, theoretically and experimentally, the SNR of an interferometric speckle visibility spectroscopy (iSVS) compared to more traditional DWS methods. We found that iSVS can provide excellent SNR performance through its ability to overcome camera noise. We also proved an iSVS system has more relaxed constraints on the reference beam properties. For an iSVS system to function properly, we only require the reference beam to exhibit local temporal stability, while incident angle, reference phase and intensity uniformity do not need to be constrained. This flexibility can potentially enable more unconventional iSVS implementation schemes.
ABSTRACT
The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.
Subject(s)
Cell-Free Nucleic Acids , Extracellular Vesicles , Neoplastic Cells, Circulating , Humans , Liquid Biopsy , Cell-Free Nucleic Acids/genetics , Biomarkers , Neoplastic Cells, Circulating/pathologyABSTRACT
Holography based on Kramers-Kronig relations (KKR) is a promising technique due to its high-space-bandwidth product. However, the absence of an iterative process limits its noise robustness, primarily stemming from the lack of a regularization constraint. This Letter reports a generalized framework aimed at enhancing the noise robustness of KKR holography. Our proposal involves employing the Hilbert-Huang transform to connect the real and imaginary parts of an analytic function. The real part is initially processed by bidimensional empirical mode decomposition into a series of intrinsic mode functions (IMFs) and a residual term. They are then selected to remove the noise and bias terms. Finally, the imaginary part can be obtained using the Hilbert transform. In this way, we efficiently suppress the noise in the synthetic complex function, facilitating high-fidelity wavefront reconstruction using â¼20% of the exposure time required by existing methods. Our work is expected to expand the applications of KKR holography, particularly in low phototoxicity biological imaging and other related scenarios.
ABSTRACT
Circulating tumor cells (CTCs) and cancer-associated fibroblasts (CAFs) from whole blood are emerging as important biomarkers that potentially aid in cancer diagnosis and prognosis. The microfilter technology provides an efficient capture platform for them but is confounded by two challenges. First, uneven microfilter surfaces makes it hard for commercial scanners to obtain images with all cells in-focus. Second, current analysis is labor-intensive with long turnaround time and user-to-user variability. Here we addressed the first challenge through developing a customized imaging system and data pre-processing algorithms. Utilizing cultured cancer and CAF cells captured by microfilters, we showed that images from our custom system are 99.3% in-focus compared to 89.9% from a top-of-the-line commercial scanner. Then we developed a deep-learning-based method to automatically identify tumor cells serving to mimic CTC (mCTC) and CAFs. Our deep learning method achieved precision and recall of 94% (± 0.2%) and 96% (± 0.2%) for mCTC detection, and 93% (± 1.7%) and 84% (± 3.1%) for CAF detection, significantly better than a conventional computer vision method, whose numbers are 92% (± 0.2%) and 78% (± 0.3%) for mCTC and 58% (± 3.9%) and 56% (± 3.5%) for CAF. Our custom imaging system combined with deep learning cell identification method represents an important advance on CTC and CAF analysis.
Subject(s)
Cancer-Associated Fibroblasts , Deep Learning , Neoplastic Cells, Circulating , Humans , Neoplastic Cells, Circulating/pathology , Cancer-Associated Fibroblasts/pathology , Biomarkers , Prognosis , Cell Line, TumorABSTRACT
Context: Cytology is the study of whole cells in diagnostic pathology. Unlike standard histologic thinly sliced specimens, cytologic preparations consist of preparations of whole cells where cells commonly cluster and aggregate. As such, cytology preparations are generally much thicker than histologic slides, resulting in large patches of defocus when examined under the microscope. A diagnostic aggregate of cells often cannot be viewed in focus together, requiring pathologists to continually manipulate the focal plane, complicating the task of accurately assessing the entire cellular aggregate and thus in making a diagnosis. Further, it is extremely difficult to acquire useful uniformly in-focus digital images of cytology preparations for applications such as remote diagnostic evaluations and artificial intelligence models. The predominant current method to address this issue is to acquire digital images at multiple focal planes of the entire slide, which demands long scanning time, complex and expensive scanning systems, and huge storage capacity. Aims: Here we report a unique imaging method that can acquire cytologic images efficiently and computationally render all-in-focus digital images that are highly compact. Methods and material: This method applies a metric-based digital refocusing to microscopy data collected with a Fourier ptychographic microscope (FPM). The digitally refocused patches of images are then synthesized into an all-in-focus image. Results: We report all-in-focus FPM results of thyroid fine needle aspiration (FNA) cytology samples, demonstrating our method's ability to overcome the height variance of 30⯵m caused by cell aggregation, and rendering images at high resolution (corresponds to a standard microscope with objective NA of 0.75) and that are all-in-focus. Conclusions: This technology is applicable to standard microscopes, and we believe can have an impact on diagnostic accuracy as well as ease and speed of diagnosing challenging specimens. While we focus on cytology slides here, we anticipate this technology's advantages will translate well for histology applications. This technique also addresses the issue of remote rapid evaluation of cytology preparations. Finally, we believe that by resolving the focus heterogeneity issues in standard digital images, this technique is a critical advance for applying machine learning to cytology specimens.
ABSTRACT
Over the past decade, the research field of Fourier Ptychographic Microscopy (FPM) has seen numerous innovative developments that significantly expands its utility. Here, we report a high numerical aperture (NA) FPM implementation that incorporates some of these innovations to achieve a synthetic NA of 1.9 - close to the maximum possible synthetic NA of 2 for a free space FPM system. At this high synthetic NA, we experimentally found that it is vital to homogenize the illumination field in order to achieve the best resolution. Our FPM implementation has a full pitch resolution of 266 nm for 465 nm light, and depth of field of 3.6 µm. In comparison, a standard transmission microscope (incoherent) with close to maximum possible NA of 0.95 has a full pitch resolution of 318 nm for 465 nm light, and depth of field of 0.65 µm. While it is generally assumed that a free-space coherent imaging system and a free-space incoherent imaging system operating at their respective maximum NA should give comparable resolution, we experimentally find that an FPM system significantly outperforms its incoherent standard microscopy counterpart in resolution by a factor of 20%. Coupled with FPM's substantially longer effective depth of field (5.5 times longer), our work indicates that, in the near-maximum NA operation regime, the FPM has significant resolution and depth of field advantages over incoherent standard microscopy.
ABSTRACT
Light scattering poses a challenge for imaging deep in scattering media as the ballistic light exponentially attenuates with depth. In contrast to the ballistic light, the multiply scattered light penetrates deeper and also contains information about the sample. One technique to image deeper is to selectively detect only a subset of the multiply scattered light, namely the 'snake' photons, which are predominantly forward scattered and retain more direct information than the more strongly scattered light. In this work, we develop a technique, termed speckle-resolved optical coherence tomography (srOCT), for efficiently detecting these 'snake' photons to enable imaging deeper in scattering media. The system couples spatio-angular filtering with speckle-resolved interferometric detection to preferentially and efficiently detect the weakly scattered 'snake' photons. With our proof-of-concept system, we demonstrate depth-resolved imaging beyond the ballistic limit, up to a depth of 90 round-trip MFPs in a scattering phantom and a depth of 4.5 mm of chicken tissue at 0.4 mm axial and lateral resolution.
ABSTRACT
Polarization of the mammalian embryo at the right developmental time is critical for its development to term and would be valuable in assessing the potential of human embryos. However, tracking polarization requires invasive fluorescence staining, impermissible in the in vitro fertilization clinic. Here, we report the use of artificial intelligence to detect polarization from unstained time-lapse movies of mouse embryos. We assembled a dataset of bright-field movie frames from 8-cell-stage embryos, side-by-side with corresponding images of fluorescent markers of cell polarization. We then used an ensemble learning model to detect whether any bright-field frame showed an embryo before or after onset of polarization. Our resulting model has an accuracy of 85% for detecting polarization, significantly outperforming human volunteers trained on the same data (61% accuracy). We discovered that our self-learning model focuses upon the angle between cells as one known cue for compaction, which precedes polarization, but it outperforms the use of this cue alone. By compressing three-dimensional time-lapsed image data into two-dimensions, we are able to reduce data to an easily manageable size for deep learning processing. In conclusion, we describe a method for detecting a key developmental feature of embryo development that avoids clinically impermissible fluorescence staining.
Subject(s)
Cell Polarity , Deep Learning , Embryo, Mammalian/cytology , Animals , Coloring Agents/chemistry , Embryo, Mammalian/chemistry , Embryo, Mammalian/embryology , Embryonic Development , Fertilization in Vitro , Humans , Mice , Staining and LabelingABSTRACT
For the past decade, optical wavefront shaping has been the standard technique to control light through scattering media. Implicit in this dominance is the assumption that manipulating optical interference is a necessity for optical control through scattering media. In this paper, we challenge this assumption by reporting on an alternate approach for light control through a disordered scattering medium - optical-channel-based intensity streaming (OCIS). Instead of actively tuning the interference between the optical paths via wavefront shaping, OCIS controls light and transmits information through scattering media through linear intensity operations. We demonstrate a set of OCIS experiments that connect to some wavefront shaping implementations, i.e. iterative wavefront optimization, digital optical phase conjugation, image transmission through transmission matrix, and direct imaging through scattering media. We experimentally created focus patterns through scattering media on a sub-millisecond timescale. We also demonstrate that OCIS enables a scattering medium mediated secure optical communication application.
Subject(s)
Light , Optical Devices , Optical Imaging/instrumentation , Optical Imaging/methods , Scattering, Radiation , Algorithms , Models, Theoretical , Optical PhenomenaABSTRACT
Global anal cancer incidence is increasing. High resolution anoscopy (HRA) currently screens for anal cancer, although the definitive test remains unknown. To improve on intraluminal imaging of the anal canal, we conducted a first-in-human study to determine feasibility and safety of a high-resolution, wide field-of-view scanning endoscope. Fourteen patients, under an IRB-approved clinical study, underwent exam under anesthesia, HRA, and imaging with the experimental device. HRA findings were photographed using an in-line camera attached to the colposcope and compared with the scanning endoscope images. Patients were followed up within 2 weeks of the procedure. The imaging device is inserted into the anal canal and the intraluminal surface is digitally photographed in 10 s and uploaded to a computer monitor for review. Ten patients completed imaging with the device. Three patients were not imaged due to severe anal stenosis. One patient was not imaged due to technical device malfunction. The device images were compared to the HRA images. No adverse event attributable to the device was reported. The intraluminal scanning endoscope can be used for circumferential anal canal imaging and is safe for clinical use. Future clinical studies are needed to evaluate the performance of this device.
Subject(s)
Anus Diseases/diagnosis , Early Detection of Cancer , Endoscopes, Gastrointestinal , Intestines/diagnostic imaging , Precancerous Conditions/diagnosis , Aged , Anal Canal/diagnostic imaging , Anal Canal/pathology , Anus Diseases/diagnostic imaging , Anus Diseases/pathology , Colposcopes/standards , Diagnostic Imaging/instrumentation , Diagnostic Imaging/methods , Feasibility Studies , Female , Humans , Intestines/ultrastructure , Male , Middle Aged , Precancerous Conditions/diagnostic imaging , Precancerous Conditions/pathologyABSTRACT
Prefilled syringes (PFSs) are commonly used for parenteral delivery of protein therapeutics. In PFSs, the inner surface of the syringe barrel is typically coated with silicone oil for lubrication. The total amount of silicone oil as well as its distribution can impact syringe functionality and particle formation. However, methods to non-destructively characterize the silicone oil distribution are limited. In this paper, we developed a method to visualize and quantify the relative distribution of silicone oil in unfilled syringes using a custom-built multi-color interferometric imaging system. We then applied the system in a preliminary study to investigate the impact of the silicone oil distribution on the number of particles formed in solution after filling and extrusion for two different types of syringes. The syringe type with significantly lower particle counts also exhibited significantly more homogeneous silicone oil distributions. Within syringe types, no significant association was found between silicone oil distribution and particle formation. Our method can be used in further studies that investigate the impact of syringe siliconization on PFS functionality and particle formation.