InstantScope: a low-cost whole slide imaging system with instant focal plane detection.
Ontology highlight
ABSTRACT:
SUBMITTER: Guo K
PROVIDER: S-EPMC4574649 | biostudies-other | 2015 Sep
REPOSITORIES: biostudies-other
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Project description:Whole slide scanners are novel devices that enable high-resolution imaging of an entire histological slide. Furthermore, the imaging is achieved in only a few minutes, which enables image rendering of large-scale studies involving multiple immunohistochemistry biomarkers. Although whole slide imaging has improved considerably, locally poor focusing causes blurred regions of the image. These artifacts may strongly affect the quality of subsequent analyses, making a slide review process mandatory. This tedious and time-consuming task requires the scanner operator to carefully assess the virtual slide and to manually select new focus points. We propose a statistical learning method that provides early image quality feedback and automatically identifies regions of the image that require additional focus points.
| S-EPMC3862630 | biostudies-literature
Project description:Digital pathology via whole-slide imaging (WSI) systems has recently been approved for the primary diagnostic use in the US. Acquiring whole-slide images with spectral information at each pixel permits the use of multiplexed antibody labeling and allow for the measurement of cellularly resolved chemical information. Here, we report the development of a high-throughput terapixel hyperspectral WSI system using prism-based slit-array dispersion. We demonstrate a slit-array detection scheme for absorption-based measurements and a slit-array projection scheme for fluorescence-based measurements. The spectral resolution and spectral range in the reported schemes can be adjusted by changing the orientation of the slit-array mask. We use our system to acquire 74 5-megapixel brightfield images at different wavelengths in ∼1 s, corresponding to a throughput of 0.375 gigapixels / s. A terapixel whole-slide spatial-spectral data cube can be obtained in ∼45 min. The reported system is compatible with existing WSI systems and can be developed as an add-on module for whole-slide spectral imaging. It may find broad applications in high-throughput chemical imaging with multiple antibody labeling. The use of slit array for structured illumination may also provide insights for developing high-throughput hyperspectral confocal imaging systems.
| S-EPMC8357323 | biostudies-literature
Project description:Faced with the need to support a growing number of whole slide imaging (WSI) file formats, our team has extended a long-standing community file format (OME-TIFF) for use in digital pathology. The format makes use of the core TIFF specification to store multi-resolution (or "pyramidal") representations of a single slide in a flexible, performant manner. Here we describe the structure of this format, its performance characteristics, as well as an open-source library support for reading and writing pyramidal OME-TIFFs.
| S-EPMC6774793 | biostudies-literature
Project description:BackgroundIn osteosarcoma survival rates could not be improved over the last 30 years. Novel biomarkers are warranted to allow risk stratification of patients for more individual treatment following initial diagnosis. Although previous studies of the tumor microenvironment have identified promising candidates, novel biomarkers have not been translated into routine histopathology. Substantial difficulties regarding immunohistochemical detection and quantification of antigens in decalcified and heterogeneous osteosarcoma might largely explain this translational short-coming. Furthermore, we hypothesized that conventional hot spot analysis is often not representative for the whole section when applied to heterogeneous tissues like osteosarcoma. We aimed to overcome these difficulties for major biomarkers of the immunovascular microenvironment.MethodsImmunohistochemistry was systematically optimized for cell surface (CD31, CD8) and intracellular antigens (FOXP3) including evaluation of 200 different antigen retrieval conditions. Distribution patterns of these antigens were analyzed in formalin-fixed and paraffin-embedded samples from 120 high-grade central osteosarcoma biopsies and computer-assisted whole-slide analysis was compared with conventional quantification methods including hot spot analysis.ResultsMore than 96% of osteosarcoma samples were positive for all antigens after optimization of immunohistochemistry. In contrast, standard immunohistochemistry retrieved false negative results in 35-65% of decalcified osteosarcoma specimens. Standard hot spot analysis was applicable for homogeneous distributed FOXP3+ and CD8+ cells. However, heterogeneous distribution of vascular CD31 did not allow reliable quantification with hot spot analysis in 85% of all samples. Computer-assisted whole-slide analysis of total CD31- immunoreactive area proved as the most appropriate quantification method.ConclusionStandard staining and quantification procedures are not applicable in decalcified formalin-fixed and paraffin-embedded samples for major parameters of the immunovascular microenvironment in osteosarcoma. Whole-slide imaging and optimized antigen retrieval overcome these limitations.
| S-EPMC3940945 | biostudies-literature
Project description:BackgroundThe aim was to develop scalable Whole Slide Imaging (sWSI), a WSI system based on mainstream smartphones coupled with regular optical microscopes. This ultra-low-cost solution should offer diagnostic-ready imaging quality on par with standalone scanners, supporting both oil and dry objective lenses of different magnifications, and reasonably high throughput. These performance metrics should be evaluated by expert pathologists and match those of high-end scanners.ObjectiveThe aim was to develop scalable Whole Slide Imaging (sWSI), a whole slide imaging system based on smartphones coupled with optical microscopes. This ultra-low-cost solution should offer diagnostic-ready imaging quality on par with standalone scanners, supporting both oil and dry object lens of different magnification. All performance metrics should be evaluated by expert pathologists and match those of high-end scanners.MethodsIn the sWSI design, the digitization process is split asynchronously between light-weight clients on smartphones and powerful cloud servers. The client apps automatically capture FoVs at up to 12-megapixel resolution and process them in real-time to track the operation of users, then give instant feedback of guidance. The servers first restitch each pair of FoVs, then automatically correct the unknown nonlinear distortion introduced by the lens of the smartphone on the fly, based on pair-wise stitching, before finally combining all FoVs into one gigapixel VS for each scan. These VSs can be viewed using Internet browsers anywhere. In the evaluation experiment, 100 frozen section slides from patients randomly selected among in-patients of the participating hospital were scanned by both a high-end Leica scanner and sWSI. All VSs were examined by senior pathologists whose diagnoses were compared against those made using optical microscopy as ground truth to evaluate the image quality.ResultsThe sWSI system is developed for both Android and iPhone smartphones and is currently being offered to the public. The image quality is reliable and throughput is approximately 1 FoV per second, yielding a 15-by-15 mm slide under 20X object lens in approximately 30-35 minutes, with little training required for the operator. The expected cost for setup is approximately US $100 and scanning each slide costs between US $1 and $10, making sWSI highly cost-effective for infrequent or low-throughput usage. In the clinical evaluation of sample-wise diagnostic reliability, average accuracy scores achieved by sWSI-scan-based diagnoses were as follows: 0.78 for breast, 0.88 for uterine corpus, 0.68 for thyroid, and 0.50 for lung samples. The respective low-sensitivity rates were 0.05, 0.05, 0.13, and 0.25 while the respective low-specificity rates were 0.18, 0.08, 0.20, and 0.25. The participating pathologists agreed that the overall quality of sWSI was generally on par with that produced by high-end scanners, and did not affect diagnosis in most cases. Pathologists confirmed that sWSI is reliable enough for standard diagnoses of most tissue categories, while it can be used for quick screening of difficult cases.ConclusionsAs an ultra-low-cost alternative to whole slide scanners, diagnosis-ready VS quality and robustness for commercial usage is achieved in the sWSI solution. Operated on main-stream smartphones installed on normal optical microscopes, sWSI readily offers affordable and reliable WSI to resource-limited or infrequent clinical users.
| S-EPMC5622289 | biostudies-literature
Project description:Plants naturally contain high levels of the stress-responsive fluorophore chlorophyll. Chlorophyll fluorescence imaging (CFI) is a powerful tool to measure photosynthetic efficiency in plants and provides the ability to detect damage from a range of biotic and abiotic stresses before visible symptoms occur. However, most CFI systems are complex, expensive systems that use pulse amplitude modulation (PAM) fluorometry. Here, we test a simple CFI system, that does not require PAM fluorometry, but instead simply images fluorescence emitted by plants. We used this technique to visualize stress induced by the photosystem II-inhibitory herbicide atrazine. After applying atrazine as a soil drench, CFI and color images were taken at 15-minute intervals, alongside measurements from a PAM fluorometer and a leaf reflectometer. Pixel intensity of the CFI images was negatively correlated with the quantum yield of photosystem II (ΦPSII) (p < 0.0001) and positively correlated with the measured reflectance in the spectral region of chlorophyll fluorescence emissions (p < 0.0001). A fluorescence-based stress index was developed using the reflectometer measurements based on wavelengths with the highest (741.2 nm) and lowest variability (548.9 nm) in response to atrazine damage. This index was correlated with ΦPSII (p < 0.0001). Low-cost CFI imaging can detect herbicide-induced stress (and likely other stressors) before there is visual damage.
| S-EPMC7999708 | biostudies-literature
Project description:Simultaneous longitudinal imaging across multiple conditions and replicates has been crucial for scientific studies aiming to understand biological processes and disease. Yet, imaging systems capable of accomplishing these tasks are economically unattainable for most academic and teaching laboratories around the world. Here, we propose the Picroscope, which is the first low-cost system for simultaneous longitudinal biological imaging made primarily using off-the-shelf and 3D-printed materials. The Picroscope is compatible with standard 24-well cell culture plates and captures 3D z-stack image data. The Picroscope can be controlled remotely, allowing for automatic imaging with minimal intervention from the investigator. Here, we use this system in a range of applications. We gathered longitudinal whole organism image data for frogs, zebrafish, and planaria worms. We also gathered image data inside an incubator to observe 2D monolayers and 3D mammalian tissue culture models. Using this tool, we can measure the behavior of entire organisms or individual cells over long-time periods.
| S-EPMC8569150 | biostudies-literature
Project description:OBJECTIVES:With the objective of bringing clinical decision support systems to reality, this article reviews histopathological whole-slide imaging informatics methods, associated challenges, and future research opportunities. TARGET AUDIENCE:This review targets pathologists and informaticians who have a limited understanding of the key aspects of whole-slide image (WSI) analysis and/or a limited knowledge of state-of-the-art technologies and analysis methods. SCOPE:First, we discuss the importance of imaging informatics in pathology and highlight the challenges posed by histopathological WSI. Next, we provide a thorough review of current methods for: quality control of histopathological images; feature extraction that captures image properties at the pixel, object, and semantic levels; predictive modeling that utilizes image features for diagnostic or prognostic applications; and data and information visualization that explores WSI for de novo discovery. In addition, we highlight future research directions and discuss the impact of large public repositories of histopathological data, such as the Cancer Genome Atlas, on the field of pathology informatics. Following the review, we present a case study to illustrate a clinical decision support system that begins with quality control and ends with predictive modeling for several cancer endpoints. Currently, state-of-the-art software tools only provide limited image processing capabilities instead of complete data analysis for clinical decision-making. We aim to inspire researchers to conduct more research in pathology imaging informatics so that clinical decision support can become a reality.
| S-EPMC3822114 | biostudies-literature
Project description:Whole-slide histology images contain information that is valuable for clinical and basic science investigations of cancer but extracting quantitative measurements from these images is challenging for researchers who are not image analysis specialists. In this article, we describe HistomicsML2, a software tool for learn-by-example training of machine learning classifiers for histologic patterns in whole-slide images. This tool improves training efficiency and classifier performance by guiding users to the most informative training examples for labeling and can be used to develop classifiers for prospective application or as a rapid annotation tool that is adaptable to different cancer types. HistomicsML2 runs as a containerized server application that provides web-based user interfaces for classifier training, validation, exporting inference results, and collaborative review, and that can be deployed on GPU servers or cloud platforms. We demonstrate the utility of this tool by using it to classify tumor-infiltrating lymphocytes in breast carcinoma and cutaneous melanoma. SIGNIFICANCE: An interactive machine learning tool for analyzing digital pathology images enables cancer researchers to apply this tool to measure histologic patterns for clinical and basic science studies.
| S-EPMC8026494 | biostudies-literature
Project description:ObjectivesThe ongoing global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic necessitates adaptations in the practice of surgical pathology at scale. Primary diagnosis by whole-slide imaging (WSI) is a key component that would aid departments in providing uninterrupted histopathology diagnosis and maintaining revenue streams from disruption. We sought to perform rapid validation of the use of WSI in primary diagnosis meeting recommendations of the College of American Pathologists guidelines.MethodsGlass slides from clinically reported cases from 5 participating pathologists with a preset washout period were digitally scanned and reviewed in settings identical to typical reporting. Cases were classified as concordant or with minor or major disagreement with the original diagnosis. Randomized subsampling was performed, and mean concordance rates were calculated.ResultsIn total, 171 cases were included and distributed equally among participants. For the group as a whole, the mean concordance rate in sampled cases (n = 90) was 83.6% counting all discrepancies and 94.6% counting only major disagreements. The mean pathologist concordance rate in sampled cases (n = 18) ranged from 90.49% to 97%.ConclusionsWe describe a novel double-blinded method for rapid validation of WSI for primary diagnosis. Our findings highlight the occurrence of a range of diagnostic reproducibility when deploying digital methods.
| S-EPMC7929400 | biostudies-literature