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Favilla CG, Baird GL, Grama K, Konecky S, Carter S, Smith W, Gitlevich R, Lebron-Cruz A, Yodh AG, McTaggart RA. Portable cerebral blood flow monitor to detect large vessel occlusion in patients with suspected stroke. J Neurointerv Surg 2024:jnis-2024-021536. [PMID: 38514189 DOI: 10.1136/jnis-2024-021536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 03/10/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Early detection of large vessel occlusion (LVO) facilitates triage to an appropriate stroke center to reduce treatment times and improve outcomes. Prehospital stroke scales are not sufficiently sensitive, so we investigated the ability of the portable Openwater optical blood flow monitor to detect LVO. METHODS Patients were prospectively enrolled at two comprehensive stroke centers during stroke alert evaluation within 24 hours of onset with National Institutes of Health Stroke Scale (NIHSS) score ≥2. A 70 s bedside optical blood flow scan generated cerebral blood flow waveforms based on relative changes in speckle contrast. Anterior circulation LVO was determined by CT angiography. A deep learning model trained on all patient data using fivefold cross-validation and learned discriminative representations from the raw speckle contrast waveform data. Receiver operating characteristic (ROC) analysis compared the Openwater diagnostic performance (ie, LVO detection) with prehospital stroke scales. RESULTS Among 135 patients, 52 (39%) had an anterior circulation LVO. The median NIHSS score was 8 (IQR 4-14). The Openwater instrument had 79% sensitivity and 84% specificity for the detection of LVO. The rapid arterial occlusion evaluation (RACE) scale had 60% sensitivity and 81% specificity and the Los Angeles motor scale (LAMS) had 50% sensitivity and 81% specificity. The binary Openwater classification (high-likelihood vs low-likelihood) had an area under the ROC (AUROC) of 0.82 (95% CI 0.75 to 0.88), which outperformed RACE (AUC 0.70; 95% CI 0.62 to 0.78; P=0.04) and LAMS (AUC 0.65; 95% CI 0.57 to 0.73; P=0.002). CONCLUSIONS The Openwater optical blood flow monitor outperformed prehospital stroke scales for the detection of LVO in patients undergoing acute stroke evaluation in the emergency department. These encouraging findings need to be validated in an independent test set and the prehospital environment.
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Affiliation(s)
- Christopher G Favilla
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Grayson L Baird
- Department of Interventional Radiology, Brown University, Providence, Rhode Island, USA
| | | | | | - Sarah Carter
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Wendy Smith
- Department of Diagnostic Imaging, Lifespan Health System, Providence, Rhode Island, USA
| | - Rebecca Gitlevich
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alexa Lebron-Cruz
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Arjun G Yodh
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ryan A McTaggart
- Department of Interventional Radiology, Brown University, Providence, Rhode Island, USA
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Maric D, Jahanipour J, Li XR, Singh A, Mobiny A, Van Nguyen H, Sedlock A, Grama K, Roysam B. Whole-brain tissue mapping toolkit using large-scale highly multiplexed immunofluorescence imaging and deep neural networks. Nat Commun 2021; 12:1550. [PMID: 33692351 PMCID: PMC7946933 DOI: 10.1038/s41467-021-21735-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 02/09/2021] [Indexed: 12/17/2022] Open
Abstract
Mapping biological processes in brain tissues requires piecing together numerous histological observations of multiple tissue samples. We present a direct method that generates readouts for a comprehensive panel of biomarkers from serial whole-brain slices, characterizing all major brain cell types, at scales ranging from subcellular compartments, individual cells, local multi-cellular niches, to whole-brain regions from each slice. We use iterative cycles of optimized 10-plex immunostaining with 10-color epifluorescence imaging to accumulate highly enriched image datasets from individual whole-brain slices, from which seamless signal-corrected mosaics are reconstructed. Specific fluorescent signals of interest are isolated computationally, rejecting autofluorescence, imaging noise, cross-channel bleed-through, and cross-labeling. Reliable large-scale cell detection and segmentation are achieved using deep neural networks. Cell phenotyping is performed by analyzing unique biomarker combinations over appropriate subcellular compartments. This approach can accelerate pre-clinical drug evaluation and system-level brain histology studies by simultaneously profiling multiple biological processes in their native anatomical context.
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Affiliation(s)
- Dragan Maric
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, 20892, USA.
| | - Jahandar Jahanipour
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, 20892, USA
- Cullen College of Engineering, University of Houston, Houston, TX, 77204, USA
| | - Xiaoyang Rebecca Li
- Cullen College of Engineering, University of Houston, Houston, TX, 77204, USA
| | - Aditi Singh
- Cullen College of Engineering, University of Houston, Houston, TX, 77204, USA
| | - Aryan Mobiny
- Cullen College of Engineering, University of Houston, Houston, TX, 77204, USA
| | - Hien Van Nguyen
- Cullen College of Engineering, University of Houston, Houston, TX, 77204, USA
| | - Andrea Sedlock
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, 20892, USA
| | - Kedar Grama
- Cullen College of Engineering, University of Houston, Houston, TX, 77204, USA
| | - Badrinath Roysam
- Cullen College of Engineering, University of Houston, Houston, TX, 77204, USA.
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Isse K, Lesniak A, Grama K, Maier J, Specht S, Castillo-Rama M, Lunz J, Roysam B, Michalopoulos G, Demetris AJ. Preexisting epithelial diversity in normal human livers: a tissue-tethered cytometric analysis in portal/periportal epithelial cells. Hepatology 2013; 57:1632-43. [PMID: 23150208 PMCID: PMC3612393 DOI: 10.1002/hep.26131] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2012] [Revised: 10/17/2012] [Accepted: 10/17/2012] [Indexed: 12/17/2022]
Abstract
UNLABELLED Routine light microscopy identifies two distinct epithelial cell populations in normal human livers: hepatocytes and biliary epithelial cells (BECs). Considerable epithelial diversity, however, arises during disease states when a variety of hepatocyte-BEC hybrid cells appear. This has been attributed to activation and differentiation of putative hepatic progenitor cells (HPC) residing in the canals of Hering and/or metaplasia of preexisting mature epithelial cells. A novel analytic approach consisting of multiplex labeling, high-resolution whole-slide imaging (WSI), and automated image analysis was used to determine if more complex epithelial cell phenotypes preexist in normal adult human livers, which might provide an alternative explanation for disease-induced epithelial diversity. "Virtually digested" WSI enabled quantitative cytometric analyses of individual cells displayed in a variety of formats (e.g., scatterplots) while still tethered to the WSI and tissue structure. We employed biomarkers specifically associated with mature epithelial forms (HNF4α for hepatocytes, CK19 and HNF1β for BEC) and explored for the presence of cells with hybrid biomarker phenotypes. The results showed abundant hybrid cells in portal bile duct BEC, canals of Hering, and immediate periportal hepatocytes. These bipotential cells likely serve as a reservoir for the epithelial diversity of ductular reactions, appearance of hepatocytes in bile ducts, and the rapid and fluid transition of BEC to hepatocytes, and vice versa. CONCLUSION Novel imaging and computational tools enable increased information extraction from tissue samples and quantify the considerable preexistent hybrid epithelial diversity in normal human liver. This computationally enabled tissue analysis approach offers much broader potential beyond the results presented here.
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Affiliation(s)
- Kumiko Isse
- Department of Pathology, University of Pittsburgh Medical Center,Department of Pathology, Division of Liver and Transplantation Pathology, Thomas E. Starzl Transplantation Institute, University of Pittsburgh
| | - Andrew Lesniak
- Department of Pathology, University of Pittsburgh Medical Center,Department of Pathology, Division of Liver and Transplantation Pathology, Thomas E. Starzl Transplantation Institute, University of Pittsburgh
| | - Kedar Grama
- Department of Electrical & Computer Engineering, University of Houston
| | - John Maier
- Department of Family Medicine, University of Pittsburgh Medical Center
| | - Susan Specht
- Department of Pathology, University of Pittsburgh Medical Center,Department of Pathology, Division of Liver and Transplantation Pathology, Thomas E. Starzl Transplantation Institute, University of Pittsburgh
| | - Marcela Castillo-Rama
- Department of Pathology, University of Pittsburgh Medical Center,Department of Pathology, Division of Liver and Transplantation Pathology, Thomas E. Starzl Transplantation Institute, University of Pittsburgh
| | - John Lunz
- Department of Pathology, University of Pittsburgh Medical Center,Department of Pathology, Division of Liver and Transplantation Pathology, Thomas E. Starzl Transplantation Institute, University of Pittsburgh
| | - Badrinath Roysam
- Department of Electrical & Computer Engineering, University of Houston
| | | | - Anthony J. Demetris
- Department of Pathology, University of Pittsburgh Medical Center,Department of Pathology, Division of Liver and Transplantation Pathology, Thomas E. Starzl Transplantation Institute, University of Pittsburgh
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Isse K, Lesniak A, Grama K, Roysam B, Minervini MI, Demetris AJ. Digital transplantation pathology: combining whole slide imaging, multiplex staining and automated image analysis. Am J Transplant 2012; 12:27-37. [PMID: 22053785 PMCID: PMC3627485 DOI: 10.1111/j.1600-6143.2011.03797.x] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. "-Omics" analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a "systems" model. Nevertheless, except for immunostaining, no transformative advancements have "modernized" routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology-global "-omic" analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes.
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Affiliation(s)
- Kumiko Isse
- Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center,Department of Pathology, Tomas E. Starzl Transplantation Institute, University of Pittsburgh
| | - Andrew Lesniak
- Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center,Department of Pathology, Tomas E. Starzl Transplantation Institute, University of Pittsburgh
| | - Kedar Grama
- Department of Electrical & Computer Engineering, University of Houston
| | - Badrinath Roysam
- Department of Electrical & Computer Engineering, University of Houston
| | - Martha I. Minervini
- Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center
| | - Anthony J Demetris
- Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center,Department of Pathology, Tomas E. Starzl Transplantation Institute, University of Pittsburgh
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Al-Kofahi Y, Lassoued W, Grama K, Nath SK, Zhu J, Oueslati R, Feldman M, Lee WMF, Roysam B. Cell-based quantification of molecular biomarkers in histopathology specimens. Histopathology 2011; 59:40-54. [PMID: 21771025 DOI: 10.1111/j.1365-2559.2011.03878.x] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
AIMS To investigate the use of a computer-assisted technology for objective, cell-based quantification of molecular biomarkers in specified cell types in histopathology specimens, with the aim of advancing current visual estimation and pixel-level (rather than cell-based) quantification methods. METHODS AND RESULTS Tissue specimens were multiplex-immunostained to reveal cell structures, cell type markers, and analytes, and imaged with multispectral microscopy. The image data were processed with novel software that automatically delineates and types each cell in the field, measures morphological features, and quantifies analytes in different subcellular compartments of specified cells.The methodology was validated with the use of cell blocks composed of differentially labelled cultured cells mixed in known proportions, and evaluated on human breast carcinoma specimens for quantifying human epidermal growth factor receptor 2, estrogen receptor, progesterone receptor, Ki67, phospho-extracellular signal-related kinase, and phospho-S6. Automated cell-level analyses closely matched human assessments, but, predictably, differed from pixel-level analyses of the same images. CONCLUSIONS Our method reveals the type, distribution, morphology and biomarker state of each cell in the field, and allows multiple biomarkers to be quantified over specified cell types, regardless of their abundance. It is ideal for studying specimens from patients in clinical trials of targeted therapeutic agents, for investigating minority stromal cell subpopulations, and for phenotypic characterization to personalize therapy and prognosis.
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Affiliation(s)
- Yousef Al-Kofahi
- Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
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Isse K, Grama K, Abbott IM, Lesniak A, Lunz JG, Lee WMF, Specht S, Corbitt N, Mizuguchi Y, Roysam B, Demetris AJ. Adding value to liver (and allograft) biopsy evaluation using a combination of multiplex quantum dot immunostaining, high-resolution whole-slide digital imaging, and automated image analysis. Clin Liver Dis 2010; 14:669-85. [PMID: 21055689 DOI: 10.1016/j.cld.2010.07.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Various technologies including nucleic acid, protein, and metabolic array analyses of blood, liver tissue, and bile are emerging as powerful tools in the study of hepatic pathophysiology. The entire lexicon of liver disease, however, has been written using classical hematoxylin-eosin staining and light microscopic examination. The authors' goal is to develop new tools to enhance histopathologic examination of liver tissue that would enrich the information gained from liver biopsy analysis, enable quantitative analysis, and bridge the gap between various "-omics" tools and interpretation of routine liver biopsy results. This article describes the progress achieved during the past 2 years in developing multiplex quantum dot (nanoparticle) staining and combining it with high-resolution whole-slide imaging using a slide scanner equipped with filters to capture 9 distinct fluorescent signals for multiple antigens. The authors first focused on precise characterization of leukocyte subsets, but soon realized that the data generated were beyond the practical limits that could be properly evaluated, analyzed, and interpreted visually by a pathologist. Therefore, the authors collaborated with the open source FARSIGHT image analysis project (http://www.farsight-toolkit.org). FARSIGHT's goal is to develop and disseminate the next-generation toolkit of automated image analysis methods to enable quantification of molecular biomarkers on a cell-by-cell basis from multiparameter images. The resulting data can be used for histocytometric studies of the complex and dynamic tissue microenvironments that are of biomedical interest. The authors envisage that these tools will eventually be incorporated into the routine practice of surgical pathology and precipitate a revolution in the specialty.
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Affiliation(s)
- Kumiko Isse
- Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center, E741 Montefiore, 200 Lothrop Street, Pittsburgh, PA 15231, USA
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