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Huang CZ, Montague JE, Ching-Roa VD, Drage MG, Ibrahim SF, Giacomelli MG. Rapid clearing and imaging of Mohs and melanoma surgical margins using a low-cost tissue processor. BIOMEDICAL OPTICS EXPRESS 2024; 15:700-714. [PMID: 38404330 PMCID: PMC10890881 DOI: 10.1364/boe.510132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 02/27/2024]
Abstract
Tissue clearing methods render biological tissues transparent while maintaining tissue structure, enabling visualization of entire tissues. Recent developments in tissue clearing have predominantly emphasized preserving intrinsic fluorescent proteins or aqueous-based tissue clearing and so typically involve complex procedures and long processing times. The utilization of tissue clearing protocols in standard of care histology settings has been less well explored, and protocols for rapid clearing of human tissue specimens are limited. This study presents a novel rapid clearing protocol and demonstrates a low-cost tissue processor for high volume rapid tissue clearing that can be intergraded into standard histology workflow. We demonstrate rapid clearing in dermatological specimens, including both nonmelanoma and melanoma excisions.
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Affiliation(s)
- Chi Z. Huang
- Department of Biomedical Engineering, University of Rochester, 207 Goergen Hall, Box 270168, Rochester, NY 14627, USA
| | - Jenna E. Montague
- Wyant College of Optical Sciences, University of Arizona, 1630 E University Blvd, Tucson, AZ, 85719, USA
| | - Vincent D. Ching-Roa
- Department of Biomedical Engineering, University of Rochester, 207 Goergen Hall, Box 270168, Rochester, NY 14627, USA
| | - Michael G. Drage
- Department of Pathology, Mass General Brigham, 399 Revolution Drive, Somerville, MA 02145, USA
| | - Sherrif F. Ibrahim
- Rochester Dermatologic Surgery, PC, 7400 Pittsford Victor Rd Suite A, Victor, NY 14564, USA
- Department of Dermatology,
University of Rochester Medical Center, 601
Elmwood Ave, Rochester, NY 14620, USA
| | - Michael G. Giacomelli
- Department of Biomedical Engineering, University of Rochester, 207 Goergen Hall, Box 270168, Rochester, NY 14627, USA
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Reddi DM, Barner LA, Burke W, Gao G, Grady WM, Liu JTC. Nondestructive 3D Pathology Image Atlas of Barrett Esophagus With Open-Top Light-Sheet Microscopy. Arch Pathol Lab Med 2023; 147:1164-1171. [PMID: 36596255 DOI: 10.5858/arpa.2022-0133-oa] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/01/2022] [Indexed: 01/04/2023]
Abstract
CONTEXT.— Anatomic pathologists render diagnosis on tissue samples sectioned onto glass slides and viewed under a bright-field microscope. This approach is destructive to the sample, which can limit its use for ancillary assays that can inform patient management. Furthermore, the subjective interpretation of a relatively small number of 2D tissue sections per sample contributes to low interobserver agreement among pathologists for the assessment (diagnosis and grading) of various lesions. OBJECTIVE.— To evaluate 3D pathology data sets of thick formalin-fixed Barrett esophagus specimens imaged nondestructively with open-top light-sheet (OTLS) microscopy. DESIGN.— Formalin-fixed, paraffin-embedded Barrett esophagus samples (N = 15) were deparaffinized, stained with a fluorescent analog of hematoxylin-eosin, optically cleared, and imaged nondestructively with OTLS microscopy. The OTLS microscopy images were subsequently compared with archived hematoxylin-eosin histology sections from each sample. RESULTS.— Barrett esophagus samples, both small endoscopic forceps biopsies and endoscopic mucosal resections, exhibited similar resolvable structures between OTLS microscopy and conventional light microscopy with up to a ×20 objective (×200 overall magnification). The 3D histologic images generated by OTLS microscopy can enable improved discrimination of cribriform and well-formed gland morphologies. In addition, a much larger amount of tissue is visualized with OTLS microscopy, which enables improved assessment of clinical specimens exhibiting high spatial heterogeneity. CONCLUSIONS.— In esophageal specimens, OTLS microscopy can generate images comparable in quality to conventional light microscopy, with the advantages of providing 3D information for enhanced evaluation of glandular morphologies and enabling much more of the tissue specimen to be visualized nondestructively.
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Affiliation(s)
- Deepti M Reddi
- From the Department of Laboratory Medicine and Pathology (Reddi, Liu), University of Washington, Seattle
| | - Lindsey A Barner
- Department of Mechanical Engineering (Barner, Gao, Liu), University of Washington, Seattle
| | - Wynn Burke
- Department of Medicine (Burke, Grady), University of Washington, Seattle
- The Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington (Burke, Grady)
| | - Gan Gao
- Department of Mechanical Engineering (Barner, Gao, Liu), University of Washington, Seattle
| | - William M Grady
- Department of Medicine (Burke, Grady), University of Washington, Seattle
- The Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington (Burke, Grady)
| | - Jonathan T C Liu
- From the Department of Laboratory Medicine and Pathology (Reddi, Liu), University of Washington, Seattle
- Department of Mechanical Engineering (Barner, Gao, Liu), University of Washington, Seattle
- Department of Bioengineering (Liu), University of Washington, Seattle
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Duenweg SR, Bobholz SA, Lowman AK, Stebbins MA, Winiarz A, Nath B, Kyereme F, Iczkowski KA, LaViolette PS. Whole slide imaging (WSI) scanner differences influence optical and computed properties of digitized prostate cancer histology. J Pathol Inform 2023; 14:100321. [PMID: 37496560 PMCID: PMC10365953 DOI: 10.1016/j.jpi.2023.100321] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 06/13/2023] [Accepted: 06/28/2023] [Indexed: 07/28/2023] Open
Abstract
Purpose Digital pathology is becoming an increasingly popular area of advancement in both research and clinically. Pathologists are now able to manage and interpret slides digitally, as well as collaborate with external pathologists with digital copies of slides. Differences in slide scanners include variation in resolution, image contrast, and optical properties, which may influence downstream image processing. This study tested the hypothesis that varying slide scanners would result in differences in computed pathomic features on prostate cancer whole mount slides. Design This study collected 192 unique tissue slides from 30 patients following prostatectomy. Tissue samples were paraffin-embedded, stained for hematoxylin and eosin (H&E), and digitized using 3 different scanning microscopes at the highest available magnification rate, for a total of 3 digitized slides per tissue slide. These scanners included a (S1) Nikon microscope equipped with an automated sliding stage, an (S2) Olympus VS120 slide scanner, and a (S3) Huron TissueScope LE scanner. A color deconvolution algorithm was then used to optimize contrast by projecting the RGB image into color channels representing optical stain density. The resulting intensity standardized images were then computationally processed to segment tissue and calculate pathomic features including lumen, stroma, epithelium, and epithelial cell density, as well as second-order features including lumen area and roundness; epithelial area, roundness, and wall thickness; and cell fraction. For each tested feature, mean values of that feature per digitized slide were collected and compared across slide scanners using mixed effect models, fit to compare differences in the tested feature associated with all slide scanners for each slide, including a random effect of subject with a nested random effect of slide to account for repeated measures. Similar models were also computed for tissue densities to examine how differences in scanner impact downstream processing. Results Each mean color channel intensity (i.e., Red, Green, Blue) differed between slide scanners (all P<.001). Of the color deconvolved images, only the hematoxylin channel was similar in all 3 scanners (all P>.05). Lumen and stroma densities between S3 and S1 slides, and epithelial cell density between S3 and S2 (P>.05) were comparable but all other comparisons were significantly different (P<.05). The second-order features were found to be comparable for all scanner comparisons, except for lumen area and epithelium area. Conclusion This study demonstrates that both optical and computed properties of digitized histological samples are impacted by slide scanner differences. Future research is warranted to better understand which scanner properties influence the tissue segmentation process and to develop harmonization techniques for comparing data across multiple slide scanners.
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Affiliation(s)
- Savannah R. Duenweg
- Departments of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Samuel A. Bobholz
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Allison K. Lowman
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Margaret A. Stebbins
- Departments of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Aleksandra Winiarz
- Departments of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Biprojit Nath
- Departments of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Fitzgerald Kyereme
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Kenneth A. Iczkowski
- Department of Pathology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Peter S. LaViolette
- Departments of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
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Virmani S, Rao A, Menon MC. Allograft tissue under the microscope: only the beginning. Curr Opin Organ Transplant 2023; 28:126-132. [PMID: 36787238 PMCID: PMC10214011 DOI: 10.1097/mot.0000000000001052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
PURPOSE OF REVIEW To review novel modalities for interrogating a kidney allograft biopsy to complement the current Banff schema. RECENT FINDINGS Newer approaches of Artificial Intelligence (AI), Machine Learning (ML), digital pathology including Ex Vivo Microscopy, evaluation of the biopsy gene expression using bulk, single cell, and spatial transcriptomics and spatial proteomics are now available for tissue interrogation. SUMMARY Banff Schema of classification of allograft histology has standardized reporting of tissue pathology internationally greatly impacting clinical care and research. Inherent sampling error of biopsies, and lack of automated morphometric analysis with ordinal outputs limit its performance in prognostication of allograft health. Over the last decade, there has been an explosion of newer methods of evaluation of allograft tissue under the microscope. Digital pathology along with the application of AI and ML algorithms could revolutionize histopathological analyses. Novel molecular diagnostics such as spatially resolved single cell transcriptomics are identifying newer mechanisms underlying the pathologic diagnosis to delineate pathways of immunological activation, tissue injury, repair, and regeneration in allograft tissues. While these techniques are the future of tissue analysis, costs and complex logistics currently limit their clinical use.
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Affiliation(s)
- Sarthak Virmani
- Section of Nephrology, Division of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
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George RS, Htoo A, Cheng M, Masterson TM, Huang K, Adra N, Kaimakliotis HZ, Akgul M, Cheng L. Artificial intelligence in prostate cancer: Definitions, current research, and future directions. Urol Oncol 2022; 40:262-270. [PMID: 35430139 DOI: 10.1016/j.urolonc.2022.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 01/19/2022] [Accepted: 03/10/2022] [Indexed: 12/24/2022]
Abstract
Multiple novel modalities tasking artificial intelligence based computational pathology applications and integrating other variables, such as risk factors, tumor microenvironment, genomic testing data, laboratory findings, clinical history, and radiology findings, will improve diagnostic consistency and generate a synergistic diagnostic workflow. In this article, we present the concise and contemporary review on the utilization of artificial intelligence in prostate cancer and identify areas for possible future applications.
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Affiliation(s)
- Rose S George
- Department of Pathology and Laboratory Medicine, Albany Medical Center, Albany, NY
| | - Arkar Htoo
- Department of Pathology and Laboratory Medicine, Albany Medical Center, Albany, NY
| | - Michael Cheng
- Department of Medicine, Indianapolis, Indianapolis, IN
| | | | - Kun Huang
- Department of Medicine, Indianapolis, Indianapolis, IN; Department of Biostatistics and Health Data Science, Indianapolis, IN; Regenstrief Institute, Indianapolis, IN
| | - Nabil Adra
- Department of Medicine, Indianapolis, Indianapolis, IN; Department of Urology, Indianapolis, IN
| | | | - Mahmut Akgul
- Department of Pathology and Laboratory Medicine, Albany Medical Center, Albany, NY.
| | - Liang Cheng
- Department of Urology, Indianapolis, IN; Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN.
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Huang C, Ching-Roa V, Liu Y, Giacomelli MG. High-speed mosaic imaging using scanner-synchronized stage position sampling. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:016502. [PMID: 35075830 PMCID: PMC8786391 DOI: 10.1117/1.jbo.27.1.016502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 12/29/2021] [Indexed: 06/14/2023]
Abstract
SIGNIFICANCE Two-photon and confocal microscopy can obtain high frame rates; however, mosaic imaging of large tissue specimens remains time-consuming and inefficient, with higher imaging rates leading to a larger fraction of time wasted translating between imaging locations. Strip scanning obtains faster mosaic imaging rates by translating a specimen at constant velocity through a line scanner at the expense of more complex stitching and geometric distortion due to the difficulty of translating at completely constant velocity. AIM We aim to develop an approach to mosaic imaging that can obtain higher accuracy and faster imaging rates while reducing computational complexity. APPROACH We introduce an approach based on scanner-synchronous position sampling that enables subwavelength accurate imaging of specimens moving at a nonuniform velocity, eliminating distortion. RESULTS We demonstrate that this approach increases mosaic imaging rates while reducing computational complexity, retaining high SNR, and retaining geometric accuracy. CONCLUSIONS Scanner synchronous strip scanning enables accurate, high-speed mosaic imaging of large specimens by reducing acquisition and processing time.
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Affiliation(s)
- Chi Huang
- University of Rochester, Department of Biomedical Engineering, Rochester, New York, United States
| | - Vincent Ching-Roa
- University of Rochester, Department of Biomedical Engineering, Rochester, New York, United States
| | - Yihan Liu
- University of Rochester, Institute of Optics, Rochester, New York, United States
| | - Michael G. Giacomelli
- University of Rochester, Department of Biomedical Engineering, Rochester, New York, United States
- University of Rochester, Institute of Optics, Rochester, New York, United States
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Kim YJ, Roh EH, Park S. A literature review of quality, costs, process-associated with digital pathology. J Exerc Rehabil 2021; 17:11-14. [PMID: 33728283 PMCID: PMC7939987 DOI: 10.12965/jer.2142018.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 01/08/2021] [Indexed: 11/22/2022] Open
Abstract
Digital pathology incorporates the acquisition, management, sharing, and interpretation of pathological information, including slides and data, in a digital environment. Digital slides are created using a scanning device to capture a high-resolution image on glass slides for analysis on a computer or a mobile device. Though digital pathology has drastically grown over the last 10 years and has created opportunities to support specialists, few have attempted to address its full-scale implementation in routine clinical practice. To incorporate new technologies in diagnostic processes, it is necessary to study their application, the value they provide to specialists, and their effects on improvements across the entire workflow, rather than studying a particular element. In this study, we aimed to identify what have the current digital pathology systems contributed to the pathological and diagnostic process. We retrieved articles published between 2010 and 2020 from the databases PubMed and Google Scholar. We explored how digital pathology systems can better utilize existing medical data and new technologies within the current diagnostic workflow. While the evidence concerning the efficacy and effectiveness of digital pathology is mounting, high-quality evidence regarding its impact on resource allocation and value for diagnosis is still needed to support clinical diagnosis and policy decision-making.
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Affiliation(s)
- Yoo Jung Kim
- Department of Health Services Management, Graduate School, Kyung Hee University, Seoul, Korea
| | - Eul Hee Roh
- Department of Business Administration, College of Management, Kyung Hee University, Seoul, Korea
| | - Sangchan Park
- Department of Business Administration, College of Management, Kyung Hee University, Seoul, Korea
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