1
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Hosseini MS, Bejnordi BE, Trinh VQH, Chan L, Hasan D, Li X, Yang S, Kim T, Zhang H, Wu T, Chinniah K, Maghsoudlou S, Zhang R, Zhu J, Khaki S, Buin A, Chaji F, Salehi A, Nguyen BN, Samaras D, Plataniotis KN. Computational pathology: A survey review and the way forward. J Pathol Inform 2024; 15:100357. [PMID: 38420608 PMCID: PMC10900832 DOI: 10.1016/j.jpi.2023.100357] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/21/2023] [Accepted: 12/23/2023] [Indexed: 03/02/2024] Open
Abstract
Computational Pathology (CPath) is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main objective for CPath is to develop infrastructure and workflows of digital diagnostics as an assistive CAD system for clinical pathology, facilitating transformational changes in the diagnosis and treatment of cancer that are mainly address by CPath tools. With evergrowing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article we provide a comprehensive review of more than 800 papers to address the challenges faced in problem design all-the-way to the application and implementation viewpoints. We have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. We hope this helps the community to locate relevant works and facilitate understanding of the field's future directions. In a nutshell, we oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. We overview this cycle from different perspectives of data-centric, model-centric, and application-centric problems. We finally sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath. For updated information on this survey review paper and accessing to the original model cards repository, please refer to GitHub. Updated version of this draft can also be found from arXiv.
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Affiliation(s)
- Mahdi S Hosseini
- Department of Computer Science and Software Engineering (CSSE), Concordia Univeristy, Montreal, QC H3H 2R9, Canada
| | | | - Vincent Quoc-Huy Trinh
- Institute for Research in Immunology and Cancer of the University of Montreal, Montreal, QC H3T 1J4, Canada
| | - Lyndon Chan
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Danial Hasan
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Xingwen Li
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Stephen Yang
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Taehyo Kim
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Haochen Zhang
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Theodore Wu
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Kajanan Chinniah
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Sina Maghsoudlou
- Department of Computer Science and Software Engineering (CSSE), Concordia Univeristy, Montreal, QC H3H 2R9, Canada
| | - Ryan Zhang
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Jiadai Zhu
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Samir Khaki
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
| | - Andrei Buin
- Huron Digitial Pathology, St. Jacobs, ON N0B 2N0, Canada
| | - Fatemeh Chaji
- Department of Computer Science and Software Engineering (CSSE), Concordia Univeristy, Montreal, QC H3H 2R9, Canada
| | - Ala Salehi
- Department of Electrical and Computer Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada
| | - Bich Ngoc Nguyen
- University of Montreal Hospital Center, Montreal, QC H2X 0C2, Canada
| | - Dimitris Samaras
- Department of Computer Science, Stony Brook University, Stony Brook, NY 11794, United States
| | - Konstantinos N Plataniotis
- The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE), University of Toronto, Toronto, ON M5S 3G4, Canada
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2
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Liu BL, Haghighi M, Westra WH. Digital Pathology is a Fast and Effective Platform for Providing Head and Neck Pathology Consultations. Am J Surg Pathol 2024; 48:985-990. [PMID: 38712588 DOI: 10.1097/pas.0000000000002239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Surgical pathology of the head and neck is one of the more challenging areas in all of diagnostic pathology. Its unparalleled diversity and complexity renders it highly vulnerable to diagnostic error compelling unconstrained access to specialized diagnostic expertise. Digital pathology (DP) is a state-of-the-art tool that could facilitate access to specialized expertise, but it is relatively untested in the context of pathology consultations. In a collaboration between Labcorp Dianon and a large academic hospital with subspecialized surgical pathology, DP was implemented to provide the pathology community access to head and neck pathology expertise. From this collaborative experience, glass slides from consecutive consult cases that had been previously diagnosed using DP were reviewed by an expert consultant in a blinded manner following an extended wash-out period. The intraobserver discrepancy rate was recorded. Major discrepancies were defined as those resulting in significant impact on clinical management and/or prognosis, whereas minor discrepancies were those with no impact on care or prognosis. Slides from 57 cases were available for review. The average wash-out period was 19 months. Five discrepancies were recorded (intraobserver concordance rate of 91%). All discrepancies were minor (major discrepancy rate, 0%; minor discrepancy rate, 9%). On appraisal of the discrepant cases, discordant diagnoses were attributed to subjective differences in interpretation rather than objective differences related to the inferiority of DP. DP decreased the median turnaround time by 97% (from 70 h 26 min to 2 h 25 min). DP provides efficient and fast access to expert consultants. The speed of case delivery does not compromise diagnostic precision. Discrepancies are uncommon, minor, and reflect subjective interpretative differences inherent to difficult and ambiguous head and neck cases, and not the inferiority of DP as a diagnostic platform. High concordance can be achieved even for those difficult and complex cases that are concentrated in the consultation practice. This observation carries profound implications regarding universal health care access to specialized diagnostic expertise.
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Affiliation(s)
- Bella L Liu
- Department of Pathology, Molecular and Cell Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
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3
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Bontoux C, Hofman V, Chamorey E, Schiappa R, Lassalle S, Long-Mira E, Zahaf K, Lalvée S, Fayada J, Bonnetaud C, Goffinet S, Ilié M, Hofman P. Reproducibility of c-Met Immunohistochemical Scoring (Clone SP44) for Non-Small Cell Lung Cancer Using Conventional Light Microscopy and Whole Slide Imaging. Am J Surg Pathol 2024:00000478-990000000-00386. [PMID: 38980727 DOI: 10.1097/pas.0000000000002274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
Emerging therapies for non-small cell lung cancer targeting c-Met overexpression have recently demonstrated promising results. However, the evaluation of c-Met expression can be challenging. We aimed to study the inter and intraobserver reproducibility of c-Met expression evaluation. One hundred ten cases with non-small cell lung cancer (40 biopsies and 70 surgical specimens) were retrospectively selected in a single laboratory (LPCE) and evaluated for c-Met expression. Six pathologists (4 seniors and 2 juniors) evaluated the H-score and made a 3-tier classification of c-Met expression for all cases, using conventional light microscopy (CLM) and whole slide imaging (WSI). The interobserver reproducibility with CLM gave global Cohen Kappa coefficients (ƙ) ranging from 0.581 (95% CI: 0.364-0.771) to 0.763 (95% CI: 0.58-0.92) using the c-Met 3-tier classification and H-score, respectively. ƙ was higher for senior pathologists and biopsy samples. The interobserver reproducibility with WSI gave a global ƙ ranging from 0.543 (95% CI: 0.33-0.724) to 0.905 (95% CI: 0.618-1) using the c-Met H-score and 2-tier classification (≥25% 3+), respectively. ƙ for intraobserver reproducibility between CLM and WSI ranged from 0.713 to 0.898 for the c-Met H-score and from 0.600 to 0.779 for the c-Met 3-tier classification. We demonstrated a moderate to excellent interobserver agreement for c-Met expression with a substantial to excellent intraobserver agreement between CLM and WSI, thereby supporting the development of digital pathology. However, some factors (scoring method, type of tissue samples, and expertise level) affect reproducibility. Our findings highlight the importance of establishing a consensus definition and providing further training, particularly for inexperienced pathologists, for c-Met immunohistochemistry assessment in clinical practice.
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Affiliation(s)
- Christophe Bontoux
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- Team 4, Institute of Research on Cancer and Aging of Nice Inserm U1081, CNRS UMR7284, Côte d'Azur University
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Véronique Hofman
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- Team 4, Institute of Research on Cancer and Aging of Nice Inserm U1081, CNRS UMR7284, Côte d'Azur University
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Emmanuel Chamorey
- Department of Statistics, Antoine Lacassagne Cancer Center, Nice, France
| | - Renaud Schiappa
- Department of Statistics, Antoine Lacassagne Cancer Center, Nice, France
| | - Sandra Lassalle
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- Team 4, Institute of Research on Cancer and Aging of Nice Inserm U1081, CNRS UMR7284, Côte d'Azur University
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Elodie Long-Mira
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- Team 4, Institute of Research on Cancer and Aging of Nice Inserm U1081, CNRS UMR7284, Côte d'Azur University
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Katia Zahaf
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Salomé Lalvée
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Julien Fayada
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Christelle Bonnetaud
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | | | - Marius Ilié
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- Team 4, Institute of Research on Cancer and Aging of Nice Inserm U1081, CNRS UMR7284, Côte d'Azur University
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
| | - Paul Hofman
- Laboratory of Clinical and Experimental Pathology
- Hospital-Integrated Biobank
- Team 4, Institute of Research on Cancer and Aging of Nice Inserm U1081, CNRS UMR7284, Côte d'Azur University
- FHU OncoAge, Côte d'Azur University
- University Hospital Institute RespirERA, Côte d'Azur University, Pasteur Hospital, CHU of Nice
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4
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Neary-Zajiczek L, Beresna L, Razavi B, Pawar V, Shaw M, Stoyanov D. Minimum resolution requirements of digital pathology images for accurate classification. Med Image Anal 2023; 89:102891. [PMID: 37536022 DOI: 10.1016/j.media.2023.102891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/22/2023] [Accepted: 07/06/2023] [Indexed: 08/05/2023]
Abstract
Digitization of pathology has been proposed as an essential mitigation strategy for the severe staffing crisis facing most pathology departments. Despite its benefits, several barriers have prevented widespread adoption of digital workflows, including cost and pathologist reluctance due to subjective image quality concerns. In this work, we quantitatively determine the minimum image quality requirements for binary classification of histopathology images of breast tissue in terms of spatial and sampling resolution. We train an ensemble of deep learning classifier models on publicly available datasets to obtain a baseline accuracy and computationally degrade these images according to our derived theoretical model to identify the minimum resolution necessary for acceptable diagnostic accuracy. Our results show that images can be degraded significantly below the resolution of most commercial whole-slide imaging systems while maintaining reasonable accuracy, demonstrating that macroscopic features are sufficient for binary classification of stained breast tissue. A rapid low-cost imaging system capable of identifying healthy tissue not requiring human assessment could serve as a triage system for reducing caseloads and alleviating the significant strain on the current workforce.
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Affiliation(s)
- Lydia Neary-Zajiczek
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, Charles Bell House, 43-45 Foley Street, Fitzrovia, London, W1W 7TS, United Kingdom; Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
| | - Linas Beresna
- Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, United Kingdom
| | - Benjamin Razavi
- University College London Medical School, 74 Huntley Street, London, WC1E 6BT, United Kingdom
| | - Vijay Pawar
- Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, United Kingdom
| | - Michael Shaw
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, Charles Bell House, 43-45 Foley Street, Fitzrovia, London, W1W 7TS, United Kingdom; Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, United Kingdom; National Physical Laboratory, Hampton Road, Teddington, TW11 0LW, United Kingdom
| | - Danail Stoyanov
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, Charles Bell House, 43-45 Foley Street, Fitzrovia, London, W1W 7TS, United Kingdom; Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, United Kingdom
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5
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Fusco N, Ivanova M, Frascarelli C, Criscitiello C, Cerbelli B, Pignataro MG, Pernazza A, Sajjadi E, Venetis K, Cursano G, Pagni F, Di Bella C, Accardo M, Amato M, Amico P, Bartoli C, Bogina G, Bortesi L, Boldorini R, Bruno S, Cabibi D, Caruana P, Dainese E, De Camilli E, Dell'Anna V, Duda L, Emmanuele C, Fanelli GN, Fernandes B, Ferrara G, Gnetti L, Gurrera A, Leone G, Lucci R, Mancini C, Marangi G, Mastropasqua MG, Nibid L, Orrù S, Pastena M, Peresi M, Perracchio L, Santoro A, Vezzosi V, Zambelli C, Zuccalà V, Rizzo A, Costarelli L, Pietribiasi F, Santinelli A, Scatena C, Curigliano G, Guerini-Rocco E, Martini M, Graziano P, Castellano I, d'Amati G. Advancing the PD-L1 CPS test in metastatic TNBC: Insights from pathologists and findings from a nationwide survey. Crit Rev Oncol Hematol 2023; 190:104103. [PMID: 37595344 DOI: 10.1016/j.critrevonc.2023.104103] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 08/11/2023] [Accepted: 08/12/2023] [Indexed: 08/20/2023] Open
Abstract
Pembrolizumab has received approval as a first-line treatment for unresectable/metastatic triple-negative breast cancer (mTNBC) with a PD-L1 combined positive score (CPS) of ≥ 10. However, assessing CPS in mTNBC poses challenges. Firstly, it represents a novel analysis for breast pathologists. Secondly, the heterogeneity of PD-L1 expression in mTNBC further complicates the assessment. Lastly, the lack of standardized assays and staining platforms adds to the complexity. In KEYNOTE trials, PD-L1 expression was evaluated using the IHC 22C3 pharmDx kit as a companion diagnostic test. However, both the 22C3 pharmDx and VENTANA PD-L1 (SP263) assays are validated for CPS assessment. Consequently, assay-platform choice, staining conditions, and scoring methods can significantly impact the testing outcomes. This consensus paper aims to discuss the intricacies of PD-L1 CPS testing in mTNBC and provide practical recommendations for pathologists. Additionally, we present findings from a nationwide Italian survey elucidating the state-of-the-art in PD-L1 CPS testing in mTNBC.
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Affiliation(s)
- Nicola Fusco
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy.
| | - Mariia Ivanova
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Chiara Frascarelli
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Carmen Criscitiello
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy; Division of New Drugs and Early Drug Development for Innovative Therapies, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Bruna Cerbelli
- Department of Medical-Surgical Sciences and Biotechnologies Sapienza University of Rome, Rome, Italy
| | - Maria Gemma Pignataro
- Department of Medical-Surgical Sciences and Biotechnologies Sapienza University of Rome, Rome, Italy
| | - Angelina Pernazza
- Department of Medical-Surgical Sciences and Biotechnologies Sapienza University of Rome, Rome, Italy
| | - Elham Sajjadi
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | | | - Giulia Cursano
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Fabio Pagni
- Department of Medicine and Surgery, University Milan Bicocca, Monza (MB), Italy; Department of Pathology, IRCCS San Gerardo Hospital, Monza (MB), Italy
| | - Camillo Di Bella
- Department of Pathology, IRCCS San Gerardo Hospital, Monza (MB), Italy
| | - Marina Accardo
- Pathology Unit, Department of Mental and Physical Health and Preventive Medicine, Università degli Studi della Campania "L. Vanvitelli", Naples, Italy
| | - Michelina Amato
- Department of Pathology, San Giovanni-Addolorata Hospital, Rome Italy
| | - Paolo Amico
- Department of Pathology, Ospedale Maria Paternò Arezzo, Ragusa, Italy
| | - Caterina Bartoli
- Morphological Diagnostic and Biomolecular Characterization Area, Complex Unit of Pathological Anatomy Empoli-Prato, Oncological Department Azienda USL Toscana Centro, Italy
| | - Giuseppe Bogina
- Pathology Unit, IRCCS Ospedale Sacro Cuore Don Calabria, Negrar di Valpolicella, Italy
| | - Laura Bortesi
- Pathology Unit, IRCCS Ospedale Sacro Cuore Don Calabria, Negrar di Valpolicella, Italy
| | - Renzo Boldorini
- Pathology Unit, University of Eastern Piedmont, Novara, Italy
| | - Sara Bruno
- Division of Pathology, ASL2 Savona, Liguria, Italy
| | - Daniela Cabibi
- Department of Sciences for the Promotion of Health and Mother and Child Care, Anatomic Pathology, University of Palermo, Palermo, Italy
| | - Pietro Caruana
- Pathology Unit, Department of Medicine and Surgery, University Hospital of Parma, Parma, Italy
| | - Emanuele Dainese
- Surgical Pathology Division, Department of Oncology, ASST Lecco, "A. Manzoni" Hospital, Lecco, Italy
| | - Elisa De Camilli
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | | | - Loren Duda
- Department of Clinical and Experimental Medicine, Pathology Unit, University of Foggia, Foggia, Italy
| | - Carmela Emmanuele
- Division of Pathology, Umberto I Hospital Presidium, Enna Provincial Health Department (ASP), Enna, Italy
| | - Giuseppe Nicolò Fanelli
- Division of Pathology, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | | | - Gerardo Ferrara
- Department of Anatomic Pathology and Cytopathology, G. Pascale National Cancer Institute Foundation (IRCCS) Naples, Italy
| | - Letizia Gnetti
- Division of Pathology, Umberto I Hospital Presidium, Enna Provincial Health Department (ASP), Enna, Italy
| | | | - Giorgia Leone
- Division of Pathology, Clinical Institute Humanitas Catania Cubba, Misterbianco (Catania), Italy
| | - Raffaella Lucci
- Pathology Unit, Monaldi Hospital, A.O. dei Colli of Naples, Naples, Italy
| | - Cristina Mancini
- Division of Pathology, Umberto I Hospital Presidium, Enna Provincial Health Department (ASP), Enna, Italy
| | - Grazia Marangi
- Anatomic Pathology Unit, SS. Annunziata Hospital, Taranto, Italy
| | - Mauro G Mastropasqua
- Department of Precision and Regenerative Medicine and Jonian Area, School of Medicine, University of Bari "Aldo Moro", Bari, Italy
| | - Lorenzo Nibid
- Research Unit of Anatomical Pathology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy; Anatomical Pathology Operative Research Unit, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, Rome, Italy
| | - Sandra Orrù
- Businco Oncologic Hospital, ARNAS Brotzu, Cagliari, Italy
| | - Maria Pastena
- IRCCS Istituto Tumori "Giovanni Paolo II", Bari, Italy
| | - Monica Peresi
- Pathology and Cytopathology Diagnostic Unit, Ospedale Villa Scassi di Genova, Genoa, Italy
| | - Letizia Perracchio
- Department of Pathology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Angela Santoro
- General Pathology Unit, Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Vania Vezzosi
- Histopathology and Molecular Diagnostics Unit, Careggi Hospital, Firenze, Italy
| | | | - Valeria Zuccalà
- Pathology Unit, Pugliese-Ciaccio Hospital Catanzaro, Catanzaro, Italy
| | - Antonio Rizzo
- Division of Pathology, Clinical Institute Humanitas Catania Cubba, Misterbianco (Catania), Italy
| | | | | | - Alfredo Santinelli
- Anatomic Pathology, Azienda Sanitaria Territoriale di Pesaro-Urbino, Pesaro, Italy
| | - Cristian Scatena
- Division of Pathology, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Giuseppe Curigliano
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Division of New Drugs and Early Drug Development for Innovative Therapies, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Elena Guerini-Rocco
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Maurizio Martini
- Department of Human and Developmental Pathology, University of Messina, Messina, Italy
| | - Paolo Graziano
- Pathology Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy
| | | | - Giulia d'Amati
- Department of Medical-Surgical Sciences and Biotechnologies Sapienza University of Rome, Rome, Italy
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6
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Sauter D, Lodde G, Nensa F, Schadendorf D, Livingstone E, Kukuk M. Deep learning in computational dermatopathology of melanoma: A technical systematic literature review. Comput Biol Med 2023; 163:107083. [PMID: 37315382 DOI: 10.1016/j.compbiomed.2023.107083] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 05/10/2023] [Accepted: 05/27/2023] [Indexed: 06/16/2023]
Abstract
Deep learning (DL) has become one of the major approaches in computational dermatopathology, evidenced by a significant increase in this topic in the current literature. We aim to provide a structured and comprehensive overview of peer-reviewed publications on DL applied to dermatopathology focused on melanoma. In comparison to well-published DL methods on non-medical images (e.g., classification on ImageNet), this field of application comprises a specific set of challenges, such as staining artifacts, large gigapixel images, and various magnification levels. Thus, we are particularly interested in the pathology-specific technical state-of-the-art. We also aim to summarize the best performances achieved thus far with respect to accuracy, along with an overview of self-reported limitations. Accordingly, we conducted a systematic literature review of peer-reviewed journal and conference articles published between 2012 and 2022 in the databases ACM Digital Library, Embase, IEEE Xplore, PubMed, and Scopus, expanded by forward and backward searches to identify 495 potentially eligible studies. After screening for relevance and quality, a total of 54 studies were included. We qualitatively summarized and analyzed these studies from technical, problem-oriented, and task-oriented perspectives. Our findings suggest that the technical aspects of DL for histopathology in melanoma can be further improved. The DL methodology was adopted later in this field, and still lacks the wider adoption of DL methods already shown to be effective for other applications. We also discuss upcoming trends toward ImageNet-based feature extraction and larger models. While DL has achieved human-competitive accuracy in routine pathological tasks, its performance on advanced tasks is still inferior to wet-lab testing (for example). Finally, we discuss the challenges impeding the translation of DL methods to clinical practice and provide insight into future research directions.
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Affiliation(s)
- Daniel Sauter
- Department of Computer Science, Fachhochschule Dortmund, 44227 Dortmund, Germany.
| | - Georg Lodde
- Department of Dermatology, University Hospital Essen, 45147 Essen, Germany
| | - Felix Nensa
- Institute for AI in Medicine (IKIM), University Hospital Essen, 45131 Essen, Germany; Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147 Essen, Germany
| | - Dirk Schadendorf
- Department of Dermatology, University Hospital Essen, 45147 Essen, Germany
| | | | - Markus Kukuk
- Department of Computer Science, Fachhochschule Dortmund, 44227 Dortmund, Germany
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7
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Vassilakos P, Clarke H, Murtas M, Stegmüller T, Wisniak A, Akhoundova F, Sando Z, Orock GE, Sormani J, Thiran JP, Petignat P. Telecytologic diagnosis of cervical smears for triage of self-sampled human papillomavirus-positive women in a resource-limited setting: concept development before implementation. J Am Soc Cytopathol 2023; 12:170-180. [PMID: 36922319 DOI: 10.1016/j.jasc.2023.02.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/12/2023] [Accepted: 02/08/2023] [Indexed: 02/17/2023]
Abstract
INTRODUCTION Cytology is an option for triaging human papillomavirus (HPV)-positive women. The interpretation of cytologic slides requires expertise and financial resources that are not always available in resource-limited settings. A solution could be offered by manual preparation and digitization of slides on site for real-time remote cytologic diagnosis by specialists. In the present study, we evaluated the operational feasibility and cost of manual preparation and digitization of thin-layer slides and the diagnostic accuracy of screening with virtual microscopy. MATERIALS AND METHODS Operational feasibility was evaluated on 30 cervical samples obtained during colposcopy. The simplicity of the process and cellularity and quality of digitized thin-layer slides were evaluated. The diagnostic accuracy of digital versus glass slides to detect cervical intraepithelial neoplasia grade 2 or worse was assessed using a cohort of 264 HPV-positive Cameroonian women aged 30 to 49 years. The histologic results served as the reference standard. RESULTS Manual preparation was found to be feasible and economically viable. The quality characteristics of the digital slides were satisfactory, and the mean cellularity was 6078 squamous cells per slide. When using the atypical squamous cells of undetermined significance or worse threshold for positivity, the diagnostic performance of screening digital slides was not significantly different statistically compared with the same set of slides screened using a light microscope (P = 0.26). CONCLUSIONS We have developed an innovative triage concept for HPV-positive women. A quality-ensured telecytologic diagnosis could be an effective solution in areas with a shortage of specialists, applying a same day "test-triage-treat" approach. Our results warrant further on-site clinical validation in a large prospective screening trial.
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Affiliation(s)
- Pierre Vassilakos
- Gynecology Division, Geneva University Hospital, Geneva, Switzerland; Geneva Foundation for Medical Education and Research, Geneva, Switzerland
| | - Holly Clarke
- Gynecology Division, Geneva University Hospital, Geneva, Switzerland.
| | - Micol Murtas
- Gynecology Division, Geneva University Hospital, Geneva, Switzerland
| | - Thomas Stegmüller
- Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland
| | - Ania Wisniak
- Gynecology Division, Geneva University Hospital, Geneva, Switzerland
| | - Farida Akhoundova
- Gynecology Division, Geneva University Hospital, Geneva, Switzerland
| | - Zacharie Sando
- Gyneco-Obstetrics and Paediatric Hospital, Yaoundé, Cameroon
| | | | - Jessica Sormani
- Gynecology Division, Geneva University Hospital, Geneva, Switzerland
| | | | - Patrick Petignat
- Gynecology Division, Geneva University Hospital, Geneva, Switzerland
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Maity S, Nauhria S, Nayak N, Nauhria S, Coffin T, Wray J, Haerianardakani S, Sah R, Spruce A, Jeong Y, Maj MC, Sharma A, Okpara N, Ike CJ, Nath R, Nelson J, Parwani AV. Virtual Versus Light Microscopy Usage among Students: A Systematic Review and Meta-Analytic Evidence in Medical Education. Diagnostics (Basel) 2023; 13:diagnostics13030558. [PMID: 36766660 PMCID: PMC9914930 DOI: 10.3390/diagnostics13030558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 01/26/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND The usage of whole-slide images has recently been gaining a foothold in medical education, training, and diagnosis. OBJECTIVES The first objective of the current study was to compare academic performance on virtual microscopy (VM) and light microscopy (LM) for learning pathology, anatomy, and histology in medical and dental students during the COVID-19 period. The second objective was to gather insight into various applications and usage of such technology for medical education. MATERIALS AND METHODS Using the keywords "virtual microscopy" or "light microscopy" or "digital microscopy" and "medical" and "dental" students, databases (PubMed, Embase, Scopus, Cochrane, CINAHL, and Google Scholar) were searched. Hand searching and snowballing were also employed for article searching. After extracting the relevant data based on inclusion and execution criteria, the qualitative data were used for the systematic review and quantitative data were used for meta-analysis. The Newcastle Ottawa Scale (NOS) scale was used to assess the quality of the included studies. Additionally, we registered our systematic review protocol in the prospective register of systematic reviews (PROSPERO) with registration number CRD42020205583. RESULTS A total of 39 studies met the criteria to be included in the systematic review. Overall, results indicated a preference for this technology and better academic scores. Qualitative analyses reported improved academic scores, ease of use, and enhanced collaboration amongst students as the top advantages, whereas technical issues were a disadvantage. The performance comparison of virtual versus light microscopy meta-analysis included 19 studies. Most (10/39) studies were from medical universities in the USA. VM was mainly used for teaching pathology courses (25/39) at medical schools (30/39). Dental schools (10/39) have also reported using VM for teaching microscopy. The COVID-19 pandemic was responsible for the transition to VM use in 17/39 studies. The pooled effect size of 19 studies significantly demonstrated higher exam performance (SMD: 1.36 [95% CI: 0.75, 1.96], p < 0.001) among the students who used VM for their learning. Students in the VM group demonstrated significantly higher exam performance than LM in pathology (SMD: 0.85 [95% CI: 0.26, 1.44], p < 0.01) and histopathology (SMD: 1.25 [95% CI: 0.71, 1.78], p < 0.001). For histology (SMD: 1.67 [95% CI: -0.05, 3.40], p = 0.06), the result was insignificant. The overall analysis of 15 studies assessing exam performance showed significantly higher performance for both medical (SMD: 1.42 [95% CI: 0.59, 2.25], p < 0.001) and dental students (SMD: 0.58 [95% CI: 0.58, 0.79], p < 0.001). CONCLUSIONS The results of qualitative and quantitative analyses show that VM technology and digitization of glass slides enhance the teaching and learning of microscopic aspects of disease. Additionally, the COVID-19 global health crisis has produced many challenges to overcome from a macroscopic to microscopic scale, for which modern virtual technology is the solution. Therefore, medical educators worldwide should incorporate newer teaching technologies in the curriculum for the success of the coming generation of health-care professionals.
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Affiliation(s)
- Sabyasachi Maity
- Department of Physiology, Neuroscience, and Behavioral Sciences, St. George’s University School of Medicine, St. George’s, Grenada
| | - Samal Nauhria
- Department of Pathology, St. Matthews University School of Medicine, Georgetown P.O. Box 30992, Cayman Islands
- Correspondence:
| | - Narendra Nayak
- Department of Microbiology, St. Matthews University School of Medicine, Georgetown P.O. Box 30992, Cayman Islands
| | - Shreya Nauhria
- Department of Psychology, University of Leicester, Leicester LE1 7RH, UK
| | - Tamara Coffin
- Medical Student Research Institute, St. George’s University School of Medicine, St. George’s, Grenada
| | - Jadzia Wray
- Medical Student Research Institute, St. George’s University School of Medicine, St. George’s, Grenada
| | - Sepehr Haerianardakani
- Medical Student Research Institute, St. George’s University School of Medicine, St. George’s, Grenada
| | - Ramsagar Sah
- Department of Public Health, Torrens University, Ultimo, Sydney, NSW 2007, Australia
| | - Andrew Spruce
- Department of Pathology, St. Matthews University School of Medicine, Georgetown P.O. Box 30992, Cayman Islands
| | - Yujin Jeong
- Department of Clinical Medicine, American University of Antigua, St. John’s, Antigua and Barbuda
| | - Mary C. Maj
- Department of Biochemistry, St. George’s University School of Medicine, St. George’s, Grenada
| | - Abhimanyu Sharma
- Department of Pathology, Government Medical College, Jammu 180001, India
| | - Nicole Okpara
- Department of Pathology, St. Matthews University School of Medicine, Georgetown P.O. Box 30992, Cayman Islands
| | - Chidubem J. Ike
- Department of Clinical Medicine, American University of Antigua, St. John’s, Antigua and Barbuda
| | - Reetuparna Nath
- Department of Education Service, St. George’s University, St. George’s, Grenada
| | - Jack Nelson
- Medical Illustrator, The Centre for Biomedical Visualization, St. George’s University, St. George’s, Grenada
| | - Anil V. Parwani
- Department of Pathology, Wexner Medical Center, The Ohio State University, Cooperative Human Tissue Network (CHTN) Midwestern Division, Columbus, OH 43210, USA
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Antonini P, Santonicco N, Pantanowitz L, Girolami I, Rizzo PC, Brunelli M, Bellevicine C, Vigliar E, Negri G, Troncone G, Fadda G, Parwani A, Marletta S, Eccher A. Relevance of the College of American Pathologists guideline for validating whole slide imaging for diagnostic purposes to cytopathology. Cytopathology 2023; 34:5-14. [PMID: 36082410 PMCID: PMC10087327 DOI: 10.1111/cyt.13178] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 08/17/2022] [Accepted: 08/31/2022] [Indexed: 12/14/2022]
Abstract
Whole slide imaging (WSI) allows pathologists to view virtual versions of slides on computer monitors. With increasing adoption of digital pathology, laboratories have begun to validate their WSI systems for diagnostic purposes according to reference guidelines. Among these the College of American Pathologists (CAP) guideline includes three strong recommendations (SRs) and nine good practice statements (GPSs). To date, the application of WSI to cytopathology has been beyond the scope of the CAP guideline due to limited evidence. Herein we systematically reviewed the published literature on WSI validation studies in cytology. A systematic search was carried out in PubMed-MEDLINE and Embase databases up to November 2021 to identify all publications regarding validation of WSI in cytology. Each article was reviewed to determine if SRs and/or GPSs recommended by the CAP guideline were adequately satisfied. Of 3963 retrieved articles, 25 were included. Only 4/25 studies (16%) satisfied all three SRs, with only one publication (1/25, 4%) fulfilling all three SRs and nine GPSs. Lack of a suitable validation dataset was the main missing SR (16/25, 64%) and less than a third of the studies reported intra-observer variability data (7/25, 28%). Whilst the CAP guideline for WSI validation in clinical practice helped the widespread adoption of digital pathology, more evidence is required to routinely employ WSI for diagnostic purposes in cytopathology practice. More dedicated validation studies satisfying all SRs and/or GPSs recommended by the CAP are needed to help expedite the use of WSI for primary diagnosis in cytopathology.
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Affiliation(s)
- Pietro Antonini
- Section of Pathology, Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy
| | - Nicola Santonicco
- Section of Pathology, Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy
| | - Liron Pantanowitz
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Ilaria Girolami
- Department of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy
| | - Paola Chiara Rizzo
- Section of Pathology, Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy
| | - Matteo Brunelli
- Section of Pathology, Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy
| | | | - Elena Vigliar
- Public Health, University of Naples Federico II, Naples, Italy
| | - Giovanni Negri
- Department of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy
| | | | - Guido Fadda
- Section of Pathological Anatomy, Department of Human Pathology in Adulthood and Childhood "G. Barresi", University Hospital G. Martino, University of Messina, Messina, Italy
| | - Anil Parwani
- Department of Pathology, The Ohio State University, Columbus, Ohio, USA
| | - Stefano Marletta
- Section of Pathology, Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
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10
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Bassani S, Santonicco N, Eccher A, Scarpa A, Vianini M, Brunelli M, Bisi N, Nocini R, Sacchetto L, Munari E, Pantanowitz L, Girolami I, Molteni G. Artificial intelligence in head and neck cancer diagnosis. J Pathol Inform 2022; 13:100153. [PMID: 36605112 PMCID: PMC9808017 DOI: 10.1016/j.jpi.2022.100153] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 10/17/2022] [Accepted: 11/02/2022] [Indexed: 11/09/2022] Open
Abstract
Introduction Artificial intelligence (AI) is currently being used to augment histopathological diagnostics in pathology. This systematic review aims to evaluate the evolution of these AI-based diagnostic techniques for diagnosing head and neck neoplasms. Materials and methods Articles regarding the use of AI for head and neck pathology published from 1982 until March 2022 were evaluated based on a search strategy determined by a multidisciplinary team of pathologists and otolaryngologists. Data from eligible articles were summarized according to author, year of publication, country, study population, tumor details, study results, and limitations. Results Thirteen articles were included according to inclusion criteria. The selected studies were published between 2012 and March 1, 2022. Most of these studies concern the diagnosis of oral cancer; in particular, 6 are related to the oral cavity, 2 to the larynx, 1 to the salivary glands, and 4 to head and neck squamous cell carcinoma not otherwise specified (NOS). As for the type of diagnostics considered, 12 concerned histopathology and 1 cytology. Discussion Starting from the pathological examination, artificial intelligence tools are an excellent solution for implementing diagnosis capability. Nevertheless, today the unavailability of large training datasets is a main issue that needs to be overcome to realize the true potential.
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Affiliation(s)
- Sara Bassani
- Otolaryngology-Head and Neck Surgery Department, University of Verona, Verona, Italy
| | - Nicola Santonicco
- Otolaryngology-Head and Neck Surgery Department, University of Verona, Verona, Italy,Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy,Corresponding author at: Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy.
| | - Aldo Scarpa
- Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | - Matteo Vianini
- Department of Otolaryngology, Villafranca Hospital, Verona, Italy
| | - Matteo Brunelli
- Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | - Nicola Bisi
- Otolaryngology-Head and Neck Surgery Department, University of Verona, Verona, Italy
| | - Riccardo Nocini
- Otolaryngology-Head and Neck Surgery Department, University of Verona, Verona, Italy
| | - Luca Sacchetto
- Otolaryngology-Head and Neck Surgery Department, University of Verona, Verona, Italy
| | - Enrico Munari
- Department of Molecular and Translational Medicine, University of Brescia, 25121 Brescia, Italy
| | | | - Ilaria Girolami
- Department of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy; Lehrkrankenhaus der Paracelsus Medizinischen Privatuniversität
| | - Gabriele Molteni
- Otolaryngology-Head and Neck Surgery Department, University of Verona, Verona, Italy
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11
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Chung A, Nasralla D, Quaglia A. Understanding the Immunoenvironment of Primary Liver Cancer: A Histopathology Perspective. J Hepatocell Carcinoma 2022; 9:1149-1169. [PMID: 36349146 PMCID: PMC9637345 DOI: 10.2147/jhc.s382310] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/01/2022] [Indexed: 11/26/2022] Open
Abstract
One of the most common cancers worldwide, primary liver cancer remains a major cause of cancer-related mortality. Hepatocellular carcinoma and cholangiocarcinoma represent the majority of primary liver cancer cases. Despite advances in the development of novel anti-cancer therapies that exploit targets within the immune system, survival rates from liver cancer remain poor. Furthermore, responses to immunotherapies, such as immune checkpoint inhibitors, have revealed limited and variable responses amongst patients with hepatocellular carcinoma, although combination immunotherapies have shown recent breakthroughs in clinical trials. This has shifted the focus towards improving our understanding of the underlying immune and molecular characteristics of liver tumours that may influence their response to immune-modulating treatments. In this review, we outline the complex interactions that occur in the tumour microenvironment of hepatocellular carcinoma and cholangiocarcinoma, respectively, from a histopathological perspective. We explore the potential role of a classification system based on immune-specific characteristics within each cancer type, the importance of understanding inter- and intra-tumoural heterogeneity and consider the future role of histopathology and novel technologies within this field.
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Affiliation(s)
- Annabelle Chung
- Department of Cellular Pathology, Royal Free Hospital, London, UK,Correspondence: Annabelle Chung, Department of Cellular Pathology, Royal Free Hospital, Pond Street, London, NW3 2QG, UK, Tel +44 20 7794 0500 ext. 35641, Email
| | - David Nasralla
- Department of Hepato-Pancreato-Biliary Surgery, Royal Free Hospital, London, UK
| | - Alberto Quaglia
- Department of Cellular Pathology, Royal Free Hospital, London, UK
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12
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Liscia DS, D’Andrea M, Biletta E, Bellis D, Demo K, Ferrero F, Petti A, Butinar R, D’Andrea E, Davini G. Use of digital pathology and artificial intelligence for the diagnosis of Helicobacter pylori in gastric biopsies. Pathologica 2022; 114:295-303. [DOI: 10.32074/1591-951x-751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 01/22/2022] [Indexed: 12/20/2022] Open
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13
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HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin–Eosin Whole-Slide Imaging. J Imaging 2022; 8:jimaging8080213. [PMID: 36005456 PMCID: PMC9410129 DOI: 10.3390/jimaging8080213] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/26/2022] [Accepted: 07/27/2022] [Indexed: 02/06/2023] Open
Abstract
Breast cancer is the most common malignancy in women worldwide, and is responsible for more than half a million deaths each year. The appropriate therapy depends on the evaluation of the expression of various biomarkers, such as the human epidermal growth factor receptor 2 (HER2) transmembrane protein, through specialized techniques, such as immunohistochemistry or in situ hybridization. In this work, we present the HER2 on hematoxylin and eosin (HEROHE) challenge, a parallel event of the 16th European Congress on Digital Pathology, which aimed to predict the HER2 status in breast cancer based only on hematoxylin–eosin-stained tissue samples, thus avoiding specialized techniques. The challenge consisted of a large, annotated, whole-slide images dataset (509), specifically collected for the challenge. Models for predicting HER2 status were presented by 21 teams worldwide. The best-performing models are presented by detailing the network architectures and key parameters. Methods are compared and approaches, core methodologies, and software choices contrasted. Different evaluation metrics are discussed, as well as the performance of the presented models for each of these metrics. Potential differences in ranking that would result from different choices of evaluation metrics highlight the need for careful consideration at the time of their selection, as the results show that some metrics may misrepresent the true potential of a model to solve the problem for which it was developed. The HEROHE dataset remains publicly available to promote advances in the field of computational pathology.
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14
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Dawson H. Digital pathology – Rising to the challenge. Front Med (Lausanne) 2022; 9:888896. [PMID: 35935788 PMCID: PMC9354827 DOI: 10.3389/fmed.2022.888896] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Digital pathology has gone through considerable technical advances during the past few years and certain aspects of digital diagnostics have been widely and swiftly adopted in many centers, catalyzed by the COVID-19 pandemic. However, analysis of requirements, careful planning, and structured implementation should to be considered in order to reap the full benefits of a digital workflow. The aim of this review is to provide a practical, concise and hands-on summary of issues relevant to implementing and developing digital diagnostics in the pathology laboratory. These include important initial considerations, possible approaches to overcome common challenges, potential diagnostic pitfalls, validation and regulatory issues and an introduction to the emerging field of image analysis in routine.
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15
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Substantial improvement of histopathological diagnosis by whole-slide image-based remote consultation. Virchows Arch 2022; 481:295-305. [PMID: 35672584 PMCID: PMC9172976 DOI: 10.1007/s00428-022-03327-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 03/11/2022] [Accepted: 04/05/2022] [Indexed: 11/04/2022]
Abstract
Consultation by subspecialty experts is the most common mode of rendering diagnosis in challenging cases in pathological practice. Our study aimed to highlight the diagnostic benefits of whole-slide image (WSI)-based remote consultation. We obtained diagnostically challenging cases from two institutions from the years 2010 and 2013, with histological diagnoses that contained keywords “probable,” “suggestive,” “suspicious,” “inconclusive,” and “uncertain.” A total of 270 cases were selected for remote consultation using WSIs scanned at 40 × . The consultation process consisted of three rounds: the first and second rounds each with 12 subspecialty experts and the third round with six multi-expertise senior pathologists. The first consultation yielded 44% concordance, and a change in diagnosis occurred in 56% of cases. The most frequent change was from inconclusive to definite diagnosis (30%), followed by minor discordance (14%), and major discordance (12%). Out of the 70 cases which reached the second round, 31 cases showed discrepancy between the two consultants. For these 31 cases, a consensus diagnosis was provided by six multi-expertise senior pathologists. Combining all WSI-based consultation rounds, the original inconclusive diagnosis was changed in 140 (52%) out of 266 cases. Among these cases, 80 cases (30%) upgraded the inconclusive diagnosis to a definite diagnosis, and 60 cases (22%) changed the diagnosis with major or minor discordance, accounting for 28 cases (10%) and 32 cases (12%), respectively. We observed significant improvement in the pathological diagnosis of difficult cases by remote consultation using WSIs, which can further assist in patient healthcare. A post-study survey highlighted various benefits of WSI-based consults.
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16
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Temprana-Salvador J, López-García P, Castellví Vives J, de Haro L, Ballesta E, Rojas Abusleme M, Arrufat M, Marques F, Casas JR, Gallego C, Pons L, Mate JL, Fernández PL, López-Bonet E, Bosch R, Martínez S, Ramón y Cajal S, Matias-Guiu X. DigiPatICS: Digital Pathology Transformation of the Catalan Health Institute Network of 8 Hospitals—Planification, Implementation, and Preliminary Results. Diagnostics (Basel) 2022; 12:diagnostics12040852. [PMID: 35453900 PMCID: PMC9025604 DOI: 10.3390/diagnostics12040852] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 03/17/2022] [Accepted: 03/28/2022] [Indexed: 11/21/2022] Open
Abstract
Complete digital pathology transformation for primary histopathological diagnosis is a challenging yet rewarding endeavor. Its advantages are clear with more efficient workflows, but there are many technical and functional difficulties to be faced. The Catalan Health Institute (ICS) has started its DigiPatICS project, aiming to deploy digital pathology in an integrative, holistic, and comprehensive way within a network of 8 hospitals, over 168 pathologists, and over 1 million slides each year. We describe the bidding process and the careful planning that was required, followed by swift implementation in stages. The purpose of the DigiPatICS project is to increase patient safety and quality of care, improving diagnosis and the efficiency of processes in the pathological anatomy departments of the ICS through process improvement, digital pathology, and artificial intelligence tools.
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Affiliation(s)
- Jordi Temprana-Salvador
- Department of Pathology, Vall d’Hebron University Hospital, CIBERONC, 08035 Barcelona, Spain; (J.C.V.); (S.R.y.C.)
- Correspondence: ; Tel.: +34-93-274-68-09
| | - Pablo López-García
- Functional Competence Center, Information Systems, Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain; (P.L.-G.); (L.d.H.); (E.B.)
| | - Josep Castellví Vives
- Department of Pathology, Vall d’Hebron University Hospital, CIBERONC, 08035 Barcelona, Spain; (J.C.V.); (S.R.y.C.)
| | - Lluís de Haro
- Functional Competence Center, Information Systems, Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain; (P.L.-G.); (L.d.H.); (E.B.)
| | - Eudald Ballesta
- Functional Competence Center, Information Systems, Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain; (P.L.-G.); (L.d.H.); (E.B.)
| | - Matias Rojas Abusleme
- Center for Telecommunications and Information Technology (Centre de Telecomunicacions i Tecnologies de la Informació, CTTI), Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain;
| | - Miquel Arrufat
- Economic and Financial Management, Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain;
| | - Ferran Marques
- Image Processing Group, Technical University of Catalonia (UPC), 08034 Barcelona, Spain; (F.M.); (J.R.C.)
| | - Josep R. Casas
- Image Processing Group, Technical University of Catalonia (UPC), 08034 Barcelona, Spain; (F.M.); (J.R.C.)
| | - Carlos Gallego
- Digital Medical Imaging System of Catalonia (SIMDCAT), TIC Salut, 08005 Barcelona, Spain;
| | - Laura Pons
- Department of Pathology, Germans Trias i Pujol University Hospital, 08916 Badalona, Spain; (L.P.); (J.L.M.); (P.L.F.)
| | - José Luis Mate
- Department of Pathology, Germans Trias i Pujol University Hospital, 08916 Badalona, Spain; (L.P.); (J.L.M.); (P.L.F.)
| | - Pedro Luis Fernández
- Department of Pathology, Germans Trias i Pujol University Hospital, 08916 Badalona, Spain; (L.P.); (J.L.M.); (P.L.F.)
| | - Eugeni López-Bonet
- Department of Pathology, Doctor Josep Trueta Hospital of Girona, 17007 Girona, Spain;
| | - Ramon Bosch
- Department of Pathology, Verge de la Cinta Hospital of Tortosa, 43500 Tarragona, Spain;
| | - Salomé Martínez
- Department of Pathology, Joan XXIII University Hospital of Tarragona, 43005 Tarragona, Spain;
| | - Santiago Ramón y Cajal
- Department of Pathology, Vall d’Hebron University Hospital, CIBERONC, 08035 Barcelona, Spain; (J.C.V.); (S.R.y.C.)
| | - Xavier Matias-Guiu
- Department of Pathology, Arnau de Vilanova University Hospital, 25198 Lleida, Spain;
- Department of Pathology, Bellvitge University Hospital, CIBERONC, 08907 Barcelona, Spain
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17
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Eloy C, Bychkov A, Pantanowitz L, Fraggetta F, Bui MM, Fukuoka J, Zerbe N, Hassell L, Parwani A. DPA-ESDIP-JSDP Task Force for Worldwide Adoption of Digital Pathology. J Pathol Inform 2022; 12:51. [PMID: 35070480 PMCID: PMC8721866 DOI: 10.4103/jpi.jpi_65_21] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 11/15/2021] [Indexed: 12/11/2022] Open
Affiliation(s)
- Catarina Eloy
- Department of Pathology, Institute of Molecular Pathology and Immunology of University of Porto (IPATIMUP), Porto, Portugal.,Department of Pathology, Medical Faculty of Porto University, Porto, Portugal
| | - Andrey Bychkov
- Department of Pathology, Kameda Medical Center, Kamogawa, Japan
| | - Liron Pantanowitz
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Marilyn M Bui
- Department of Pathology, Moffitt Cancer Center & Research Institute, Tampa, Florida, USA
| | - Junya Fukuoka
- Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Norman Zerbe
- Charité - University Medicine Berlin & Research IT Services, Berlin Institute of Health & Institute of Pathology, Berlin, Germany
| | - Lewis Hassell
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Anil Parwani
- Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
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18
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Kusta O, Rift CV, Risør T, Santoni-Rugiu E, Brodersen JB. Lost in digitization – A systematic review about the diagnostic test accuracy of digital pathology solutions. J Pathol Inform 2022; 13:100136. [PMID: 36268077 PMCID: PMC9577136 DOI: 10.1016/j.jpi.2022.100136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 08/30/2022] [Accepted: 08/31/2022] [Indexed: 10/25/2022] Open
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19
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Salama AM, Hanna MG, Giri D, Kezlarian B, Jean MH, Lin O, Vallejo C, Brogi E, Edelweiss M. Digital validation of breast biomarkers (ER, PR, AR, and HER2) in cytology specimens using three different scanners. Mod Pathol 2022; 35:52-59. [PMID: 34518629 PMCID: PMC8702445 DOI: 10.1038/s41379-021-00908-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 08/08/2021] [Accepted: 08/09/2021] [Indexed: 11/30/2022]
Abstract
Progression in digital pathology has yielded new opportunities for a remote work environment. We evaluated the utility of digital review of breast cancer immunohistochemical prognostic markers (IHC) using whole slide images (WSI) from formalin fixed paraffin embedded (FFPE) cytology cell block specimens (CB) using three different scanners.CB from 20 patients with breast cancer diagnosis and available IHC were included. Glass slides including 20 Hematoxylin and eosin (H&E), 20 Estrogen Receptor (ER), 20 Progesterone Receptor (PR), 16 Androgen Receptor (AR), and 20 Human Epidermal Growth Factor Receptor 2 (HER2) were scanned on 3 different scanners. Four breast pathologists reviewed the WSI and recorded their semi-quantitative scoring for each marker. Kappa concordance was defined as complete agreement between glass/digital pairs. Discordances between microscopic and digital reads were classified as a major when a clinically relevant change was seen. Minor discordances were defined as differences in scoring percentages/staining pattern that would not have resulted in a clinical implication. Scanner precision was tabulated according to the success rate of each scan on all three scanners.In total, we had 228 paired glass/digital IHC reads on all 3 scanners. There was strong concordance kappa ≥0.85 for all pathologists when comparing paired microscopic/digital reads. Strong concordance (kappa ≥0.86) was also seen when comparing reads between scanners.Twenty-three percent of the WSI required rescanning due to barcode detection failures, 14% due to tissue detection failures, and 2% due to focus issues. Scanner 1 had the best average precision of 92%. HER2 IHC had the lowest intra-scanner precision (64%) among all stains.This study is the first to address the utility of WSI in breast cancer IHC in CB and to validate its reporting using 3 different scanners. Digital images are reliable for breast IHC assessment in CB and offer similar reproducibility to microscope reads.
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Affiliation(s)
- Abeer M Salama
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Matthew G Hanna
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Dilip Giri
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Brie Kezlarian
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Marc-Henri Jean
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Oscar Lin
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Christina Vallejo
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Edi Brogi
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Marcia Edelweiss
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
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20
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Shi W, Georgiou P, Akram A, Proute MC, Serhiyenia T, Kerolos ME, Pradeep R, Kothur NR, Khan S. Diagnostic Pitfalls of Digital Microscopy Versus Light Microscopy in Gastrointestinal Pathology: A Systematic Review. Cureus 2021; 13:e17116. [PMID: 34548958 PMCID: PMC8437006 DOI: 10.7759/cureus.17116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 08/11/2021] [Indexed: 12/15/2022] Open
Abstract
Digital microscopy (DM) is one of the cutting-edge advances in pathology, which entails improved efficiency, diagnostic advantages, and potential application in virtual diagnosis, particularly in the current era of the coronavirus disease (COVID-19) pandemic. However, the diagnostic challenges are the remaining concerns for its wider adoption by pathologists, and these concerns should be addressed in a specific subspecialty. We aim to identify the common diagnostic pitfalls of whole slide imaging (WSI), one modality of DM, in gastrointestinal (GI) pathology. From validating studies of primary diagnosis performance, we included 16 records with features on GI cases involved, at least two weeks wash-out periods, and more than 60 case study designs. A tailored quality appraisal assessment was utilized to evaluate the risks of bias for these diagnostic accuracy studies. Furthermore, due to the highly heterogeneous studies and unstandardized definition of discordance, we extract the discordant cases in GI pathology and calculate the discrepant rate, resulting from 0.5% to 64.28%. Targeting discrepancy cases between digital microscopy and light microscopy, we demonstrate five main diagnostic pitfalls regarding WSI as follows: additional time to review slides in WSI, hard to identify dysplasia nucleus, missed organisms like Helicobacter pylori (H. pylori), specific cell recognitions, and technical issues. After detailed reviews and analysis, we generate two essential suggestions for further GI cases signing out by DM. One is to use systematized 20x scans for diagnostic workouts and requesting 40x or even 60x scans for challenging cases; another is that a high-volume slides training should be set before the real clinical application of WSI for primary diagnosis, particularly in GI pathology.
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Affiliation(s)
- Wangpan Shi
- Pathology, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Petros Georgiou
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA.,Department of Oncology, Oxford University, Oxford, GBR
| | - Aqsa Akram
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Matthew C Proute
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Tatsiana Serhiyenia
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Mina E Kerolos
- General Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Roshini Pradeep
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Nageshwar R Kothur
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Safeera Khan
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
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21
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Colling R, Colling H, Browning L, Verrill C. Validation of grading of non-invasive urothelial carcinoma by digital pathology for routine diagnosis. BMC Cancer 2021; 21:995. [PMID: 34488682 PMCID: PMC8420048 DOI: 10.1186/s12885-021-08698-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 08/13/2021] [Indexed: 11/30/2022] Open
Abstract
Background Pathological grading of non-invasive urothelial carcinoma has a direct impact upon management. This study evaluates the reproducibility of grading these tumours on glass slides and digital pathology. Methods Forty eight non-invasive urothelial bladder carcinomas were graded by three uropathologists on glass and on a digital platform using the 1973 WHO and 2004 ISUP/WHO systems. Results Consensus grades for glass and digital grading gave Cohen’s kappa scores of 0.78 (2004) and 0.82 (1973). Of 142 decisions made on the key therapeutic borderline of low grade versus high grade urothelial carcinoma (2004) by the three pathologists, 85% were in agreement. For the 1973 grading system, agreement overall was 90%. Conclusions Agreement on grading on glass slide and digital screen assessment is similar or in some cases improved, suggesting at least non-inferiority of DP for grading of non-invasive urothelial carcinoma.
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Affiliation(s)
- Richard Colling
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK. .,Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
| | - Hayleigh Colling
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK.,Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
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22
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Bertram CA, Stathonikos N, Donovan TA, Bartel A, Fuchs-Baumgartinger A, Lipnik K, van Diest PJ, Bonsembiante F, Klopfleisch R. Validation of digital microscopy: Review of validation methods and sources of bias. Vet Pathol 2021; 59:26-38. [PMID: 34433345 PMCID: PMC8761960 DOI: 10.1177/03009858211040476] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Digital microscopy (DM) is increasingly replacing traditional light microscopy (LM) for performing routine diagnostic and research work in human and veterinary pathology. The DM workflow encompasses specimen preparation, whole-slide image acquisition, slide retrieval, and the workstation, each of which has the potential (depending on the technical parameters) to introduce limitations and artifacts into microscopic examination by pathologists. Performing validation studies according to guidelines established in human pathology ensures that the best-practice approaches for patient care are not deteriorated by implementing DM. Whereas current publications on validation studies suggest an overall high reliability of DM, each laboratory is encouraged to perform an individual validation study to ensure that the DM workflow performs as expected in the respective clinical or research environment. With the exception of validation guidelines developed by the College of American Pathologists in 2013 and its update in 2021, there is no current review of the application of methods fundamental to validation. We highlight that there is high methodological variation between published validation studies, each having advantages and limitations. The diagnostic concordance rate between DM and LM is the most relevant outcome measure, which is influenced (regardless of the viewing modality used) by different sources of bias including complexity of the cases examined, diagnostic experience of the study pathologists, and case recall. Here, we review 3 general study designs used for previous publications on DM validation as well as different approaches for avoiding bias.
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Affiliation(s)
- Christof A Bertram
- University of Veterinary Medicine, Vienna, Austria.,Freie Universität Berlin, Berlin, Germany
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23
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Browning L, Colling R, Verrill C. WHO/ISUP grading of clear cell renal cell carcinoma and papillary renal cell carcinoma; validation of grading on the digital pathology platform and perspectives on reproducibility of grade. Diagn Pathol 2021; 16:75. [PMID: 34419085 PMCID: PMC8380382 DOI: 10.1186/s13000-021-01130-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 07/12/2021] [Indexed: 11/10/2022] Open
Abstract
Background There are recognised potential pitfalls in digital diagnosis in urological pathology, including the grading of dysplasia. The World Health Organisation/International Society of Urological Pathology (WHO/ISUP) grading system for renal cell carcinoma (RCC) is prognostically important in clear cell RCC (CCRCC) and papillary RCC (PRCC), and is included in risk stratification scores for CCRCC, thus impacting on patient management. To date there are no systematic studies examining the concordance of WHO/ISUP grading between digital pathology (DP) and glass slide (GS) images. We present a validation study examining intraobserver agreement in WHO/ISUP grade of CCRCC and PRCC. Methods Fifty CCRCCs and 10 PRCCs were graded (WHO/ISUP system) by three specialist uropathologists on three separate occasions (DP once then two GS assessments; GS1 and GS2) separated by wash-out periods of at least two-weeks. The grade was recorded for each assessment, and compared using Cohen’s and Fleiss’s kappa. Results There was 65 to 78% concordance of WHO/ISUP grading on DP and GS1. Furthermore, for the individual pathologists, the comparative kappa scores for DP versus GS1, and GS1 versus GS2, were 0.70 and 0.70, 0.57 and 0.73, and 0.71 and 0.74, and with no apparent tendency to upgrade or downgrade on DP versus GS. The interobserver kappa agreement was less, at 0.58 on DP and 0.45 on GS. Conclusion Our results demonstrate that the assessment of WHO/ISUP grade on DP is noninferior to that on GS. There is an apparent slight improvement in agreement between pathologists on RCC grade when assessed on DP, which may warrant further study.
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Affiliation(s)
- Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Headley Way, OX3 9DU, Oxford, UK. .,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Headley Way, OX3 9DU, Oxford, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, OX3 9DU, Oxford, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Headley Way, OX3 9DU, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, OX3 9DU, Oxford, UK
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24
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Klein C, Zeng Q, Arbaretaz F, Devêvre E, Calderaro J, Lomenie N, Maiuri MC. Artificial Intelligence for solid tumor diagnosis in digital pathology. Br J Pharmacol 2021; 178:4291-4315. [PMID: 34302297 DOI: 10.1111/bph.15633] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 02/05/2021] [Accepted: 02/07/2021] [Indexed: 11/30/2022] Open
Abstract
Tumor diagnosis relies on the visual examination of histological slides by pathologists through a microscope eyepiece. Digital pathology, the digitalization of histological slides at high magnification with slides scanners, has raised the opportunity to extract quantitative information thanks to image analysis. In the last decade, medical image analysis has made exceptional progress due to the development of artificial intelligence (AI) algorithms. AI has been successfully used in the field of medical imaging and more recently in digital pathology. The feasibility and usefulness of AI assisted pathology tasks have been demonstrated in the very last years and we can expect those developments to be applied on routine histopathology in the future. In this review, we will describe and illustrate this technique and present the most recent applications in the field of tumor histopathology.
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Affiliation(s)
- Christophe Klein
- Centre de recherche des Cordeliers, Centre d'Imagerie, Histologie et Cytométrie (CHIC), INSERM, Sorbonne Université, Université de Paris, Paris, France
| | - Qinghe Zeng
- Centre de recherche des Cordeliers, Centre d'Imagerie, Histologie et Cytométrie (CHIC), INSERM, Sorbonne Université, Université de Paris, Paris, France.,Laboratoire d'informatique Paris Descartes (LIPADE), Université de Paris, Paris, France
| | - Floriane Arbaretaz
- Centre de recherche des Cordeliers, Centre d'Imagerie, Histologie et Cytométrie (CHIC), INSERM, Sorbonne Université, Université de Paris, Paris, France
| | - Estelle Devêvre
- Centre de recherche des Cordeliers, Centre d'Imagerie, Histologie et Cytométrie (CHIC), INSERM, Sorbonne Université, Université de Paris, Paris, France
| | - Julien Calderaro
- Département de pathologie, Hôpital Henri Mondor, Créteil, France
| | - Nicolas Lomenie
- Laboratoire d'informatique Paris Descartes (LIPADE), Université de Paris, Paris, France
| | - Maria Chiara Maiuri
- Centre de recherche des Cordeliers, Centre d'Imagerie, Histologie et Cytométrie (CHIC), INSERM, Sorbonne Université, Université de Paris, Paris, France
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25
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Zhong Y, Sun W, Zhou L, Tang M, Zhang W, Xu J, Jiang Y, Liu L, Xu Y. Application of remote online learning in oral histopathology teaching in China. Med Oral Patol Oral Cir Bucal 2021; 26:e533-e540. [PMID: 34162817 PMCID: PMC8254891 DOI: 10.4317/medoral.24441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 06/14/2021] [Indexed: 11/18/2022] Open
Abstract
Background The aim of this study was to investigate the application of remote learning and virtual microscopy in oral histopathology teaching, a unique experience in China. The oral histopathology teaching in Nanjing Medical University has been extraordinary. Material and Methods 98 third-year dental students of Grade 2016 took oral histopathology theoretical course face-to-face in 2019 (Traditional group). The 94 participants of Grade 2017 took online oral histopathology course using digital methods(E-Learning platform and Virtual Simulation Experiment Teaching Center for Dentistry) in 2020. During the practical laboratory sessions, the students in both Traditional group and Online group observed the same glass slides for morphological learning. A questionnaire survey explored students' attitudes towards the remote online learning. Results: The mean Theory test scores of the Online group (80.93±12.15) were significantly higher than those of the Traditional group (73.65±8.46) (P < 0.01). The mean total scores of the Online group (82.94±10.76) were significantly higher than those of the Traditional group (77.25±7.55) (P < 0.01). The percentage of high total test score (test score > 85) of the Online group (54%) was also significantly higher than that of the Traditional group (15%) (P< 0.01). Furthermore, both remote learning and virtual microscopy courses were well accepted by students according to the questionnaire. Conclusions This study found that remote learning and virtual technology have a positive impact on oral histopathology. The findings reveal that the application of remote online learning has enhanced oral histopathology teaching in China. Key words:Oral histopathology, dental undergraduate students, virtual microscopy, remote online learning, questionnaire.
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Affiliation(s)
- Y Zhong
- Department of Basic Science of Stomatology, Affiliated Hospital of Stomatology, Nanjing Medical University Nanjing 210029, China
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26
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Azam AS, Miligy IM, Kimani PKU, Maqbool H, Hewitt K, Rajpoot NM, Snead DRJ. Diagnostic concordance and discordance in digital pathology: a systematic review and meta-analysis. J Clin Pathol 2021; 74:448-455. [PMID: 32934103 PMCID: PMC8223673 DOI: 10.1136/jclinpath-2020-206764] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 07/10/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Digital pathology (DP) has the potential to fundamentally change the way that histopathology is practised, by streamlining the workflow, increasing efficiency, improving diagnostic accuracy and facilitating the platform for implementation of artificial intelligence-based computer-assisted diagnostics. Although the barriers to wider adoption of DP have been multifactorial, limited evidence of reliability has been a significant contributor. A meta-analysis to demonstrate the combined accuracy and reliability of DP is still lacking in the literature. OBJECTIVES We aimed to review the published literature on the diagnostic use of DP and to synthesise a statistically pooled evidence on safety and reliability of DP for routine diagnosis (primary and secondary) in the context of validation process. METHODS A comprehensive literature search was conducted through PubMed, Medline, EMBASE, Cochrane Library and Google Scholar for studies published between 2013 and August 2019. The search protocol identified all studies comparing DP with light microscopy (LM) reporting for diagnostic purposes, predominantly including H&E-stained slides. Random-effects meta-analysis was used to pool evidence from the studies. RESULTS Twenty-five studies were deemed eligible to be included in the review which examined a total of 10 410 histology samples (average sample size 176). For overall concordance (clinical concordance), the agreement percentage was 98.3% (95% CI 97.4 to 98.9) across 24 studies. A total of 546 major discordances were reported across 25 studies. Over half (57%) of these were related to assessment of nuclear atypia, grading of dysplasia and malignancy. These were followed by challenging diagnoses (26%) and identification of small objects (16%). CONCLUSION The results of this meta-analysis indicate equivalent performance of DP in comparison with LM for routine diagnosis. Furthermore, the results provide valuable information concerning the areas of diagnostic discrepancy which may warrant particular attention in the transition to DP.
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Affiliation(s)
- Ayesha S Azam
- Cellular Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, Coventry, UK
- Tissue Image Analytics Laboratory, Department of Computer Science, University of Warwick, Coventry, West Midlands, UK
| | - Islam M Miligy
- Nottingham Breast Cancer Research Centre (NBCRC), School of Medicine, University of Nottingham, Nottingham, Nottinghamshire, UK
| | - Peter K-U Kimani
- Warwick Medical School, University of Warwick, Coventry, West Midlands, UK
| | - Heeba Maqbool
- Cellular Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, Coventry, UK
| | - Katherine Hewitt
- Cellular Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, Coventry, UK
| | - Nasir M Rajpoot
- Tissue Image Analytics Laboratory, Department of Computer Science, University of Warwick, Coventry, West Midlands, UK
| | - David R J Snead
- Cellular Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, Coventry, UK
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27
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Samuelson MI, Chen SJ, Boukhar SA, Schnieders EM, Walhof ML, Bellizzi AM, Robinson RA, Rajan K D A. Rapid Validation of Whole-Slide Imaging for Primary Histopathology Diagnosis. Am J Clin Pathol 2021; 155:638-648. [PMID: 33511392 PMCID: PMC7929400 DOI: 10.1093/ajcp/aqaa280] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVES The 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. METHODS Glass 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. RESULTS In 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%. CONCLUSIONS We 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.
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Affiliation(s)
- Megan I Samuelson
- Department of Pathology, University of Iowa Hospitals and Clinics, University of Iowa, Iowa City, IA, USA
| | - Stephanie J Chen
- Department of Pathology, University of Iowa Hospitals and Clinics, University of Iowa, Iowa City, IA, USA
| | - Sarag A Boukhar
- Department of Pathology, University of Iowa Hospitals and Clinics, University of Iowa, Iowa City, IA, USA
| | - Eric M Schnieders
- Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Mackenzie L Walhof
- Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Andrew M Bellizzi
- Department of Pathology, University of Iowa Hospitals and Clinics, University of Iowa, Iowa City, IA, USA
| | - Robert A Robinson
- Department of Pathology, University of Iowa Hospitals and Clinics, University of Iowa, Iowa City, IA, USA
| | - Anand Rajan K D
- Department of Pathology, University of Iowa Hospitals and Clinics, University of Iowa, Iowa City, IA, USA
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28
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Breast Digital Pathology: Way of the Future. CURRENT BREAST CANCER REPORTS 2021. [DOI: 10.1007/s12609-021-00413-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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29
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Quantifying intraepithelial lymphocytes and subepithelial collagen band in microscopic colitis, extracting insights into the interrelationship of lymphocytic and collagenous colitis. Ann Diagn Pathol 2021; 52:151741. [PMID: 33865186 DOI: 10.1016/j.anndiagpath.2021.151741] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 02/11/2021] [Accepted: 03/28/2021] [Indexed: 01/10/2023]
Abstract
Microscopic colitis (MC) is the umbrella term for the conditions termed lymphocytic colitis (LC) and collagenous colitis (CC). LC with thickening of the subepithelial collagen band or CC with increased number of intraepithelial T- lymphocytes (IELs) is often seen in MC and may lead to difficulties in correct histological classification. We investigated the extent of overlapping features of CC and LC in 60 cases of MC by measuring the exact thickness of the subepithelial collagen band in Van Gieson stained slides and quantifying number of IELs in CD3 stained slides by digital image analysis. A thickened collagen band was observed in nine out of 29 cases with LC (31%) and an increased number of IELs in all 23 cases of CC (100%). There was no correlation between the thickness of the collagen band and number of IELs. Due to the increased number of IELs in all cases of CC we consider the lymphocytic inflammatory infiltration of the mucosa to be the essential histopathological feature of MC. However, although LC and CC are related due to the lymphocytic inflammation, the non-linear correlation of number of IELs and thickness of the collagenous band indicate differences in their pathogenesis.
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30
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Girolami I, Marletta S, Eccher A. Commentary: The Digital Fate of Glomeruli in Renal Biopsy. J Pathol Inform 2021; 12:14. [PMID: 34012718 PMCID: PMC8112342 DOI: 10.4103/jpi.jpi_102_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 01/09/2021] [Accepted: 01/09/2021] [Indexed: 11/04/2022] Open
Affiliation(s)
- Ilaria Girolami
- Division of Pathology, Central Hospital Bolzano, Bolzano, Italy
| | - Stefano Marletta
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
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Polónia A, Campelos S, Ribeiro A, Aymore I, Pinto D, Biskup-Fruzynska M, Veiga RS, Canas-Marques R, Aresta G, Araújo T, Campilho A, Kwok S, Aguiar P, Eloy C. Artificial Intelligence Improves the Accuracy in Histologic Classification of Breast Lesions. Am J Clin Pathol 2021; 155:527-536. [PMID: 33118594 DOI: 10.1093/ajcp/aqaa151] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVES This study evaluated the usefulness of artificial intelligence (AI) algorithms as tools in improving the accuracy of histologic classification of breast tissue. METHODS Overall, 100 microscopic photographs (test A) and 152 regions of interest in whole-slide images (test B) of breast tissue were classified into 4 classes: normal, benign, carcinoma in situ (CIS), and invasive carcinoma. The accuracy of 4 pathologists and 3 pathology residents were evaluated without and with the assistance of algorithms. RESULTS In test A, algorithm A had accuracy of 0.87, with the lowest accuracy in the benign class (0.72). The observers had average accuracy of 0.80, and most clinically relevant discordances occurred in distinguishing benign from CIS (7.1% of classifications). With the assistance of algorithm A, the observers significantly increased their average accuracy to 0.88. In test B, algorithm B had accuracy of 0.49, with the lowest accuracy in the CIS class (0.06). The observers had average accuracy of 0.86, and most clinically relevant discordances occurred in distinguishing benign from CIS (6.3% of classifications). With the assistance of algorithm B, the observers maintained their average accuracy. CONCLUSIONS AI tools can increase the classification accuracy of pathologists in the setting of breast lesions.
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Affiliation(s)
- António Polónia
- Department of Pathology, Ipatimup Diagnostics, Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
- I3S – Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal
| | - Sofia Campelos
- Department of Pathology, Ipatimup Diagnostics, Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
- I3S – Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal
| | - Ana Ribeiro
- Department of Pathology, Centro Hospitalar de Vila Nova de Gaia / Espinho, EPE, Vila Nova de Gaia, Portugal
| | - Ierece Aymore
- Department of Pathology, Ipatimup Diagnostics, Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
- I3S – Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal
| | - Daniel Pinto
- Department of Pathology, Centro Hospitalar de Lisboa Ocidental, EPE, Lisboa, Portugal
| | - Magdalena Biskup-Fruzynska
- Department of Tumor Pathology, Maria Sklodowska-Curie National Research Institute of Oncology (MSCNRIO), Gliwice, Poland
| | | | | | - Guilherme Aresta
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
- Faculty of Engineering, University of Porto, Porto, Portugal
| | - Teresa Araújo
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
- Faculty of Engineering, University of Porto, Porto, Portugal
| | - Aurélio Campilho
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
- Faculty of Engineering, University of Porto, Porto, Portugal
| | | | - Paulo Aguiar
- I3S – Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal
- Instituto Nacional de Engenharia Biomédica (INEB), Universidade do Porto, Porto, Portugal
| | - Catarina Eloy
- Department of Pathology, Ipatimup Diagnostics, Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
- I3S – Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal
- Faculty of Medicine, University of Porto, Porto, Portugal
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32
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Fully digital pathology laboratory routine and remote reporting of oral and maxillofacial diagnosis during the COVID-19 pandemic: a validation study. Virchows Arch 2021; 479:585-595. [PMID: 33713188 PMCID: PMC7955219 DOI: 10.1007/s00428-021-03075-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 02/25/2021] [Accepted: 03/02/2021] [Indexed: 11/25/2022]
Abstract
The role of digital pathology in remote reporting has seen an increase during the COVID-19 pandemic. Recently, recommendations had been made regarding the urgent need of reorganizing head and neck cancer diagnostic services to provide a safe work environment for the staff. A total of 162 glass slides from 109 patients over a period of 5 weeks were included in this validation and were assessed by all pathologists in both analyses (digital and conventional) to allow intraobserver comparison. The intraobserver agreement between the digital method (DM) and conventional method (CM) was considered almost perfect (κ ranged from 0.85 to 0.98, with 95% CI, ranging from 0.81 to 1). The most significant and frequent disagreements within trainees encompassed epithelial dysplasia grading and differentiation among severe dysplasia (carcinoma in situ) and oral squamous cell carcinoma. The most frequent pitfall from DM was lag in screen mirroring. The lack of details of inflammatory cells and the need for a higher magnification to assess dysplasia were pointed in one case each. The COVID-19 crisis has accelerated and consolidated the use of online meeting tools, which would be a valuable resource even in the post-pandemic scenario. Adaptation in laboratory workflow, the advent of digital pathology and remote reporting can mitigate the impact of similar future disruptions to the oral and maxillofacial pathology laboratory workflow avoiding delays in diagnosis and report, to facilitate timely management of head and neck cancer patients. Graphical abstract ![]()
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33
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Giaretto S, Renne SL, Rahal D, Bossi P, Colombo P, Spaggiari P, Manara S, Sollai M, Fiamengo B, Brambilla T, Fernandes B, Rao S, Elamin A, Valeri M, De Carlo C, Belsito V, Lancellotti C, Cieri M, Cagini A, Terracciano L, Roncalli M, Di Tommaso L. Digital Pathology During the COVID-19 Outbreak in Italy: Survey Study. J Med Internet Res 2021; 23:e24266. [PMID: 33503002 PMCID: PMC7901595 DOI: 10.2196/24266] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/09/2020] [Accepted: 12/14/2020] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Transition to digital pathology usually takes months or years to be completed. We were familiarizing ourselves with digital pathology solutions at the time when the COVID-19 outbreak forced us to embark on an abrupt transition to digital pathology. OBJECTIVE The aim of this study was to quantitatively describe how the abrupt transition to digital pathology might affect the quality of diagnoses, model possible causes by probabilistic modeling, and qualitatively gauge the perception of this abrupt transition. METHODS A total of 17 pathologists and residents participated in this study; these participants reviewed 25 additional test cases from the archives and completed a final psychologic survey. For each case, participants performed several different diagnostic tasks, and their results were recorded and compared with the original diagnoses performed using the gold standard method (ie, conventional microscopy). We performed Bayesian data analysis with probabilistic modeling. RESULTS The overall analysis, comprising 1345 different items, resulted in a 9% (117/1345) error rate in using digital slides. The task of differentiating a neoplastic process from a nonneoplastic one accounted for an error rate of 10.7% (42/392), whereas the distinction of a malignant process from a benign one accounted for an error rate of 4.2% (11/258). Apart from residents, senior pathologists generated most discrepancies (7.9%, 13/164). Our model showed that these differences among career levels persisted even after adjusting for other factors. CONCLUSIONS Our findings are in line with previous findings, emphasizing that the duration of transition (ie, lengthy or abrupt) might not influence the diagnostic performance. Moreover, our findings highlight that senior pathologists may be limited by a digital gap, which may negatively affect their performance with digital pathology. These results can guide the process of digital transition in the field of pathology.
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Affiliation(s)
- Simone Giaretto
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
| | - Salvatore Lorenzo Renne
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Daoud Rahal
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Paola Bossi
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Piergiuseppe Colombo
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Paola Spaggiari
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Sofia Manara
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Mauro Sollai
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Barbara Fiamengo
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Tatiana Brambilla
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Bethania Fernandes
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Stefania Rao
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Abubaker Elamin
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
| | - Marina Valeri
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Camilla De Carlo
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Vincenzo Belsito
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Cesare Lancellotti
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Miriam Cieri
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Angelo Cagini
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Luigi Terracciano
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Massimo Roncalli
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
| | - Luca Di Tommaso
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (MI), Italy
- Department of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano (MI), Italy
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Aryal GM, Aryal B, Kandel KP, Neupane BB. Cellulose-based micro-fibrous materials imaged with a home-built smartphone microscope. Microsc Res Tech 2021; 84:1794-1801. [PMID: 33608938 DOI: 10.1002/jemt.23736] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 01/21/2021] [Accepted: 02/01/2021] [Indexed: 12/29/2022]
Abstract
Micro-fibrous materials are one of the highly explored materials and form a major component of composite materials. In resource-limited settings, an affordable and easy to implement method that can characterize such material would be important. In this study, we report on a smartphone microscopic system capable of imaging a sample in transmission mode. As a proof of concept, we implemented the method to image handmade paper samples-cellulosic micro-fibrous material of different thickness. With 1 mm diameter ball lens, individual cellulose fibers, fiber web, and micro-porous regions were resolved in the samples. Imaging performance of the microscopic system was also compared with a commercial bright field microscope. For thin samples, we found the image quality comparable to commercial system. Also, the diameter of cellulose fiber measured from both methods was found to be similar. We also used the system to image surfaces of a three ply surgical facemask. Finally, we explored the application of the system in the study of chemical induced fiber damage. This study suggested that the smartphone microscope system can be an affordable alternative in imaging thin micro-fibrous material in resource limited setting.
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Affiliation(s)
- Girja Mani Aryal
- Central Department of Chemistry, Tribhuvan University, Kathmandu, Nepal.,Research Centre for Applied Science and Technology, Tribhuvan University, Kathmandu, Nepal
| | - Bishwa Aryal
- Central Department of Chemistry, Tribhuvan University, Kathmandu, Nepal
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35
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Feng M, Chen J, Xiang X, Deng Y, Zhou Y, Zhang Z, Zheng Z, Bao J, Bu H. An Advanced Automated Image Analysis Model for Scoring of ER, PR, HER-2 and Ki-67 in Breast Carcinoma. IEEE ACCESS 2021; 9:108441-108451. [DOI: 10.1109/access.2020.3011294] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
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36
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Bello IO, Wennerstrand PM, Suleymanova I, Siponen M, Qannam A, Nieminen P, Leivo I, Almangush A, Salo T. Biopsy quality is essential for preoperative prognostication in oral tongue cancer. APMIS 2020; 129:118-127. [PMID: 33320967 DOI: 10.1111/apm.13104] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 12/06/2020] [Indexed: 12/19/2022]
Abstract
A role for incisional biopsy in preoperative prognostication is increasingly being advocated in oral tongue squamous cell carcinomas (OTSCC). Biopsies at two locations were compared, and prognostic factors in biopsies and their corresponding resections were evaluated. A total of 138 OTSCC biopsy slides from Finland and Saudi Arabia were compared for size (horizontal and vertical) and invasive front. The Finnish cases were assessed for tumor stroma ratio (TSR) and tumor-infiltrating lymphocytes (TILs) using light microscopy and digital image analysis assessment and compared. Furthermore, TSR, TILs, and previously analyzed budding and depth of invasion (BD) score in biopsies were compared with their evaluation in the corresponding resections. Fifty-nine percent of Finnish and 42% of Saudi Arabian biopsies were ≥ 5 mm deep, while 98% of Saudi Arabian and 76% of Finnish biopsies were ≥ 5 mm wide. Assessment of invasion front was possible in 72% of Finnish in comparison with 40% of Saudi Arabian biopsies. There was 86.8% agreement between TSR and 75% agreement between TIL evaluation using light microscopy and digital assessment. Significant agreement was obtained on comparing the TSR (p = 0.04) and BD (p < 0.001) values in biopsies and resections. Biopsies of ≥ 5 mm depth from representative OTSCC areas are essential for prognostic information. Clinical pathologists are advised to assess BD score and TSR for prognostic features in such biopsies.
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Affiliation(s)
- Ibrahim O Bello
- Department of Oral Medicine and Diagnostic Sciences, King Saud University, Riyadh, Saudi Arabia.,Department of Pathology, University of Helsinki, Helsinki, Finland
| | | | - Ilida Suleymanova
- Department of Oral and Maxillofacial Diseases, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Maria Siponen
- Institute of Dentistry, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.,Oral Health Teaching Clinic and Department of Oral and Maxillofacial Diseases, Kuopio University Hospital, Kuopio, Finland
| | - Ahmed Qannam
- Department of Oral Medicine and Diagnostic Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Pentti Nieminen
- Medical Informatics and Data Analysis Research Group, University of Oulu, Oulu, Finland
| | - Ilmo Leivo
- Institute of Biomedicine, Pathology, University of Turku, Turku, Finland
| | - Alhadi Almangush
- Department of Pathology, University of Helsinki, Helsinki, Finland.,Institute of Biomedicine, Pathology, University of Turku, Turku, Finland.,Faculty of Dentistry, University of Misurata, Misurata, Libya
| | - Tuula Salo
- Department of Pathology, University of Helsinki, Helsinki, Finland.,Department of Oral and Maxillofacial Diseases, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Cancer and Translational Medicine Research Unit, Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, Finland
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37
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The histopathological diagnosis of atypical meningioma: glass slide versus whole slide imaging for grading assessment. Virchows Arch 2020; 478:747-756. [PMID: 33305338 PMCID: PMC7990834 DOI: 10.1007/s00428-020-02988-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 11/14/2020] [Accepted: 12/03/2020] [Indexed: 12/23/2022]
Abstract
Limited studies on whole slide imaging (WSI) in surgical neuropathology reported a perceived limitation in the recognition of mitoses. This study analyzed and compared the inter- and intra-observer concordance for atypical meningioma, using glass slides and WSI. Two neuropathologists and two residents assessed the histopathological features of 35 meningiomas-originally diagnosed as atypical-in a representative glass slide and corresponding WSI. For each histological parameter and final diagnosis, we calculated the inter- and intra-observer concordance in the two viewing modes and the predictive accuracy on recurrence. The concordance rates for atypical meningioma on glass slides and on WSI were 54% and 60% among four observers and 63% and 74% between two neuropathologists. The inter-observer agreement was higher using WSI than with glass slides for all parameters, with the exception of high mitotic index. For all histological features, we found median intra-observer concordance of ≥ 79% and similar predictive accuracy for recurrence between the two viewing modes. The higher concordance for atypical meningioma using WSI than with glass slides and the similar predictive accuracy for recurrence in the two modalities suggest that atypical meningioma may be safely diagnosed using WSI.
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38
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Panayides AS, Amini A, Filipovic ND, Sharma A, Tsaftaris SA, Young A, Foran D, Do N, Golemati S, Kurc T, Huang K, Nikita KS, Veasey BP, Zervakis M, Saltz JH, Pattichis CS. AI in Medical Imaging Informatics: Current Challenges and Future Directions. IEEE J Biomed Health Inform 2020; 24:1837-1857. [PMID: 32609615 PMCID: PMC8580417 DOI: 10.1109/jbhi.2020.2991043] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for efficient medical data management strategies in the context of AI in big healthcare data analytics. It then provides a synopsis of contemporary and emerging algorithmic methods for disease classification and organ/ tissue segmentation, focusing on AI and deep learning architectures that have already become the de facto approach. The clinical benefits of in-silico modelling advances linked with evolving 3D reconstruction and visualization applications are further documented. Concluding, integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications. The latter, is projected to enable informed, more accurate diagnosis, timely prognosis, and effective treatment planning, underpinning precision medicine.
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39
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Pallua JD, Brunner A, Zelger B, Schirmer M, Haybaeck J. The future of pathology is digital. Pathol Res Pract 2020; 216:153040. [PMID: 32825928 DOI: 10.1016/j.prp.2020.153040] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 05/31/2020] [Indexed: 02/07/2023]
Abstract
Information, archives, and intelligent artificial systems are part of everyday life in modern medicine. They already support medical staff by mapping their workflows with shared availability of cases' referral information, as needed for example, by the pathologist, and this support will be increased in the future even more. In radiology, established standards define information models, data transmission mechanisms, and workflows. Other disciplines, such as pathology, cardiology, and radiation therapy, now define further demands in addition to these established standards. Pathology may have the highest technical demands on the systems, with very complex workflows, and the digitization of slides generating enormous amounts of data up to Gigabytes per biopsy. This requires enormous amounts of data to be generated per biopsy, up to the gigabyte range. Digital pathology allows a change from classical histopathological diagnosis with microscopes and glass slides to virtual microscopy on the computer, with multiple tools using artificial intelligence and machine learning to support pathologists in their future work.
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Affiliation(s)
- J D Pallua
- Department of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Müllerstraße 44, A-6020, Innsbruck, Austria.
| | - A Brunner
- Department of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Müllerstraße 44, A-6020, Innsbruck, Austria
| | - B Zelger
- Department of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Müllerstraße 44, A-6020, Innsbruck, Austria
| | - M Schirmer
- Department of Internal Medicine, Clinic II, Medical University of Innsbruck, Anichstrasse 35, A-6020, Innsbruck, Austria
| | - J Haybaeck
- Department of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Müllerstraße 44, A-6020, Innsbruck, Austria; Department of Pathology, Medical Faculty, Otto-von-Guericke University Magdeburg, Leipzigerstrasse 44, D-Magdeburg, Germany; Diagnostic & Research Center for Molecular BioMedicine, Institute of Pathology, Medical University of Graz, Neue Stiftingtalstrasse 6, A-8010, Graz, Austria
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40
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Eccher A, Girolami I, Brunelli M, Novelli L, Mescoli C, Malvi D, D'Errico A, Luchini C, Furian L, Zaza G, Cardillo M, Boggi U, Pantanowitz L. Digital pathology for second opinion consultation and donor assessment during organ procurement: Review of the literature and guidance for deployment in transplant practice. Transplant Rev (Orlando) 2020; 34:100562. [PMID: 32576430 DOI: 10.1016/j.trre.2020.100562] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 05/01/2020] [Accepted: 05/15/2020] [Indexed: 01/20/2023]
Abstract
Telepathology has been an important application for second opinion consultation ever since the introduction of digital pathology. However, little is known regarding teleconsultation for second opinion in transplantation. There is also limited literature on telepathology during organ donor procurement, typically utilized when general pathologists on-call request back-up to help assess donor biopsies for organ suitability or to diagnose newly discovered tumors with urgent time constraints. In this review, we searched Pubmed/Embase and websites of transplant organizations to collect and analyze published evidence on teleconsultation for donor evaluation and organ procurement. Of 2725 records retrieved using the key terms 'telepathology', 'second opinion' and 'transplantation', 26 suitable studies were included. Most records were from North America and included validation studies of telepathology being used for remote frozen section interpretation of donor biopsies with whole slide imaging. The data from these published studies supports the transition towards digital teleconsultation in transplant settings where consultations among pathologists are still handled by pathologists being called on site, via telephone and/or email.
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Affiliation(s)
- Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy.
| | - Ilaria Girolami
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Matteo Brunelli
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Luca Novelli
- Institute for Histopathology and Molecular Diagnosis, Careggi University Hospital, Florence, Italy
| | - Claudia Mescoli
- Department of Medicine (DIMED), Surgical Pathology & Cytopathology Unit, University and Hospital Trust of Padua, Padua, Italy
| | - Deborah Malvi
- Pathology Unit, University of Bologna, Policlinico St. Orsola-Malpighi Hospital, Bologna, Italy
| | - Antonia D'Errico
- Pathology Unit, University of Bologna, Policlinico St. Orsola-Malpighi Hospital, Bologna, Italy
| | - Claudio Luchini
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Lucrezia Furian
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, University and Hospital Trust of Padua, Padua, Italy
| | - Gianluigi Zaza
- Renal Unit, University and Hospital Trust of Verona, Verona, Italy
| | | | - Ugo Boggi
- Division of General and Transplant Surgery, University of Pisa, Pisa, Italy
| | - Liron Pantanowitz
- Department of Pathology, UPMC Shadyside Hospital, University of Pittsburgh, Pittsburgh, PA, USA
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41
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Feng M, Deng Y, Yang L, Jing Q, Zhang Z, Xu L, Wei X, Zhou Y, Wu D, Xiang F, Wang Y, Bao J, Bu H. Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma. Diagn Pathol 2020; 15:65. [PMID: 32471471 PMCID: PMC7257511 DOI: 10.1186/s13000-020-00957-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 04/08/2020] [Indexed: 02/08/2023] Open
Abstract
Background The scoring of Ki-67 is highly relevant for the diagnosis, classification, prognosis, and treatment in breast invasive ductal carcinoma (IDC). Traditional scoring method of Ki-67 staining followed by manual counting, is time-consumption and inter−/intra observer variability, which may limit its clinical value. Although more and more algorithms and individual platforms have been developed for the assessment of Ki-67 stained images to improve its accuracy level, most of them lack of accurate registration of immunohistochemical (IHC) images and their matched hematoxylin-eosin (HE) images, or did not accurately labelled each positive and negative cell with Ki-67 staining based on whole tissue sections (WTS). In view of this, we introduce an accurate image registration method and an automatic identification and counting software of Ki-67 based on WTS by deep learning. Methods We marked 1017 breast IDC whole slide imaging (WSI), established a research workflow based on the (i) identification of IDC area, (ii) registration of HE and IHC slides from the same anatomical region, and (iii) counting of positive Ki-67 staining. Results The accuracy, sensitivity, and specificity levels of identifying breast IDC regions were 89.44, 85.05, and 95.23%, respectively, and the contiguous HE and Ki-67 stained slides perfectly registered. We counted and labelled each cell of 10 Ki-67 slides as standard for testing on WTS, the accuracy by automatic calculation of Ki-67 positive rate in attained IDC was 90.2%. In the human-machine competition of Ki-67 scoring, the average time of 1 slide was 2.3 min with 1 GPU by using this software, and the accuracy was 99.4%, which was over 90% of the results provided by participating doctors. Conclusions Our study demonstrates the enormous potential of automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on WTS, and the automated scoring of Ki67 can thus successfully address issues of consistency, reproducibility and accuracy. We will provide those labelled images as an open-free platform for researchers to assess the performance of computer algorithms for automated Ki-67 scoring on IHC stained slides.
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Affiliation(s)
- Min Feng
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.,Department of Pathology, West China Second University Hospital, Sichuan University & key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610041, China.,Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Yang Deng
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Libo Yang
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.,Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Qiuyang Jing
- Department of Pathology, West China Second University Hospital, Sichuan University & key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610041, China
| | - Zhang Zhang
- Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lian Xu
- Department of Pathology, West China Second University Hospital, Sichuan University & key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610041, China.,Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Xiaoxia Wei
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.,Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.,Department of Pathology, Chengfei Hospital, Chengdu, China
| | - Yanyan Zhou
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Diwei Wu
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Fei Xiang
- Chengdu Knowledge Vision Science and Technology Co., Ltd, Chengdu, China
| | - Yizhe Wang
- Chengdu Knowledge Vision Science and Technology Co., Ltd, Chengdu, China
| | - Ji Bao
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Hong Bu
- Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China. .,Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.
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42
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Church DL, Naugler C. Essential role of laboratory physicians in transformation of laboratory practice and management to a value-based patient-centric model. Crit Rev Clin Lab Sci 2020; 57:323-344. [PMID: 32180485 DOI: 10.1080/10408363.2020.1720591] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
The laboratory is a vital part of the continuum of patient care. In fact, there are few programs in the healthcare system that do not rely on ready access and availability of complex diagnostic laboratory services. The existing transactional model of laboratory "medical practice" will not be able to meet the needs of the healthcare system as it rapidly shifts toward value-based care and precision medicine, which demands that practice be based on total system indicators, clinical effectiveness, and patient outcomes. Laboratory "value" will no longer be focused primarily on internal testing quality and efficiencies but rather on the relative cost of diagnostic testing compared to direct improvement in clinical and system outcomes. The medical laboratory as a "business" focused on operational efficiency and cost-controls must transform to become an essential clinical service that is a tightly integrated equal partner in direct patient care. We would argue that this paradigm shift would not be necessary if laboratory services had remained a "patient-centric" medical practice throughout the last few decades. This review is focused on the essential role of laboratory physicians in transforming laboratory practice and management to a value-based patient-centric model. Value-based practice is necessary not only to meet the challenges of the new precision medicine world order but also to bring about sustainable healthcare service delivery.
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Affiliation(s)
- Deirdre L Church
- Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Medicine, Faculty of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Faculty of Medicine, University of Calgary, Calgary, AB, Canada
| | - Christopher Naugler
- Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Faculty of Medicine, University of Calgary, Calgary, AB, Canada
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43
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Melo RCN, Raas MWD, Palazzi C, Neves VH, Malta KK, Silva TP. Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders. Front Med (Lausanne) 2020; 6:310. [PMID: 31970160 PMCID: PMC6960181 DOI: 10.3389/fmed.2019.00310] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Accepted: 12/09/2019] [Indexed: 12/11/2022] Open
Abstract
Histological analysis of hepatic tissue specimens is essential for evaluating the pathology of several liver disorders such as chronic liver diseases, hepatocellular carcinomas, liver steatosis, and infectious liver diseases. Manual examination of histological slides on the microscope is a classically used method to study these disorders. However, it is considered time-consuming, limited, and associated with intra- and inter-observer variability. Emerging technologies such as whole slide imaging (WSI), also termed virtual microscopy, have increasingly been used to improve the assessment of histological features with applications in both clinical and research laboratories. WSI enables the acquisition of the tissue morphology/pathology from glass slides and translates it into a digital form comparable to a conventional microscope, but with several advantages such as easy image accessibility and storage, portability, sharing, annotation, qualitative and quantitative image analysis, and use for educational purposes. WSI-generated images simultaneously provide high resolution and a wide field of observation that can cover the entire section, extending any single field of view. In this review, we summarize current knowledge on the application of WSI to histopathological analyses of liver disorders as well as to understand liver biology. We address how WSI may improve the assessment and quantification of multiple histological parameters in the liver, and help diagnose several hepatic conditions with important clinical implications. The WSI technical limitations are also discussed.
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Affiliation(s)
- Rossana C N Melo
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Maximilian W D Raas
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil.,Faculty of Medical Sciences, Radboud University, Nijmegen, Netherlands
| | - Cinthia Palazzi
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Vitor H Neves
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Kássia K Malta
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Thiago P Silva
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
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Girolami I, Pantanowitz L, Marletta S, Brunelli M, Mescoli C, Parisi A, Barresi V, Parwani A, Neil D, Scarpa A, Rossi ED, Eccher A. Diagnostic concordance between whole slide imaging and conventional light microscopy in cytopathology: A systematic review. Cancer Cytopathol 2020; 128:17-28. [DOI: 10.1002/cncy.22195] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Accepted: 09/23/2019] [Indexed: 08/29/2023]
Affiliation(s)
- Ilaria Girolami
- Department of Pathology and Diagnostics University and Hospital Trust of Verona Verona Italy
| | - Liron Pantanowitz
- Department of Pathology UPMC Shadyside Hospital University of Pittsburgh Pittsburgh Pennsylvania
| | - Stefano Marletta
- Department of Pathology and Diagnostics University and Hospital Trust of Verona Verona Italy
| | - Matteo Brunelli
- Department of Pathology and Diagnostics University and Hospital Trust of Verona Verona Italy
| | - Claudia Mescoli
- Surgical Pathology and Cytopathology Unit Department of Medicine University and Hospital Trust of Padua Padua Italy
| | - Alice Parisi
- Department of Pathology and Diagnostics University and Hospital Trust of Verona Verona Italy
| | - Valeria Barresi
- Department of Pathology and Diagnostics University and Hospital Trust of Verona Verona Italy
| | - Anil Parwani
- Department of Pathology Ohio State University Columbus Ohio
| | - Desley Neil
- Department of Histopathology University Hospital Birmingham National Health Service Foundation Trust Birmingham United Kingdom
| | - Aldo Scarpa
- Department of Pathology and Diagnostics University and Hospital Trust of Verona Verona Italy
| | - Esther Diana Rossi
- Division of Anatomic Pathology and Histology Catholic University of Sacred Heart Agostino Gemelli School of Medicine Rome Italy
| | - Albino Eccher
- Department of Pathology and Diagnostics University and Hospital Trust of Verona Verona Italy
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Fiehn AMK, Clausen LN, Engel U, Munck LK, Kristensson M, Engel PJH. Establishment of digital cutoff values for intraepithelial lymphocytes in biopsies from colonic mucosa with lymphocytic colitis. Pathol Res Pract 2019; 215:152580. [DOI: 10.1016/j.prp.2019.152580] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/31/2019] [Accepted: 08/03/2019] [Indexed: 12/22/2022]
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46
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Gupta R, Kurc T, Sharma A, Almeida JS, Saltz J. The Emergence of Pathomics. CURRENT PATHOBIOLOGY REPORTS 2019. [DOI: 10.1007/s40139-019-00200-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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