1
|
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.
Collapse
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
| |
Collapse
|
2
|
Rogers L, Galezowski A, Ganshorn H, Goldsmith D, Legge C, Waine K, Zachar E, Davies JL. The use of telepathology in veterinary medicine: a scoping review. J Vet Diagn Invest 2024; 36:490-497. [PMID: 38742388 PMCID: PMC11185107 DOI: 10.1177/10406387241241270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024] Open
Abstract
Telepathology, as a subset of teleconsulting, is pathology interpretation performed at a distance. Telepathology is not a new phenomenon, but since ~2015, significant advances in information technology and telecommunications coupled with the pandemic have led to unprecedented sophistication, accessibility, and use of telepathology in human and veterinary medicine. Furthermore, telepathology can connect veterinary practices to distant laboratories and provide support for underserved animals and communities. Through our scoping review, we provide an overview of how telepathology is being used in veterinary medicine, identify gaps in the literature, and highlight future areas of research and service development. We searched MEDLINE, CAB Abstracts, and the gray literature, and included all relevant literature. Despite the widespread use of digital microscopy in large veterinary diagnostic laboratories, we identified a paucity of literature describing the use of telepathology in veterinary medicine, with a significant gap in studies addressing the validation of whole-slide imaging for primary diagnosis. Underutilization of telepathology to support postmortem examinations conducted in the field was also identified, which indicates a potential area for service development. The use of telepathology is increasing in veterinary medicine, and pathologists must keep pace with the changing technology, ensure the validation of innovative technologies, and identify novel uses to advance the profession.
Collapse
Affiliation(s)
- Lindsay Rogers
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Angelica Galezowski
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Heather Ganshorn
- Library and Cultural Resources, University of Calgary, Calgary, Alberta, Canada
| | - Dayna Goldsmith
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Carolyn Legge
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Katie Waine
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Erin Zachar
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Jennifer L. Davies
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
| |
Collapse
|
3
|
Tresserra F, Fabra G, Luque O, Castélla M, Gómez C, Fernández-Cid C, Rodríguez I. Validation of digital image slides for diagnosis in cervico-vaginal cytology. REVISTA ESPANOLA DE PATOLOGIA : PUBLICACION OFICIAL DE LA SOCIEDAD ESPANOLA DE ANATOMIA PATOLOGICA Y DE LA SOCIEDAD ESPANOLA DE CITOLOGIA 2024; 57:182-189. [PMID: 38971618 DOI: 10.1016/j.patol.2024.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/19/2024] [Accepted: 03/26/2024] [Indexed: 07/08/2024]
Abstract
OBJECTIVE To test the diagnostic concordance between microscopic (MI) and digital (DG) observation of cervico-vaginal (CV) cytology in a validation study of the technique. METHODS Five cytotechnologists (CT) reviewed 888 routine CV cytology cases from the Cervical Pathology Unit of our center over a 2-week period of time. The cases were first observed by MI and at the end of the day the cases were observed by DG. STATISTICAL ANALYSIS USED Agreement calculated using the Kappa index. RESULTS Most of the diagnoses corresponded to benign (64%) or inflammatory conditions (14%) and 24% corresponded to the intraepithelial lesion or malignancy (ILM) category. The overall kappa coefficient of concordance was strong (0.87). Among the different CTs it was almost perfect in two, strong in two and moderate in one. In 18 cases (10%) there were discrepancies between techniques in the category of ILM. In 10 (56%) cases there was an overdiagnosis in DG and in 8 (44%) an overdiagnosis in MI. Only in two cases, the diagnostic discrepancy exceeded one degree of difference between lesions, and they were ASCUS or AGUS for DG and CIN 2 for MI. CONCLUSIONS In this validation test in which routine cases during a two-week period have been used, observing the cases with both techniques on the same day, we have obtained a strong degree of concordance. The discordances obtained have not been considered relevant.
Collapse
Affiliation(s)
- Francisco Tresserra
- Cytology Laboratory, Gynecology Service, Dexeus Women's Health, Dexeus University Hospital, Barcelona, Spain.
| | - Gemma Fabra
- Cytology Laboratory, Gynecology Service, Dexeus Women's Health, Dexeus University Hospital, Barcelona, Spain
| | - Olga Luque
- Cytology Laboratory, Gynecology Service, Dexeus Women's Health, Dexeus University Hospital, Barcelona, Spain
| | - Miriam Castélla
- Cytology Laboratory, Gynecology Service, Dexeus Women's Health, Dexeus University Hospital, Barcelona, Spain
| | - Carla Gómez
- Cytology Laboratory, Gynecology Service, Dexeus Women's Health, Dexeus University Hospital, Barcelona, Spain
| | - Carmen Fernández-Cid
- Cytology Laboratory, Gynecology Service, Dexeus Women's Health, Dexeus University Hospital, Barcelona, Spain
| | - Ignacio Rodríguez
- Epidemiology Unit, Gynecology Service, Dexeus Women's Health, Dexeus University Hospital, Barcelona, Spain
| |
Collapse
|
4
|
Shehabeldin A, Rohra P, Sellen LD, Zhao J, Alqaidy D, Aramin H, Hameed N, Perez YE, Lai Z, Tong YT, Milton DR, Edgerton ME, Fuller G, Hansel D, Prieto VG, Ballester LY, Aung PP. Utility of Whole Slide Imaging for Intraoperative Consultation: Experience of a Large Academic Center. Arch Pathol Lab Med 2024; 148:715-721. [PMID: 37756559 DOI: 10.5858/arpa.2023-0105-oa] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/13/2023] [Indexed: 09/29/2023]
Abstract
CONTEXT.— In the United States, review of digital whole slide images (WSIs) using specific systems is approved for primary diagnosis but has not been implemented for intraoperative consultation. OBJECTIVE.— To evaluate the safety of review of WSIs and compare the efficiency of review of WSIs and glass slides (GSs) for intraoperative consultation. DESIGN.— Ninety-one cases previously submitted for frozen section evaluation were randomly selected from 8 different anatomic pathology subspecialties. GSs from these cases were scanned on a Leica Aperio AT2 scanner at ×20 magnification (0.25 μm/pixel). The slides were deidentified, and a short relevant clinical history was provided for each slide. Nine board-certified general pathologists who do not routinely establish primary diagnoses using WSIs reviewed the WSIs using Leica Aperio ImageScope viewing software. After a washout period of 2-3 weeks, the pathologists reviewed the corresponding GSs using a light microscope (Olympus BX43). The pathologists recorded the diagnosis and time to reach the diagnosis. Intraobserver concordance, time to diagnosis, and specificity and sensitivity compared to the original diagnosis were evaluated. RESULTS.— The rate of intraobserver concordance between GS results and WSI results was 93.7%. Mean time to diagnosis was 1.25 minutes for GSs and 1.76 minutes for WSIs (P < .001). Specificity was 91% for GSs and 90% for WSIs; sensitivity was 92% for GSs and 92% for WSIs. CONCLUSIONS.— Time to diagnosis was longer with WSIs than with GSs, and scanning GSs and uploading the data to whole slide imaging systems takes time. However, review of WSIs appears to be a safe alternative to review of GSs. Use of WSIs allows reporting from a remote site during a public health emergency such as the COVID-19 pandemic and facilitates subspecialty histopathology services.
Collapse
Affiliation(s)
- Ahmed Shehabeldin
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Prih Rohra
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Linton D Sellen
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Jianping Zhao
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Doaa Alqaidy
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Hermineh Aramin
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Nadia Hameed
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Ydamis Estrella Perez
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Zongshan Lai
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Yi Tat Tong
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Denái R Milton
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Mary E Edgerton
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Gregory Fuller
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Donna Hansel
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Victor G Prieto
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Leomar Y Ballester
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| | - Phyu P Aung
- From the Departments of Pathology (Shehabeldin, Rohra, Sellen, Zhao, Alqaidy, Aramin, Hameed, Perez, Lai, Tong, Edgerton, Fuller, Hansel, Prieto, Ballester, Aung) and Biostatistics (Milton), The University of Texas MD Anderson Cancer Center, Houston
| |
Collapse
|
5
|
dos Santos RTN, Faria CAB, Martins NF, Duda Júnior LGDS, Azevêdo ABF, da Silva WR, Sobral APV. Use of digital strategies in the diagnosis of oral squamous cell carcinoma: a scoping review. PeerJ 2024; 12:e17329. [PMID: 38737735 PMCID: PMC11086294 DOI: 10.7717/peerj.17329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 04/11/2024] [Indexed: 05/14/2024] Open
Abstract
Telediagnosis uses information and communication technologies to support diagnosis, shortening geographical distances. It helps make decisions about various oral lesions. The objective of this scoping review was to map the existing literature on digital strategies to assist in the diagnosis of oral squamous cell carcinoma. this review was structured based on the 5-stage methodology proposed by Arksey and O'Malley, the Joanna Briggs Institute Manual for Evidence Synthesis and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. The methods were registered on the Open Science Framework. The research question was: What digital strategies have been used to assist in the diagnosis of oral squamous cell carcinoma? The search was conducted on PubMed/MEDLINE, Scopus, Web of Science, Embase, and ScienceDirect. Inclusion criteria comprised studies on telediagnosis, teleconsultation or teleconsultation mediated by a professional and studies in English, without date restrictions. The search conducted in June 2023 yielded 1,798 articles, from which 16 studies were included. Telediagnosis was reported in nine studies, involving data screening through applications, clinical images from digital cameras, mobile phones or artificial intelligence. Histopathological images were reported in four studies. Both, telediagnosis and teleconsultation, were mentioned in seven studies, utilizing images and information submission services to platforms, WhatsApp or applications. One study presented teleconsultations involving slides and another study introduced teleconsultation mediated by a professional. Digital strategies telediagnosis and teleconsultations enable the histopathological diagnosis of oral cancer through clinical or histopathological images. The higher the observed diagnostic agreement, the better the performance of the strategy.
Collapse
Affiliation(s)
| | | | | | | | | | - Weslay Rodrigues da Silva
- Department of Oral and Maxillofacial Pathology, University of Pernambuco, Recife, Pernambuco, Brazil
| | - Ana Paula Veras Sobral
- Department of Oral and Maxillofacial Pathology, University of Pernambuco, Recife, Pernambuco, Brazil
| |
Collapse
|
6
|
Goacher E, Mathew R, Fayaye O, Chakrabarty A, Feltbower R, Loughrey C, Roberts P, Chumas P. Can quantifying the extent of 'high grade' features help explain prognostic variability in anaplastic astrocytoma? Br J Neurosurg 2024; 38:314-321. [PMID: 33377401 DOI: 10.1080/02688697.2020.1866163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 12/11/2020] [Accepted: 12/15/2020] [Indexed: 10/22/2022]
Abstract
PURPOSE Both phenotypic and genotypic variations now underpin glioma classification, thus helping to more accurately guide their clinical management. However, WHO Grade III anaplastic astrocytoma (AA) remains an unpredictable, heterogeneous entity; displaying a variable prognosis, clinical course and treatment response. This study aims to examine whether additional tumour characteristics influence either overall survival (OS) or 3-year survival in AA. MATERIALS AND METHODS Data were collected on all newly diagnosed cases of AA between 2003 and 2014, followed up for a minimum of 3 years. Molecular information was obtained from case records and if missing, was re-analysed. Histological slides were independently examined for Ki-67 proliferation index, cellularity and number of mitotic figures. Kaplan-Meier and Cox regression analyses were used to assess OS. RESULTS In total, 50 cases were included with a median OS of 14.5 months (range: 1-150 months). Cumulative 3-year survival was 31.5%. Median age was 50 years (range: 24 - 77). Age, IDH1 mutation status, lobar location, oncological therapy and surgical resection were significant independent prognostic indicators for OS. In cases demonstrating an OS ≥ 3 years (n = 15), Ki-67 index, number of mitotic figures and percentage areas of 'high cellularity' were significantly reduced, i.e. more characteristic of lower-grade/WHO Grade II glioma. CONCLUSIONS IDH1 status, age, treatment and location remain the most significant prognostic indicators for patients with AA. However, Ki-67 index, mitotic figures and cellularity may help identify AA cases more likely to survive < 3 years, i.e. AA cases more similar to glioblastoma and those cases more likely to survive > 3 years, i.e. more similar to a low-grade glioma.
Collapse
Affiliation(s)
- Edward Goacher
- Department of Neurosurgery, Royal Hallamshire Hospital, Sheffield, UK
| | - Ryan Mathew
- Department of Neurosurgery, Leeds General Infirmary, Leeds, UK
- School of Medicine, University of Leeds, Leeds, UK
| | | | - Aruna Chakrabarty
- Department of Histopathology, St. James's University Hospital, Leeds, UK
| | | | - Carmel Loughrey
- Department of Oncology, St. James's University Hospital, Leeds, UK
| | - Paul Roberts
- Department of Cytogenetics, St. James's University Hospital, Leeds, UK
| | - Paul Chumas
- Department of Neurosurgery, Leeds General Infirmary, Leeds, UK
| |
Collapse
|
7
|
Rozario SY, Sarkar M, Farlie MK, Lazarus MD. Responding to the healthcare workforce shortage: A scoping review exploring anatomical pathologists' professional identities over time. ANATOMICAL SCIENCES EDUCATION 2024; 17:351-365. [PMID: 36748328 DOI: 10.1002/ase.2260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 01/16/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Anatomical pathology (AP) is an anatomy-centric medical specialty devoted to tissue-based diagnosis of disease. The field faces a current and predicted workforce shortage, likely increasing diagnostic wait times and delaying patient access to urgent treatment. A lack of AP exposure is proposed to preclude recruitment to the field, as medical students are afforded only a limited understanding of who a pathologist is and what they do (their professional identity/PI and role). Anatomical sciences educators may be well placed to increase student understanding of anatomical pathologists' PI features, but until features of anatomical pathologists' PI are understood, recommendations for anatomy educators are premature. Thus, this scoping review asked: "What are the professional identity features of anatomical pathologists reported in the literature, and how have these changed over time?" A six-stage scoping review was performed. Medline and PubMed, Global Health, and Embase were used to identify relevant studies (n = 74). Team-based framework analysis identified that features of anatomical pathologists' professional identity encompass five overarching themes: professional practice, views about the role, training and education, personal implications, and technology. Technology was identified as an important theme of anatomical pathologists' PI, as it intersected with many other PI feature themes, including diagnosis and collaboration. This review found that pathologists may sometimes perceive professional competition with technology, such as artificial intelligence. These findings suggest unique opportunities for integrating AP-specific PI features into anatomy teaching, which may foster student interest in AP, and potentially increase recruitment into the field.
Collapse
Affiliation(s)
- Shemona Y Rozario
- Centre for Human Anatomy Education (CHAE), Department of Anatomy and Developmental Biology, Biomedical Discovery Institute, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
| | - Mahbub Sarkar
- Monash Centre for Scholarship in Health Education (MCSHE), Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
| | - Melanie K Farlie
- Monash Centre for Scholarship in Health Education (MCSHE), Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
- Department of Physiotherapy, Faculty of Medicine Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
| | - Michelle D Lazarus
- Centre for Human Anatomy Education (CHAE), Department of Anatomy and Developmental Biology, Biomedical Discovery Institute, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
- Monash Centre for Scholarship in Health Education (MCSHE), Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
| |
Collapse
|
8
|
Li JW, Wang LM, Ichimasa K, Lin KW, Ngu JCY, Ang TL. Use of artificial intelligence in the management of T1 colorectal cancer: a new tool in the arsenal or is deep learning out of its depth? Clin Endosc 2024; 57:24-35. [PMID: 37743068 PMCID: PMC10834280 DOI: 10.5946/ce.2023.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 05/11/2023] [Indexed: 09/26/2023] Open
Abstract
The field of artificial intelligence is rapidly evolving, and there has been an interest in its use to predict the risk of lymph node metastasis in T1 colorectal cancer. Accurately predicting lymph node invasion may result in fewer patients undergoing unnecessary surgeries; conversely, inadequate assessments will result in suboptimal oncological outcomes. This narrative review aims to summarize the current literature on deep learning for predicting the probability of lymph node metastasis in T1 colorectal cancer, highlighting areas of potential application and barriers that may limit its generalizability and clinical utility.
Collapse
Affiliation(s)
- James Weiquan Li
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore
- Academic Medicine Center, Duke-NUS Medical School, Singapore
| | - Lai Mun Wang
- Department of Laboratory Medicine, Changi General Hospital, Singapore Health Services, Singapore
| | - Katsuro Ichimasa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Kenneth Weicong Lin
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore
- Academic Medicine Center, Duke-NUS Medical School, Singapore
| | - James Chi-Yong Ngu
- Department of General Surgery, Changi General Hospital, Singapore Health Services, Singapore
| | - Tiing Leong Ang
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore
- Academic Medicine Center, Duke-NUS Medical School, Singapore
| |
Collapse
|
9
|
Schwen LO, Kiehl TR, Carvalho R, Zerbe N, Homeyer A. Digitization of Pathology Labs: A Review of Lessons Learned. J Transl Med 2023; 103:100244. [PMID: 37657651 DOI: 10.1016/j.labinv.2023.100244] [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: 06/07/2023] [Revised: 07/18/2023] [Accepted: 08/23/2023] [Indexed: 09/03/2023] Open
Abstract
Pathology laboratories are increasingly using digital workflows. This has the potential of increasing laboratory efficiency, but the digitization process also involves major challenges. Several reports have been published describing the individual experiences of specific laboratories with the digitization process. However, a comprehensive overview of the lessons learned is still lacking. We provide an overview of the lessons learned for different aspects of the digitization process, including digital case management, digital slide reading, and computer-aided slide reading. We also cover metrics used for monitoring performance and pitfalls and corresponding values observed in practice. The overview is intended to help pathologists, information technology decision makers, and administrators to benefit from the experiences of others and to implement the digitization process in an optimal way to make their own laboratory future-proof.
Collapse
Affiliation(s)
- Lars Ole Schwen
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.
| | - Tim-Rasmus Kiehl
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Pathology, Berlin, Germany
| | - Rita Carvalho
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Pathology, Berlin, Germany
| | - Norman Zerbe
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Pathology, Berlin, Germany
| | - André Homeyer
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| |
Collapse
|
10
|
Evans H, Hero E, Minhas F, Wahab N, Dodd K, Sahota H, Ganguly R, Robinson A, Neerudu M, Blessing E, Borkar P, Snead D. Standardized Clinical Annotation of Digital Histopathology Slides at the Point of Diagnosis. Mod Pathol 2023; 36:100297. [PMID: 37544362 DOI: 10.1016/j.modpat.2023.100297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/26/2023] [Accepted: 07/25/2023] [Indexed: 08/08/2023]
Abstract
As digital pathology replaces conventional glass slide microscopy as a means of reporting cellular pathology samples, the annotation of digital pathology whole slide images is rapidly becoming part of a pathologist's regular practice. Currently, there is no recognizable organization of these annotations, and as a result, pathologists adopt an arbitrary approach to defining regions of interest, leading to irregularity and inconsistency and limiting the downstream efficient use of this valuable effort. In this study, we propose a Standardized Annotation Reporting Style for digital whole slide images. We formed a list of 167 commonly annotated entities (under 12 specialty subcategories) based on review of Royal College of Pathologists and College of American Pathologists documents, feedback from reporting pathologists in our NHS department, and experience in developing annotation dictionaries for PathLAKE research projects. Each entity was assigned a suitable annotation shape, SNOMED CT (SNOMED International) code, and unique color. Additionally, as an example of how the approach could be expanded to specific tumor types, all lung tumors in the fifth World Health Organization of thoracic tumors 2021 were included. The proposed standardization of annotations increases their utility, making them identifiable at low power and searchable across and between cases. This would aid pathologists reporting and reviewing cases and enable annotations to be used for research. This structured approach could serve as the basis for an industry standard and be easily adopted to ensure maximum functionality and efficiency in the use of annotations made during routine clinical examination of digital slides.
Collapse
Affiliation(s)
- Harriet Evans
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom; Warwick Medical School, University of Warwick, Coventry, United Kingdom.
| | - Emily Hero
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom; Histopathology Department, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
| | - Fayyaz Minhas
- Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, United Kingdom
| | - Noorul Wahab
- Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, United Kingdom
| | - Katherine Dodd
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom
| | - Harvir Sahota
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom; Department of Psychiatry, Coventry and Warwickshire Partnership Trust, Coventry, United Kingdom
| | - Ratnadeep Ganguly
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom
| | - Andrew Robinson
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom
| | - Manjuvani Neerudu
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom
| | - Elaine Blessing
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom
| | - Pallavi Borkar
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom
| | - David Snead
- Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom; Warwick Medical School, University of Warwick, Coventry, United Kingdom
| |
Collapse
|
11
|
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.
Collapse
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
| |
Collapse
|
12
|
Stutterheim HW, ter Hoeve ND, Maarse W, van der Wall E, van Diest PJ. Time Trends in Histopathological Findings in Mammaplasty Specimens in a Dutch Academic Pathology Laboratory. PLASTIC AND RECONSTRUCTIVE SURGERY-GLOBAL OPEN 2023; 11:e4966. [PMID: 37361508 PMCID: PMC10287115 DOI: 10.1097/gox.0000000000004966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 03/09/2023] [Indexed: 06/28/2023]
Abstract
Reduction mammaplasties are often performed at a relatively young age. Necessity of routine pathological investigation of the removed breast tissue to exclude breast cancer has been debated. Past studies have shown 0.05%-4.5% significant findings in reduction specimens, leading to an ongoing debate whether this is cost-effective. There is also no current Dutch guideline on pathological investigation of mammaplasty specimens. Because the incidence of breast cancer is rising, especially among young women, we re-evaluated the yield of routine pathological investigation of mammaplasty specimens over three decades in search of time trends. Methods Reduction specimens from 3430 female patients examined from 1988 to 2021 in the UMC Utrecht were evaluated. Significant findings were defined as those that may lead to more intensive follow-up or surgical intervention. Results Mean age of patients was 39 years. Of the specimens, 67.4% were normal; 28.9% displayed benign changes; 2.7%, benign tumors; 0.3%, premalignant changes; 0.8%, in situ; and 0.1%, invasive cancers. Most patients with significant findings were in their forties (P < 0.001), the youngest patient being 29 years. Significant findings increased from 2016 onward (P = 0.0001), 86.8% found after 2016. Conclusions Over three decades, 1.2% of mammaplasty specimens displayed significant findings on routine pathology examination, with an incidence rising to 2.1% from 2016 onward. The main reason for this recent increase is probably attributable to super-specialization by the pathologists. While awaiting formal cost-effectiveness studies, the frequency of significant findings for now seems to justify routine pathological examination of mammaplasty reduction specimens.
Collapse
Affiliation(s)
| | - Natalie D. ter Hoeve
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Wiesje Maarse
- Department of Plastic, Reconstructive and Hand Surgery, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Elsken van der Wall
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Paul J. van Diest
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| |
Collapse
|
13
|
Hu W, Li X, Li C, Li R, Jiang T, Sun H, Huang X, Grzegorzek M, Li X. A state-of-the-art survey of artificial neural networks for Whole-slide Image analysis: From popular Convolutional Neural Networks to potential visual transformers. Comput Biol Med 2023; 161:107034. [PMID: 37230019 DOI: 10.1016/j.compbiomed.2023.107034] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 04/13/2023] [Accepted: 05/10/2023] [Indexed: 05/27/2023]
Abstract
In recent years, with the advancement of computer-aided diagnosis (CAD) technology and whole slide image (WSI), histopathological WSI has gradually played a crucial aspect in the diagnosis and analysis of diseases. To increase the objectivity and accuracy of pathologists' work, artificial neural network (ANN) methods have been generally needed in the segmentation, classification, and detection of histopathological WSI. However, the existing review papers only focus on equipment hardware, development status and trends, and do not summarize the art neural network used for full-slide image analysis in detail. In this paper, WSI analysis methods based on ANN are reviewed. Firstly, the development status of WSI and ANN methods is introduced. Secondly, we summarize the common ANN methods. Next, we discuss publicly available WSI datasets and evaluation metrics. These ANN architectures for WSI processing are divided into classical neural networks and deep neural networks (DNNs) and then analyzed. Finally, the application prospect of the analytical method in this field is discussed. The important potential method is Visual Transformers.
Collapse
Affiliation(s)
- Weiming Hu
- Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Xintong Li
- Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Chen Li
- Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
| | - Rui Li
- Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Tao Jiang
- School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China; International Joint Institute of Robotics and Intelligent Systems, Chengdu University of Information Technology, Chengdu, China
| | - Hongzan Sun
- Shengjing Hospital of China Medical University, Shenyang, China
| | - Xinyu Huang
- Institute for Medical Informatics, University of Luebeck, Luebeck, Germany
| | - Marcin Grzegorzek
- Institute for Medical Informatics, University of Luebeck, Luebeck, Germany; Department of Knowledge Engineering, University of Economics in Katowice, Katowice, Poland
| | - Xiaoyan Li
- Cancer Hospital of China Medical University, Shenyang, China.
| |
Collapse
|
14
|
Wong CM, Kezlarian BE, Lin O. Current status of machine learning in thyroid cytopathology. J Pathol Inform 2023; 14:100309. [PMID: 37077698 PMCID: PMC10106504 DOI: 10.1016/j.jpi.2023.100309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 04/03/2023] Open
Abstract
The implementation of Digital Pathology has allowed the development of computational Pathology. Digital image-based applications that have received FDA Breakthrough Device Designation have been primarily focused on tissue specimens. The development of Artificial Intelligence-assisted algorithms using Cytology digital images has been much more limited due to technical challenges and a lack of optimized scanners for Cytology specimens. Despite the challenges in scanning whole slide images of cytology specimens, there have been many studies evaluating CP to create decision-support tools in Cytopathology. Among different Cytology specimens, thyroid fine needle aspiration biopsy (FNAB) specimens have one of the greatest potentials to benefit from machine learning algorithms (MLA) derived from digital images. Several authors have evaluated different machine learning algorithms focused on thyroid cytology in the past few years. The results are promising. The algorithms have mostly shown increased accuracy in the diagnosis and classification of thyroid cytology specimens. They have brought new insights and demonstrated the potential for improving future cytopathology workflow efficiency and accuracy. However, many issues still need to be addressed to further build on and improve current MLA models and their applications. To optimally train and validate MLA for thyroid cytology specimens, larger datasets obtained from multiple institutions are needed. MLAs hold great potential in improving thyroid cancer diagnostic speed and accuracy that will lead to improvements in patient management.
Collapse
Affiliation(s)
| | | | - Oscar Lin
- Corresponding author at: Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| |
Collapse
|
15
|
Marletta S, Pantanowitz L, Santonicco N, Caputo A, Bragantini E, Brunelli M, Girolami I, Eccher A. Application of Digital Imaging and Artificial Intelligence to Pathology of the Placenta. Pediatr Dev Pathol 2023; 26:5-12. [PMID: 36448447 DOI: 10.1177/10935266221137953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Digital imaging, including the use of artificial intelligence, has been increasingly applied to investigate the placenta and its related pathology. However, there has been no comprehensive review of this body of work to date. The aim of this study was to therefore review the literature regarding digital pathology of the placenta. A systematic literature search was conducted in several electronic databases. Studies involving the application of digital imaging and artificial intelligence techniques to human placental samples were retrieved and analyzed. Relevant articles were categorized by digital image technique and their relevance to studying normal and diseased placenta. Of 2008 retrieved articles, 279 were included. Digital imaging research related to the placenta was often coupled with immunohistochemistry, confocal microscopy, 3D reconstruction, and/or deep learning algorithms. By significantly increasing pathologists' ability to recognize potentially prognostic relevant features and by lessening inter-observer variability, published data overall indicate that the application of digital pathology to placental and perinatal diseases, along with clinical and radiology correlation, has great potential to improve fetal and maternal health care including the selection of targeted therapy in high-risk pregnancy.
Collapse
Affiliation(s)
- Stefano Marletta
- Department of Pathology and Diagnostics, Section of Pathology, University Hospital of Verona, Verona, Italy
| | | | - Nicola Santonicco
- Department of Pathology and Diagnostics, Section of Pathology, University Hospital of Verona, Verona, Italy
| | - Alessandro Caputo
- Department of Medicine and Surgery, University of Salerno, Salerno, Italy
| | - Emma Bragantini
- Department of Pathology, Santa Chiara Hospital, Trento, Italy
| | - Matteo Brunelli
- Department of Pathology and Diagnostics, Section of Pathology, University Hospital of Verona, Verona, Italy
| | - Ilaria Girolami
- Department of Pathology & Clinical Labs, University of Michigan, Ann Arbor, MI, USA
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| |
Collapse
|
16
|
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.
Collapse
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
| |
Collapse
|
17
|
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.
Collapse
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
| |
Collapse
|
18
|
Schmidle P, Braun SA. [Digitalization in dermatopathology]. DERMATOLOGIE (HEIDELBERG, GERMANY) 2022; 73:845-852. [PMID: 36085178 DOI: 10.1007/s00105-022-05059-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/24/2022] [Indexed: 06/15/2023]
Abstract
The histomorphological analysis of tissue sections by specially trained dermatopathologists is a central component for making the dermatological diagnosis. It is the foundation for the understanding of clinical aspects, pathophysiology and not least the treatment of skin diseases and is therefore an essential part of modern dermatology. New technological developments in recent years offer a variety of possibilities to digitalize dermatopathology, which could significantly change and even revolutionize the work of dermatopathologists in the coming years; however, like any new development there are limiting factors and open questions that need to be discussed. This article is intended to provide an overview of the current state of the art and to highlight the corresponding opportunities and risks on the road to digital dermatopathology.
Collapse
Affiliation(s)
- Paul Schmidle
- Klinik für Hautkrankheiten, Universitätsklinikum Münster, Von-Esmarch-Str. 58, 48149, Münster, Deutschland.
| | - Stephan A Braun
- Klinik für Hautkrankheiten, Universitätsklinikum Münster, Von-Esmarch-Str. 58, 48149, Münster, Deutschland
- Klinik für Dermatologie, Medizinische Fakultät, Heinrich-Heine-Universität, Düsseldorf, Deutschland
| |
Collapse
|
19
|
A New Artificial Intelligence-Based Method for Identifying Mycobacterium Tuberculosis in Ziehl–Neelsen Stain on Tissue. Diagnostics (Basel) 2022; 12:diagnostics12061484. [PMID: 35741294 PMCID: PMC9221616 DOI: 10.3390/diagnostics12061484] [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: 05/19/2022] [Revised: 06/14/2022] [Accepted: 06/15/2022] [Indexed: 11/16/2022] Open
Abstract
Mycobacteria identification is crucial to diagnose tuberculosis. Since the bacillus is very small, finding it in Ziehl–Neelsen (ZN)-stained slides is a long task requiring significant pathologist’s effort. We developed an automated (AI-based) method of identification of mycobacteria. We prepared a training dataset of over 260,000 positive and over 700,000,000 negative patches annotated on scans of 510 whole slide images (WSI) of ZN-stained slides (110 positive and 400 negative). Several image augmentation techniques coupled with different custom computer vision architectures were used. WSIs automatic analysis was followed by a report indicating areas more likely to present mycobacteria. Our model performs AI-based diagnosis (the final decision of the diagnosis of WSI belongs to the pathologist). The results were validated internally on a dataset of 286,000 patches and tested in pathology laboratory settings on 60 ZN slides (23 positive and 37 negative). We compared the pathologists’ results obtained by separately evaluating slides and WSIs with the results given by a pathologist aided by automatic analysis of WSIs. Our architecture showed 0.977 area under the receiver operating characteristic curve. The clinical test presented 98.33% accuracy, 95.65% sensitivity, and 100% specificity for the AI-assisted method, outperforming any other AI-based proposed methods for AFB detection.
Collapse
|
20
|
Rizzo PC, Girolami I, Marletta S, Pantanowitz L, Antonini P, Brunelli M, Santonicco N, Vacca P, Tumino N, Moretta L, Parwani A, Satturwar S, Eccher A, Munari E. Technical and Diagnostic Issues in Whole Slide Imaging Published Validation Studies. Front Oncol 2022; 12:918580. [PMID: 35785212 PMCID: PMC9246412 DOI: 10.3389/fonc.2022.918580] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 05/24/2022] [Indexed: 01/07/2023] Open
Abstract
ObjectiveDigital pathology with whole-slide imaging (WSI) has many potential clinical and non-clinical applications. In the past two decades, despite significant advances in WSI technology adoption remains slow for primary diagnosis. The aim of this study was to identify common pitfalls of WSI reported in validation studies and offer measures to overcome these challenges.MethodsA systematic search was conducted in the electronic databases Pubmed-MEDLINE and Embase. Inclusion criteria were all validation studies designed to evaluate the feasibility of WSI for diagnostic clinical use in pathology. Technical and diagnostic problems encountered with WSI in these studies were recorded.ResultsA total of 45 studies were identified in which technical issues were reported in 15 (33%), diagnostic issues in 8 (18%), and 22 (49%) reported both. Key technical problems encompassed slide scan failure, prolonged time for pathologists to review cases, and a need for higher image resolution. Diagnostic challenges encountered were concerned with grading dysplasia, reliable assessment of mitoses, identification of microorganisms, and clearly defining the invasive front of tumors.ConclusionDespite technical advances with WSI technology, some critical concerns remain that need to be addressed to ensure trustworthy clinical diagnostic use. More focus on the quality of the pre-scanning phase and training of pathologists could help reduce the negative impact of WSI technical difficulties. WSI also seems to exacerbate specific diagnostic tasks that are already challenging among pathologists even when examining glass slides with conventional light microscopy.
Collapse
Affiliation(s)
- Paola Chiara Rizzo
- Department of Pathology and Diagnostics and Public Health, Section of Pathology, University Hospital of Verona, Verona, Italy
| | | | - Stefano Marletta
- Department of Pathology and Diagnostics and Public Health, Section of Pathology, University Hospital of Verona, Verona, Italy
- Department of Pathology, Pederzoli Hospital, Peschiera del Garda, Italy
| | - Liron Pantanowitz
- Department of Pathology & Clinical Labs, University of Michigan, Ann Arbor, MI, United States
| | - Pietro Antonini
- Department of Pathology and Diagnostics and Public Health, Section of Pathology, University Hospital of Verona, Verona, Italy
| | - Matteo Brunelli
- Department of Pathology and Diagnostics and Public Health, Section of Pathology, University Hospital of Verona, Verona, Italy
| | - Nicola Santonicco
- Department of Pathology and Diagnostics and Public Health, Section of Pathology, University Hospital of Verona, Verona, Italy
| | - Paola Vacca
- Bambino Gesù Children’s Hospital, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - Nicola Tumino
- Bambino Gesù Children’s Hospital, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - Lorenzo Moretta
- Bambino Gesù Children’s Hospital, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - Anil Parwani
- Department of Pathology, Ohio State University Medical Center, Columbus, OH, United States
| | - Swati Satturwar
- Department of Pathology, Ohio State University Medical Center, Columbus, OH, United States
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
- *Correspondence: Albino Eccher,
| | - Enrico Munari
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| |
Collapse
|
21
|
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.
Collapse
|
22
|
Forest T, Aeffner F, Bangari DS, Bawa B, Carter J, Fikes J, High W, Hayashi SM, Jacobsen M, McKinney L, Rudmann D, Steinbach T, Schumacher V, Turner O, Ward JM, Willson CJ. Scientific and Regulatory Policy Committee Points to Consider: Primary Digital Histopathology Evaluation and Peer Review for Good Laboratory Practice (GLP) Nonclinical Toxicology Studies. Toxicol Pathol 2022; 50:531-543. [PMID: 35657014 DOI: 10.1177/01926233221099273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The Society of Toxicologic Pathology's Scientific and Regulatory Policy Committee formed a working group to consider the present and future use of digital pathology in toxicologic pathology in general and specifically its use in primary evaluation and peer review in Good Laboratory Practice (GLP) environments. Digital histopathology systems can save costs by reducing travel, enhancing organizational flexibility, decreasing slide handling, improving collaboration, increasing access to historical images, and improving quality and efficiency through integration with laboratory information management systems. However, the resources to implement and operate a digital pathology system can be significant. Given the magnitude and risks involved in the decision to adopt digital histopathology, this working group used pertinent previously published survey results and its members' expertise to create a Points-to-Consider article to assist organizations with building and implementing digital pathology workflows. With the aim of providing a comprehensive perspective, the current publication summarizes aspects of digital whole-slide imaging relevant to nonclinical histopathology evaluations, and then presents points to consider applicable to both primary digital histopathology evaluation and digital peer review in GLP toxicology studies. The Supplemental Appendices provide additional tabulated resources.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Wanda High
- High Preclinical Pathology Consulting, Rochester, New York, USA
| | - Shim-Mo Hayashi
- Laboratory of Veterinary Pathology, Tokyo University of Agriculture and Technology, Fuchu, Tokyo, Japan
- Division of Food Additives, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan
| | - Matthew Jacobsen
- Regulatory Safety Centre of Excellence, Clinical Pharmacology & Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - LuAnn McKinney
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Daniel Rudmann
- Charles River Laboratories International, Inc., Wilmington, Massachusetts, USA
| | - Thomas Steinbach
- Experimental Pathology Laboratories, Inc., Research Triangle Park, North Carolina, USA
| | | | | | | | - Cynthia J Willson
- Integrated Laboratory Systems, Research Triangle Park, North Carolina, USA
| |
Collapse
|
23
|
Go H. Digital Pathology and Artificial Intelligence Applications in Pathology. Brain Tumor Res Treat 2022; 10:76-82. [PMID: 35545826 PMCID: PMC9098984 DOI: 10.14791/btrt.2021.0032] [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: 12/21/2021] [Revised: 01/17/2022] [Accepted: 03/13/2022] [Indexed: 11/20/2022] Open
Abstract
Digital pathology is revolutionizing pathology. The introduction of digital pathology made it possible to comprehensively change the pathology diagnosis workflow, apply and develop pathological artificial intelligence (AI) models, generate pathological big data, and perform telepathology. AI algorithms, including machine learning and deep learning, are used for the detection, segmentation, registration, processing, and classification of digitized pathological images. Pathological AI algorithms can be helpfully utilized for diagnostic screening, morphometric analysis of biomarkers, the discovery of new meanings of prognosis and therapeutic response in pathological images, and improvement of diagnostic efficiency. In order to develop a successful pathological AI model, it is necessary to consider the selection of a suitable type of image for a subject, utilization of big data repositories, the setting of an effective annotation strategy, image standardization, and color normalization. This review will elaborate on the advantages and perspectives of digital pathology, AI-based approaches, the applications in pathology, and considerations and challenges in the development of pathological AI models.
Collapse
Affiliation(s)
- Heounjeong Go
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
| |
Collapse
|
24
|
Mremi A, Bentzer NK, Mchome B, Mlay J, Blaakær J, Rasch V, Schledermann D. The role of telepathology in diagnosis of pre-malignant and malignant cervical lesions: Implementation at a tertiary hospital in Northern Tanzania. PLoS One 2022; 17:e0266649. [PMID: 35421156 PMCID: PMC9009664 DOI: 10.1371/journal.pone.0266649] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/25/2022] [Indexed: 01/16/2023] Open
Abstract
Introduction Adequate and timely access to pathology services is a key to scale up cancer control, however, there is an extremely shortage of pathologists in Tanzania. Telepathology (scanned images microscopy) has the potential to increase access to pathology services and it is increasingly being employed for primary diagnosis and consultation services. However, the experience with the use of telepathology in Tanzania is limited. We aimed to investigate the feasibility of using scanned images for primary diagnosis of pre-malignant and malignant cervical lesions by assessing its equivalency to conventional (glass slide) microscopy in Tanzania. Methods In this laboratory-based study, assessment of hematoxylin and eosin stained glass slides of 175 cervical biopsies were initially performed conventionally by three pathologists independently. The slides were scanned at x 40 and one to three months later, the scanned images were reviewed by the pathologists in blinded fashion. The agreement between initial and review diagnoses across participating pathologists was described and measured using Cohen’s kappa coefficient (κ). Results The overall concordance of diagnoses established on conventional microscopy compared to scanned images across three pathologists was 87.7%; κ = 0.54; CI (0.49–0.57).The overall agreement of diagnoses established by local pathologist on conventional microscopy compared to scanned images was 87.4%; κ = 0.73; CI (0.65–0.79). The concordance of diagnoses established by senior pathologist compared to local pathologist on conventional microscopy and scanned images was 96% and 97.7% respectively. The inter-observer agreement (κ) value were 0.93, CI (0.87–1.00) and 0.94, CI (0.88–1.00) for conventional microscopy and scanned images respectively. Conclusions All κ coefficients expressed good intra- and inter-observer agreement, suggesting that telepathology is sufficiently accurate for primary diagnosis in surgical pathology. The discrepancies in interpretation of pre-malignant lesions highlights the importance of p16 immunohistochemistry in definitive diagnosis in these lesions. Sustainability factors including hardware and internet connectivity are essential components to be considered before telepathology may be deemed suitable for widely use in Tanzania.
Collapse
Affiliation(s)
- Alex Mremi
- Department of Pathology, Kilimanjaro Christian Medical Centre, Moshi, Tanzania
- Department of Obstetrics and Gynecology, Kilimanjaro Christian Medical University College, Moshi, Tanzania
- * E-mail:
| | | | - Bariki Mchome
- Department of Obstetrics and Gynecology, Kilimanjaro Christian Medical University College, Moshi, Tanzania
- Department of Obstetrics and Gynecology, Kilimanjaro Christian Medical Centre, Moshi, Tanzania
| | - Joseph Mlay
- Department of Obstetrics and Gynecology, Kilimanjaro Christian Medical University College, Moshi, Tanzania
- Department of Obstetrics and Gynecology, Kilimanjaro Christian Medical Centre, Moshi, Tanzania
| | - Jan Blaakær
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Obstetrics and Gynecology, Odense University Hospital, Odense, Denmark
| | - Vibeke Rasch
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Obstetrics and Gynecology, Odense University Hospital, Odense, Denmark
| | | |
Collapse
|
25
|
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.
Collapse
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
| |
Collapse
|
26
|
Forest T, Aeffner F, Bangari DS, Bawa B, Carter J, Fikes J, High WB, Hayashi SM, Jacobsen M, McKinney L, Rudmann D, Steinbach T, Schumacher V, Turner OC, Ward JM, Willson CJ. Scientific and Regulatory Policy Committee Brief Communication: 2019 Survey on Use of Digital Histopathology Systems in Nonclinical Toxicology Studies. Toxicol Pathol 2022; 50:397-401. [PMID: 35321602 DOI: 10.1177/01926233221084621] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Histopathologic evaluation and peer review using digital whole-slide images (WSIs) is a relatively new medium for assessing nonclinical toxicology studies in Good Laboratory Practice (GLP) environments. To better understand the present and future use of digital pathology in nonclinical toxicology studies, the Society of Toxicologic Pathology (STP) formed a working group to survey STP members with the goal of creating recommendations for implementation. The survey was administered in December 2019, immediately before the COVID-19 pandemic, and the results suggested that the use of digital histopathology for routine GLP histopathology assessment was not widespread. Subsequently, in follow-up correspondence during the pandemic, many responding institutions either began investigating or adopting digital WSI systems to reduce employee exposure to COVID-19. Therefore, the working group presents the survey results as a pre-pandemic baseline data set. Recommendations for use of WSI systems in GLP environments will be the subject of a separate publication.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Wanda B High
- High Preclinical Pathology Consulting, Rochester, New York, USA
| | - Shim-Mo Hayashi
- Tokyo University of Agriculture and Technology, Fuchu, Japan.,National Institute of Health Sciences, Kawasaki, Japan
| | | | - LuAnn McKinney
- US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Daniel Rudmann
- Charles River Laboratories International, Inc., Wilmington, Massachusetts, USA
| | - Thomas Steinbach
- Experimental Pathology Laboratories, Inc., Research Triangle Park, North Carolina, USA
| | | | | | | | | |
Collapse
|
27
|
Hanna MG, Ardon O, Reuter VE, Sirintrapun SJ, England C, Klimstra DS, Hameed MR. Integrating digital pathology into clinical practice. Mod Pathol 2022; 35:152-164. [PMID: 34599281 DOI: 10.1038/s41379-021-00929-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/03/2021] [Accepted: 09/12/2021] [Indexed: 11/09/2022]
Abstract
The field of anatomic pathology has been evolving in the last few decades and the advancements have been largely fostered by innovative technology. Immunohistochemistry enabled a paradigm shift in discovery and diagnostic evaluation, followed by booming genomic advancements which allowed for submicroscopic pathologic characterization, and now the field of digital pathology coupled with machine learning and big data acquisition is paving the way to revolutionize the pathology medical domain. Whole slide imaging (WSI) is a disruptive technology where glass slides are digitized to produce on-screen whole slide images. Specifically, in the past decade, there have been significant advances in digital pathology systems that have allowed this technology to promote integration into clinical practice. Whole slide images (WSI), or digital slides, can be viewed and navigated comparable to glass slides on a microscope, as digital files. Whole slide imaging has increased in adoption among pathologists, pathology departments, and scientists for clinical, educational, and research initiatives. Integration of digital pathology systems requires a coordinated effort with numerous stakeholders, not only within the pathology department, but across the entire enterprise. Each pathology department has distinct needs, use cases and blueprints, however the framework components and variables for successful clinical integration can be generalized across any organization seeking to undergo a digital transformation at any scale. This article will review those components and considerations for integrating digital pathology systems into clinical practice.
Collapse
Affiliation(s)
- Matthew G Hanna
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Orly Ardon
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Victor E Reuter
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Christine England
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - David S Klimstra
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Meera R Hameed
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| |
Collapse
|
28
|
Clarke E, Doherty D, Randell R, Grek J, Thomas R, Ruddle RA, Treanor D. Faster than light (microscopy): superiority of digital pathology over microscopy for assessment of immunohistochemistry. J Clin Pathol 2022; 76:333-338. [PMID: 35039452 PMCID: PMC10176378 DOI: 10.1136/jclinpath-2021-207961] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/23/2021] [Indexed: 11/03/2022]
Abstract
AIMS Digital pathology offers the potential for significant benefits in diagnostic pathology, but currently the efficiency of slide viewing is a barrier to adoption. We hypothesised that presenting digital slides for simultaneous viewing of multiple sections of tissue for comparison, as in those with immunohistochemical panels, would allow pathologists to review cases more quickly. METHODS Novel software was developed to view synchronised parallel tissue sections on a digital pathology workstation. Sixteen histopathologists reviewed three liver biopsy cases including an immunohistochemical panel using the digital microscope, and three different liver biopsy cases including an immunohistochemical panel using the light microscope. The order of cases and interface was fully counterbalanced. Time to diagnosis was recorded and mean times are presented as data approximated to a normalised distribution. RESULTS Mean time to diagnosis was 4 min 3 s using the digital microscope and 5 min 24 s using the light microscope, saving 1 min 21 s (95% CI 16 s to 2 min 26 s; p=0.02), using the digital microscope. Overall normalised mean time to diagnosis was 85% on the digital pathology workstation compared with 115% on the microscope, a relative reduction of 26%. CONCLUSIONS With appropriate interface design, it is quicker to review immunohistochemical slides using a digital microscope than the conventional light microscope, without incurring any major diagnostic errors. As digital pathology becomes more integrated with routine clinical workflow and pathologists increase their experience of the technology, it is anticipated that other tasks will also become more time-efficient.
Collapse
Affiliation(s)
- Emily Clarke
- Division of Pathology and Data Analytics, University of Leeds, Leeds, UK .,Department of Histopathology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Daniel Doherty
- Division of Pathology and Data Analytics, University of Leeds, Leeds, UK.,Department of Histopathology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Rebecca Randell
- Faculty of Health Studies, University of Bradford, Bradford, UK.,Wolfson Centre for Applied Health Research, Bradford, UK
| | - Jonathan Grek
- Northern Ontario School of Medicine, Thunder Bay, Ontario, Canada
| | - Rhys Thomas
- Division of Pathology and Data Analytics, University of Leeds, Leeds, UK
| | - Roy A Ruddle
- School of Computing and Leeds Institute of Data Analytics, University of Leeds, Leeds, UK
| | - Darren Treanor
- Division of Pathology and Data Analytics, University of Leeds, Leeds, UK.,Department of Histopathology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| |
Collapse
|
29
|
Mayall F, Smethurst HB, Semkin L, Mandalia T, Sohail M, Hadden R, Biddlestone L. A feasibility study of multisite networked digital pathology reporting in England. J Pathol Inform 2022; 13:4. [PMID: 35136671 PMCID: PMC8794026 DOI: 10.4103/jpi.jpi_61_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 12/16/2021] [Accepted: 11/18/2021] [Indexed: 11/04/2022] Open
Abstract
Background: Materials and Methods: Results: Conclusions:
Collapse
|
30
|
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: 3] [Impact Index Per Article: 1.5] [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
|
31
|
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.
Collapse
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.
| |
Collapse
|
32
|
Girolami I, Neri S, Eccher A, Brunelli M, Hanna M, Pantanowitz L, Hanspeter E, Mazzoleni G. Frozen section telepathology service: Efficiency and benefits of an e-health policy in South Tyrol. Digit Health 2022; 8:20552076221116776. [PMID: 35923756 PMCID: PMC9340333 DOI: 10.1177/20552076221116776] [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: 05/30/2022] [Accepted: 07/13/2022] [Indexed: 12/03/2022] Open
Abstract
Objective/Background Telepathology has been widely adopted to allow intraoperative pathology
examinations to be performed remotely and for obtaining second opinion
teleconsultation. In the Italian northern region of South Tyrol, the
widespread geographical distances and consequent cost for the health system
of having a travelling pathologist cover intraoperative consultations in
peripheral hospitals was a key driver for the implementation of a
telepathology system. Methods In 2010, four Menarini D-Sight whole slide scanners to digitize entire
pathology slides were placed in the peripheral hospitals of Merano,
Bressanone, Brunico, and in the hub hospital of Bolzano. Digital
workstations were also installed to allow pathologists to remotely perform
intraoperative consultations with digital slides. This study reviews the
outcome after 12 years of telepathology for this intended clinical use. Results After an initial validation phase with 100 cases which yielded a sensitivity
of 65% (CI 43–84%) and specificity of 100% (CI 95–100%), there were 2058
intraoperative consultations handled by telepathology. The cases evaluated
were mainly breast sentinel lymph nodes, followed by urological,
gynecological and general surgical pathology frozen section specimens. There
were no false-positive cases and 165 (8%) false-negative cases, yielding an
overall sensitivity and specificity of 65% (CI 61–69%) and 100% (CI
99–100%), respectively. Conclusion Telepathology is reliable for remote intraoperative diagnosis and, despite
technical issues and initial acquaintance issues, proved beneficial for
patient care in satellite hospitals, improved standardization, promoted
innovation, and resulted in cost savings for the health system.
Collapse
Affiliation(s)
- Ilaria Girolami
- Department of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy
| | - Stefania Neri
- Department of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Matteo Brunelli
- Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy
| | - Mattew Hanna
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Liron Pantanowitz
- Department of Pathology & Clinical Labs, University of Michigan, Ann Arbor, MI, USA
| | - Esther Hanspeter
- Department of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy
| | - Guido Mazzoleni
- Department of Pathology, Provincial Hospital of Bolzano (SABES-ASDAA), Bolzano-Bozen, Italy
| |
Collapse
|
33
|
Patel A, Balis UGJ, Cheng J, Li Z, Lujan G, McClintock DS, Pantanowitz L, Parwani A. Contemporary Whole Slide Imaging Devices and Their Applications within the Modern Pathology Department: A Selected Hardware Review. J Pathol Inform 2021; 12:50. [PMID: 35070479 PMCID: PMC8721869 DOI: 10.4103/jpi.jpi_66_21] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 09/22/2021] [Indexed: 12/21/2022] Open
Abstract
Digital pathology (DP) has disrupted the practice of traditional pathology, including applications in education, research, and clinical practice. Contemporary whole slide imaging (WSI) devices include technological advances that help address some of the challenges facing modern pathology, such as increasing workloads with fewer subspecialized pathologists, expanding integrated delivery networks with global reach, and greater customization when working up cases for precision medicine. This review focuses on integral hardware components of 43 market available and soon-to-be released digital WSI devices utilized throughout the world. Components such as objective lens type and magnification, scanning camera, illumination, and slide capacity were evaluated with respect to scan time, throughput, accuracy of scanning, and image quality. This analysis of assorted modern WSI devices offers essential, valuable information for successfully selecting and implementing a digital WSI solution for any given pathology practice.
Collapse
Affiliation(s)
- Ankush Patel
- Department of Pathology, The Ohio State University, Columbus, Ohio, USA
| | | | - Jerome Cheng
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Zaibo Li
- Department of Pathology, The Ohio State University, Columbus, Ohio, USA
| | - Giovanni Lujan
- Department of Pathology, The Ohio State University, Columbus, Ohio, USA
| | | | - Liron Pantanowitz
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Anil Parwani
- Department of Pathology, The Ohio State University, Columbus, Ohio, USA
| |
Collapse
|
34
|
Cummins DM, Chaudhry IH, Harries M. Scarring Alopecias: Pathology and an Update on Digital Developments. Biomedicines 2021; 9:biomedicines9121755. [PMID: 34944572 PMCID: PMC8698437 DOI: 10.3390/biomedicines9121755] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 11/15/2021] [Accepted: 11/20/2021] [Indexed: 01/06/2023] Open
Abstract
Primary cicatricial alopecias (PCA) represent a challenging group of disorders that result in irreversible hair loss from the destruction and fibrosis of hair follicles. Scalp skin biopsies are considered essential in investigating these conditions. Unfortunately, the recognised complexity of histopathologic interpretation is compounded by inadequate sampling and inappropriate laboratory processing. By sharing our successes in developing the communication pathway between the clinician, laboratory and histopathologist, we hope to mitigate some of the difficulties that can arise in managing these conditions. We provide insight from clinical and pathology practice into how diagnoses are derived and the key histological features observed across the most common PCAs seen in practice. Additionally, we highlight the opportunities that have emerged with advances in digital pathology and how these technologies may be used to develop clinicopathological relationships, improve working practices, enhance remote learning, reduce inefficiencies, optimise diagnostic yield, and harness the potential of artificial intelligence (AI).
Collapse
Affiliation(s)
- Donna M. Cummins
- The Dermatology Centre, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Manchester M6 8HD, UK;
| | - Iskander H. Chaudhry
- Department of Pathology, Royal Liverpool University Hospital, Liverpool L7 8XP, UK;
| | - Matthew Harries
- The Dermatology Centre, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Manchester M6 8HD, UK;
- Centre for Dermatology Research, University of Manchester, MAHSC and NIHR Manchester, Biomedical Research Centre, Manchester M13 9WU, UK
- Correspondence:
| |
Collapse
|
35
|
Fraggetta F, L’Imperio V, Ameisen D, Carvalho R, Leh S, Kiehl TR, Serbanescu M, Racoceanu D, Della Mea V, Polonia A, Zerbe N, Eloy C. Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP). Diagnostics (Basel) 2021; 11:2167. [PMID: 34829514 PMCID: PMC8623219 DOI: 10.3390/diagnostics11112167] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/15/2021] [Accepted: 11/19/2021] [Indexed: 12/12/2022] Open
Abstract
The interest in implementing digital pathology (DP) workflows to obtain whole slide image (WSI) files for diagnostic purposes has increased in the last few years. The increasing performance of technical components and the Food and Drug Administration (FDA) approval of systems for primary diagnosis led to increased interest in applying DP workflows. However, despite this revolutionary transition, real world data suggest that a fully digital approach to the histological workflow has been implemented in only a minority of pathology laboratories. The objective of this study is to facilitate the implementation of DP workflows in pathology laboratories, helping those involved in this process of transformation to identify: (a) the scope and the boundaries of the DP transformation; (b) how to introduce automation to reduce errors; (c) how to introduce appropriate quality control to guarantee the safety of the process and (d) the hardware and software needed to implement DP systems inside the pathology laboratory. The European Society of Digital and Integrative Pathology (ESDIP) provided consensus-based recommendations developed through discussion among members of the Scientific Committee. The recommendations are thus based on the expertise of the panel members and on the agreement obtained after virtual meetings. Prior to publication, the recommendations were reviewed by members of the ESDIP Board. The recommendations comprehensively cover every step of the implementation of the digital workflow in the anatomic pathology department, emphasizing the importance of interoperability, automation and tracking of the entire process before the introduction of a scanning facility. Compared to the available national and international guidelines, the present document represents a practical, handy reference for the correct implementation of the digital workflow in Europe.
Collapse
Affiliation(s)
- Filippo Fraggetta
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Pathology Unit, “Gravina” Hospital, Caltagirone, ASP Catania, Via Portosalvo 1, 95041 Caltagirone, Italy
| | - Vincenzo L’Imperio
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Department of Medicine and Surgery, Pathology, ASST Monza, San Gerardo Hospital, University of Milano-Bicocca, 20900 Monza, Italy
| | - David Ameisen
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Imginit SAS, 152 Boulevard du Montparnasse, 75014 Paris, France
| | - Rita Carvalho
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| | - Sabine Leh
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Department of Pathology, Haukeland University Hospital, Jonas Lies Vei 65, 5021 Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Jonas Lies Vei 87, 5021 Bergen, Norway
| | - Tim-Rasmus Kiehl
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| | - Mircea Serbanescu
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Department of Medical Informatics and Biostatistics, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania
| | - Daniel Racoceanu
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Sorbonne Université, Institut du Cerveau—Paris Brain Institute—ICM, Inserm, CNRS, APHP, Inria Team “Aramis”, Hôpital de la Pitié Salpêtrière, 75013 Paris, France
| | - Vincenzo Della Mea
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Department of Mathematics, Computer Science and Physics, University of Udine, 33100 Udine, Italy
| | - Antonio Polonia
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Ipatimup Diagnostics, Institute of Molecular Pathology and Immunology of Porto University (Ipatimup), 4200-804 Porto, Portugal
- Medical Faculty, University of Porto, 4200-319 Porto, Portugal
| | - Norman Zerbe
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| | - Catarina Eloy
- European Society of Digital and Integrative Pathology (ESDIP), Rua da Constituição n°668, 1° Esq/Traseiras, 4200-194 Porto, Portugal; (F.F.); (V.L.); (D.A.); (R.C.); (S.L.); (T.-R.K.); (M.S.); (D.R.); (V.D.M.); (A.P.); (N.Z.)
- Ipatimup Diagnostics, Institute of Molecular Pathology and Immunology of Porto University (Ipatimup), 4200-804 Porto, Portugal
- Medical Faculty, University of Porto, 4200-319 Porto, Portugal
| |
Collapse
|
36
|
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.
Collapse
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
| |
Collapse
|
37
|
Lakhtakia R. Virtual Microscopy in Undergraduate Pathology Education: An early transformative experience in clinical reasoning. Sultan Qaboos Univ Med J 2021; 21:428-435. [PMID: 34522409 PMCID: PMC8407892 DOI: 10.18295/squmj.4.2021.009] [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: 05/22/2020] [Revised: 08/12/2020] [Accepted: 09/10/2020] [Indexed: 11/25/2022] Open
Abstract
Objectives Whole-slide imaging and virtual microscopy (VM) have revolutionised teaching, diagnosis and research in histopathology. This study aimed to establish the feasibility of achieving early integration of clinical reasoning with undergraduate pathology teaching on a VM platform and to determine its student-centricity through student feedback. Methods This study was conducted at the Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates, between August and December 2017. A total of 38 VM-centred clinical cases were introduced to 49 students in an integrated undergraduate medical curriculum. The cases were aligned to curricular objectives, reinforced the pathologic basis of disease with critical thinking and were delivered across 15 interactive small-group sessions. A simulated cross-disciplinary integration and judicious choice of pertinent diagnostic investigations were linked to principles of management. Feedback was obtained through a mixed-methods approach. Results User-friendliness, gradual learning curve of VM and annotation-capacity were scored as 4–5 (on a Likert scale of 1–5) by 91.84%, 87.76% and 83.67% of the participants, respectively. Most students agreed that the content matched the stage of learning (81.63%), theme of the week (91.84%) and development of a strong clinical foundation (77.55%). Integration (85.71%) and clinico-pathological correlation (83.67%) were the strengths of this educational effort. High student attendance (~100%) and improved assessment scores on critical thinking (80%) were observed. Software lacunae included frequent logouts and lack of note-taking tools. Easy access was a significant student-centric advantage. Conclusion A VM-centred approach with a clinico-pathological correlation has been successfully introduced to inculcate integrated learning. Using the pathologic basis of disease as a fulcrum and critical reasoning as an anchor, a digitally-enabled generation of medical students have embraced this educational tool for tutor-guided, student-centred learning.
Collapse
Affiliation(s)
- Ritu Lakhtakia
- Department of Pathology, Mohammed Bin Rashid University of Medicine and Health Sciences, College of Medicine, Dubai, United Arab Emirates
| |
Collapse
|
38
|
Zuraw A, Aeffner F. Whole-slide imaging, tissue image analysis, and artificial intelligence in veterinary pathology: An updated introduction and review. Vet Pathol 2021; 59:6-25. [PMID: 34521285 DOI: 10.1177/03009858211040484] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Since whole-slide imaging has been commercially available for over 2 decades, digital pathology has become a constantly expanding aspect of the pathology profession that will continue to significantly impact how pathologists conduct their craft. While some aspects, such as whole-slide imaging for archiving, consulting, and teaching, have gained broader acceptance, other facets such as quantitative tissue image analysis and artificial intelligence-based assessments are still met with some reservations. While most vendors in this space have focused on diagnostic applications, that is, viewing one or few slides at a time, some are developing solutions tailored more specifically to the various aspects of veterinary pathology including updated diagnostic, discovery, and research applications. This has especially advanced the use of digital pathology in toxicologic pathology and drug development, for primary reads as well as peer reviews. It is crucial that pathologists gain a deeper understanding of digital pathology and tissue image analysis technology and their applications in order to fully use these tools in a way that enhances and improves the pathologist's assessment as well as work environment. This review focuses on an updated introduction to the basics of digital pathology and image analysis and introduces emerging topics around artificial intelligence and machine learning.
Collapse
Affiliation(s)
| | - Famke Aeffner
- Amgen Inc, Amgen Research, South San Francisco, CA, USA
| |
Collapse
|
39
|
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.
Collapse
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
| |
Collapse
|
40
|
Rajaganesan S, Kumar R, Rao V, Pai T, Mittal N, Sahay A, Menon S, Desai S. Comparative Assessment of Digital Pathology Systems for Primary Diagnosis. J Pathol Inform 2021; 12:25. [PMID: 34447605 PMCID: PMC8356707 DOI: 10.4103/jpi.jpi_94_20] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 12/09/2020] [Accepted: 01/14/2021] [Indexed: 11/06/2022] Open
Abstract
Background: Despite increasing interest in whole-slide imaging (WSI) over optical microscopy (OM), limited information on comparative assessment of various digital pathology systems (DPSs) is available. Materials and Methods: A comprehensive evaluation was undertaken to investigate the technical performance–assessment and diagnostic accuracy of four DPSs with an objective to establish the noninferiority of WSI over OM and find out the best possible DPS for clinical workflow. Results: A total of 2376 digital images, 15,775 image reads (OM - 3171 + WSI - 12,404), and 6100 diagnostic reads (OM - 1245, WSI - 4855) were generated across four DPSs (coded as DPS: 1, 2, 3, and 4) using a total 240 cases (604 slides). Onsite technical evaluation revealed successful scan rate: DPS3 < DPS2 < DPS4 < DPS1; mean scanning time: DPS4 < DPS1 < DPS2 < DPS3; and average storage space: DPS3 < DPS2 < DPS1 < DPS4. Overall diagnostic accuracy, when compared with the reference standard for OM and WSI, was 95.44% (including 2.48% minor and 2.08% major discordances) and 93.32% (including 4.28% minor and 2.4% major discordances), respectively. The difference between the clinically significant discordances by WSI versus OM was 0.32%. Major discordances were observed mostly using DPS4 and least in DPS1; however, the difference was statistically insignificant. Almost perfect (κ ≥ 0.8)/substantial (κ = 0.6–0.8) inter/intra-observer agreement between WSI and OM was observed for all specimen types, except cytology. Overall image quality was best for DPS1 followed by DPS4. Mean digital artifact rate was 6.8% (163/2376 digital images) and maximum artifacts were noted in DPS2 (n = 77) followed by DPS3 (n = 36). Most pathologists preferred viewing software of DPS1 and DPS2. Conclusion: WSI was noninferior to OM for all specimen types, except for cytology. Each DPS has its own pros and cons; however, DPS1 closely emulated the real-world clinical environment. This evaluation is intended to provide a roadmap to pathologists for the selection of the appropriate DPSs while adopting WSI.
Collapse
Affiliation(s)
| | - Rajiv Kumar
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Vidya Rao
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Trupti Pai
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Neha Mittal
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Ayushi Sahay
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Santosh Menon
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Sangeeta Desai
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| |
Collapse
|
41
|
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.
Collapse
Affiliation(s)
- Christof A Bertram
- University of Veterinary Medicine, Vienna, Austria.,Freie Universität Berlin, Berlin, Germany
| | | | | | | | | | | | | | | | | |
Collapse
|
42
|
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.
Collapse
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
| |
Collapse
|
43
|
Schüffler PJ, Geneslaw L, Yarlagadda DVK, Hanna MG, Samboy J, Stamelos E, Vanderbilt C, Philip J, Jean MH, Corsale L, Manzo A, Paramasivam NHG, Ziegler JS, Gao J, Perin JC, Kim YS, Bhanot UK, Roehrl MHA, Ardon O, Chiang S, Giri DD, Sigel CS, Tan LK, Murray M, Virgo C, England C, Yagi Y, Sirintrapun SJ, Klimstra D, Hameed M, Reuter VE, Fuchs TJ. Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center. J Am Med Inform Assoc 2021; 28:1874-1884. [PMID: 34260720 PMCID: PMC8344580 DOI: 10.1093/jamia/ocab085] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 03/25/2021] [Accepted: 05/04/2021] [Indexed: 02/07/2023] Open
Abstract
OBJECTIVE Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes. MATERIALS AND METHODS We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent. RESULTS The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases. CONCLUSIONS We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.
Collapse
Affiliation(s)
- Peter J Schüffler
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Institute of Pathology, Technical University of Munich, Munich, Germany
| | - Luke Geneslaw
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - D Vijay K Yarlagadda
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Matthew G Hanna
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Jennifer Samboy
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Evangelos Stamelos
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Chad Vanderbilt
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - John Philip
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Health Informatics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Marc-Henri Jean
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Lorraine Corsale
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Allyne Manzo
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Neeraj H G Paramasivam
- Department of Information Systems, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - John S Ziegler
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Jianjiong Gao
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Juan C Perin
- Department of Information Systems, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Young Suk Kim
- School of Medicine, Stanford University, Stanford, California, USA
| | - Umeshkumar K Bhanot
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Michael H A Roehrl
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Orly Ardon
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Sarah Chiang
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Dilip D Giri
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Carlie S Sigel
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Lee K Tan
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Melissa Murray
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Christina Virgo
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Christine England
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Yukako Yagi
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - S Joseph Sirintrapun
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - David Klimstra
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Meera Hameed
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Victor E Reuter
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Thomas J Fuchs
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| |
Collapse
|
44
|
Katare P, Gorthi SS. Recent technical advances in whole slide imaging instrumentation. J Microsc 2021; 284:103-117. [PMID: 34254690 DOI: 10.1111/jmi.13049] [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: 03/20/2021] [Revised: 07/05/2021] [Accepted: 07/06/2021] [Indexed: 11/28/2022]
Abstract
Microscopic observation of biological specimen smears is the mainstay of diagnostic pathology, as defined by the Digital Pathology Association. Though automated systems for this are commercially available, their bulky size and high cost renders them unusable for remote areas. The research community is investing much effort towards building equivalent but portable, low-cost systems. An overview of such research is presented here, including a comparative analysis of recent reports. This paper also reviews recently reported systems for automated staining and smear formation, including microfluidic devices; and optical and computational automated microscopy systems including smartphone-based devices. Image pre-processing and analysis methods for automated diagnosis are also briefly discussed. It concludes with a set of foreseeable research directions that could lead to affordable, integrated and accurate whole slide imaging systems.
Collapse
Affiliation(s)
- Prateek Katare
- Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, India
| | - Sai Siva Gorthi
- Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, India
| |
Collapse
|
45
|
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: 35] [Impact Index Per Article: 11.7] [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.
Collapse
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
| |
Collapse
|
46
|
Bodén ACS, Molin J, Garvin S, West RA, Lundström C, Treanor D. The human-in-the-loop: an evaluation of pathologists' interaction with artificial intelligence in clinical practice. Histopathology 2021; 79:210-218. [PMID: 33590577 DOI: 10.1111/his.14356] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 01/24/2021] [Accepted: 02/14/2021] [Indexed: 12/21/2022]
Abstract
AIMS One of the major drivers of the adoption of digital pathology in clinical practice is the possibility of introducing digital image analysis (DIA) to assist with diagnostic tasks. This offers potential increases in accuracy, reproducibility, and efficiency. Whereas stand-alone DIA has great potential benefit for research, little is known about the effect of DIA assistance in clinical use. The aim of this study was to investigate the clinical use characteristics of a DIA application for Ki67 proliferation assessment. Specifically, the human-in-the-loop interplay between DIA and pathologists was studied. METHODS AND RESULTS We retrospectively investigated breast cancer Ki67 areas assessed with human-in-the-loop DIA and compared them with visual and automatic approaches. The results, expressed as standard deviation of the error in the Ki67 index, showed that visual estimation ('eyeballing') (14.9 percentage points) performed significantly worse (P < 0.05) than DIA alone (7.2 percentage points) and DIA with human-in-the-loop corrections (6.9 percentage points). At the overall level, no improvement resulting from the addition of human-in-the-loop corrections to the automatic DIA results could be seen. For individual cases, however, human-in-the-loop corrections could address major DIA errors in terms of poor thresholding of faint staining and incorrect tumour-stroma separation. CONCLUSION The findings indicate that the primary value of human-in-the-loop corrections is to address major weaknesses of a DIA application, rather than fine-tuning the DIA quantifications.
Collapse
Affiliation(s)
- Anna C S Bodén
- Department of Clinical Pathology, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.,Centre for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | | | - Stina Garvin
- Department of Clinical Pathology, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Rebecca A West
- Leeds Teaching Hospitals NHS Trust, Leeds, UK.,Department of Histopathology, Dewsbury and District Hospital, Dewsbury, UK
| | - Claes Lundström
- Centre for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.,Sectra AB, Linköping, Sweden
| | - Darren Treanor
- Department of Clinical Pathology, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.,Centre for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.,Leeds Teaching Hospitals NHS Trust, Leeds, UK.,Pathology and Data Analytics, University of Leeds, Leeds, UK
| |
Collapse
|
47
|
Gavrielides MA, Ronnett BM, Vang R, Sheikhzadeh F, Seidman JD. Selection of Representative Histologic Slides in Interobserver Reproducibility Studies: Insights from Expert Review for Ovarian Carcinoma Subtype Classification. J Pathol Inform 2021; 12:15. [PMID: 34012719 PMCID: PMC8112350 DOI: 10.4103/jpi.jpi_56_20] [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: 06/25/2020] [Revised: 09/02/2020] [Accepted: 10/28/2020] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Observer studies in pathology often utilize a limited number of representative slides per case, selected and reported in a nonstandardized manner. Reference diagnoses are commonly assumed to be generalizable to all slides of a case. We examined these issues in the context of pathologist concordance for histologic subtype classification of ovarian carcinomas (OCs). MATERIALS AND METHODS A cohort of 114 OCs consisting of 72 cases with a single representative slide (Group 1) and 42 cases with multiple representative slides (148 slides, 2-6 sections per case, Group 2) was independently reviewed by three experts in gynecologic pathology (case-based review). In a follow-up study, each individual slide was independently reviewed in a randomized order by the same pathologists (section-based review). RESULTS Average interobserver concordance varied from 100% for Group 1 to 64.3% for Group 2 (86.8% across all cases). Across Group 2, 19 cases (45.2%) had at least one slide classified as a different subtype than the subtype assigned from case-based review, demonstrating the impact of intratumoral heterogeneity. Section-based concordance across individual sections from Group 2 was comparable to case-based concordance for those cases indicating diagnostic challenges at the individual section level. Findings demonstrate the increased diagnostic complexity of heterogeneous tumors that require multiple section sampling and its impact on pathologist performance. CONCLUSIONS The proportion of cases with multiple representative slides in cohorts used in validation studies, such as those conducted to evaluate artificial intelligence/machine learning tools, can influence diagnostic performance, and if not accounted for, can cause disparities between research and real-world observations and between research studies. Case selection in validation studies should account for tumor heterogeneity to create balanced datasets in terms of diagnostic complexity.
Collapse
Affiliation(s)
- Marios A. Gavrielides
- Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA, (Currently at AstraZeneca, Precision Medicine and Biosamples, Gaithersburg, Maryland, USA)
| | - Brigitte M. Ronnett
- Department of Pathology and Gynecology and Obstetrics, The Johns Hopkins Hospital, Baltimore, Maryland, USA
| | - Russell Vang
- Department of Pathology and Gynecology and Obstetrics, The Johns Hopkins Hospital, Baltimore, Maryland, USA
| | - Fahime Sheikhzadeh
- Electrical and Computer Engineering Department, University of British Columbia, Vancouver, Canada, (Currently at Roche Diagnostics, San Francisco, California, USA)
| | - Jeffrey D Seidman
- Division of Molecular Genetics and Pathology, Office of In Vitro Diagnostics and Radiological Health, Office of Product Evaluation and Quality, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| |
Collapse
|
48
|
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.
Collapse
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
| |
Collapse
|
49
|
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 ![]()
Collapse
|
50
|
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.
Collapse
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
| |
Collapse
|