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Marletta S, Pantanowitz L, Santonicco N, Caputo A, Bragantini E, Brunelli M, Girolami I, Eccher A. Response to Letter to the Editor: "Remote Placental Sign-Out: What Digital Pathology Can Offer for Pediatric Pathologists". Pediatr Dev Pathol 2024; 27:377-378. [PMID: 38468494 DOI: 10.1177/10935266231225791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Affiliation(s)
- Stefano Marletta
- Division of Pathology, Humanitas Istituto Clinico Catanese, Catania, Italy
- Section of Pathology, Department of Pathology and Diagnostics, University Hospital of Verona, Verona, Italy
| | - Liron Pantanowitz
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Nicola Santonicco
- Section of Pathology, Department of Pathology and Diagnostics, 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, Trentino-Alto Adige, Italy
| | - Matteo Brunelli
- Section of Pathology, Department of Pathology and Diagnostics, University Hospital of Verona, Verona, Italy
| | - Ilaria Girolami
- Division of Pathology, Central Hospital Bolzano, Bolzano, Trentino-Alto Adige, Italy
| | - Albino Eccher
- Section of Pathology, Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, Modena, Emilia-Romagna, Italy
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Munari E, Scarpa A, Cima L, Pozzi M, Pagni F, Vasuri F, Marletta S, Dei Tos AP, Eccher A. Cutting-edge technology and automation in the pathology laboratory. Virchows Arch 2024; 484:555-566. [PMID: 37930477 PMCID: PMC11062949 DOI: 10.1007/s00428-023-03637-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/18/2023] [Accepted: 08/25/2023] [Indexed: 11/07/2023]
Abstract
One of the goals of pathology is to standardize laboratory practices to increase the precision and effectiveness of diagnostic testing, which will ultimately enhance patient care and results. Standardization is crucial in the domains of tissue processing, analysis, and reporting. To enhance diagnostic testing, innovative technologies are also being created and put into use. Furthermore, although problems like algorithm training and data privacy issues still need to be resolved, digital pathology and artificial intelligence are emerging in a structured manner. Overall, for the field of pathology to advance and for patient care to be improved, standard laboratory practices and innovative technologies must be adopted. In this paper, we describe the state-of-the-art of automation in pathology laboratories in order to lead technological progress and evolution. By anticipating laboratory needs and demands, the aim is to inspire innovation tools and processes as positively transformative support for operators, organizations, and patients.
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Affiliation(s)
- Enrico Munari
- Pathology Unit, Department of Molecular and Translational Medicine, University of Brescia, Piazza Del Mercato, 15, 25121, Brescia, BS, Italy.
| | - Aldo Scarpa
- Pathology Unit, Department of Diagnostics and Public Health, University of Verona, Verona, Italy.
| | - Luca Cima
- Pathology Unit, Department of Laboratory Medicine, Santa Chiara Hospital, APSS, Trento, Italy
| | - Matteo Pozzi
- Bruno Kessler Foundation, Trento, Italy
- University of Trento, CIBIO Department, Trento, Italy
| | - Fabio Pagni
- Pathology Unit, Department of Medicine and Surgery, University of Milano-Bicocca, IRCCS Fondazione San Gerardo Dei Tintori, Monza, Italy
| | - Francesco Vasuri
- Pathology Unit, IRCCS, Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy
| | - Stefano Marletta
- Pathology Unit, Department of Diagnostics and Public Health, University of Verona, Verona, Italy
- Department of Pathology, Pederzoli Hospital, Peschiera del Garda, Italy
| | - Angelo Paolo Dei Tos
- Surgical Pathology and Cytopathology Unit, Department of Medicine-DIMED, University of Padua School of Medicine, Padua, Italy
| | - Albino Eccher
- Section of Pathology, Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, Modena, Italy
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Begum NF, Ramalingam K, Ramani P. Storage, Retention, and Use of Leftover Pathology Specimens: The Underestimated Treasures. Cureus 2024; 16:e53025. [PMID: 38410328 PMCID: PMC10895552 DOI: 10.7759/cureus.53025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/26/2024] [Indexed: 02/28/2024] Open
Abstract
The proper regulations for storage, retention, and use of archived specimens in pathology laboratories and academic institutions are yet to be established. These specimens could be used appropriately for research purposes. Ideal storage and retention in a controlled environment is necessary, and there is a lack of established rules regarding the ownership of the tissue specimens, paraffin blocks, and slides. Though there are numerous uses of formalin-fixed tissue specimens, blocks, and slides, there are also problems in archiving them that hinder their use. This review article addresses the above issues and proposes simple guidelines for the effective use of archived specimens.
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Affiliation(s)
- N Fazulunnisa Begum
- Oral Pathology and Microbiology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Karthikeyan Ramalingam
- Oral Pathology and Microbiology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Pratibha Ramani
- Oral Pathology and Microbiology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
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Cazzaniga G, Eccher A, Munari E, Marletta S, Bonoldi E, Della Mea V, Cadei M, Sbaraglia M, Guerriero A, Dei Tos AP, Pagni F, L’Imperio V. Natural Language Processing to extract SNOMED-CT codes from pathological reports. Pathologica 2023; 115:318-324. [PMID: 38180139 PMCID: PMC10767798 DOI: 10.32074/1591-951x-952] [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: 11/16/2023] [Accepted: 11/17/2023] [Indexed: 01/06/2024] Open
Abstract
Objective The use of standardized structured reports (SSR) and suitable terminologies like SNOMED-CT can enhance data retrieval and analysis, fostering large-scale studies and collaboration. However, the still large prevalence of narrative reports in our laboratories warrants alternative and automated labeling approaches. In this project, natural language processing (NLP) methods were used to associate SNOMED-CT codes to structured and unstructured reports from an Italian Digital Pathology Department. Methods Two NLP-based automatic coding systems (support vector machine, SVM, and long-short term memory, LSTM) were trained and applied to a series of narrative reports. Results The 1163 cases were tested with both algorithms, showing good performances in terms of accuracy, precision, recall, and F1 score, with SVM showing slightly better performances as compared to LSTM (0.84, 0.87, 0.83, 0.82 vs 0.83, 0.85, 0.83, 0.82, respectively). The integration of an explainability allowed identification of terms and groups of words of importance, enabling fine-tuning, balancing semantic meaning and model performance. Conclusions AI tools allow the automatic SNOMED-CT labeling of the pathology archives, providing a retrospective fix to the large lack of organization of narrative reports.
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Affiliation(s)
- Giorgio Cazzaniga
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Italy
| | - Albino Eccher
- Section of Pathology, Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, Modena, Italy
| | - Enrico Munari
- Department of Diagnostic and Public Health, Section of Pathology, University of Verona, Verona, Italy
| | - Stefano Marletta
- Department of Diagnostic and Public Health, Section of Pathology, University of Verona, Verona, Italy
| | - Emanuela Bonoldi
- Unit of Surgical Pathology and Cytogenetics, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Vincenzo Della Mea
- Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy
| | - Moris Cadei
- Pathology Unit, ASST Spedali Civili di Brescia, Brescia, Italy
| | - Marta Sbaraglia
- Surgical Pathology and Cytopathology Unit, Department of Medicine-DIMED, University of Padua School of Medicine, Padua, Italy
| | - Angela Guerriero
- Surgical Pathology and Cytopathology Unit, Department of Medicine-DIMED, University of Padua School of Medicine, Padua, Italy
| | - Angelo Paolo Dei Tos
- Surgical Pathology and Cytopathology Unit, Department of Medicine-DIMED, University of Padua School of Medicine, Padua, Italy
| | - Fabio Pagni
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Italy
| | - Vincenzo L’Imperio
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Italy
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Eccher A, Dei Tos AP, Scarpa A, L'Imperio V, Munari E, Troncone G, Naccarato AG, Seminati D, Pagni F. Cost analysis of archives in the pathology laboratories: from safety to management. J Clin Pathol 2023; 76:659-663. [PMID: 37532289 PMCID: PMC10511949 DOI: 10.1136/jcp-2023-209035] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 07/26/2023] [Indexed: 08/04/2023]
Abstract
CONTEXT Despite the reluctance to invest and the challenging estimation of necessary supporting costs, optimising the archives seems to be one of the hottest topics in the future management of the pathology laboratories. Historically, archives were only partially designed to securely store and organise tissue specimens, and tracking systems were often flawed, posing significant risks to patients' health and legal ramifications for pathologists. OBJECTIVE The current review explores the available data from the literature on archives' management in pathology, including comprehensive business plans, structure setup, outfit, inventories, ongoing conservation and functional charges. DATA SOURCES Electronic searches in PubMed-MEDLINE and Embase were made to extract pertinent articles from the literature. Works about the archiving process and storage were included and analysed to extract information. Prepublication servers were ignored. Italian Institutional Regional databases for public competitive bidding processes were queried too. CONCLUSIONS A new emergent feeling in the pathology laboratory is growing for archives management; the digital pathology era is a great opportunity to apply innovation to tracking systems and samples preservation. The main aim is a critical evaluation of the return of investment in developing automatic and tracked archiving processes for improving not only quality, efficacy and efficiency of the labs but also patients' healthcare.
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Affiliation(s)
- Albino Eccher
- Department of Diagnostics and Public Health, Università degli Studi di Verona, Verona, Italy
| | | | - Aldo Scarpa
- Department of Diagnostics and Public Health, Università degli Studi di Verona, Verona, Italy
| | - Vincenzo L'Imperio
- Department of Medicine and Surgery, Pathology, University of Milan-Bicocca, Milano, Italy
| | - Enrico Munari
- Department of Pathology, University of Brescia, Brescia, Italy
| | - Giancarlo Troncone
- Public Health, University of Naples Federico II School of Medicine and Surgery, Napoli, Italy
| | | | - Davide Seminati
- Department of Medicine and Surgery, Pathology, University of Milan-Bicocca, Milano, Italy
| | - Fabio Pagni
- Department of Medicine and Surgery, Pathology, University of Milan-Bicocca, Milano, Italy
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Frascarelli C, Bonizzi G, Musico CR, Mane E, Cassi C, Guerini Rocco E, Farina A, Scarpa A, Lawlor R, Reggiani Bonetti L, Caramaschi S, Eccher A, Marletta S, Fusco N. Revolutionizing Cancer Research: The Impact of Artificial Intelligence in Digital Biobanking. J Pers Med 2023; 13:1390. [PMID: 37763157 PMCID: PMC10532470 DOI: 10.3390/jpm13091390] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/05/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND Biobanks are vital research infrastructures aiming to collect, process, store, and distribute biological specimens along with associated data in an organized and governed manner. Exploiting diverse datasets produced by the biobanks and the downstream research from various sources and integrating bioinformatics and "omics" data has proven instrumental in advancing research such as cancer research. Biobanks offer different types of biological samples matched with rich datasets comprising clinicopathologic information. As digital pathology and artificial intelligence (AI) have entered the precision medicine arena, biobanks are progressively transitioning from mere biorepositories to integrated computational databanks. Consequently, the application of AI and machine learning on these biobank datasets holds huge potential to profoundly impact cancer research. METHODS In this paper, we explore how AI and machine learning can respond to the digital evolution of biobanks with flexibility, solutions, and effective services. We look at the different data that ranges from specimen-related data, including digital images, patient health records and downstream genetic/genomic data and resulting "Big Data" and the analytic approaches used for analysis. RESULTS These cutting-edge technologies can address the challenges faced by translational and clinical research, enhancing their capabilities in data management, analysis, and interpretation. By leveraging AI, biobanks can unlock valuable insights from their vast repositories, enabling the identification of novel biomarkers, prediction of treatment responses, and ultimately facilitating the development of personalized cancer therapies. CONCLUSIONS The integration of biobanking with AI has the potential not only to expand the current understanding of cancer biology but also to pave the way for more precise, patient-centric healthcare strategies.
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Affiliation(s)
- Chiara Frascarelli
- Division of Pathology, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy; (C.F.); (E.M.); (E.G.R.); (N.F.)
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
| | - Giuseppina Bonizzi
- Biobank for Translational and Digital Medicine, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy; (G.B.); (C.R.M.); (C.C.)
| | - Camilla Rosella Musico
- Biobank for Translational and Digital Medicine, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy; (G.B.); (C.R.M.); (C.C.)
| | - Eltjona Mane
- Division of Pathology, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy; (C.F.); (E.M.); (E.G.R.); (N.F.)
| | - Cristina Cassi
- Biobank for Translational and Digital Medicine, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy; (G.B.); (C.R.M.); (C.C.)
| | - Elena Guerini Rocco
- Division of Pathology, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy; (C.F.); (E.M.); (E.G.R.); (N.F.)
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
| | - Annarosa Farina
- Central Information Systems and Technology Directorate, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy;
| | - Aldo Scarpa
- Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37134 Verona, Italy; (A.S.); (S.M.)
| | - Rita Lawlor
- ARC-Net Research Centre and Department of Diagnostics and Public Health, University of Verona, 37134 Verona, Italy;
| | - Luca Reggiani Bonetti
- Section of Pathology, Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, 41121 Modena, Italy; (L.R.B.); (S.C.)
| | - Stefania Caramaschi
- Section of Pathology, Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, 41121 Modena, Italy; (L.R.B.); (S.C.)
| | - Albino Eccher
- Section of Pathology, Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, 41121 Modena, Italy; (L.R.B.); (S.C.)
| | - Stefano Marletta
- Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37134 Verona, Italy; (A.S.); (S.M.)
- Division of Pathology, Humanitas Cancer Center, 95045 Catania, Italy
| | - Nicola Fusco
- Division of Pathology, IEO, European Institute of Oncology IRCCS, 20139 Milan, Italy; (C.F.); (E.M.); (E.G.R.); (N.F.)
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
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