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Eccher A, L'Imperio V, Pantanowitz L, Cazzaniga G, Del Carro F, Marletta S, Gambaro G, Barreca A, Becker JU, Gobbo S, Della Mea V, Alberici F, Pagni F, Dei Tos AP. Galileo-an Artificial Intelligence tool for evaluating pre-implantation kidney biopsies. J Nephrol 2024:10.1007/s40620-024-02094-4. [PMID: 39356416 DOI: 10.1007/s40620-024-02094-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Accepted: 08/25/2024] [Indexed: 10/03/2024]
Abstract
BACKGROUND Pre-transplant procurement biopsy interpretation is challenging, also because of the low number of renal pathology experts. Artificial intelligence (AI) can assist by aiding pathologists with kidney donor biopsy assessment. Herein we present the "Galileo" AI tool, designed specifically to assist the on-call pathologist with interpreting pre-implantation kidney biopsies. METHODS A multicenter cohort of whole slide images acquired from core-needle and wedge biopsies of the kidney was collected. A deep learning algorithm was trained to detect the main findings evaluated in the pre-implantation setting (normal glomeruli, globally sclerosed glomeruli, ischemic glomeruli, arterioles and arteries). The model obtained on the Aiforia Create platform was validated on an external dataset by three independent pathologists to evaluate the performance of the algorithm. RESULTS Galileo demonstrated a precision, sensitivity, F1 score and total area error of 81.96%, 94.39%, 87.74%, 2.81% and 74.05%, 71.03%, 72.5%, 2% in the training and validation sets, respectively. Galileo was significantly faster than pathologists, requiring 2 min overall in the validation phase (vs 25, 22 and 31 min by 3 separate human readers, p < 0.001). Galileo-assisted detection of renal structures and quantitative information was directly integrated in the final report. CONCLUSIONS The Galileo AI-assisted tool shows promise in speeding up pre-implantation kidney biopsy interpretation, as well as in reducing inter-observer variability. This tool may represent a starting point for further improvements based on hard endpoints such as graft survival.
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Affiliation(s)
- Albino Eccher
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, Modena, Italy
| | - Vincenzo L'Imperio
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Monza, Italy.
| | - Liron Pantanowitz
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Giorgio Cazzaniga
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Monza, Italy
| | - Fabio Del Carro
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Monza, Italy
| | | | - Giovanni Gambaro
- Division of Nephrology, Department of Medicine, University of Verona, Verona, Italy
| | - Antonella Barreca
- Pathology Unit, Città della Salute e della Scienza di Torino University Hospital, Turin, Italy
| | - Jan Ulrich Becker
- Institute of Pathology, University Hospital of Cologne, Cologne, Germany
| | - Stefano Gobbo
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy
| | - Vincenzo Della Mea
- Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy
| | - Federico Alberici
- Division of Nephrology and Dialysis, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia and ASST-Spedali Civili of Brescia, Brescia, Italy
| | - Fabio Pagni
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Monza, Italy
| | - Angelo Paolo Dei Tos
- Surgical Pathology and Cytopathology Unit, Department of Medicine-DIMED, University of Padua School of Medicine, Padua, Italy
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Proffer SL, Reinhart J, Ridgeway JL, Barry B, Kamath C, Gerdes EW, Todd A, Cervenka DJ, DiCaudo DJ, Sokumbi O, Johnson EF, Peters MS, Wieland CN, Comfere NI. Digital dermatopathology implementation: Experience at a multisite academic institution. J Cutan Pathol 2024; 51:696-704. [PMID: 38783791 DOI: 10.1111/cup.14629] [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: 01/08/2024] [Revised: 04/01/2024] [Accepted: 04/13/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Technology has revolutionized not only direct patient care but also diagnostic care processes. This study evaluates the transition from glass-slide microscopy to digital pathology (DP) at a multisite academic institution, using mixed methods to understand user perceptions of digitization and key productivity metrics of practice change. METHODS Participants included dermatopathologists, pathology reporting specialists, and clinicians. Electronic surveys and individual or group interviews included questions related to technology comfort, trust in DP, and rationale for DP adoption. Case volumes and turnaround times were abstracted from the electronic health record from Qtr 4 2020 to Qtr 1 2023 (inclusive). Data were analyzed descriptively, while interviews were analyzed using methods of content analysis. RESULTS Thirty-four staff completed surveys and 22 participated in an interview. Case volumes and diagnostic turnaround time did not differ across the institution during or after implementation timelines (p = 0.084; p = 0.133, respectively). 82.5% (28/34) of staff agreed that DP improved the sign-out experience, with accessibility, ergonomics, and annotation features described as key factors. Clinicians reported positive perspectives of DP impact on patient safety and interdisciplinary collaboration. CONCLUSIONS Our study demonstrates that DP has a high acceptance rate, does not adversely impact productivity, and may improve patient safety and care collaboration.
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Affiliation(s)
- Sydney L Proffer
- Department of Dermatology, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Jacob Reinhart
- Department of Dermatology, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Jennifer L Ridgeway
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Barbara Barry
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Celia Kamath
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Erin Wissler Gerdes
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Austin Todd
- Division of Clinical Trials and Biostatistics of the Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Derek J Cervenka
- Department of Dermatology, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - David J DiCaudo
- Department of Dermatology, Mayo Clinic, Scottsdale, Arizona, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Arizona, USA
| | | | - Emma F Johnson
- Department of Dermatology, Mayo Clinic Rochester, Rochester, Minnesota, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Margot S Peters
- Department of Dermatology, Mayo Clinic Rochester, Rochester, Minnesota, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Carilyn N Wieland
- Department of Dermatology, Mayo Clinic Rochester, Rochester, Minnesota, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Nneka I Comfere
- Department of Dermatology, Mayo Clinic Rochester, Rochester, Minnesota, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
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3
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Jain E, Patel A, Parwani AV, Shafi S, Brar Z, Sharma S, Mohanty SK. Whole Slide Imaging Technology and Its Applications: Current and Emerging Perspectives. Int J Surg Pathol 2024; 32:433-448. [PMID: 37437093 DOI: 10.1177/10668969231185089] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Abstract
Background. Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. It utilizes virtual microscopy wherein glass slides are converted into digital slides and are viewed by pathologists by automated image analysis. Its impact on pathology workflow, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and institutional collaboration exemplifies a significant innovative movement. The recent US Food and Drug Administration approval to WSI for its use in primary surgical pathology diagnosis has opened opportunities for wider application of this technology in routine practice. Main Text. The ongoing technological advances in digital scanners, image visualization methods, and the integration of artificial intelligence-derived algorithms with these systems provide avenues to exploit its applications. Its benefits are innumerable such as ease of access through the internet, avoidance of physical storage space, and no risk of deterioration of staining quality or breakage of slides to name a few. Although the benefits of WSI to pathology practices are many, the complexities of implementation remain an obstacle to widespread adoption. Some barriers including the high cost, technical glitches, and most importantly professional hesitation to adopt a new technology have hindered its use in routine pathology. Conclusions. In this review, we summarize the technical aspects of WSI, its applications in diagnostic pathology, training, and research along with future perspectives. It also highlights improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology. WSI provides a golden opportunity for pathologists to guide its evolution, standardization, and implementation to better acquaint them with the key aspects of this technology and its judicial use. Also, implementation of routine digital pathology is an extra step requiring resources which (currently) does not usually result increased efficiency or payment.
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Affiliation(s)
- Ekta Jain
- Department of Pathology and Laboratory Medicine, CORE Diagnostics, Gurgaon, India
| | - Ankush Patel
- Department of Pathology, Wexner Medical Center, Columbus, OH, USA
| | - Anil V Parwani
- Department of Pathology, Wexner Medical Center, Columbus, OH, USA
| | - Saba Shafi
- Department of Pathology, Wexner Medical Center, Columbus, OH, USA
| | - Zoya Brar
- Department of Pathology and Laboratory Medicine, CORE Diagnostics, Gurgaon, India
| | - Shivani Sharma
- Department of Pathology and Laboratory Medicine, CORE Diagnostics, Gurgaon, India
| | - Sambit K Mohanty
- Department of Pathology and Laboratory Medicine, CORE Diagnostics, Gurgaon, India
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Eccher A, Becker JU, Pagni F, Cazzaniga G, Rossi M, Gambaro G, L’Imperio V, Marletta S. The Puzzle of Preimplantation Kidney Biopsy Decision-Making Process: The Pathologist Perspective. Life (Basel) 2024; 14:254. [PMID: 38398762 PMCID: PMC10890315 DOI: 10.3390/life14020254] [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: 01/11/2024] [Revised: 02/11/2024] [Accepted: 02/13/2024] [Indexed: 02/25/2024] Open
Abstract
Kidney transplantation is the best treatment for end-stage renal disease since it offers the greatest survival benefit compared to dialysis. The gap between the number of renal transplants performed and the number of patients awaiting renal transplants leads to a steadily increasing pressure on the scientific community. Kidney preimplantation biopsy is used as a component of the evaluation of organ quality before acceptance for transplantation. However, the reliability and predictive value of biopsy data are controversial. Most of the previously proposed predictive models were not associated with graft survival, but what has to be reaffirmed is that histologic examination of kidney tissue can provide an objective window on the state of the organ that cannot be deduced from clinical records and renal functional studies. The balance of evidence indicates that reliable decisions about donor suitability must be made based on the overall picture. This work discusses recent trends that can reduce diagnostic timing and variability among players in the decision-making process that lead to kidney transplants, from the pathologist's perspective.
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Affiliation(s)
- Albino Eccher
- Department of Medical and Sciences for Children and Adults, University of Modena and Reggio Emilia, University Hospital of Modena, 41100 Modena, Italy
| | - Jan Ulrich Becker
- Institute of Pathology, University Hospital of Cologne, 50923 Cologne, Germany;
| | - Fabio Pagni
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, 20126 Milano, Italy; (F.P.); (G.C.); (V.L.)
| | - Giorgio Cazzaniga
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, 20126 Milano, Italy; (F.P.); (G.C.); (V.L.)
| | - Mattia Rossi
- Division of Nephrology, Department of Medicine, University of Verona, 37129 Verona, Italy; (M.R.); (G.G.)
| | - Giovanni Gambaro
- Division of Nephrology, Department of Medicine, University of Verona, 37129 Verona, Italy; (M.R.); (G.G.)
| | - Vincenzo L’Imperio
- Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, 20126 Milano, Italy; (F.P.); (G.C.); (V.L.)
| | - Stefano Marletta
- Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37129 Verona, Italy;
- Division of Pathology, Humanitas Istituto Clinico Catanese, 95045 Catania, Italy
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Caliò A, Barreca A, Marletta S, Achenza MIS, Alessi M, Angelico R, Apicella L, Argiolas D, Bossini N, Carrano R, Carriero C, Castellano G, Comai G, Di Bella C, D’Ignoto F, Gallico A, Gastaldon F, Merlotti G, Paloschi V, Panarese A, Parodi A, Perna F, Picciotto D, Regalia A, Rossini M, Russo E, Salerno MP, Toti L, Tulissi P, Vischini G, Zaza G, Eccher A. Histology for nephrology, from pre-implantation to post-transplant kidney biopsy. Lesson learned from ReBIrth (Renal BIopsy for Kidney Transplantation Therapy). Pathologica 2023; 115:199-204. [PMID: 37314869 PMCID: PMC10688244 DOI: 10.32074/1591-951x-858] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 06/06/2023] [Indexed: 06/16/2023] Open
Abstract
A meeting entitled Renal BIopsy for Kidney Transplantation Therapy (ReBIrth) took place on May 31st, 2022 in Bologna, Italy. The meeting drew together nephrologists, surgeons, and pathologists and recognized as experts in the field of kidney transplantation in Italy. In this paper, we present our experience working with kidney transplants in the current era of immunosuppression therapy. The primary aim is to report the histopathological characteristics of failed kidney allografts after a consensus of experts reviewed the cases on a wholeslide imaging digital platform. Regardless of the cases discussed, digital pathology was reliable in identifying all the morphological and immunohistochemical features required to improve the correct use of immunosuppressive therapy to prevent graft failure and optimize patient management.
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Affiliation(s)
- Anna Caliò
- Department of Diagnostic and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | - Antonella Barreca
- Pathology Unit, “Città della Salute e della Scienza di Torino” University Hospital, Turin, Italy
| | - Stefano Marletta
- Department of Diagnostic and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
- Department of Pathology, Pederzoli Hospital, Peschiera del Garda, Italy
| | | | - Marianna Alessi
- Department of Medicine, Nephrology, University of Padova, Padova, Italy
| | - Roberta Angelico
- Department of Surgical Sciences, HPB and Transplant Unit, University of Rome Tor Vergata, Roma Italy
| | - Luca Apicella
- Division of Nephrology, Dialysis and Renal Transplantation, University Hospital “San Giovanni di Dio e Ruggi d’Aragona”, Salerno, Italy
| | - Davide Argiolas
- Renal Transplant Unit, Azienda Ospedaliera Brotzu, Cagliari, Italy
| | - Nicola Bossini
- Division of Nephrology and Dialysis, ASST Spedali Civili, Brescia, Italy
| | - Rosa Carrano
- UOSD Nefrologia e Trapianto Renale, Dipartimento di Chirurgia Generale e Chirurgie Specialistiche dei Trapianti di Rene, Nefrologia, Cure Intensive e del Dolore, Azienda Ospedaliera Universitaria Federico II, Napoli, Italy
| | | | - Giuseppe Castellano
- Nephrology, Dialysis and Transplantation, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Giorgia Comai
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Caterina Di Bella
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, University of Padua, Padua, Italy
| | | | - Agnese Gallico
- Division of Nephrology and Dialysis, ASST Spedali Civili, Brescia, Italy
| | - Fiorella Gastaldon
- Unità Operativa Complessa di Nefrologia, Dialisi e Trapianto Renale, AULSS8 Berica, Ospedale San Bortolo, Vicenza, Italy
| | - Guido Merlotti
- Nephrology and Kidney Transplantation Unit, Department of Translational Medicine, University of Piemonte Orientale (UPO), “Maggiore della Carità” University Hospital, Novara, Italy
| | - Vera Paloschi
- Transplant Medicine Unit, Department of Internal Medicine, IRCCS San Raffaele Hospital, Milano, Italy
| | - Alessandra Panarese
- Department of Biotechnological and Applied Clinical Sciences (DISCAB), University of L’Aquila, L’Aquila, Italy
| | - Angelica Parodi
- Unit of Nephrology Dialysis and Transplantation, Department of Internal Medicine, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Francesco Perna
- Fondazione Policlinico A. Gemelli – UOS Trapianti di Rene, Roma, Italy
| | - Daniela Picciotto
- Unit of Nephrology Dialysis and Transplantation, Department of Internal Medicine, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Anna Regalia
- Nephrology, Dialysis and Transplantation, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Michele Rossini
- Nephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
| | - Enrico Russo
- General Surgery and Kidney Transplantation Unit, “OO.RR. San Giovanni di Dio e Ruggi d’Aragona” University Hospital, Salerno, Italy
| | | | - Luca Toti
- Transplant and HPB Unit, Department of Surgical Sciences, University of Rome Tor Vergata, Rome, Italy
| | - Patrizia Tulissi
- Unità complessa di Nefrologia, Dialisi e Trapianto, Udine, Italy
| | - Gisella Vischini
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Gianluigi Zaza
- Nephrology, Dialysis and Transplantation Unit, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy
| | - Albino Eccher
- Department of Diagnostic and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
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Zaza G, Cucchiari D, Becker JU, de Vries APJ, Eccher A, Florquin S, Kers J, Rabant M, Rossini M, Pengel L, Marson L, Furian L. European Society for Organ Transplantation (ESOT)-TLJ 3.0 Consensus on Histopathological Analysis of Pre-Implantation Donor Kidney Biopsy: Redefining the Role in the Process of Graft Assessment. Transpl Int 2023; 36:11410. [PMID: 37470063 PMCID: PMC10353313 DOI: 10.3389/ti.2023.11410] [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: 03/28/2023] [Accepted: 05/31/2023] [Indexed: 07/21/2023]
Abstract
The ESOT TLJ 3.0. consensus conference brought together leading experts in transplantation to develop evidence-based guidance on the standardization and clinical utility of pre-implantation kidney biopsy in the assessment of grafts from Expanded Criteria Donors (ECD). Seven themes were selected and underwent in-depth analysis after formulation of PICO (patient/population, intervention, comparison, outcomes) questions. After literature search, the statements for each key question were produced, rated according the GRADE approach [Quality of evidence: High (A), Moderate (B), Low (C); Strength of Recommendation: Strong (1), Weak (2)]. The statements were subsequently presented in-person at the Prague kick-off meeting, discussed and voted. After two rounds of discussion and voting, all 7 statements reached an overall agreement of 100% on the following issues: needle core/wedge/punch technique representatively [B,1], frozen/paraffin embedded section reliability [B,2], experienced/non-experienced on-call renal pathologist reproducibility/accuracy of the histological report [A,1], glomerulosclerosis/other parameters reproducibility [C,2], digital pathology/light microscopy in the measurement of histological variables [A,1], special stainings/Haematoxylin and Eosin alone comparison [A,1], glomerulosclerosis reliability versus other histological parameters to predict the graft survival, graft function, primary non-function [B,1]. This methodology has allowed to reach a full consensus among European experts on important technical topics regarding pre-implantation biopsy in the ECD graft assessment.
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Affiliation(s)
- Gianluigi Zaza
- Nephrology, Dialysis and Transplantation Unit, Department of Medical and Surgical Sciences, University/Hospital of Foggia, Foggia, Italy
| | - David Cucchiari
- Department of Nephrology and Kidney Transplantation, Hospital Clínic, Barcelona, Spain
| | - Jan Ulrich Becker
- Institut für Pathologie und Molekularpathologie, University Hospital of Cologne, Cologne, Germany
| | - Aiko P. J. de Vries
- Division of Nephrology, Department of Medicine, Transplant Center, Leiden University Medical Center, Leiden, Netherlands
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Sandrine Florquin
- Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Jesper Kers
- Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Marion Rabant
- Department of Pathology, Necker-Enfants Malades University Hospital, Paris, France
| | - Michele Rossini
- Nephrology, Dialysis and Transplantation Unit, University/Hospital of Bari, Bari, Italy
| | - Liset Pengel
- Centre for Evidence in Transplantation, Oxford, United Kindom
| | - Lorna Marson
- Department of Surgery, University of Edinburgh, Edinburgh, United Kingdom
| | - Lucrezia Furian
- Kidney and Pancreas Transplantation Unit, University of Padova, Padova, Italy
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Kaushal RK, Yadav S, Sahay A, Karnik N, Agrawal T, Dave V, Singh N, Shah A, Desai SB. Validation of Remote Digital Pathology based diagnostic reporting of Frozen Sections from home. J Pathol Inform 2023; 14:100312. [PMID: 37214151 PMCID: PMC10192998 DOI: 10.1016/j.jpi.2023.100312] [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: 03/03/2023] [Revised: 04/07/2023] [Accepted: 04/12/2023] [Indexed: 05/24/2023] Open
Abstract
Background Despite the promising applications of whole-slide imaging (WSI) for frozen section (FS) diagnosis, its adoption for remote reporting is limited. Objective To assess the feasibility and performance of home-based remote digital consultation for FS diagnosis. Material & Method Cases accessioned beyond regular working hours (5 pm-10 pm) were reported simultaneously using optical microscopy (OM) and WSI. Validation of WSI for FS diagnosis from a remote site, i.e. home, was performed by 5 pathologists. Cases were scanned using a portable scanner (Grundium Ocus®40) and previewed on consumer-grade computer devices through a web-based browser (http://grundium.net). Clinical data and diagnostic reports were shared through a google spreadsheet. The diagnostic concordance, inter- and intra-observer agreement for FS diagnosis by WSI versus OM, and turnaround time (TAT), were recorded. Results The overall diagnostic accuracy for OM and WSI (from home) was 98.2% (range 97%-100%) and 97.6% (range 95%-99%), respectively, when compared with the reference standard. Almost perfect inter-observer (k = 0.993) and intra-observer (k = 0.987) agreement for WSI was observed by 4 pathologists. Pathologists used consumer-grade laptops/desktops with an average screen size of 14.58 inches (range = 12.3-17.7 inches) and a network speed of 64 megabits per second (range: 10-90 Mbps). The mean diagnostic assessment time per case for OM and WSI was 1:48 min and 5:54 min, respectively. Mean TAT of 27.27 min per case was observed using WSI from home. Seamless connectivity was observed in approximately 75% of cases. Conclusion This study validates the role of WSI for remote FS diagnosis for its safe and efficient adoption in clinical use.
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Affiliation(s)
- Rajiv Kumar Kaushal
- Corresponding author at: Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Dr Ernest Borges Marg, Parel, Mumbai 400 012, India.
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Eccher A, Antonini P, Barreca A, Fabbrizio B, Boggi U, Rizzo PC, Girolami I. Digital Slide and Simulation-Based Learning in Pre-Implantation Kidney Biopsies. CURRENT TRANSPLANTATION REPORTS 2023. [DOI: 10.1007/s40472-023-00392-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
AbstractAlthough controversial, procurement kidney biopsies and histology are commonly used in kidney allocation from deceased donors. The long series of models developed for this question, incorporating a variety of clinical and histologic variables, failed to properly predict the long-term graft survival. This failure could be explained by many factors, including the lack of expertise in terms of skilled available nephropathologists in the urgent setting of biopsies assessment. Simulation-based learning is a form of experiential learning that provides learners with a real-world-like opportunity to develop and practice their knowledge and skills but in a simulated environment. Digital pathology with whole-slide imaging is a powerful tool for knowledge delivering, as it offers the opportunity to facilitate meeting of general pathologists with experts, with availability of second opinion consultation and tailored training on specific cases. In the back of these considerations, we report on the content of the web-meeting “Digital slide and simulation-based learning in pre-implantation kidney” which was fully dedicated to the evaluation of pre-implantation kidney biopsy, with a very practical approach and a direct interaction between two expert renal transplant pathologists and the audience of general pathologists.
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Wu B, Moeckel G. Application of digital pathology and machine learning in the liver, kidney and lung diseases. J Pathol Inform 2023; 14:100184. [PMID: 36714454 PMCID: PMC9874068 DOI: 10.1016/j.jpi.2022.100184] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 11/28/2022] [Accepted: 12/28/2022] [Indexed: 01/05/2023] Open
Abstract
The development of rapid and accurate Whole Slide Imaging (WSI) has paved the way for the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the recent years allowed the rapid development of various AI technologies to blossom. WSI-based digital pathology combined with neural networks can automate arduous and time-consuming tasks of slide evaluation. Machine Learning (ML)-based AI has been demonstrated to outperform pathologists by eliminating inter- and intra-observer subjectivity, obtaining quantitative data from slide images, and extracting hidden image patterns that are relevant to disease subtype and progression. In this review, we outline the functionality of different AI technologies such as neural networks and deep learning and discover how aspects of different diseases make them benefit from the implementation of AI. AI has proven to be valuable in many different organs, with this review focusing on the liver, kidney, and lungs. We also discuss how AI and image analysis not only can grade diseases objectively but also discover aspects of diseases that have prognostic value. In the end, we review the current status of the integration of AI in pathology and share our vision on the future of digital pathology.
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Affiliation(s)
- Benjamin Wu
- Horace Mann School, Bronx, NY, USA,Corresponding author at: 950 Post Rd., Scarsdale, NY 10583, USA.
| | - Gilbert Moeckel
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
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10
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Eccher A, Pagni F, Marletta S, Munari E, Dei Tos AP. Perspective of a Pathologist on Benchmark Strategies for Artificial Intelligence Development in Organ Transplantation. Crit Rev Oncog 2023; 28:1-6. [PMID: 37968987 DOI: 10.1615/critrevoncog.2023048797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
Transplant pathology of donors is a highly specialized field comprising both the evaluation of organ donor biopsy for the oncological risk transmission and to guide the organ allocation. Timing is critical in transplant procurement since organs must be recovered as soon as possible to ensure the best possible outcome for the recipient. To all this is added the fact that the evaluation of a donor causes difficulties in many cases and the impact of these assessments is paramount, considering the possible recovery of organs that would have been erroneously discarded or, conversely, the possibly correct discarding of donors with unacceptable risk profiles. In transplant pathology histology is still the gold standard for diagnosis dictating the subsequent decisions and course of clinical care. Digital pathology has played an important role in accelerating healthcare progression and nowadays artificial intelligence powered computational pathology can effectively improve diagnostic needs, supporting the quality and safety of the process. Mapping the shape of the journey would suggest a progressive approach from supervised to semi/unsupervised models, which would involve training these models directly for clinical endpoints. In machine learning, this generally delivers better performance, compensating for a potential lack in interpretability. With planning and enough confidence in the performance of learning-based methods from digital pathology and artificial intelligence, there is great potential to augment the diagnostic quality and correlation with clinical endpoints. This may improve the donor pool and vastly reduce diagnostic and prognostic errors that are known but currently are unavoidable in transplant donor pathology.
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Affiliation(s)
- Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Fabio Pagni
- Department of Medicine and Surgery, Pathology, University of Milano-Bicocca, IRCCS (Scientific Institute for Research, Hospitalization and Healthcare) Fondazione San Gerardo dei Tintori, Monza, Italy
| | - Stefano Marletta
- Department of Diagnostics and Public Health, Section of Pathology, University of Verona, Verona, Italy; Division of Pathology Humanitas Cancer Center, Catania, Italy
| | - Enrico Munari
- Pathology Unit, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Angelo Paolo Dei Tos
- Surgical Pathology & Cytopathology Unit, Department of Medicine (DIMED), University of Padua, Padua, Italy
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11
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Stewart DE, Foutz J, Kamal L, Weiss S, McGehee HS, Cooper M, Gupta G. The Independent Effects of Procurement Biopsy Findings on Ten-Year Outcomes of Extended Criteria Donor Kidney Transplants. Kidney Int Rep 2022; 7:1850-1865. [PMID: 35967103 PMCID: PMC9366372 DOI: 10.1016/j.ekir.2022.05.027] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 05/23/2022] [Indexed: 11/01/2022] Open
Abstract
Introduction Methods Results Conclusion
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12
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Computer-assisted evaluation enhances the quantification of interstitial fibrosis in renal implantation biopsies, measures differences between frozen and paraffin sections, and predicts delayed graft function. J Nephrol 2022; 35:1819-1829. [PMID: 35438423 PMCID: PMC9458593 DOI: 10.1007/s40620-022-01315-y] [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: 06/15/2021] [Accepted: 03/19/2022] [Indexed: 11/24/2022]
Abstract
Background (Pre-)Implantation biopsies provide important data on the quality of donor kidneys. Interstitial fibrosis, as a known predictor for kidney disease progression, is an essential feature of this evaluation. However, the assessment of frozen sections of implantation biopsies is challenging and can result in the disposal of candidate organs. We sought to apply digital image analysis (DIA) to quantify the differences between frozen and paraffin sections when evaluating interstitial fibrosis, identify factors that influence these variations and test the predictive value of the computerised measures. Methods We quantified the differences between frozen and paraffin sections in the same biopsy samples by measuring Sirius red-stained interstitial areas (SRIA) in DIA. We compared them to the original reports, and retrospectively correlated our findings to clinical data, graft function and outcome in 73 patients. Results Frozen sections display a broader interstitial area than paraffin sections, in some cases up to one-third more (mean difference + 7.8%, range − 7 to 29%). No donor-related factors (age or gender, cold ischemia time, or non-heart-beating donor) influenced significantly this difference. Compared to the original assessment of frozen vs paraffin sections in optical microscopy, the DIA of interstitial fibrosis shows a higher consistency (ICC 0.69). Our approach further allows to distinguish SRIA in paraffin sections as an independent predictor for delayed graft function (OR = 1.1; p = 0.028). Conclusions DIA is superior to and more consistent than routine optic microscopy for interstitial fibrosis evaluation. This method could improve implantation biopsy diagnostics and help to reduce disposal of organs. Graphical abstract Supplementary Information The online version contains supplementary material available at 10.1007/s40620-022-01315-y.
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13
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Girolami I, Pantanowitz L, Marletta S, Hermsen M, van der Laak J, Munari E, Furian L, Vistoli F, Zaza G, Cardillo M, Gesualdo L, Gambaro G, Eccher A. Artificial intelligence applications for pre-implantation kidney biopsy pathology practice: a systematic review. J Nephrol 2022; 35:1801-1808. [PMID: 35441256 PMCID: PMC9458558 DOI: 10.1007/s40620-022-01327-8] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 03/28/2022] [Indexed: 10/29/2022]
Abstract
BACKGROUND Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ allocation and post-transplant graft biopsy for assessment of rejection or graft damage. The introduction of digital pathology with whole-slide imaging (WSI) in clinical research, trials and practice has catalyzed the application of artificial intelligence (AI) for histopathology, with development of novel machine-learning models for tissue interrogation and discovery. We aimed to review the literature for studies specifically applying AI algorithms to WSI-digitized pre-implantation kidney biopsy. METHODS A systematic search was carried out in the electronic databases PubMed-MEDLINE and Embase until 25th September, 2021 with a combination of the key terms "kidney", "biopsy", "transplantation" and "artificial intelligence" and their aliases. Studies dealing with the application of AI algorithms coupled with WSI in pre-implantation kidney biopsies were included. The main theme addressed was detection and quantification of tissue components. Extracted data were: author, year and country of the study, type of biopsy features investigated, number of cases, type of algorithm deployed, main results of the study in terms of diagnostic outcome, and the main limitations of the study. RESULTS Of 5761 retrieved articles, 7 met our inclusion criteria. All studies focused largely on AI-based detection and classification of glomerular structures and to a lesser extent on tubular and vascular structures. Performance of AI algorithms was excellent and promising. CONCLUSION All studies highlighted the importance of expert pathologist annotation to reliably train models and the need to acknowledge clinical nuances of the pre-implantation setting. Close cooperation between computer scientists and practicing as well as expert renal pathologists is needed, helping to refine the performance of AI-based models for routine pre-implantation kidney biopsy clinical practice.
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Affiliation(s)
- Ilaria Girolami
- Division of Pathology, Central Hospital Bolzano, Bolzano, Italy
| | - Liron Pantanowitz
- Department of Pathology and Clinical Labs, University of Michigan, Ann Arbor, MI, USA
| | - Stefano Marletta
- Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy
| | - Meyke Hermsen
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jeroen van der Laak
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Enrico Munari
- Pathology Unit, Department of Molecular and Translational Medicine, Spedali Civili-University of Brescia, Brescia, Italy
| | - Lucrezia Furian
- Department of Surgical, Oncological and Gastroenterological Sciences, Unit of Kidney and Pancreas Transplantation, University of Padua, Padua, Italy
| | - Fabio Vistoli
- Division of General and Transplant Surgery, University of Pisa, Pisa, Italy
| | - Gianluigi Zaza
- Department of Nephro-Urology, Nephrology, Dialysis and Transplant Unit, University of Foggia, Foggia, Italy
| | | | - Loreto Gesualdo
- Nephrology, Dialysis, and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy
| | - Giovanni Gambaro
- Department of General Medicine, Renal Unit, University and Hospital Trust of Verona, Verona, Italy
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, P.le Stefani n. 1, 37126, Verona, Italy.
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Lentine KL, Fleetwood VA, Caliskan Y, Randall H, Wellen JR, Lichtenberger M, Dedert C, Rothweiler R, Marklin G, Brockmeier D, Schnitzler MA, Husain SA, Mohan S, Kasiske BL, Cooper M, Mannon RB, Axelrod DA. Deceased Donor Procurement Biopsy Practices, Interpretation, and Histology-Based Decision Making: A Survey of U.S. Transplant Centers. Kidney Int Rep 2022; 7:1268-1277. [PMID: 35685316 PMCID: PMC9171615 DOI: 10.1016/j.ekir.2022.03.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/13/2022] [Accepted: 03/21/2022] [Indexed: 10/31/2022] Open
Abstract
Introduction Methods Results Conclusion
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15
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de Sandes-Freitas TV, Perdigão RLD, dos Santos Portas A, de Almeida ARF, Sanders-Pinheiro H. Innovations in Kidney Transplantation. INNOVATIONS IN NEPHROLOGY 2022:365-378. [DOI: 10.1007/978-3-031-11570-7_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2025]
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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.
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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
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Neri F, Eccher A, Rigotti P, Girolami I, Zaza G, Gambaro G, Mastrosimini M, Bencini G, Bella CD, Mescoli C, Boschiero L, Marletta S, Tos PAD, Furian L. Advantages of Using a Web-based Digital Platform for Kidney Preimplantation Biopsies. J Pathol Inform 2021; 12:41. [PMID: 34881096 PMCID: PMC8609286 DOI: 10.4103/jpi.jpi_23_21] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/02/2021] [Accepted: 06/20/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND In the setting of kidney transplantation, histopathology of kidney biopsies is a key element in the organ assessment and allocation. Despite the broad diffusion of the Remuzzi-Karpinski score on preimplantation kidney biopsies, scientific evidence of its correlation to the transplantation outcome is controversial. The main issues affecting the prognostic value of histopathology are the referral to general on-call pathologists and the semiquantitative feature of the score, which can raise issues of interpretation. Digital pathology has shown very reliable and effective in the oncological diagnosis and treatment; however, the spread of such technologies is lagging behind in the field of transplantation. The aim of our study was to create a digital online platform where whole-slide images (WSI) of preimplantation kidney biopsies could be uploaded and stored. METHODS We included 210 kidney biopsies collected between January 2015 and December 2019 from the joint collaboration of the transplantation centers of Padua and Verona. The selected slides, stained with hematoxylin and eosin, were digitized and uploaded on a shared web platform. For each case, the on-call pathologists' Remuzzi grades were obtained from the original report, together with the clinical data and the posttransplantation follow-up. RESULTS The storage of WSI of preimplantation kidney biopsies would have several clinical, scientific, and educational advantages. The clinical utility relies on the possibility to consult online expert pathologists and real-time quality checks of diagnosis. From the perspective of follow-up, the archived digitized biopsies can offer a useful comparison to posttransplantation biopsies. In addition, the digital online platform is a precious tool for multidisciplinary meetings aimed both at the clinical discussion and at the design of research projects. Furthermore, this archive of readily available WSI is an important educational resource for the training of professionals. CONCLUSIONS Finally, the web platform lays the foundation for the introduction of artificial intelligence in the field of transplantation that would help create new diagnostic algorithms and tools with the final aim of increasing the precision of organ assessment and its predictive value for transplant outcome.
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Affiliation(s)
- Flavia Neri
- Department of Surgical, Oncological and Gastroenterological Sciences, Unit of Kidney and Pancreas Transplantation, University of Padua, Padua, Italy
| | - Albino Eccher
- Department of Pathology and Diagnostic, University and Hospital Trust of Verona, Verona, Italy
| | - Paolo Rigotti
- Department of Surgical, Oncological and Gastroenterological Sciences, Unit of Kidney and Pancreas Transplantation, University of Padua, Padua, Italy
| | - Ilaria Girolami
- Division of Pathology, Central Hospital Bolzano, Bolzano, Italy
| | - Gianluigi Zaza
- Department of General Medicine, Renal Unit, University and Hospital Trust of Verona, Verona, Italy
| | - Giovanni Gambaro
- Department of General Medicine, Renal Unit, University and Hospital Trust of Verona, Verona, Italy
| | - MariaGaia Mastrosimini
- Department of Pathology and Diagnostic, University and Hospital Trust of Verona, Verona, Italy
| | - Giulia Bencini
- Department of Surgical, Oncological and Gastroenterological Sciences, Unit of Kidney and Pancreas Transplantation, University of Padua, Padua, Italy
| | - Caterina Di Bella
- Department of Surgical, Oncological and Gastroenterological Sciences, Unit of Kidney and Pancreas Transplantation, University of Padua, Padua, Italy
| | - Claudia Mescoli
- Department of Medicine, Surgical Pathology and Cytopathology Unit, University of Padua, Padua, Italy
| | - Luigino Boschiero
- Department of Surgical Sciences, Kidney Transplant Center, Hospital Trust of Verona, Verona, Italy
| | - Stefano Marletta
- Department of Pathology and Diagnostic, University and Hospital Trust of Verona, Verona, Italy
| | - Paolo Angelo Dei Tos
- Department of Medicine, Surgical Pathology and Cytopathology Unit, University of Padua, Padua, Italy
| | - Lucrezia Furian
- Department of Surgical, Oncological and Gastroenterological Sciences, Unit of Kidney and Pancreas Transplantation, University of Padua, Padua, Italy
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Emmons BR, Husain SA, King KL, Adler JT, Mohan S. Variations in deceased donor kidney procurement biopsy practice patterns: A survey of U.S. organ procurement organizations. Clin Transplant 2021; 35:e14411. [PMID: 34196034 PMCID: PMC8556234 DOI: 10.1111/ctr.14411] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Procurement biopsies have become a common practice in the evaluation and allocation of deceased donor kidneys in the United States despite questions about their value and reproducibility. We sought to determine the extent of OPO-level differences in criteria used to decide which deceased donor kidneys undergo a procurement biopsy and to assess the degree of variability in procurement biopsy technique and interpretation across OPOs. METHODS Each of the country's 58 OPOs were invited to participate in the survey. OPOs were divided into two groups based on organ availability ratio and deceased donor kidney discard rate. RESULTS AND CONCLUSIONS Fifty-out-of-fifty-eight invited OPOs (86% response rate) responded to the survey between November 2020 and December 2020. Thirty (60%) OPOs reported that they have formal criteria for performing kidney procurement biopsy, but for 29 of these OPOs, transplant centers can request biopsy on kidneys that do not meet criteria. OPOs used a total of seven different variables and 12 different numerical thresholds to define impaired kidney function that would prompt a procurement biopsy. Additionally, wide variability was seen in biopsy technique and procedures for biopsy interpretation and reporting of findings to transplant programs. These findings identify a clear opportunity for standardization of procurement biopsies to best practices.
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Affiliation(s)
- Brendan R. Emmons
- Department of Medicine, Division of Nephrology, Columbia University Medical Center, New York, NY
| | - S. Ali Husain
- Department of Medicine, Division of Nephrology, Columbia University Medical Center, New York, NY
- The Columbia University Renal Epidemiology (CURE) Group, New York, NY
| | - Kristen L. King
- Department of Medicine, Division of Nephrology, Columbia University Medical Center, New York, NY
- The Columbia University Renal Epidemiology (CURE) Group, New York, NY
| | - Joel T. Adler
- Department of Surgery, Division of Transplant Surgery, Brigham and Women’s Hospital, Boston, MA
- Center for Surgery and Public Health at Brigham and Women’s Hospital, Boston, MA
| | - Sumit Mohan
- Department of Medicine, Division of Nephrology, Columbia University Medical Center, New York, NY
- The Columbia University Renal Epidemiology (CURE) Group, New York, NY
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY
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DiPalma J, Suriawinata AA, Tafe LJ, Torresani L, Hassanpour S. Resolution-based distillation for efficient histology image classification. Artif Intell Med 2021; 119:102136. [PMID: 34531005 PMCID: PMC8449014 DOI: 10.1016/j.artmed.2021.102136] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 07/07/2021] [Accepted: 08/02/2021] [Indexed: 12/14/2022]
Abstract
Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive strain on all parts of the computing pipeline. This paper proposes a novel deep learning-based methodology for improving the computational efficiency of histology image classification. The proposed approach is robust when used with images that have reduced input resolution, and it can be trained effectively with limited labeled data. Moreover, our approach operates at either the tissue- or slide-level, removing the need for laborious patch-level labeling. Our method uses knowledge distillation to transfer knowledge from a teacher model pre-trained at high resolution to a student model trained on the same images at a considerably lower resolution. Also, to address the lack of large-scale labeled histology image datasets, we perform the knowledge distillation in a self-supervised fashion. We evaluate our approach on three distinct histology image datasets associated with celiac disease, lung adenocarcinoma, and renal cell carcinoma. Our results on these datasets demonstrate that a combination of knowledge distillation and self-supervision allows the student model to approach and, in some cases, surpass the teacher model's classification accuracy while being much more computationally efficient. Additionally, we observe an increase in student classification performance as the size of the unlabeled dataset increases, indicating that there is potential for this method to scale further with additional unlabeled data. Our model outperforms the high-resolution teacher model for celiac disease in accuracy, F1-score, precision, and recall while requiring 4 times fewer computations. For lung adenocarcinoma, our results at 1.25× magnification are within 1.5% of the results for the teacher model at 10× magnification, with a reduction in computational cost by a factor of 64. Our model on renal cell carcinoma at 1.25× magnification performs within 1% of the teacher model at 5× magnification while requiring 16 times fewer computations. Furthermore, our celiac disease outcomes benefit from additional performance scaling with the use of more unlabeled data. In the case of 0.625× magnification, using unlabeled data improves accuracy by 4% over the tissue-level baseline. Therefore, our approach can improve the feasibility of deep learning solutions for digital pathology on standard computational hardware and infrastructures.
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Affiliation(s)
- Joseph DiPalma
- Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA
| | - Arief A Suriawinata
- Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756, USA
| | - Laura J Tafe
- Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756, USA
| | - Lorenzo Torresani
- Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA
| | - Saeed Hassanpour
- Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA; Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
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20
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Girolami I, Marletta S, Eccher A. Commentary: The Digital Fate of Glomeruli in Renal Biopsy. J Pathol Inform 2021; 12:14. [PMID: 34012718 PMCID: PMC8112342 DOI: 10.4103/jpi.jpi_102_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 01/09/2021] [Accepted: 01/09/2021] [Indexed: 11/04/2022] Open
Affiliation(s)
- Ilaria Girolami
- Division of Pathology, Central Hospital Bolzano, Bolzano, Italy
| | - Stefano Marletta
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
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21
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Wood-Trageser M, Xu Q, Zeevi A, Randhawa P, Lesniak D, Demetris A. Precision transplant pathology. Curr Opin Organ Transplant 2020; 25:412-419. [PMID: 32520786 PMCID: PMC7737245 DOI: 10.1097/mot.0000000000000772] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
PURPOSE OF REVIEW Transplant pathology contributes substantially to personalized treatment of organ allograft recipients. Rapidly advancing next-generation human leukocyte antigen (HLA) sequencing and pathology are enhancing the abilities to improve donor/recipient matching and allograft monitoring. RECENT FINDINGS The present review summarizes the workflow of a prototypical patient through a pathology practice, highlighting histocompatibility assessment and pathologic review of tissues as areas that are evolving to incorporate next-generation technologies while emphasizing critical needs of the field. SUMMARY Successful organ transplantation starts with the most precise pratical donor-recipient histocompatibility matching. Next-generation sequencing provides the highest resolution donor-recipient matching and enables eplet mismatch scores and more precise monitoring of donor-specific antibodies (DSAs) that may arise after transplant. Multiplex labeling combined with hand-crafted machine learning is transforming traditional histopathology. The combination of traditional blood/body fluid laboratory tests, eplet and DSA analysis, traditional and next-generation histopathology, and -omics-based platforms enables risk stratification and identification of early subclinical molecular-based changes that precede a decline in allograft function. Needs include software integration of data derived from diverse platforms that can render the most accurate assessment of allograft health and needs for immunosuppression adjustments.
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Affiliation(s)
- M.A. Wood-Trageser
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA 15213 USA
- Division of Liver and Transplantation Pathology, Department of Pathology, University of Pittsburgh, PA 15213, USA
| | - Qinyong Xu
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA 15213 USA
- Division of Liver and Transplantation Pathology, Department of Pathology, University of Pittsburgh, PA 15213, USA
| | - A. Zeevi
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA 15213 USA
- Division of Liver and Transplantation Pathology, Department of Pathology, University of Pittsburgh, PA 15213, USA
| | - P. Randhawa
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA 15213 USA
- Division of Liver and Transplantation Pathology, Department of Pathology, University of Pittsburgh, PA 15213, USA
| | - D. Lesniak
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA 15213 USA
- Division of Liver and Transplantation Pathology, Department of Pathology, University of Pittsburgh, PA 15213, USA
| | - A.J. Demetris
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA 15213 USA
- Division of Liver and Transplantation Pathology, Department of Pathology, University of Pittsburgh, PA 15213, USA
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Eccher A, Girolami I, Brunelli M, Novelli L, Mescoli C, Malvi D, D'Errico A, Luchini C, Furian L, Zaza G, Cardillo M, Boggi U, Pantanowitz L. Digital pathology for second opinion consultation and donor assessment during organ procurement: Review of the literature and guidance for deployment in transplant practice. Transplant Rev (Orlando) 2020; 34:100562. [PMID: 32576430 DOI: 10.1016/j.trre.2020.100562] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 05/01/2020] [Accepted: 05/15/2020] [Indexed: 01/20/2023]
Abstract
Telepathology has been an important application for second opinion consultation ever since the introduction of digital pathology. However, little is known regarding teleconsultation for second opinion in transplantation. There is also limited literature on telepathology during organ donor procurement, typically utilized when general pathologists on-call request back-up to help assess donor biopsies for organ suitability or to diagnose newly discovered tumors with urgent time constraints. In this review, we searched Pubmed/Embase and websites of transplant organizations to collect and analyze published evidence on teleconsultation for donor evaluation and organ procurement. Of 2725 records retrieved using the key terms 'telepathology', 'second opinion' and 'transplantation', 26 suitable studies were included. Most records were from North America and included validation studies of telepathology being used for remote frozen section interpretation of donor biopsies with whole slide imaging. The data from these published studies supports the transition towards digital teleconsultation in transplant settings where consultations among pathologists are still handled by pathologists being called on site, via telephone and/or email.
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Affiliation(s)
- Albino Eccher
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy.
| | - Ilaria Girolami
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Matteo Brunelli
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Luca Novelli
- Institute for Histopathology and Molecular Diagnosis, Careggi University Hospital, Florence, Italy
| | - Claudia Mescoli
- Department of Medicine (DIMED), Surgical Pathology & Cytopathology Unit, University and Hospital Trust of Padua, Padua, Italy
| | - Deborah Malvi
- Pathology Unit, University of Bologna, Policlinico St. Orsola-Malpighi Hospital, Bologna, Italy
| | - Antonia D'Errico
- Pathology Unit, University of Bologna, Policlinico St. Orsola-Malpighi Hospital, Bologna, Italy
| | - Claudio Luchini
- Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Lucrezia Furian
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, University and Hospital Trust of Padua, Padua, Italy
| | - Gianluigi Zaza
- Renal Unit, University and Hospital Trust of Verona, Verona, Italy
| | | | - Ugo Boggi
- Division of General and Transplant Surgery, University of Pisa, Pisa, Italy
| | - Liron Pantanowitz
- Department of Pathology, UPMC Shadyside Hospital, University of Pittsburgh, Pittsburgh, PA, USA
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Melo RCN, Raas MWD, Palazzi C, Neves VH, Malta KK, Silva TP. Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders. Front Med (Lausanne) 2020; 6:310. [PMID: 31970160 PMCID: PMC6960181 DOI: 10.3389/fmed.2019.00310] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Accepted: 12/09/2019] [Indexed: 12/11/2022] Open
Abstract
Histological analysis of hepatic tissue specimens is essential for evaluating the pathology of several liver disorders such as chronic liver diseases, hepatocellular carcinomas, liver steatosis, and infectious liver diseases. Manual examination of histological slides on the microscope is a classically used method to study these disorders. However, it is considered time-consuming, limited, and associated with intra- and inter-observer variability. Emerging technologies such as whole slide imaging (WSI), also termed virtual microscopy, have increasingly been used to improve the assessment of histological features with applications in both clinical and research laboratories. WSI enables the acquisition of the tissue morphology/pathology from glass slides and translates it into a digital form comparable to a conventional microscope, but with several advantages such as easy image accessibility and storage, portability, sharing, annotation, qualitative and quantitative image analysis, and use for educational purposes. WSI-generated images simultaneously provide high resolution and a wide field of observation that can cover the entire section, extending any single field of view. In this review, we summarize current knowledge on the application of WSI to histopathological analyses of liver disorders as well as to understand liver biology. We address how WSI may improve the assessment and quantification of multiple histological parameters in the liver, and help diagnose several hepatic conditions with important clinical implications. The WSI technical limitations are also discussed.
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Affiliation(s)
- Rossana C N Melo
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Maximilian W D Raas
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil.,Faculty of Medical Sciences, Radboud University, Nijmegen, Netherlands
| | - Cinthia Palazzi
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Vitor H Neves
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Kássia K Malta
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Thiago P Silva
- Laboratory of Cellular Biology, Department of Biology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
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