Research

21 pages, 6016 KiB

Open AccessArticle

DigiPatICS: Digital Pathology Transformation of the Catalan Health Institute Network of 8 Hospitals—Planification, Implementation, and Preliminary Results

by Jordi Temprana-Salvador, Pablo López-García, Josep Castellví Vives, Lluís de Haro, Eudald Ballesta, Matias Rojas Abusleme, Miquel Arrufat, Ferran Marques, Josep R. Casas, Carlos Gallego, Laura Pons, José Luis Mate, Pedro Luis Fernández, Eugeni López-Bonet, Ramon Bosch, Salomé Martínez, Santiago Ramón y Cajal and Xavier Matias-Guiu

Diagnostics 2022, 12(4), 852; https://doi.org/10.3390/diagnostics12040852 - 30 Mar 2022

Cited by 14 | Viewed by 6511

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, [...] Read more.

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. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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10 pages, 976 KiB

Open AccessArticle

Digital Pathology Implementation in Private Practice: Specific Challenges and Opportunities

by Diana Montezuma, Ana Monteiro, João Fraga, Liliana Ribeiro, Sofia Gonçalves, André Tavares, João Monteiro and Isabel Macedo-Pinto

Diagnostics 2022, 12(2), 529; https://doi.org/10.3390/diagnostics12020529 - 18 Feb 2022

Cited by 17 | Viewed by 4223

Abstract

Digital pathology (DP) is being deployed in many pathology laboratories, but most reported experiences refer to public health facilities. In this paper, we report our experience in DP transition at a high-volume private laboratory, addressing the main challenges in DP implementation in a [...] Read more.

Digital pathology (DP) is being deployed in many pathology laboratories, but most reported experiences refer to public health facilities. In this paper, we report our experience in DP transition at a high-volume private laboratory, addressing the main challenges in DP implementation in a private practice setting and how to overcome these issues. We started our implementation in 2020 and we are currently scanning 100% of our histology cases. Pre-existing sample tracking infrastructure facilitated this process. We are currently using two high-capacity scanners (Aperio GT450DX) to digitize all histology slides at 40×. Aperio eSlide Manager WebViewer viewing software is bidirectionally linked with the laboratory information system. Scanning error rate, during the test phase, was 2.1% (errors detected by the scanners) and 3.5% (manual quality control). Pre-scanning phase optimizations and vendor feedback and collaboration were crucial to improve WSI quality and are ongoing processes. Regarding pathologists’ validation, we followed the Royal College of Pathologists recommendations for DP implementation (adapted to our practice). Although private sector implementation of DP is not without its challenges, it will ultimately benefit from DP safety and quality-associated features. Furthermore, DP deployment lays the foundation for artificial intelligence tools integration, which will ultimately contribute to improving patient care. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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11 pages, 1111 KiB

Open AccessArticle

Digital Pathology Workflow Implementation at IPATIMUP

by Catarina Eloy, João Vale, Mónica Curado, António Polónia, Sofia Campelos, Ana Caramelo, Rui Sousa and Manuel Sobrinho-Simões

Diagnostics 2021, 11(11), 2111; https://doi.org/10.3390/diagnostics11112111 - 15 Nov 2021

Cited by 34 | Viewed by 3820

Abstract

The advantages of the digital methodology are well known. In this paper, we provide a detailed description of the process for the digital transformation of the pathology laboratory at IPATIMUP, the major modifications that operate throughout the processing pipeline, and the advantages of [...] Read more.

The advantages of the digital methodology are well known. In this paper, we provide a detailed description of the process for the digital transformation of the pathology laboratory at IPATIMUP, the major modifications that operate throughout the processing pipeline, and the advantages of its implementation. The model of digital workflow implementation at IPATIMUP demonstrates that careful planning and adoption of simple measures related to time, space, and sample management can be adopted by any pathology laboratory to achieve higher quality and easy digital transformation. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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19 pages, 3215 KiB

Open AccessArticle

A Survival Guide for the Rapid Transition to a Fully Digital Workflow: The “Caltagirone Example”

by Filippo Fraggetta, Alessandro Caputo, Rosa Guglielmino, Maria Giovanna Pellegrino, Giampaolo Runza and Vincenzo L'Imperio

Diagnostics 2021, 11(10), 1916; https://doi.org/10.3390/diagnostics11101916 - 16 Oct 2021

Cited by 34 | Viewed by 3262

Abstract

Digital pathology for the routine assessment of cases for primary diagnosis has been implemented by few laboratories worldwide. The Gravina Hospital in Caltagirone (Sicily, Italy), which collects cases from 7 different hospitals distributed in the Catania area, converted the entire workflow to digital [...] Read more.

Digital pathology for the routine assessment of cases for primary diagnosis has been implemented by few laboratories worldwide. The Gravina Hospital in Caltagirone (Sicily, Italy), which collects cases from 7 different hospitals distributed in the Catania area, converted the entire workflow to digital starting from 2019. Before the transition, the Caltagirone pathology laboratory was characterized by a non-tracked workflow, based on paper requests, hand-written blocks and slides, as well as manual assembling and delivering of the cases and glass slides to the pathologists. Moreover, the arrangement of the spaces and offices in the department was illogical and under-productive for the linearity of the workflow. For these reasons, an adequate 2D barcode system for tracking purposes, the redistribution of the spaces inside the laboratory and the implementation of the whole-slide imaging (WSI) technology based on a laboratory information system (LIS)-centric approach were adopted as a needed prerequisite to switch to a digital workflow. The adoption of a dedicated connection for transfer of clinical and administrative data between different software and interfaces using an internationally recognised standard (Health Level 7, HL7) in the pathology department further facilitated the transition, helping in the integration of the LIS with WSI scanners. As per previous reports, the components and devices chosen for the pathologists’ workstations did not significantly impact on the WSI-based reporting phase in primary histological diagnosis. An analysis of all the steps of this transition has been made retrospectively to provide a useful “handy” guide to lead the digital transition of “analog”, non-tracked pathology laboratories following the experience of the Caltagirone pathology department. Following the step-by-step instructions, the implementation of a paperless routine with more standardized and safe processes, the possibility to manage the priority of the cases and to implement artificial intelligence (AI) tools are no more an utopia for every “analog” pathology department. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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Review

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26 pages, 4741 KiB

Open AccessReview

Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence

by Ankush U. Patel, Nada Shaker, Sambit Mohanty, Shivani Sharma, Shivam Gangal, Catarina Eloy and Anil V. Parwani

Diagnostics 2022, 12(8), 1778; https://doi.org/10.3390/diagnostics12081778 - 22 Jul 2022

Cited by 5 | Viewed by 2255

Abstract

Diagnostic devices, methodological approaches, and traditional constructs of clinical pathology practice, cultivated throughout centuries, have transformed radically in the wake of explosive technological growth and other, e.g., environmental, catalysts of change. Ushered into the fray of modern laboratory medicine are digital imaging devices [...] Read more.

Diagnostic devices, methodological approaches, and traditional constructs of clinical pathology practice, cultivated throughout centuries, have transformed radically in the wake of explosive technological growth and other, e.g., environmental, catalysts of change. Ushered into the fray of modern laboratory medicine are digital imaging devices and machine-learning (ML) software fashioned to mitigate challenges, e.g., practitioner shortage while preparing clinicians for emerging interconnectivity of environments and diagnostic information in the era of big data. As computer vision shapes new constructs for the modern world and intertwines with clinical medicine, cultivating clarity of our new terrain through examining the trajectory and current scope of computational pathology and its pertinence to clinical practice is vital. Through review of numerous studies, we find developmental efforts for ML migrating from research to standardized clinical frameworks while overcoming obstacles that have formerly curtailed adoption of these tools, e.g., generalizability, data availability, and user-friendly accessibility. Groundbreaking validatory efforts have facilitated the clinical deployment of ML tools demonstrating the capacity to effectively aid in distinguishing tumor subtype and grade, classify early vs. advanced cancer stages, and assist in quality control and primary diagnosis applications. Case studies have demonstrated the benefits of streamlined, digitized workflows for practitioners alleviated by decreased burdens. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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14 pages, 500 KiB

Open AccessReview

Virtual Pathology Education in Medical Schools Worldwide during the COVID-19 Pandemic: Advantages, Challenges Faced, and Perspectives

by Angela Ishak, Mousa M. AlRawashdeh, Maria Meletiou-Mavrotheris and Ilias P. Nikas

Diagnostics 2022, 12(7), 1578; https://doi.org/10.3390/diagnostics12071578 - 29 Jun 2022

Cited by 9 | Viewed by 2604

Abstract

The COVID-19 pandemic shifted pathology education in medical schools worldwide towards online delivery. To achieve this goal, various innovative platforms were used by pathology educators and medical students, facilitating both synchronous and asynchronous learning. The aim of this study was to review the [...] Read more.

The COVID-19 pandemic shifted pathology education in medical schools worldwide towards online delivery. To achieve this goal, various innovative platforms were used by pathology educators and medical students, facilitating both synchronous and asynchronous learning. The aim of this study was to review the published evidence regarding remote pathology teaching at the medical school level during this period, present our own experience, and provide some perspectives regarding the best mode of pathology teaching post-pandemic. Among its advantages, virtual pathology education was considered among students and educators as convenient, flexible, and engaging, while learning outcomes were met and students’ academic performance was in general satisfactory. However, several challenges were faced. For instance, suboptimal internet connection compromised the flow of classes and was even associated with a lower academic performance. The lack of hands-on laboratory activities, such as operating the light microscope and tissue grossing, and the reduced student interactions among themselves and their instructors, were also pointed out as significant drawbacks of remote pathology education. Whereas online education has multiple advantages, experiencing the physical university environment, in-person interactions and teamwork, exposure to the “hidden curriculum”, and hands-on activities are vital for medical school education and future student development. In conclusion, the implementation of a blended approach in pathology education—where online and face-to-face sessions are jointly used to promote students’ engagement, interaction with their instructors and peers, and learning—could be the most optimal approach to pathology teaching in medical schools post-pandemic. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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11 pages, 2221 KiB

Open AccessReview

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

by Rachel N. Flach, Nina L. Fransen, Andreas F. P. Sonnen, Tri Q. Nguyen, Gerben E. Breimer, Mitko Veta, Nikolas Stathonikos, Carmen van Dooijeweert and Paul J. van Diest

Diagnostics 2022, 12(5), 1042; https://doi.org/10.3390/diagnostics12051042 - 21 Apr 2022

Cited by 9 | Viewed by 2450

Abstract

Building on a growing number of pathology labs having a full digital infrastructure for pathology diagnostics, there is a growing interest in implementing artificial intelligence (AI) algorithms for diagnostic purposes. This article provides an overview of the current status of the digital pathology [...] Read more.

Building on a growing number of pathology labs having a full digital infrastructure for pathology diagnostics, there is a growing interest in implementing artificial intelligence (AI) algorithms for diagnostic purposes. This article provides an overview of the current status of the digital pathology infrastructure at the University Medical Center Utrecht and our roadmap for implementing AI algorithms in the next few years. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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Other

Jump to: Research, Review

28 pages, 2945 KiB

Open AccessSystematic Review

Virtual Versus Light Microscopy Usage among Students: A Systematic Review and Meta-Analytic Evidence in Medical Education

by Sabyasachi Maity, Samal Nauhria, Narendra Nayak, Shreya Nauhria, Tamara Coffin, Jadzia Wray, Sepehr Haerianardakani, Ramsagar Sah, Andrew Spruce, Yujin Jeong, Mary C. Maj, Abhimanyu Sharma, Nicole Okpara, Chidubem J. Ike, Reetuparna Nath, Jack Nelson and Anil V. Parwani

Diagnostics 2023, 13(3), 558; https://doi.org/10.3390/diagnostics13030558 - 02 Feb 2023

Cited by 6 | Viewed by 2557

Abstract

Background: The usage of whole-slide images has recently been gaining a foothold in medical education, training, and diagnosis. Objectives: The first objective of the current study was to compare academic performance on virtual microscopy (VM) and light microscopy (LM) for learning pathology, anatomy, [...] Read more.

Background: The usage of whole-slide images has recently been gaining a foothold in medical education, training, and diagnosis. Objectives: The first objective of the current study was to compare academic performance on virtual microscopy (VM) and light microscopy (LM) for learning pathology, anatomy, and histology in medical and dental students during the COVID-19 period. The second objective was to gather insight into various applications and usage of such technology for medical education. Materials and methods: Using the keywords “virtual microscopy” or “light microscopy” or “digital microscopy” and “medical” and “dental” students, databases (PubMed, Embase, Scopus, Cochrane, CINAHL, and Google Scholar) were searched. Hand searching and snowballing were also employed for article searching. After extracting the relevant data based on inclusion and execution criteria, the qualitative data were used for the systematic review and quantitative data were used for meta-analysis. The Newcastle Ottawa Scale (NOS) scale was used to assess the quality of the included studies. Additionally, we registered our systematic review protocol in the prospective register of systematic reviews (PROSPERO) with registration number CRD42020205583. Results: A total of 39 studies met the criteria to be included in the systematic review. Overall, results indicated a preference for this technology and better academic scores. Qualitative analyses reported improved academic scores, ease of use, and enhanced collaboration amongst students as the top advantages, whereas technical issues were a disadvantage. The performance comparison of virtual versus light microscopy meta-analysis included 19 studies. Most (10/39) studies were from medical universities in the USA. VM was mainly used for teaching pathology courses (25/39) at medical schools (30/39). Dental schools (10/39) have also reported using VM for teaching microscopy. The COVID-19 pandemic was responsible for the transition to VM use in 17/39 studies. The pooled effect size of 19 studies significantly demonstrated higher exam performance (SMD: 1.36 [95% CI: 0.75, 1.96], p < 0.001) among the students who used VM for their learning. Students in the VM group demonstrated significantly higher exam performance than LM in pathology (SMD: 0.85 [95% CI: 0.26, 1.44], p < 0.01) and histopathology (SMD: 1.25 [95% CI: 0.71, 1.78], p < 0.001). For histology (SMD: 1.67 [95% CI: −0.05, 3.40], p = 0.06), the result was insignificant. The overall analysis of 15 studies assessing exam performance showed significantly higher performance for both medical (SMD: 1.42 [95% CI: 0.59, 2.25], p < 0.001) and dental students (SMD: 0.58 [95% CI: 0.58, 0.79], p < 0.001). Conclusions: The results of qualitative and quantitative analyses show that VM technology and digitization of glass slides enhance the teaching and learning of microscopic aspects of disease. Additionally, the COVID-19 global health crisis has produced many challenges to overcome from a macroscopic to microscopic scale, for which modern virtual technology is the solution. Therefore, medical educators worldwide should incorporate newer teaching technologies in the curriculum for the success of the coming generation of health-care professionals. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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Graphical abstract

32 pages, 1270 KiB

Open AccessSystematic Review

Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review

by Athena Davri, Effrosyni Birbas, Theofilos Kanavos, Georgios Ntritsos, Nikolaos Giannakeas, Alexandros T. Tzallas and Anna Batistatou

Diagnostics 2022, 12(4), 837; https://doi.org/10.3390/diagnostics12040837 - 29 Mar 2022

Cited by 31 | Viewed by 6734

Abstract

Colorectal cancer (CRC) is the second most common cancer in women and the third most common in men, with an increasing incidence. Pathology diagnosis complemented with prognostic and predictive biomarker information is the first step for personalized treatment. The increased diagnostic load in [...] Read more.

Colorectal cancer (CRC) is the second most common cancer in women and the third most common in men, with an increasing incidence. Pathology diagnosis complemented with prognostic and predictive biomarker information is the first step for personalized treatment. The increased diagnostic load in the pathology laboratory, combined with the reported intra- and inter-variability in the assessment of biomarkers, has prompted the quest for reliable machine-based methods to be incorporated into the routine practice. Recently, Artificial Intelligence (AI) has made significant progress in the medical field, showing potential for clinical applications. Herein, we aim to systematically review the current research on AI in CRC image analysis. In histopathology, algorithms based on Deep Learning (DL) have the potential to assist in diagnosis, predict clinically relevant molecular phenotypes and microsatellite instability, identify histological features related to prognosis and correlated to metastasis, and assess the specific components of the tumor microenvironment. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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20 pages, 798 KiB

Open AccessGuidelines

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)

by Filippo Fraggetta, Vincenzo L’Imperio, David Ameisen, Rita Carvalho, Sabine Leh, Tim-Rasmus Kiehl, Mircea Serbanescu, Daniel Racoceanu, Vincenzo Della Mea, Antonio Polonia, Norman Zerbe and Catarina Eloy

Diagnostics 2021, 11(11), 2167; https://doi.org/10.3390/diagnostics11112167 - 22 Nov 2021

Cited by 50 | Viewed by 8240

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Digital Pathology: Records of Successful Implementations)

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