scholarly journals Digital Whole Slide Imaging Compared With Light Microscopy for Primary Diagnosis in Surgical Pathology

2020 ◽  
Vol 144 (10) ◽  
pp. 1245-1253 ◽  
Author(s):  
Alexander D. Borowsky ◽  
Eric F. Glassy ◽  
William Dean Wallace ◽  
Nathash S. Kallichanda ◽  
Cynthia A. Behling ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Diagnostic Category ◽  
Primary Diagnosis ◽  
Current Standard ◽  
Diagnostic Categories ◽  
Standard Glass ◽  
Specific Subset ◽  
Glass Slides ◽  
Major Discrepancy ◽  
Whole Slide Images

Context.— The adoption of digital capture of pathology slides as whole slide images (WSI) for educational and research applications has proven utility. Objective.— To compare pathologists' primary diagnoses derived from WSI versus the standard microscope. Because WSIs differ in format and method of observation compared with the current standard glass slide microscopy, this study is critical to potential clinical adoption of digital pathology. Design.— The study enrolled a total of 2045 cases enriched for more difficult diagnostic categories and represented as 5849 slides were curated and provided for diagnosis by a team of 19 reading pathologists separately as WSI or as glass slides viewed by light microscope. Cases were reviewed by each pathologist in both modalities in randomized order with a minimum 31-day washout between modality reads for each case. Each diagnosis was compared with the original clinical reference diagnosis by an independent central adjudication review. Results.— The overall major discrepancy rates were 3.64% for WSI review and 3.20% for manual slide review diagnosis methods, a difference of 0.44% (95% CI, −0.15 to 1.03). The time to review a case averaged 5.20 minutes for WSI and 4.95 minutes for glass slides. There was no specific subset of diagnostic category that showed higher rates of modality-specific discrepancy, though some categories showed greater discrepancy than others in both modalities. Conclusions.— WSIs are noninferior to traditional glass slides for primary diagnosis in anatomic pathology.

scholarly journals A Digital Pathology Solution to Resolve the Tissue Floater Conundrum

2020 ◽  
Author(s):  
Liron Pantanowitz ◽  
Pamela Michelow ◽  
Scott Hazelhurst ◽  
Shivam Kalra ◽  
Charles Choi ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Primary Diagnosis ◽  
Image Search ◽  
Molecular Tests ◽  
Tissue Identification ◽  
Digital Database ◽  
Glass Slides ◽  
Search Tool ◽  
Hematoxylin And Eosin ◽  
Whole Slide Images

Context.— Pathologists may encounter extraneous pieces of tissue (tissue floaters) on glass slides because of specimen cross-contamination. Troubleshooting this problem, including performing molecular tests for tissue identification if available, is time consuming and often does not satisfactorily resolve the problem. Objective.— To demonstrate the feasibility of using an image search tool to resolve the tissue floater conundrum. Design.— A glass slide was produced containing 2 separate hematoxylin and eosin (H&E)-stained tissue floaters. This fabricated slide was digitized along with the 2 slides containing the original tumors used to create these floaters. These slides were then embedded into a dataset of 2325 whole slide images comprising a wide variety of H&E stained diagnostic entities. Digital slides were broken up into patches and the patch features converted into barcodes for indexing and easy retrieval. A deep learning-based image search tool was employed to extract features from patches via barcodes, hence enabling image matching to each tissue floater. Results.— There was a very high likelihood of finding a correct tumor match for the queried tissue floater when searching the digital database. Search results repeatedly yielded a correct match within the top 3 retrieved images. The retrieval accuracy improved when greater proportions of the floater were selected. The time to run a search was completed within several milliseconds. Conclusions.— Using an image search tool offers pathologists an additional method to rapidly resolve the tissue floater conundrum, especially for those laboratories that have transitioned to going fully digital for primary diagnosis.

scholarly journals Whole-Slide Imaging Digital Pathology as a Platform for Teleconsultation: A Pilot Study Using Paired Subspecialist Correlations

2009 ◽  
Vol 133 (12) ◽  
pp. 1949-1953 ◽  
Author(s):  
David C. Wilbur ◽  
Kalil Madi ◽  
Robert B. Colvin ◽  
Lyn M. Duncan ◽  
William C. Faquin ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Glass Slide ◽  
Whole Slide Imaging ◽  
Improve Performance ◽  
Standard Glass ◽  
Digital Format ◽  
Glass Slides ◽  
Technical Issues ◽  
Fine Resolution ◽  
Whole Slide Images

Abstract Context.—Whole-slide imaging technology offers promise for rapid, Internet-based telepathology consultations between institutions. Before implementation, technical issues, pathologist adaptability, and morphologic pitfalls must be well characterized. Objective.—To determine whether interpretation of whole-slide images differed from glass-slide interpretation in difficult surgical pathology cases. Design.—Diagnostically challenging pathology slides from a variety of anatomic sites from an outside laboratory were scanned into whole digital format. Digital and glass slides were independently diagnosed by 2 subspecialty pathologists. Reference, digital, and glass-slide interpretations were compared. Operator comments on technical issues were gathered. Results.—Fifty-three case pairs were analyzed. There was agreement among digital, glass, and reference diagnoses in 45 cases (85%) and between digital and glass diagnoses in 48 (91%) cases. There were 5 digital cases (9%) discordant with both reference and glass diagnoses. Further review of each of these cases indicated an incorrect digital whole-slide interpretation. Neoplastic cases showed better correlation (93%) than did cases of nonneoplastic disease (88%). Comments on discordant cases related to digital whole technology focused on issues such as fine resolution and navigating ability at high magnification. Conclusions.—Overall concordance between digital whole-slide and standard glass-slide interpretations was good at 91%. Adjustments in technology, case selection, and technology familiarization should improve performance, making digital whole-slide review feasible for broader telepathology subspecialty consultation applications.

scholarly journals A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association

2018 ◽  
Vol 143 (2) ◽  
pp. 222-234 ◽  
Author(s):  
Mark D. Zarella ◽  
Douglas Bowman; ◽  
Famke Aeffner ◽  
Navid Farahani ◽  
Albert Xthona; ◽  
...  
Keyword(s):  
Practical Knowledge ◽  
Digital Pathology ◽  
Executive Leadership ◽  
The United States ◽  
White Paper ◽  
Primary Diagnosis ◽  
Basic Function ◽  
Whole Slide Imaging ◽  
Interinstitutional Collaboration ◽  
Glass Slides

Context.— 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. Its basic function is to digitize glass slides, but its impact on pathology workflows, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and intrainstitutional and interinstitutional collaboration exemplifies a significant innovative movement with far-reaching effects. Although the benefits of WSI to pathology practices, academic centers, and research institutions are many, the complexities of implementation remain an obstacle to widespread adoption. In the wake of the first regulatory clearance of WSI for primary diagnosis in the United States, some barriers to adoption have fallen. Nevertheless, implementation of WSI remains a difficult prospect for many institutions, especially those with stakeholders unfamiliar with the technologies necessary to implement a system or who cannot effectively communicate to executive leadership and sponsors the benefits of a technology that may lack clear and immediate reimbursement opportunity. Objectives.— To present an overview of WSI technology—present and future—and to demonstrate several immediate applications of WSI that support pathology practice, medical education, research, and collaboration. Data Sources.— Peer-reviewed literature was reviewed by pathologists, scientists, and technologists who have practical knowledge of and experience with WSI. Conclusions.— Implementation of WSI is a multifaceted and inherently multidisciplinary endeavor requiring contributions from pathologists, technologists, and executive leadership. Improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology, can help prospective users identify the best path for success.

scholarly journals Complete Digital Pathology for Routine Histopathology Diagnosis in a Multicenter Hospital Network

2019 ◽  
Vol 144 (2) ◽  
pp. 221-228 ◽  
Author(s):  
Juan Antonio Retamero ◽  
Jose Aneiros-Fernandez ◽  
Raimundo G. del Moral
Keyword(s):  
Management System ◽  
Digital Pathology ◽  
Primary Diagnosis ◽  
Computer Assisted ◽  
Image Management ◽  
University Hospitals ◽  
Implementation Phase ◽  
Sample Tracking ◽  
Glass Slides ◽  
Image Management System

Context.— Complete digital pathology and whole slide imaging for routine histopathology diagnosis is currently in use in few laboratories worldwide. Granada University Hospitals, Spain, which comprises 4 hospitals, adopted full digital pathology for primary histopathology diagnosis in 2016. Objective.— To describe the methodology adopted and the resulting experience at Granada University Hospitals in transitioning to full digital diagnosis. Design.— All histopathology glass slides generated for routine diagnosis were digitized at ×40 using the Philips IntelliSite Pathology Solution, which includes an ultrafast scanner and an image management system. All hematoxylin-eosin–stained preparations and immunohistochemistry and histochemistry slides were digitized. The existing sample-tracking software and image management system were integrated to allow data interchange through the Health Level 7 protocol. Results.— Circa 160 000 specimens have been signed out using digital pathology for primary diagnosis. This comprises more than 800 000 digitized glass slides. The scanning error rate during the implementation phase was below 1.5%, and subsequent workflow optimization rendered this rate negligible. Since implementation, Granada University Hospitals pathologists have signed out 21% more cases per year on average. Conclusions.— Digital pathology is an adequate medium for primary histopathology diagnosis. Successful digitization relies on existing sample tracking and integration of the information technology infrastructure. Rapid and reliable scanning at ×40 equivalent was key to the transition to a fully digital workflow. Digital pathology resulted in efficiency gains in the preanalytical and analytical phases, and created the basis for computational pathology: the use of computer-assisted tools to aid diagnosis.

Clinical Examination and Validation of Primary Diagnosis in Anatomic Pathology Using Whole Slide Digital Images

2011 ◽  
Vol 135 (3) ◽  
pp. 372-378
Author(s):  
Drazen M Jukić ◽  
Laura M Drogowski ◽  
Jamie Martina ◽  
Anil V Parwani
Keyword(s):  
Clinical Examination ◽  
Digital Images ◽  
Digital Pathology ◽  
Primary Diagnosis ◽  
Anatomic Pathology ◽  
Glass Slides ◽  
Diagnostic Certainty ◽  
Low Rate ◽  
Diagnostic Consistency

Abstract Context.—Novel anatomic pathology technologies allow pathologists to digitally view and diagnose cases. Although digital pathology advocates champion its strengths and move to integrate it into practice and workflow, the capabilities and limitations of digital slides have not been fully investigated. Objectives.—To estimate intrapathologist diagnostic discrepancy between glass and digital slides and to determine pathologists' diagnostic certainty when diagnosing with the 2 formats. Design.—Intrapathologist diagnostic consistency between glass and digital slides was measured. Three pathologists diagnosed 101 cases digitally and with corresponding glass slides. Discrepancies between formats were evaluated, and diagnostic precision and certainty were compared. Results.—A total of 606 diagnoses were evaluated in pairs (202 per pathologist). Seven cases did not transfer to the database and were eliminated from further study. We report no discrepancies between media in 75%, 87%, and 83% of the cases diagnosed by the 3 pathologists, respectively; significant discrepancies were identified in 3%, 3%, and 7% of cases by each pathologist. In total, we identified significant clinical and therapeutic discrepancies in 13 of 296 cases (4.4%). The certainty values provided by each pathologist were similar between formats. Conclusions.—This study did not detect significant differences between diagnoses based on digital and glass slides. We believe that this study further supports the integration of digital slides into pathology workflow, particularly considering the low rate of discrepancy documented here.

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

Diagnostics ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1916
Author(s):  
Filippo Fraggetta ◽  
Alessandro Caputo ◽  
Rosa Guglielmino ◽  
Maria Giovanna Pellegrino ◽  
Giampaolo Runza ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Primary Diagnosis ◽  
Pathology Laboratory ◽  
Digital Workflow ◽  
Pathology Department ◽  
Health Level 7 ◽  
2D Barcode ◽  
Glass Slides ◽  
Rapid Transition ◽  
Routine Assessment

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.

scholarly journals Artificial Intelligence and Digital Microscopy Applications in Diagnostic Hematopathology

Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 797 ◽  
Author(s):  
Hanadi El El Achi ◽  
Joseph D. Khoury
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Digital Images ◽  
Digital Pathology ◽  
Digital Microscopy ◽  
Clinical Environment ◽  
Lymphoproliferative Diseases ◽  
Glass Slides ◽  
Pathology Data ◽  
Whole Slide Images

Digital Pathology is the process of converting histology glass slides to digital images using sophisticated computerized technology to facilitate acquisition, evaluation, storage, and portability of histologic information. By its nature, digitization of analog histology data renders it amenable to analysis using deep learning/artificial intelligence (DL/AI) techniques. The application of DL/AI to digital pathology data holds promise, even if the scope of use cases and regulatory framework for deploying such applications in the clinical environment remains in the early stages. Recent studies using whole-slide images and DL/AI to detect histologic abnormalities in general and cancer in particular have shown encouraging results. In this review, we focus on these emerging technologies intended for use in diagnostic hematology and the evaluation of lymphoproliferative diseases.

Proof of Concept: The Use of Whole-Slide Images (WSI) for Peer Review of Tissues on Routine Regulatory Toxicology Studies

2021 ◽  
pp. 019262332098325
Author(s):  
Alys E. Bradley ◽  
Maurice G. Cary ◽  
Kaori Isobe ◽  
Stuart Naylor ◽  
Stephen Drew
Keyword(s):  
Peer Review ◽  
Proof Of Concept ◽  
Regulatory Toxicology ◽  
Glass Slides ◽  
Microscopic Findings ◽  
Slight Discrepancy ◽  
Whole Slide Images ◽  
Diagnostic Discrepancies

This Proof of Concept (POC) study was to assess whether assessment of whole slide images (WSI) of the 2 target tissues for a contemporaneous peer review can elicit concordant results to the findings generated by the Study Pathologist from the glass slides. Well-focused WSI of liver and spleen from 4 groups of mice, that had previously been diagnosed to be the target tissues by an experienced veterinary toxicologic pathologist examining glass slides, were independently reviewed by 3 veterinary pathologists with varying experience in assessment of WSIs. Diagnostic discrepancies were then reviewed by an experienced adjudicating pathologist. Assessment of microscopic findings using WSI showed concordance with the glass slides, with only slight discrepancy in severity grades noted. None of the lesions recorded by the Study pathologist were “missed” and no lesions were added by the pathologists evaluating WSIs, thus demonstrating equivalence of the WSI to glass slides for this study.

scholarly journals Two Ensemble-CNN Approaches for Colorectal Cancer Tissue Type Classification

2021 ◽  
Vol 7 (3) ◽  
pp. 51
Author(s):  
Emanuela Paladini ◽  
Edoardo Vantaggiato ◽  
Fares Bougourzi ◽  
Cosimo Distante ◽  
Abdenour Hadid ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Digital Pathology ◽  
Texture Features ◽  
Tissue Type ◽  
Cancer Tissue ◽  
Learning Methods ◽  
Feature Based ◽  
Type Classification ◽  
Whole Slide Images

In recent years, automatic tissue phenotyping has attracted increasing interest in the Digital Pathology (DP) field. For Colorectal Cancer (CRC), tissue phenotyping can diagnose the cancer and differentiate between different cancer grades. The development of Whole Slide Images (WSIs) has provided the required data for creating automatic tissue phenotyping systems. In this paper, we study different hand-crafted feature-based and deep learning methods using two popular multi-classes CRC-tissue-type databases: Kather-CRC-2016 and CRC-TP. For the hand-crafted features, we use two texture descriptors (LPQ and BSIF) and their combination. In addition, two classifiers are used (SVM and NN) to classify the texture features into distinct CRC tissue types. For the deep learning methods, we evaluate four Convolutional Neural Network (CNN) architectures (ResNet-101, ResNeXt-50, Inception-v3, and DenseNet-161). Moreover, we propose two Ensemble CNN approaches: Mean-Ensemble-CNN and NN-Ensemble-CNN. The experimental results show that the proposed approaches outperformed the hand-crafted feature-based methods, CNN architectures and the state-of-the-art methods in both databases.

scholarly journals A deep-learning-based prognostic nomogram integrating microscopic digital pathology and macroscopic magnetic resonance images in nasopharyngeal carcinoma: a multi-cohort study

2020 ◽  
Vol 12 ◽  
pp. 175883592097141
Author(s):  
Fan Zhang ◽  
Lian-Zhen Zhong ◽  
Xun Zhao ◽  
Di Dong ◽  
Ji-Jin Yao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Magnetic Resonance ◽  
Nasopharyngeal Carcinoma ◽  
Treatment Failure ◽  
Digital Pathology ◽  
Imaging Features ◽  
Multi Scale ◽  
External Test ◽  
Whole Slide Images ◽  
Independent Cohort

Background: To explore the prognostic value of radiomics-based and digital pathology-based imaging biomarkers from macroscopic magnetic resonance imaging (MRI) and microscopic whole-slide images for patients with nasopharyngeal carcinoma (NPC). Methods: We recruited 220 NPC patients and divided them into training ( n = 132), internal test ( n = 44), and external test ( n = 44) cohorts. The primary endpoint was failure-free survival (FFS). Radiomic features were extracted from pretreatment MRI and selected and integrated into a radiomic signature. The histopathological signature was extracted from whole-slide images of biopsy specimens using an end-to-end deep-learning method. Incorporating two signatures and independent clinical factors, a multi-scale nomogram was constructed. We also tested the correlation between the key imaging features and genetic alternations in an independent cohort of 16 patients (biological test cohort). Results: Both radiomic and histopathologic signatures presented significant associations with treatment failure in the three cohorts (C-index: 0.689–0.779, all p < 0.050). The multi-scale nomogram showed a consistent significant improvement for predicting treatment failure compared with the clinical model in the training (C-index: 0.817 versus 0.730, p < 0.050), internal test (C-index: 0.828 versus 0.602, p < 0.050) and external test (C-index: 0.834 versus 0.679, p < 0.050) cohorts. Furthermore, patients were stratified successfully into two groups with distinguishable prognosis (log-rank p < 0.0010) using our nomogram. We also found that two texture features were related to the genetic alternations of chromatin remodeling pathways in another independent cohort. Conclusion: The multi-scale imaging features showed a complementary value in prognostic prediction and may improve individualized treatment in NPC.

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