Clinical digital neuropathology: experience and observations from a departmental digital pathology training programme, validation and deployment

2020 ◽  
pp. jclinpath-2019-206343 ◽  
Author(s):  
Bethany Jill Williams ◽  
Azzam Ismail ◽  
Arundhati Chakrabarty ◽  
Darren Treanor
Keyword(s):  
Frozen Section ◽  
Digital Pathology ◽  
Ground Truth ◽  
Training Programme ◽  
Primary Diagnosis ◽  
Glass Slide ◽  
Digital Slide ◽  
Neuropathological Diagnosis ◽  
Pathology Training ◽  
Diagnostic Pitfalls

AimTo train and individually validate the neuropathologists in digital primary diagnosis and frozen section reporting using a novel protocol endorsed by the Royal College of Pathologists. The protocol allows early exposure to live digital reporting in a risk mitigated environment.MethodsTwo specialist neuropathologists completed training in the use of a digital microscopy system for primary neuropathological diagnosis and frozen section assessment. Participants were exposed to training sets of 20 histology cases and 10 frozen sections designed to help them identify their personal digital diagnostic pitfalls. Following this, the pathologists viewed 340 live, complete neuropathology cases. All primary diagnoses were made on digital slides with immediate glass slide reconciliation before final case sign-out.ResultsThere was 100% clinical concordance between the digital slide and glass slide assessment of frozen section cases for each pathologist, and these assessments corresponded with the ground truth diagnoses obtained from examination of definitive histology. For primary diagnosis, there was complete clinical concordance between digital slide and glass slide diagnosis in 98.1% of cases. The majority of discordances were related to grading differences attributable to mitotic count differences.ConclusionNeuropathologists can develop the ability to make primary digital diagnosis competently and confidently following a course of individual training and validation.

Digital pathology for intraoperative frozen section diagnosis of thoracic specimens: an evaluation of a system using remote sampling and whole slide imaging diagnosis

2019 ◽  
Vol 73 (8) ◽  
pp. 503-506
Author(s):  
Jon Griffin ◽  
Panagiota Kitsanta ◽  
Branko Perunovic ◽  
S Kim Suvarna ◽  
Jonathan Bury
Keyword(s):  
Critical Incident ◽  
Frozen Section ◽  
Digital Pathology ◽  
Ground Truth ◽  
Final Diagnosis ◽  
Glass Slide ◽  
Whole Slide Imaging ◽  
Digital Slide ◽  
Frozen Section Diagnosis ◽  
Service Reorganisation

BackgroundDigital pathology is now used for primary diagnostic work as well as teaching, research and consultation. In our multisite institution service reorganisation led to histopathology being located in a separate hospital from some surgical specialities. We implemented remotely supervised specimen sampling and frozen section diagnosis using digital pathology. In this study we assessed the concordance of glass and digital slide diagnosis using this system.MethodsWe reviewed cases from the first 2 years of digital frozen section reporting at our institution. Cases with potential digital to glass slide discordance were reviewed by three experienced thoracic histopathologists. The reasons for discordance were determined and common themes identified. We also reviewed critical incidents relating to digital pathology during the study period.ResultsThe study population comprised 211 cases. Frozen section to final diagnosis concordance between digital and glass slide diagnosis was found in 196 (92.6%) cases. The 15 potentially discordant cases were reviewed. Intraobserver concordance between glass and digital slide review ranged from 9/15 to 12/15 cases across the three pathologists. Glass slide review diagnosis showed better concordance with ground truth in two cases; digital slide review was more accurate in two cases. One relevant critical incident was identified during the study period.DiscussionThis is the largest study to examine digital pathology for thoracic frozen section diagnosis and shows that this is a safe and feasible alternative to glass slide diagnosis. Discordance between digital and glass slide diagnoses were unrelated to the processes of whole slide imaging and digital microscopy.

scholarly journals DeepScope: Nonintrusive Whole Slide Saliency Annotation and Prediction from Pathologists at the Microscope

2016 ◽  
Author(s):  
Andrew J. Schaumberg ◽  
S. Joseph Sirintrapun ◽  
Hikmat A. Al-Ahmadie ◽  
Peter J. Schüffler ◽  
Thomas J. Fuchs
Keyword(s):  
Large Scale ◽  
Digital Pathology ◽  
Image Data ◽  
Clinical Work ◽  
The United States ◽  
Saliency Map ◽  
Primary Diagnosis ◽  
Observation Time ◽  
Glass Slide ◽  
Treasure Chest

AbstractModern digital pathology departments have grown to produce whole-slide image data at petabyte scale, an unprecedented treasure chest for medical machine learning tasks. Unfortunately, most digital slides are not annotated at the image level, hindering large-scale application of supervised learning. Manual labeling is prohibitive, requiring pathologists with decades of training and outstanding clinical service responsibilities. This problem is further aggravated by the United States Food and Drug Administration’s ruling that primary diagnosis must come from a glass slide rather than a digital image. We present the first end-to-end framework to overcome this problem, gathering annotations in a nonintrusive manner during a pathologist’s routine clinical work: (i) microscope-specific 3D-printed commodity camera mounts are used to video record the glass-slide-based clinical diagnosis process; (ii) after routine scanning of the whole slide, the video frames are registered to the digital slide; (iii) motion and observation time are estimated to generate a spatial and temporal saliency map of the whole slide. Demonstrating the utility of these annotations, we train a convolutional neural network that detects diagnosis-relevant salient regions, then report accuracy of 85.15% in bladder and 91.40% in prostate, with 75.00% accuracy when training on prostate but predicting in bladder, despite different pathologists examining the different tissues. When training on one patient but testing on another, AUROC in bladder is 0.7929±0.1109 and in prostate is 0.9568±0.0374. Our tool is available at https://bitbucket.org/aschaumberg/deepscope.

scholarly journals Implementation of Whole Slide Imaging for Clinical Purposes: Issues to Consider From the Perspective of Early Adopters

2017 ◽  
Vol 141 (7) ◽  
pp. 944-959 ◽  
Author(s):  
Andrew J. Evans ◽  
Mohamed E. Salama ◽  
Walter H. Henricks ◽  
Liron Pantanowitz
Keyword(s):  
Transition Period ◽  
Clinical Laboratory ◽  
Panel Discussion ◽  
Digital Pathology ◽  
Primary Diagnosis ◽  
Glass Slide ◽  
Whole Slide Imaging ◽  
Early Adopters ◽  
Implementation Team ◽  
Intended Use

Context.— There is growing interest in the use of digital pathology, especially whole slide imaging, for diagnostic purposes. Many issues need to be considered when incorporating this technology into a clinical laboratory. The College of American Pathologists (CAP) established a Digital Pathology Committee to support the development of CAP programs related to digital pathology. One of its many initiatives was a panel discussion entitled “Implementing Whole-Slide Imaging for Clinical Use: What to Do and What to Avoid,” given for 3 years at the CAP annual meetings starting in 2014. Objectives.— To review major issues to consider when implementing whole slide imaging for clinical purposes as covered during the panel discussion. Design.— The views expressed and recommendations given are based primarily on the personal experience of the authors as early adopters of this technology. It is not intended to be an exhaustive review of digital pathology. Results.— Implementation is best approached in phases. Early efforts are directed toward identifying initial clinical applications and assembling an implementation team. Scanner selection should be based on intended use and budget. Recognizing pathologist concerns over the use of digital pathology for diagnostic purposes, ensuring adequate training, and performing appropriate validation studies will enhance adoption. Once implemented, the transition period from glass slide to image-based diagnostics will be associated with challenges, especially those related to a hybrid glass slide–digital slide workflow. Conclusions.— With appropriate preparation, planning, and stepwise implementation, whole slide imaging can be used safely and reliably for frozen sections, consultation, quality assurance, and primary diagnosis.

Practical guide to training and validation for primary diagnosis with digital pathology

2019 ◽  
Vol 73 (7) ◽  
pp. 418-422 ◽  
Author(s):  
Bethany Jill Williams ◽  
Darren Treanor
Keyword(s):  
Royal College ◽  
Digital Pathology ◽  
Clinical Pathology ◽  
Evidence Base ◽  
Primary Diagnosis ◽  
Teaching Hospitals ◽  
Digital Slide ◽  
Practical Advice ◽  
Practical Guide ◽  
Current Standards

Numerous clinical pathology departments are deploying or planning to deploy digital pathology systems for all or part of their diagnostic output. Digital pathology is an evolving technology, and it is important that departments uphold or improve on current standards. Leeds Teaching Hospitals NHS Trust has been scanning 100% of histology slides since September 2018. In this practical paper, we will share our approach to training and validation, which has been incorporated into the Royal College of Pathologists’ guidance for digital pathology implementation. We will offer an overview of the Royal College endorsed training and validation protocol and the evidence base on which it is based. We will provide practical advice on implementation of the protocol and highlight areas of digital reporting that can prove difficult for the novice digital pathologist. In addition, we will share a detailed topographical list of types of diagnostic tasks and features which should form the basis of digital slide training sets.

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 Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Christian Crouzet ◽  
Gwangjin Jeong ◽  
Rachel H. Chae ◽  
Krystal T. LoPresti ◽  
Cody E. Dunn ◽  
...  
Keyword(s):  
Deep Learning ◽  
Prussian Blue ◽  
Processing Speed ◽  
Digital Pathology ◽  
Ground Truth ◽  
Individual Variability ◽  
Rgb Images ◽  
Cerebral Microhemorrhages ◽  
Phasor Analysis ◽  
Better Than

AbstractCerebral microhemorrhages (CMHs) are associated with cerebrovascular disease, cognitive impairment, and normal aging. One method to study CMHs is to analyze histological sections (5–40 μm) stained with Prussian blue. Currently, users manually and subjectively identify and quantify Prussian blue-stained regions of interest, which is prone to inter-individual variability and can lead to significant delays in data analysis. To improve this labor-intensive process, we developed and compared three digital pathology approaches to identify and quantify CMHs from Prussian blue-stained brain sections: (1) ratiometric analysis of RGB pixel values, (2) phasor analysis of RGB images, and (3) deep learning using a mask region-based convolutional neural network. We applied these approaches to a preclinical mouse model of inflammation-induced CMHs. One-hundred CMHs were imaged using a 20 × objective and RGB color camera. To determine the ground truth, four users independently annotated Prussian blue-labeled CMHs. The deep learning and ratiometric approaches performed better than the phasor analysis approach compared to the ground truth. The deep learning approach had the most precision of the three methods. The ratiometric approach has the most versatility and maintained accuracy, albeit with less precision. Our data suggest that implementing these methods to analyze CMH images can drastically increase the processing speed while maintaining precision and accuracy.

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 Update on the current opinion, status and future development of digital pathology in Switzerland in light of COVID-19

2021 ◽  
pp. jclinpath-2021-207768
Author(s):  
Viktor Hendrik Koelzer ◽  
Rainer Grobholz ◽  
Inti Zlobec ◽  
Andrew Janowczyk
Keyword(s):  
Early Stage ◽  
Digital Pathology ◽  
Primary Diagnosis ◽  
Imaging Systems ◽  
Whole Slide Imaging ◽  
University Hospitals ◽  
Primary Diagnostics ◽  
Personal Experiences ◽  
Standard Operating ◽  
Analogue To Digital

AimsThe transition from analogue to digital pathology (DP) in Switzerland has coincided with the COVID-19 crisis. The Swiss Digital Pathology Consortium conducted a national survey to assess the experience of pathologists in dealing with the challenges of the pandemic and how this has influenced the outlook and adoption of DP.MethodsA survey containing 20 questions relating to DP, personal experiences and challenges during the pandemic was addressed to Swiss pathologists at different experience stages in private practice, community and university hospitals.ResultsAll 74 respondents were pathologists, with 81.1% reporting more than 5 years of diagnostic service experience. 32.5% reported having read 100 digital slides or more in a diagnostic context. 39.2% reported using whole slide imaging systems at their primary workplace. Key DP use cases before the COVID-19 lockdown were tumour boards (39.2%), education (60.8%) and research (44.6%), with DP used for primary diagnosis in 13.5%. During the COVID-19 crisis, the use of DP for primary diagnostics more than doubled (30% vs 13.5%), with internal consults as important drivers (22.5% vs 16.5%), while research use (25% vs 44.6%) and external consults (17.5% vs 41.9%) strongly decreased. Key challenges identified included a lack of established standard operating procedures and availability of specialised hardware and software.ConclusionsThis survey indicates that the crisis acted as a catalyst in promoting DP adoption in centres where basic workflows were already established while posing major technical and organisational challenges in institutions that were at an early stage of DP implementation.

scholarly journals Intraoperative frozen section consultation by remote whole-slide imaging analysis –validation and comparison to robotic remote microscopy

2019 ◽  
Vol 73 (6) ◽  
pp. 350-352 ◽  
Author(s):  
Thomas Menter ◽  
Stefan Nicolet ◽  
Daniel Baumhoer ◽  
Markus Tolnay ◽  
Alexandar Tzankov
Keyword(s):  
Frozen Section ◽  
Digital Pathology ◽  
Handling Time ◽  
Image Resolution ◽  
Imaging Analysis ◽  
Specimen Handling ◽  
Intraoperative Frozen Section ◽  
Promising Tool ◽  
Digital Microscope ◽  
Slide Image

Digital pathology including whole slide image (WSI) acquisition is a promising tool for histopathologic teleconsultation. To test and validate the use of WSI in comparison with robotic microscopy for intraoperative frozen section consultation of peripheral hospitals serviced by our department, we compared the VENTANA DP 200 slide scanner with an established remote-controlled digital microscope. Thirty cases were retrospectively analysed. In comparison with a median specimen handling time of 19 min using remote-controlled microscopy, the WSI handling was significantly shorter (11 min, p=0.0089) and offered better image quality, for example, allowing to detect a positive resection margin by a malignant melanoma that had been missed using the former system. Prospectively assessed on 12 cases, the median handling time was 6 min. Here, we demonstrate the applicability and the advantages of WSI for intraoperative frozen section teleconsultation. WSI-based telepathology prooves to be an efficient and reliable tool providing superior turn-around time and image resolution.

scholarly journals Comparative assessment of digital pathology systems for primary diagnosis

2021 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Rajiv Kumar ◽  
Sathyanarayanan Rajaganesan ◽  
Vidya Rao ◽  
Trupti Pai ◽  
Neha Mittal ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Primary Diagnosis ◽  
Comparative Assessment
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