APW-EDM White Paper

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Foreword

This is the collaborative space of the white paper "Anatomic Pathology Workflow in an Era of Digital Medicine (APW-EDM)"

The latest draft of the white paper is downloadable from this folder

Temporary documents from Nicholas Jones available via dropbox

Current contributors are:

  • Raj C. Dash, MD,
  • Riki Merrick,
  • Francesca Frexia,
  • Francesca Vanzo, ,
  • John David L. Nolen,
  • Dan Rutz,
  • Nicholas C. Jones,
  • Gunter Haroske,
  • François Macary,
  • Laurent Duval

Introduction

This document, the IHE PaLM “Anatomic Pathology Workflow in an Era of Digital Imaging” White Paper, describes use cases, data elements, actors, and transactions necessary to support anatomic pathology workflows that leverage digital technologies. Abbreviation for the title is APW-EDM.

This white paper lays out a collection of future integration profiles to address how vended systems for supporting anatomic pathology workflows interact and is intended to replace the former Anatomic Pathology Workflow (APW) profile. The first objective is to better take into account the latest advancements in digital imaging, spanning but not necessarily limited to two primary aspects of anatomic pathology workflow:

  • the gross/macroscopic examination leveraging state-of-the art more interoperable imaging modalities,
  • the histologic/microscopic examination taking advantage of whole slide imaging technology.

The second objective is to break down the APW profile into a set of smaller, easier to implement building blocks, each of these focusing on one key aspect of the anatomic pathology digital workflow. The expectation is to collect sufficient feedback from all stakehoders of digital pathology (vendors, pathologists, institutions) in order to confirm and/or refine this set of profiles before starting to build them as new supplements to the Pathology and Laboratory Medicine Technical Framework.

At a collaborative meeting of IHE PALM and DICOM in May 2018, work effort prioritization was discussed. Many of the use cases require image acquisition as a fundamental prerequisite. The consensus of the group was to pursue an in depth evaluation and produce detailed documentation as a first, short term effort focused on image acquisition workflow, actors, and transactions. Digital asset identification may be one of the elements flushed out as part of the initial image acquisition interoperability effort although there was some discussion on whether this was a necessity.

Open Issues

  • APW-EDM-01: Involve industrial offer for archiving and communication of whole slide images, as well as slide scanner manufacturers
  • APW-EDM-02: Check the market for imaging modalities, PACS, and image reviewing and annotating software solutions, supporting the DICOM standard with the DICOM 122 supplement “Specimen Module and Revised Pathology SOP Classes” and the DICOM 145 supplement “Whole Slide Microscopic Image IOD and SOP Classes”

Closed Issues

  • APW-EDM-03: Tissue microarrays may break the current specimen model. DICOM does cover this as a use case. Tissue microarrays are not used in clinical care, and so are left out of the scope of the profiles that will be derived from this white paper.

Use Cases

Use Case #1: Image Slides for Secondary Review / Consultation

Contributor assigned: Nicholas C. Jones, edited by RCD 5/20/2018

There are numerous contexts for consultation requests which have subtle, but important differences. Understanding these contexts and the pertinent variations for workflow are necessary to understand systems design, management, and operations for secondary reviews.

  • 1.a. Pathologist requested consults, pre-primary diagnosis.
    • 1.a.1. Intra-institutional: The pathologist is requesting a second opinion (through digital review) to another pathologist at their institution, either at the same site or another site in their network.
    • 1.a.2. Inter-institutional: The requester pathologist is requesting consultation from an outside hospital, usually due to the challenge of the case or the need for an external subspecialist.
  • 1.b. Patient requested second opinion, post-primary diagnosis.
  • 1.c. Physician requested second opinion, post-primary diagnosis
  • 1.d. Second-opinion broker requests, post-primary diagnosis.
  • 1.e. Legal cases, post-primary diagnosis.
  • 1.f. Consultation for intraoperative interpretations of frozen section or rapid FNA slides.

Notes:

  • 1. Relative to terminology we will call the requesting party the requester, and the person fulfilling that request the consultant. Also note that all references to "second opinions" could also mean third, or fourth opinions, especially if the original primary/final diagnosis was in disagreement with the true second opinion.
  • 2. Please also refer to additional descriptive text moved to discussion page.

References:

  • 1. NCJ's Consultation Workshop ppt from 2015 DPA

Related Niche Use Case: Sub-contracting for special analyses on specimens (Gunter Haroske)

Created as increasing workload sub-contracted to special laboratories, e.g. for molecular analyses.

  • Specimen collected and transported
  • Specimen gross exam with possible digital imaging and annotation
  • Specimen processing
  • Glass slides produced as usual
  • All glass slides fed into high volume automated digital scanner
  • Scanner tags images requiring manual intervention
  • Digital images deposited in network share, VNA, or PACS
  • Interface message to LIS sent as each barcode read off slide
  • Acknowledgment from LIS indicates case is valid and ready for association with digital slide assets
  • Additional message sent when slide digitization completed
  • Interface message sent every time slide viewed or annotated
  • Case with all digital assets analysed by the pathologist
  • Selection of relevant assets/slides/blocks for consultation or sub-contracting
  • Mailing of relevant assets/slides/blocks to external lab
  • AP reporting (preliminary)
  • Mailing of the (preliminary) report
  • Receiving results of consultation / sub-contracted tests
  • critical reflexion
  • AP reporting (synoptic, final)
  • Mailing of the final synoptic report.

Use Case #2: Immunohistochemistry Positive Control Slides

Contributor assigned: Raj Dash

Creating digital copies of immunohistochemistry (IHC) positive control slides to preclude the need for creating multiple positive control slides for distribution to pathologists

The value proposition for this use case is in savings in application of expensive IHC antibody to multiple glass slides. Standard workflow calls for distribution of positive control stained glass slides to pathologists interpreting patient tissue reactivity to a particular antibody. If a single glass slide can be created for a single antibody being run in a particular batch and have that slide digitized and made available to all pathologists electronically, the quantity of expensive antibody utilized can be reduced.

  • Request for IHC stain processed as usual
  • Only one IHC positive control run per batch in which a particular antibody
  • IHC positive control slides imaged and saved to network folder
  • Positive controls NOT distributed as physical glass slides resulting in cost savings
  • Glass IHC slides reviewed by pathologist but same positive control reviewed digitally by all pathologists for a given IHC (e.g. only a single cytokeratin positive control slide is created during a batch run even if requested across many different patient samples)

Please note that this imputes the need to have one slide associated with multiple cases. However, typical workflow today does NOT require a formal linkage between the positive control and specific patient case records within laboratory information systems. Having metadata that reflects the date of testing for both the IHC testing on patient slides and the creation of positive antibody controls will be sufficient. Generally speaking if a positive control fails completely, IHC laboratory quality control should hold patient material and repeat testing. In most circumstances there is subtle variation in antibody staining for which review of positive control staining is imperative. Once this has been performed, persistence of this digital asset need not be maintained. Most laboratories will dispose of positive control slides when submitted for filing. Some pathology departments may favor maintaining positive control images for a period of time. Information systems that manage digitized positive control slides should be able to organize slides not just by case accession number but also by a lab-specific batch number and/or by date of testing and have those images explicitly dissociated with an LIS patient case record but readily retrievable at the time of initial case review for primary diagnosis applications.

Use Case #3: Managing Digital Assets for Primary Diagnosis

Contributor assigned: Raj Dash, JD Nolen

These workflows include use of whole slide images for primary diagnosis. The first workflow described is a general workflow for glass slide production in a surgical pathology laboratory, followed by modification for a digital pathology sign out rather than direct transport of slides to the pathologist for viewing under a microscope.

Primary workflow steps and considerations to create digital copies of all glass slides for primary diagnosis:

  • Glass slides produced as usual
    • Specimen collected and transported
    • Specimen gross exam with possible digital imaging and annotation
    • Specimen processing
    • Block embedding in paraffin
    • Slide generation through block cutting
    • The glass slide may be manually stained or placed in an automated stainer, which might be optionally interfaced with the AP-LIS to draw forth information on precisely what type of stain should be performed on the unstained tissue present glass slide
    • The stained slide is cover-slipped using mounting medium
    • The stained slide is dried sufficiently to be placed into a digital scanner
  • All glass slides fed into high volume automated digital scanner
  • Scanner reads label on glass slide and interprets barcode, which reflects the accession number, block and slide level in a hierarchical manner. The barcode may be preceded and followed by a delimiter so that interpreting software recognizes the presence of a scanning event
    • For example, \SP18-000555 B3-L2\, would indicate the 555th case accessioned in the year 2018, the second container designated "B", the third block of tissue submitted during gross examination, and the second deepest level cut by the histotechnologist for placement on a glass slide.
    • The scanner may communicate with the AP-LIS to adjust parameters specifically for the glass slide being scanned
      • A unidirectional interface may push parameters into a buffer in the scanner in expectation of physical loading of the glass slide OR
        • Upon completion of scanning and storage of image, the image storage system will indicate to AP-LIS the availability of a digital resource for viewing
      • A bidirectional interface may request and pull parameters from the AP-LIS as glass slides are recognized as having been loaded into the scanner
        • Upon completion of scanning and storage of image, the scanner will indicate to AP-LIS the availability of a digital resource for viewing
  • Scanner tags images requiring manual intervention
  • Digital images ultimately deposited in a network share, vendor neutral archive (VNA), or picture archiving and communication system (PACS)
  • Those glass slides that are unable to be scanned are sent to the pathologist for review
  • The AP-LIS presents a work list to the pathologist and perhaps in conjunction with additional software (e.g. PACS or IMS) clearly indicates the presence or absence of digital assets.
    • If a glass slide could not be scanned, it should be clearly called out to the pathologist so that he/she may ensure that all diagnostic material is reviewed
  • Digital slides are quickly able to be accessed and reviewed for interpretation by the pathologist
    • It should be clear what slides have been viewed completely, partially viewed, or not viewed at all
      • Different pathologists may have different interpretations of what "viewed completely" entails (e.g. review of all tissue at a certain magnification must occur)
    • Pathologists should be able to annotate images to flag features or regions of interest (these should be customizable by the pathologist)
      • Pathologists should be able to quickly go back to an annotation by searching for metadata
    • Pathologists should be able to flag certain digital assets for review by a consultant
    • The system should maintain an audit trail of all viewing and annotation activities
    • The system should uniquely "stamp" all digital assets at the time of case verification by the pathologist to preserve them in their current state for future review.
      • If a digital asset is rescanned, deleted, further annotated, it should be clear if this occurred before or after case verification and/or if a pathologist has viewed, been informed of, and/or approved of the activity

Storage considerations:

  • Rather than the maintaining digital versions all glass slides, a process for culling should be considered
    • A pathologist may manually annotate which slides should be retained in perpetuity or a configuration option may be set to indicate that any slides with annotations should be preserved
    • All other digital versions of slides should be able to go through an archiving or deletion process to reduce the storage footprint for a case
    • Different types of slides may undergo different processes (e.g. Cytopathology Z-stacked slides may lose all but one plane or may undergo post-processing to have the most in focus tile maintained while others are deleted)


1st pass from JD:

For every step in the life cycle of a pathology specimen, digital artifacts are made. Most are small and primarily for management and tracking (identifiers, timestamps), but digital images made of case material can be large and complex. The images fall into two main categories, images used in the formation of the clinical diagnosis of the case and those obtained as either “proof of work” or for quality control purposes. Examples of clinical diagnosis images include:

  • Photographs of the specimen being removed in the OR
  • Pictures of gross dissection of specimen upon arrival in the laboratory
  • Microscopic images from slide review.

Examples of "proof of work" images include:

  • Picture of specimen/container upon arrival in the laboratory.
  • Picture of tissue section to be embedded
  • Image of immunohistochemical QC slide (positive and negative controls)

A sample workflow using digital images follows.

A patient is in the OR, and a tumor is excised. Before the removal of the tumor, the surgeon captures pictures of the tumor, showing the relationship of the tumor to the rest of the surgical field.

  • Digital image(s) from case tagged with the patient identifier and the encounter/event ID in EHR.
  • These images are stored in the healthcare system's VNA.
  • EHR makes a "request of the APLIS for a case number/tissue request ID to associate with the image(s)

The surgery continues and the tumor is removed, and the same case number/tissue request ID is associated with the removed specimen(s). Upon receipt of the specimen(s) in the lab, the case is accessioned in the APLIS, and all case material is labeled with the case number and appropriate part numbers.

  • The images obtained in the OR are tagged with the AP case number.

Upon grossing, gross images of the case are obtained.

  • These images are tagged with the AP case number along with relevant case metadata (part, section) and any annotations (arrows, etc.) added to the images.
  • These images are also sent to the healthcare system's VNA.

The sections of tissue are processed into slides in the usual manner, with various QC and "proof of work" images collected along the way.

  • All images collected via processing steps are indexed with the appropriate case number and block/slide identifiers before sending to VNA.

After staining (both H&E, IHC, and special), all glass slides are sent to the high volume digital scanner.

  • Slide images are indexed with relevant case metadata (block, slide, stain) and sent to the VNA.

Once the digital work is done and acknowledgment is received in the APLIS, the digital case is assembled by the APLIS to be presented to the pathologist for first read and possibly signout.

  • The APLIS collects all of the digital image metadata (not the images), and assembles a virtual case (an association of all images on the case).

The pathologist reviews the case, and his/her viewing of the case images is recorded in the APLIS.

  • Each image review is tracked in the system and added to the case metadata held in the APLIS.

Use Case #4: Sharing and Cooperating on Gross Examination Images

Contributor assigned: Laurent Duval

Definition: Grossing is the first step of sample preparation is macroscopic examination during which the sample is examined visually before microscopic examination.

Workflow: The process of grossing is performed in a meticulous and systematic fashion including all of the following main steps:

  • Verify Specimen Labeling and Patient Identification
  • Review Clinical Information
  • Examine and Palpate All External Surfaces of the Specimen
  • Understand the Resection Margins
  • Inking Resection Margins
  • Dissecting and Sectioning the Specimen
  • Examining the Cut Specimen
  • Preparing samples for microscopic review in designated "cassettes"
  • Capturing and annotating images at various points in the above workflow may be helpful in conveying complex findings and correlating gross and microscopic tissue relationships

Main Use Cases:

  • Sharing and collaborating/consulting on Gross Examination Images brings value and may be critical for evaluation of complex specimens where anatomic details must be well understood before pathologists can make educated judgments about the extent of the patient’s condition and need for further resection.
  • Pre Analytics: Another area would be around Sample Tracking, when the sample collection might not occur at clinical site. Specimen fixation / transportation quality are essential for minimizing error rates and improving staining quality, and could guarantee a proper gross examination. Additional data to be considered for that purpose:
    • Correlation between a gross examination feature and a microscopic features (e.g. "the tissue sections marked with a triangle were noted to have a clip in them")
    • Tissue fixation quality (QC step)
    • Temperature tracker during transportation (data logger)

Gross Examination and Digitalization: Grossing tables with Image AND Voice recording devices make possible to record sample type, sub type, size and morphology, thus the macroscopy image and the related clinical data define the orientation for diagnosis.

  • Request for cassettes can be also recorded at grossing step.

Pathologists could give a reliable diagnosis when microscopic images are coupled with macroscopic ones. In the era of the digitalization of pathology, it should be now possible to access micro and macro images / description from one place.

Interoperability: Need to consider a platform (ideally web) where sample images could be uploaded and be used interchangeably with regular whole-slide images: they can be annotated, shared or even discussed via teleconsultation. Sample information recorded at grossing (sample description, pre analytics...) to be exchanged with HIS (Hospital Information System), APLIS (Laboratory Information System) and / or WAM (Work Area Manager), Middleware from medical devices company.

Use Case #5: Incorporation of Legacy Digital Images for Use in APW

Contributor assigned: Raj Dash, JD Nolen, Dan Rutz, Anil Parwani

Legacy digital images may exist today in laboratories in a number of different file formats and include both still images (gross and microscopic) as well as whole slide images (microscopic only). File formats for whole slide images today include those originally produced by Aperio (.svs, .tif), Hamamatsu (.vms, .vmu, .ndpi), Leica (.scn), MIRAX (.mrxs), Philips (.tiff), Sakura (.svslide), Trestle (.tif), Ventana (.bif, .tif), and generic tiled TIFF (.tif). The DICOM standard for whole slide images reflects a hierarchy of tiles that allow for efficient transfer of data relative to both the source information and the destination display/device capability and requirements. DICOM facilitates association of patient and image metadata as part of a data "wrapper" around the actual image data.

With the implementation of an LIS, EHR, image management system (IMS) or archival system (PACS or VNA), the bulk transfer of existing digital assets (DICOM and non-DICOM) will likely be required to facilitate at least rudimentary association between a patient, anatomic pathology tissue collection event, and various digital assets that might be available associated with that particular patient encounter. It is possible that the format of image data and associated metadata are in different formats during different time periods during which legacy information systems were utilized to acquire and manage the digital assets that exist in an organization as "legacy digital data". The value of this data will increase if future vended solutions recognize the need for association of this existing data with pathology "cases", "specimens", and/or patient "encounters".

Due to ever-increasing prevalence of digital assets, consistent growth of information technology systems, and occasional turnover of LIS platforms, the need to maintain and incorporate “legacy” digital assets in laboratory pathology workflows will continue to be a necessary aspect of the full APW spectrum. Legacy migration will consistently come from multiple perspectives including: migration to a new primary LIS/digital cockpit, migration to a new image management system (WSI integrated solution, PACS, or VNA), addition of a new post-analytic system, and increasing scope of asset collection (biobanking, etc.). The legacy asset incorporation/conversion use case shares boundaries with a number of other use cases especially including consultation workflows, notably including: Incoming asset identifier management, Transfer of assets, replication of existing case structure and patient data, varying quality of source data that cannot be guaranteed. However, it maintains several unique features including the (relatively) massive scale of content covered compared to other workflows, potential value vs. complexity in handling internal audit & tracking data on historical cases, and the likelihood that nearly all organizations engaged in digital pathology practices will need to account for this situation regardless of their business scope and participation in other use cases.

Central challenges to legacy asset incorporation are:

1. Identifier management (patient, case/report, specimen, block/slide/container, provider, user/technologist, physical labeling, etc.)

2. Replication of case structure, prior process & result data, and associated relevant patient information.

3. Accurate bulk assignment of legacy digital images to the correct patient, encounter, case, and associated more granular physical assets (specimens, blocks, slides, etc).

Use Case #6: Image Analysis, Machine Learning and In Silico Workflows

Contributor assigned: Raj Dash

Data analytics and machine learning promise to provide significant value to those that embrace digital pathology workflows. Recent publications have demonstrated the capability of machine learning algorithms to fulfill complex diagnostic tasks, such as identification of lymph node metastases on digitized H&E images of lymph nodes1. Some studies purport that these machine algorithms already have the potential to exceed the capabilities of human pathologists. For example, a laboratory information system (LIS) may allow ordering of analytic “tasks” on digital assets, similar to the paradigm in which immunohistochemistry might be ordered as tasks to be performed on physical tissue today in LIS platforms. In addition, LIS systems should be able to recognize when certain digital assets routinely require analytic tasks to be performed in a particular sequence as part of a digital “protocol”. For example as part of the routine processing of whole slide images acquired of sentinel lymph nodes of breast, the deep learning algorithm for metastasis identification might be run automatically immediately after whole slide scanning has been completed.

It should be permissible for these algorithm "tasks" to irreversibly modify digital assets through a layered annotation process as well as return metadata to store in to the LIS as a relevant diagnostic data point (e.g. Ki67 proliferation index for a region of interest), or finally create a dataset for further process by downstream "tasks" that are part of a larger analytic process or protocol.

References:

1Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer, JAMA. 2017 Dec 12;318(22):2199-2210

Use Case #7: Quality Control / Quality Assurance and Error Correction Workflows to Support Digital Pathology

Contributor assigned:Nicholas C. Jones

Definitions: Quality Evaluation (QE): An assessment from a device, software algorithm, or person about the quality of a target physical or digital asset. Quality Control (QC): A system for verifying and maintaining a desired level of quality in an individual test or process. Quality Assurance (QA): Systemic monitoring of quality control results and quality practice parameters to assure that all systems are functioning in a manner appropriate to excellence in health care delivery. Specimen: A physical object (or a collection of objects) is a specimen when the laboratory considers it a single discrete, uniquely identified unit that is the subject of one or more steps in the laboratory (diagnostic) workflow. Container (Or Specimen Container): A physical object containing a specimen.

7a. Identification issues and ontologies for images. Any lab, APLIS, or Digital Pathology vendor should ensure first that they understand the identification processes, metadata ontologies, and troubleshooting requirements for digital pathology. (See discussion section for details.)

7b. Quality Evaluations for WSI

  • Pre-processing: orders, identification, slide, tissue
  • Scanning: Systems have internal analytics, sensors, and error-checking
  • Post-scanning tech QE
  • Pathologist QE
  • Other personnel QE
  • Image analysis QE

7c. Quality Evaluations for other pathology images

  • Identification and association of images (i.e. gross image having correct metadata association/file name plus reference to case within the image)
  • Order matching of images
  • Pre-processing
  • Imaging process
  • Post-imaging QE

7d. Quality Control for Imaging processes - Systems, workflows, and protocols should detail all routine quality evaluations and workflow steps.

  • At the most basic level: documents should specify workflow processes including all steps to evaluate and maintain quality
  • Quality Evaluations (see above)
  • Documentation: Imaging laboratory human made logs, scanner or server system logs, audit trail logs, reporting processes, interface engine logs or reports
  • Calibrations: may include aspects like color calibration of scanners or monitors, periodic evaluation of staining/color representation of slides
  • Troubleshooting worklists

7e. Quality Assurance for Imaging processes

  • Design and documentation of workflows and quality control
  • Explicit periodic analyses of operations and metrics for quality and results
    • These could include analysis of log files (via reports from systems), ST QE/QC metrics, pathologist rescan request rate, WSI deferral rates
    • Turn-around-time (TAT) analysis of processes
  • Digital Pathology QA conferences
    • In initial validation or verification within a laboratory prior to clinical implementation, most validation studies/processes end with an adjudication panel of pathologists reviewing glass slides via microscope and WSIs to evaluate discrepancies/discordances between interpretations and determine root causes. These can be extended to include imaging and histology/lab personnel upon initial validation to help set quality control purposes for the laboratory.
    • Departments may wish to do periodic conferences to evaluate quality issues and improve quality control processes. This may be especially important for a feedback loop to laboratory and scanning personnel and iron out complex problems.
    • Many systems may allow for tagging images for QA review at a later time; this should correlate to QE/QC data.
    • There may need to be QA processes for sub-populations of tissue types, slide types, subspecialties, or diagnosis types.
  • Aggregation for inspection for regulatory purposes - likely to include tracer cases, analysis of protocols, QE processes, follow up from prior inspections, etc.
    • Adverse Event Reporting - in some scenarios, groups may want or need to report adverse events of systems to vendors, FDA or other relevant outside groups.

7f. Quality Control and Assurance for Digital Diagnosis

  • Randomized reinterpretation of digital cases via microscope. (Similar to cytotechnologist QC or regular surgical pathology QA processes.)
  • Periodic re-verification/validation of image analytic results (i.e. occasional ordering of FISH evaluation to assert her2 image analysis functions are still achieving consilience)
  • Randomized or periodic testing or auditing of equipment precision

7g. Quality Control and Assurance for Image Management, File Management, and Network Management

  • Log file aggregation and analysis for systemic errors
  • Random audit of tracer cases to verify image availability
  • Monitoring of network load, network speeds, and other measures of network performance.
  • System backups and auditing of file integrity (both for main archives and backups)
  • Network security or vulnerability audits

Additional Considerations: Digital Pathology for support of Anatomic Pathology Quality Control and Quality Assurance

  • Archiving of cases and managing surgical pathology re-reviews (by conference or repeat interpretation)
  • Computer image analysis of images for slide quality to improve feedback loops to laboratory
    • Algorithms might be used to detect sub-optimal slide preparation (i.e. tissue folds, edge artifact) to systematize and analyze metrics for slide quality.
    • Qualitative metrics for color analysis stain variation over time (i.e. maintaining consistency for laboratory's H&E stain)
  • Viewing trail auditing (either ad hoc or systemic) to analyze use/human factors issues (i.e. resident screening patterns to document increasing competency) or to alert user of unscreened slides (i.e. Alert: you have not viewed the slides from specimen B!)
  • Maintain libraries of reference scans of optimal stains to document IHC tests (especially rarer or newer stains)
  • Aggregation of order, tracking, results data and timestamps across multiple systems (i.e. aggregating order times, specimen tracking, performed procedure steps/modality performed procedure steps to evaluate scanning turnaround time versus re-scan & rejection rates, scanner utilization). Note that the utility of logs and tracking information increase exponentially if they can be aggregated together with respect to the same images (i.e. matching slide UID with scanning UIDs and timestamps, DICOM header information), and such data will be necessary for laboratories to accurately plan for large scale conversion to digital workflows. Such data can also be used to identify and track problematic cases (i.e investigating which cases get delayed) for continuous process improvement.
  • Structured part type descriptions (as opposed to free text) and structured gross description / sectioning codes could allow for nuanced quality analyses of WSIs to evaluate problems in grossing and sectioning of tissue.
  • Analysis of tissue shape (i.e. through automated tissue alignment/image registration across multiple slides or just user visualization) could allow for systematic double-check of human errors in identification; in other words, another way to do slide/block (or perhaps slide/block/specimen). Note in this instance, this might be subject to the availability of tissue section order; the system would likely need to know the H&E is the first cut, the TTF1 the second, etc., so this should be communicated across systems.


Use Case #8: Digital Pathology in Support of Clinical Conferences

Contributor assigned:Nicholas C. Jones

Categories include:

  • Consensus conferences
  • Internal quality assurance conferences

Technical notes:

  • It is commonplace for slides to be imaged for the purposes of such conferences. Workflows may vary in a primary diagnosis scenario.
  • Although such conferences may use "thick clients" for WSI viewers, it may be considered more commonplace to use thin clients for such scenarios. As such, in a thick-client primary diagnosis setting, the determination of a set of WSIs previously scanned may warrant upload of scans to a thin client hosting server, or transmission from a file store or from one thick client to another. (This latter scenario could occur if a hospital used a thin client system for internal client cases, and a separate thin client system for telepathology cases received outside the hospital network.)
  • To provide inter-operable vendor support for such conferences, it may be desirable to support modeling of sets of requests for multiple patients to pathology for the purposes of such conferences.
  • Many digital pathology thin client systems allow for the organization of multiple cases, even for disparate patients, into sets or be indexed together in other forms, which can help assist in the process of organizing rapid, efficient, accurate switching between cases for multiple patients in these settings.
  • While conferences are not generally tied to billing, from the perspective of cost accounting (saving multiple physicians time) they are extremely valuable. From the perspective of prospective clinical accuracy and providing constant feedback loops to and between clinicians, they are invaluable.

Use Case #9: Image Registration Functions

Contributor: Nicholas C. Jones

Image registration involves the creation of a cross-image coordinate system of multiple images for the same object(s) or "scene."

  • 10.a. Image registration for swapping to correlated position on different slide from a single block.
  • 10.b. Image registration for correlated multi-slide view from a single block. This allows for simultaneous presentation of multiple slides at once off the same block by allowing the user to control the location of one slide and having the system move the view of the other slides to the corresponding locations.

10.c. Image registration beyond just a series of serial sections of a block have been researched, and although these are (to our knowledge) not currently in clinical use, further possibilities have been documented in research environments.

Use Case #10: Digital Pathology in Support of Intraoperative Procedures

Contributor assigned: Raj Dash

Intraoperative consultations occur frequently to help guide surgical procedures and/or assess the diagnostic adequacy of tissue removed during surgical or a biopsy procedures. Typical staffing models to cover this type of clinical service generally involve a single pathologist supporting the needs of multiple operating rooms for a period of time (e.g. 24 hours). This coverage model pragmatically allows for efficient use of limited pathologist resources. Situations often arise where this isolated individual may need to call upon the sub-specialty expertise of others. Rapid imaging of frozen tissue sections provides a mechanism for remote viewing by the pathologist on call as well as consultation from the primary pathologist to a sub-specialty pathologist. Requirements for digital histology imaging in this context requires rapid image acquisition (less than 10 minutes) and may require linkage to other data elements, including the gross image for orientation, clinical history, and procedural context (i.e. why the patient is undergoing a procedure, why tissue is being sent for evaluation, specific questions to be answered to guide the procedure, etc.).

It should be noted that while demographic information must always be present in association with tissue submitted for intraoperative consultation, many laboratories may choose not to immediately create/accession a new case into the AP-LIS due to time constraints. An image management system should be able to accommodate situations in which case creation in the AP-LIS is deferred to the point in time in which the case has been completed and is ready to proceed with gross examination. In this situation, digital assets labeled with patient demographic identifiers only need to be supplementally identified to create linkage to the appropriate AP-LIS case.

The whole slide image produced during intraoperative consultation may be at varying "levels" of depth as the tissue is cut through to obtain a full thickness cross section and will almost always be accompanied with a deeper "permanent section" that represents the tissue remnant following standard histologic processing. Correlation between the frozen and permanent sections is a documentation requirement in most laboratories and usually occurs as the attending pathologist signing out the case reviews the final set of microscopic images.