Molecular Genetic Pathology || Pathology Informatics

Pathology Informatics 18Roy E. Lee, Long Phi Le, and John Gilbertson

Contents

18.1 Definition and Scope of Pathology

Informatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500

18.2 The Major Components of Pathology

Informatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500

18.2.1 The Study of Information . . . . . . . . . . . . . . . . . . 500

18.2.2 The Study of Information Systems . . . . . . . . 500

18.2.3 The Study of Processes and Workflows . . . 501

18.2.4 Information, System, and Process

Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501

18.3 Pathology Informatics and the

Diagnostics Laboratory . . . . . . . . . . . . . . . . . . 501

18.3.1 Codependency and

Shared Responsibility . . . . . . . . . . . . . . . . . . . . . . 501

18.3.2 Future Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502

18.4 The Laboratory Information System

and the Diagnostic Process . . . . . . . . . . . . . . . 502

18.4.1 The Total Testing Cycle . . . . . . . . . . . . . . . . . . . 502

18.4.2 Involvement by the LIS . . . . . . . . . . . . . . . . . . . . 502

18.5 Molecular Informatics . . . . . . . . . . . . . . . . . . . . 505

18.5.1 Unique Aspects of Molecular

Informatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505

18.6 Pathology Imaging . . . . . . . . . . . . . . . . . . . . . . . . 508

18.6.1 Specific Uses of Digital Imaging . . . . . . . . . . 508

18.6.2 Telepathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 509

18.6.3 Digital Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . 509

18.6.4 Current Status, Challenges, and Potential of

Digital Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . 510

18.6.5 Nontraditional Imaging Techniques . . . . . . . 510

18.7 Image Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511

18.7.1 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511

18.7.2 Working Examples . . . . . . . . . . . . . . . . . . . . . . . . . 511

18.7.3 Limitations to Image Analysis on Whole

Slide Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511

18.7.4 Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512

18.8 Digital Pathology, Image Analysis, and

the Laboratory Information System . . . . 512

18.8.1 Image Orders and Workflow . . . . . . . . . . . . . . . 512

18.8.2 Specimen Identification and Messaging . . . 512

18.8.3 Imaging at Sign Out . . . . . . . . . . . . . . . . . . . . . . . . 513

Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513

R.E. Lee, MD (*)

Pathology and Laboratory Medicine Institute,

The Cleveland Clinic, Cleveland, OH, USA

L.P. Le, MD, PhD � J. Gilbertson, MD

Harvard Medical School, Department of Pathology,

The Massachusetts General Hospital, Boston, MA, USA

L. Cheng, D.Y. Zhang, J.N. Eble (eds.), Molecular Genetic Pathology,DOI 10.1007/978-1-4614-4800-6_18, # Springer Science+Business Media New York 2013

499

18.1 Definition and Scope ofPathology Informatics

• Pathology informatics can be conveniently

defined as the study and management of

pathology information, information systems,

and processes (Table 18.1)

• The definition is based on the observation that

laboratory processes, the data those processes

consume and generate, and the computer

systems that manage that data and those

processes are intimately related

• Informatics is not synonymous with “informa-

tion technology” (IT) or “information services”

(IS) (Fig. 18.1). While informatics teams work

closely with IT/IS groups, the latter tend to be

focused on one component of informatics – the

technical implementation and maintenance of

information systems

18.2 The Major Components ofPathology Informatics

• Pathology informatics implemented at the

Massachusetts General Hospital is based on

four main areas of study: information, infor-

mation systems, processes (workflows), and

management

18.2.1 The Study of Information

• What information is required for a given process

• Measurements of information quality

• Information extraction (e.g., image analysis

and natural language processing)

• Annotation and meta-data

• Information models and architectures

• Programming principles (information

manipulation)

• Human processing and use of information

(e.g., human–computer interaction and user

interface design)

• Decision support principles (Bayes theorem)

• Information exchange and standards: data

standards (e.g., SNOMED, ICD) and messag-

ing standards (e.g., HL7, DICOM)

18.2.2 The Study of InformationSystems

• Laboratory information systems (LIS): archi-

tecture and operations (see below)

• Image management systems (e.g., picture

archival and communication systems [PACS])

• Bioinformatics systems

• Other clinical information systems (CIS):

ADT (admission, discharge, and transfer)

systems, CIS, electronic medical record

Table 18.1 Simplified breakdown of major areas under medical informatics. Because these three areas are often

confused with one another, it is important to define them here. Clinical informatics differs from pathology informatics

mainly in that the type of data and systems cover a scope outside of pathology and laboratory medicine and places less

emphasis on process optimization and redesign. Of note, bioinformatics is the only one of these three areas that explicitly

includes “computational tools” (IT) in its definition. Overall, medical informatics does not necessarily imply the use of

IT; however, in today’s age, IT makes the most sense to use, instead of traditional filing cabinets, and pen and paper

Clinical informatics Pathology informatics Bioinformatics

Concerned with information use in

healthcare by clinicians: clinical

decision support, CPOE, system

design, system implementation (e.g.,

electronic health records and health

information systems)

Concerned with laboratory

information, its systems (e.g.,

laboratory information system), and

associated processes. Pathology

informatics differs from clinical

informatics in that it is the branch of

medical informatics covering

pathology data and the processes and

systems it covers. A greater proportion

is devoted to process optimization,

such as Lean Six Sigma

Associated with “hard-core” number-

crunching algorithms for analysis and

study of data at the DNA, RNA, and

protein levels and less about information

flow and processes. NIH definition

(2000): research, development, or

application of computational tools and

approaches for expanding the user of

biological, medical, behavioral, or

health data, including those to acquire,

store, organize, archive, analyze, or

visualize such data

500 R.E. Lee et al.

(EMR)/electronic health record/patient medical

record systems, and financial systems

• System interoperability and connectivity

(interfaces and standards)

• System life cycle (creation, implementation,

maintenance, decommission) of clinical systems

• User training

18.2.3 The Study of Processes andWorkflows

• Process theory (industrial engineering)

• Process analysis, improvement, and valida-

tion: (e.g., business process management

(BPM), failure modes and effects analysis

(FMEA), and Lean Six Sigma)

• People working in systems (e.g., Just Culture)

• Outcomes measurement

• Process modeling and simulation

• Decision support processes

18.2.4 Information, System, andProcess Management

• Pathology informatics involves large, com-

plex, highly integrated, and interconnected

systems supporting hundreds of users and

processes. Successful system development

and implementation and management in the

pathology environment require significant

communication and management skills

– Project management

– System management

– Capital and accounting finance

– Software development management

– Validation studies management

– System selection, implementation, and

maintenance (e.g., total cost of ownership)

– Regulatory compliance

18.3 Pathology Informatics and theDiagnostics Laboratory

18.3.1 Codependency andShared Responsibility

• A modern diagnostic laboratory cannot

function without an effective information

system, and an effective information system

cannot be designed, implemented, or

maintained without a clear understanding of

the operations and missions of the lab. There

are numerous reasons for this:

– The primary product: Accurate, actionable

clinical information, in the form of final-

ized results or “signed out” reports, is the

primary product of pathology labs

– Required inputs: Laboratory operations

depend on access to clinical, patient, spec-

imen, and financial information

– Management of processes: Diagnostic lab-

oratories run complex processes that need

to run efficiently, at low variance, and with

limited failures. The processes must be val-

idated and documented

– Communications: Communication

between the lab and the rest of the clinical

care team (usually through formal orders

and results/reports as well as ad hoc) is

central to the value of the laboratory and

the safety of the patient

– Automation: Automation, standardization,

machine-readable specimen identification

(barcodes), and clear, human- and

Fig. 18.1 The term “informatics” is not synonymous

with information technology. In pathology informatics,

these three major components of pathology information,

information services/technology, and laboratory processes

are intimately linked and related

18 Pathology Informatics 501

machine-readable results/reports have been

shown to improve efficiency, patient

safety, and effective communication

between the lab and the clinic

– Data sharing and interoperability: Pathol-

ogy/laboratory results are used by multiple

downstream information systems

(reporting systems, electronic information

systems, etc.). Studies have shown that the

majority of data in most EMRs originates

in diagnostic laboratories and that most

significant medical decisions depend on

laboratory data

• Each above activity is a shared responsibility

between medical staff, laboratory technical

staff, the information management team, and

information system developers. System devel-

opers must understand the laboratory’s goals,

missions, and customers, and laboratory staff

should understand that the LIS is their best

tool for feedback, quality assurance, and lab-

oratory efficiency/value

18.3.2 Future Trends

• Demographic trends (national and interna-

tional), the explosion of genetic and molecular

testing and digital imaging, and increasing use

clinical decision support systems, workflow

efficiency engines, utilization and value stud-

ies, and the convergence of basic science and

clinical application (all of which will require

high-quality, standardized, machine-readable

laboratory data) will drive increased needs for

sophisticated LIS and pathology informatics

for the foreseeable future

18.4 The Laboratory InformationSystem and the DiagnosticProcess

• Though normally considered a computer sys-

tem, the LIS can be thought of more broadly as

a set of related processes, operations, and pro-

cedures, some or all of which are supported by

one or more computer systems. The primary

goal of an LIS is to support the operations of

a clinical laboratory. It therefore makes sense to

discuss the LIS in terms of laboratory operations

18.4.1 The Total Testing Cycle

• The total testing cycle (TTC) is a classic, high-

level model of the diagnostic laboratory pro-

cess (Fig. 18.2). The TTC models laboratory

testing as a largely linear process beginning

when testing is first considered by the clinician

and continues through the clinical and labora-

tory processes needed to order the test, collect

and transport the specimen, prepare the spec-

imen for testing, run the test, and through the

interpretation of the test result first by lab staff

and pathologists (which may result in further

testing) and finally by clinicians. The process

is modeled as a cycle because the results of

one test often results in the ordering of others

18.4.2 Involvement by the LIS

• The LIS (and related information systems) is

involved in every step of the TTC

18.4.2.1 Ordering and Order Entry• Ordering is the process through which the

ordering clinician chooses and orders tests or

other laboratory services (such as anatomic

pathology analysis of tissue specimens).

Traditionally done through paper requisitions,

it is increasingly done through computerized

“provider order entry” systems (CPOE).

By interfacing with other systems (the LIS,

test formularies, lab handbooks, etc.),

sophisticated CPOE systems allow clinicians

to search for tests, obtain advice on appropri-

ate test selection and cost, manage utilization,

collect clinical information or clinical justifi-

cation necessary for the laboratory doing the

test, or provide mechanism for the ordering

physician to talk directly to a pathologist

• Order communication and specimen transport

– Orders are passed to the LIS, usually

through an ordering interface, and patient

502 R.E. Lee et al.

and encounter information is sent to the

LIS through an ADT (admission, dis-

charge, and transfer) interface. In some

systems, the LIS prints barcoded containers

in clinic for identification of the specimens;

in other cases, specimen identification is

done by a separate process in the

clinic. Increasingly barcoded specimens

are tracked during transport from the clinic

to the lab

• Accessioning

– Accessioning is the process through which

the laboratory (through the LIS) takes pos-

session of the specimen; verifies patient,

insurance, order, and specimen informa-

tion; reconciles discrepancies; and associ-

ates the specimen(s) with the specific

laboratory processes that will eventually

lead to a diagnostic report. Laboratories

often provide their services for multiple

clinics and hospitals and receive specimens

in many different ways, making accessions

an important and complex process

• Diagnostic processes

– Diagnostic processes (also known as pro-

tocols or workups) define the way the lab

are activities that the lab employs to gener-

ate the information needed to solve the

clinical question at hand. Processes can be

iterative or nested. Depending of the com-

plexity of the diagnostic question, a lab

may employ multiple subprocesses (e.g.,

specimen dissection and description, tissue

processing, embedding, tissue sectioning,

staining, molecular studies, and micro-

scope examination) involving multiple

subdivision of specimens (e.g., parts,

blocks, slides, and aliquots) and even dif-

ferent laboratories in the pathology depart-

ment or at outside institutions (e.g.,

surgical pathology, molecular pathology,

flow cytometry, and reference laboratories)

to fully work up a case. A major role of the

LIS is to organize and keep track of this

complex flow of specimens, processing,

testing, and data. LIS has several mecha-

nisms to do this

• Unique specimen identification, usually

by barcode

• Tracking the physical location of speci-

mens and knowing where each speci-

men should be and where it should go

next (“routing”)

• Protocols defining where specimens

should go (routing) and how they should

be processed/analyzed at each location.

Protocols tend to be specific to specific

specimen types: For example, a breast

Fig. 18.2 The total testing

cycle: The TTC is a model

of the generic clinical

testing process. It begins

with a clinical question and

the decision to test, through

the ordering, specimen

collection and

transportation to the steps

necessary to generate,

interpret, and report results

in lab and communicate

them to the

clinic. Information systems

are involved in virtually

every step in the cycle


biopsy may have a different route and

may be subjected to different protocols

(e.g., different processing, more slides,

more stains, and fewer images) than

a kidney resection

• Status: Each case and tissue asset in the

LIS is given a status depending on its

completeness in the diagnostic cycle.

Examples include “Accessioned,” “In

histology,” “Final,” and “Signed out”

• Primary or secondary protocols

– Diagnostic processes can be iterative:

The first set of protocols on a tissue biopsy

may be designed to establish the presence (or

absence) of cancer. If cancer is established,

the lab might use other protocols to classify

the cancer using tumor markers. The use

of these secondary protocols can be automa-

tically triggered based on the results of initial

test results (reflex testing) or done on the

order of the pathologist working up the case

• Interpretation and reporting

– In a simple case such as the measurement

of serum electrolytes, results can be

accepted by the LIS from the analyzer and

reported to the clinic (usually via a CIS, see

below) after the test or batch passed quality

assurance. Such test results are usually sent

with minimal interpretive information such

as normal reference ranges. For complex

testing requiring an interpretive report

from the lab (e.g., anatomic pathology),

each report is reviewed by the primary

pathologist for the case who then signs out

each case (usually through electronic sig-

nature) in the LIS

• The pathology report

• In some areas of pathology (such as surgical

pathology, cytology, molecular pathology,

and autopsy), a clinical report is needed to

communicate

– What specimens were received

– What processes/workup were done

– Specific laboratory data or results (e.g.,

“size of tumor” or “number of lymph

nodes dissected”)

– Diagnostic interpretation (e.g., “prostatic

adenocarcinoma, Gleason 3 + 4 ¼ 7”)

– Clinical communications and notes (e.g.,

“interpretation is limited by extensive cau-

tery artifact”)

– In addition, the pathology report contains

information on the pathologists and clini-

cians associated with the case, the clinical

context, diagnostic and procedure codes,

and information used in a wide range of

operational and financial reports as

discussed in the “Postdiagnostic activities”

section below

– The LIS provides a series of tools for the

creation of the pathology report including

the ability to create specific report tem-

plates for different types of cases, word

processing including spell checking,

“quick text,” or “macros” for the inclusion

of standard text by typing short, relatively

simple codes. In many cases, LIS allows

structured data entry in which information

is entered in specific data elements directly

into the system with a defined set of valid

values and stored as discrete data elements

in the database. For example, the College

of American Pathologists tumor templates

are often implemented through a structured

data entry tool in the system, thus

bypassing the use of paper

• Report and result communication

– Laboratory reports created in the LIS are

communicated to clinicians through

a variety of mechanisms including printing

and mailing, dedicated printers in clinical

offices, faxing and, increasingly, secure

Internet/web-based report distribution sys-

tems. However, the great majority of

reports are communicated, via HL7 inter-

faces, to EMR systems and CIS

– The LIS is usually able to display pathol-

ogy reports in a much more sophisticated

way than the EMR. There are two main

related reasons for this: (1) The HL7 inter-

faces that communicate the report cannot

easily communicate formatting informa-

tion (such as tables or font), and (2) EMR

systems tend not to support sophisticated

formatting. This is a significant problem for

laboratory – clinic communication – and

504 R.E. Lee et al.

is slowly being mitigated by improved

interfaces and support for open, standard-

ized file formats such as the portable docu-

ment format (PDF)

• Alerts, preliminary reports, addenda, and

amendments

• In addition to the standard results and pathol-

ogy reports, LIS provides other mechanisms

for communications between lab and clinic

– Alerts: Usually used to communicate lab

results that fall in predefined “critical

ranges,” alerts can be implemented as font

or formatting changes in the report (or

EMR), automated paging or direct phone

calls to the ordering or responsible physician

– Preliminary reports: can be used for

a variety of purposes, for example, to notify

the clinic that a case result will be delayed

– Addenda: an addition to a signed out report

that adds new data (but usually does not

change the clinical impact of the diagnosis

reported in the signed out report)

– Amendment: a mechanism for changing

a signed out report with information that

could have significant clinical impact.

Because of the potential clinical impact,

amendments are usually issued with some

form of active clinical alert (vide supra)

• Postdiagnostic activities

• After result reporting or report sign out, the LIS

continues to manage data, reports, and speci-

mens. Typical postdiagnostic activities include

– Management of cases for clinical conferences

– Management of specimens: clinical archives

for specimens, aliquot, blocks, and slides.

The archive time frame can range from

days to years depending on the importance

of the specimen and the cost associated with

storage. In many cases, specimen archiving

is mandated by law

– Management reports: The LIS in a large

hospital or practice will generate hundreds

of reports needed for management and con-

trol of lab operations, workload, efficiency,

and finance

– Billing reports: The LIS generates reports

that include the information needed to bill

for lab services. Typically, these reports are

passed to billing systems that use the data

to validate charges and generate actual

invoices that are passed to third-party

payers, lab clients, or patients

– Reports to registries, research databases,

and regulatory agencies. Examples include

reports to cancer registries, enterprise

research databases that provide de-

identified clinical data to researchers, and

regulatory and certification agencies

18.5 Molecular Informatics

• Molecular studies have become commonplace

in virtually all aspects of pathology, especially

in areas such as microbiology and anatomic

pathology. Molecular testing includes a wide

range of modalities, mostly in the form of

single gene tests from commercial vendors

and laboratory-developed tests. Multigene or

genomic level testing and sequencing will

become more widespread as the technology

becomes more affordable and the practice of

personalized medicine becomes more routine

• Molecular informatics as a subset of pathol-

ogy informatics focused on the flow of infor-

mation through a molecular laboratory,

starting from test ordering through reporting,

and has substantial similarities and significant

differences compared to informatics in tradi-

tional clinical and anatomic pathology labora-

tories, especially in data storage requirements

(Table 18.2)

18.5.1 Unique Aspects of MolecularInformatics

18.5.1.1 Samples, Analytes, and Testing• Sample types of varying quantity and quality

that need to be accessioned and tracked as

assets

– Blood: useful for germ line testing or

blood-related diseases; typically yields suf-

ficient quantity and high-quality material

– Fresh/frozen tissue: similar to blood but

often not routinely available


– Body fluids: varying quantity and quality of

material

– Formalin-fixed paraffin-embedded (FFPE)

tissue: standard specimen in most anatomic

pathology laboratories; varying quantity and

quality affected by age of tissue and degree

of formalin fixation which leads to cross-

linking and fragmentation of nucleic acids

• Various analytes/substrates derived from the

initial specimen which contribute different

information (DNA, mRNA, noncoding

RNA); one specimen may yield multiple

molecular derivatives or assets, which may

be challenging for tracking

• The means of testing, data analysis, interpre-

tation, and reporting vary according to

whether the target mutations are germ line

(inherited as in familial diseases) or somatic

(acquired after fertilization as in cancer)

• Various types ofmutations to be detectedwhich

would command different testing modalities

– Single-nucleotide polymorphisms (SNP) or

single-nucleotide variants (SNV)

– Small insertions and deletions (indels)

– Copy number variations (CNV)

– Structural rearrangements (translocations,

inversions)

– Epigenetics (DNA methylation)

– Several types of data may be obtained from

the same molecular derivative

18.5.1.2 Data Types• Qualitative (e.g., base substitution/insertion/

deletion, translocation between two gene

partners, and positive detection of a band on

a gel)

• Quantitative (e.g., fragment size, copy number

change, somatic mutation at a low allele fre-

quency in a tumor specimen, HIV viral load

testing, and bcr-abl testing for minimal resid-

ual disease in chronic myelogenous leukemia)

• May be very complex with multiple muta-

tions/changes detected for one sample

18.5.1.3 Interpretation of Results• Various forms of results output: PCR gel

image, fragment capillary electrophoresis

tracings, fluorescently probed tissue slides

viewed under microscopy, quantitative real-

time PCR data based on interpolation of stan-

dard curves, copy number profile from

genome-wide copy number analysis, and

sequence data from capillary electrophoreto-

grams or pyrograms

Table 18.2 Example comparisons of data storage requirements between anatomic, clinical, and molecular pathology.

Numbers are in uncompressed files and, although not necessarily exact, serve to illustrate the differences in magnitude of

data storage between themselves

Category Test/entity Data storage requirements

Anatomicpathology

Annual storage needs on AP

LIS

<1 TB per year, assuming 100,000 cases per year

Pathology imaging Depends on compression scheme, scanning magnification, amount of

tissue on slide, number of focal planes per virtual slide, and number of

slides per case. A major academic institution generating over 2,000 slides

per day could easily consume over 33 TB per month (surgical pathology

only – excluding cytology)

Clinicalpathology

Blood banking: transfusion

service

�21 GB/year added to database (assuming 60,000 cases/year)

Clinical labs <1 GB/year (assuming volume of 100,000 cases per year)

Molecularpathology

aCGH �70 MB per case (text only)

�275–300 MB/case (if image file included)

Sanger sequencing �400–500 KB per amplicon (�400–600 bp lengths each, and including

both *.ab1 files for forward and reverse primer reactions)

Next-generation sequencing

(exome only)

�13 GB (Illumina HiSeq platform) per run

Next-generation sequencing

(whole genome)

�500–600 GB (Illumina HiSeq platform) per run

506 R.E. Lee et al.

• Various utility of results: diagnosis, prognosis,

and therapeutic significance

• Most one target (single nucleotide or single

gene)-based assays are interpreted in a binary

(positive or negative) fashion or quantitatively

(if signal is present, then disease is present with

burden relative to level of detection); these

interpretations tend to be “static” in nature that

is based on prior established knowledge about

recurrent mutations and their functional effects

• Assays testing for the entire sequence of a

gene (whole gene sequencing) or with

genome-wide scope (array comparative geno-

mic hybridization)may detect variants that have

not been previously described in addition to

ones that are recurrent and have known conse-

quences; new variants require extensive

literature search, cross-checking with mutation

databases, in silico modeling, and population

statistics to further characterize their meaning

(benign, likely benign, of unknown signifi-

cance, likely pathogenic, pathogenic); often,

data on these new mutations are incomplete or

lacking, requiring a classification of “unknown

significance”; variants of unknown significance

may need to be reclassified as new studies

reveal their functional relevance; therefore,

whole gene or genome-wide tests require

“dynamic” interpretation

• Detected rare variants may be private for

a certain family or subpopulation; testing of

additional members may yield added informa-

tion for linkage analysis and proper classifica-

tion of the variants

• Molecular testing which has traditionally

relied on test interpretation for one individual

based on known variants will have to adopt

population-based interpretation to yield the

most meaning out of genetic information

(e.g., what proportion of cancer patients with

a particular gene mutation)

18.5.1.4 Data Curation/Archiving• As molecular testing becomes more complex,

involving many genes and genome-wide

coverage, data curation/archiving is imperative

• Processes should be in place to easily

capture molecular results from instruments,

annotations/interpretations from molecular

pathologists/geneticists, findings from clini-

cians (phenotype), and all other laboratory/

radiological data

• A comprehensive collection of structured

medical testing and clinical phenotype data

affords the ability to easily query for popula-

tion-based statistics and clinical genotype cor-

relation to classify variants of unknown

significance

• Structured data should also be collected

throughout the test workflow for sample track-

ing, quality assurance, quality control, and

process management

18.5.1.5 Reporting• Reports from the molecular pathology labora-

tory may include both qualitative and quanti-

tative elements

• Reporting mutations or genetic changes

should be based on standardized nomenclature

so that recipients from other institutions may

comprehend the test results

• Results may be simple as in a single-base

substitution or complex involving

a multitude of mutations detected in

a genome-wide manner; results may be inter-

related (e.g., expression or methylation data

for a gene that was also sequenced at the DNA

level) and should be correlated to make sense

of the observations

• Molecular data particularly those resulting

from genome-wide studies will require clever

visualization tools to quickly navigate through

complex datasets; a simple text-based report

may not be sufficient

• Reporting of variants may require documenta-

tion of references and primary literature which

should be archived with the laboratory muta-

tion database; references and interpretations

may change as more functional data are

accumulated

18.5.1.6 Workflow in a MolecularPathology Laboratory IsComplex

• Molecular tests usually require multiple pro-

cesses handled by multiple personnel


• Sample tracking and quality control check-

points are needed to successfully operate

a high-volume molecular laboratory, particu-

larly for high-throughput tests

• Automation should be applied as much as

possible to ensure testing accuracy and

consistency and to enable the allocation of

human resources for other intellectually

demanding tasks

• Digitization should be implemented where

possible to increase workflow efficiency

(e.g., digital document management to

achieve a paperless operation)

18.5.1.7 Future Issues• The arrival of next-generation sequencing into

the clinical molecular laboratories will push

the limits of current molecular informatics

systems

• All aspects of molecular informatics

(accessioning, workflow, sample tracking,

data curation, results interpretation, reporting,

and so forth) will be further taxed with the

increased data burden and complexity of

high-throughput sequencing

• Next-generation sequencing allows the con-

current testing of many genetically barcoded

samples for many targets, yielding billions of

bases of information (gigabytes to terabytes of

information)

• Next-generation sequencing as a single testing

modality may potentially detect point muta-

tions, indels, copy number, gene expression,

structural rearrangements, and methylation

status all in one assay

• Operation of a next-generation sequencing

laboratory will require not only molecular

informatics for routine laboratory operation

but also a multitude of other informatics

disciplines for successful implementation:

Bioinformatics and biostatistics for analysis

and interpretation, medical informatics for

genotype–phenotype correlation and reporting,

and information technology and information

systems support to provide the infrastructure

for the data and computation demands of

next-generation sequencing

18.6 Pathology Imaging

• Digital imaging is used extensively in the

pathology laboratory (Fig. 18.3)

• The main reasons for digitization

– Documentation of specimens

– Digital management of documents

– Visualization of data

– Communication (e.g., telepathology)

– Computation (e.g., image analysis)

– The ability to use multispectral (nonwhite)

light for analysis

18.6.1 Specific Uses of Digital Imaging

• Documentation of gross and autopsy speci-

mens, microbiology plates, gels, gram stains,

urine sediment, and microscope fields in

histopathology, cytology, hematology, and

parasitology

Fig. 18.3 Current versus digital workflows:

Predigitization (blue), digitization (green), and postdigi-

tization (yellow) steps are shown. This picture illustrates

how every step in the process is important – errors or

tissue folds on the slide will affect each upcoming step

508 R.E. Lee et al.

• Document management

• Display of complex data, such as flow

cytometry

• Telepathology

• Diagnostic image analysis or image-based

diagnostic decision support; for example,

automated Pap smear screeners

• The use of multiple, specific wavelengths of

light, as inmultiple target FISH or quantum dots

18.6.2 Telepathology

• Telepathology is a mechanism for laboratory

to laboratory communications that allows dig-

ital images created at one site to be viewed and

interpreted at another. Virtually, any lab oper-

ation (from grossing to electron microscopy)

can be managed through telepathology

• Fundamental requirements

– Ability to digitize the specimen at the

sending site

– A network that can support the

communication

– Ability to display at the receiving site

18.6.2.1 Three Main Types ofTelepathology

• Static

– Relatively small, single fields are captured

and sent through the network. Static

telepathology is useful when the diagnostic

material can be meaningfully imaged in

a limited number of discrete fields and/or

the when the diagnostic request is to confirm

a specific finding. It has been used

effectively in microbiology, parasitology,

and Pap cytology (confirmation of the

output of an automated screener)

• Robotic

– A video camera is connected to a robotic

microscope. An operator at a distant site

operates the robotic microscope and views

the video images. In some implementation,

a high-resolution still camera is also attached

to the microscope, allowing the operator to

capture and view high-fidelity images.While

robotic systems require relatively high

bandwidth, they have been used successfully

to support remote hospitals for both routine

pathology and frozen section diagnosis

• Whole slide imaging

– As the name implies, all of the tissue on

a microscope slide is digitized at high reso-

lution and is stored on a server as a complex,

compressed “pyramid” file that saves the

whole slide image at multiple resolutions

(or “levels”) roughly corresponding to the

resolutions one would see under a

microscope with 4x, 10x, 20x, and 40x

objective lens and 10x oculars. Each level

is divided into multiple, small “tiles” that

can be independently sent from the server

to the remote client system. The pathologist

is initially presented with a low-resolution

“thumbnail” image and “pan and zoom”

into and around the image by clicking on

the image, with the server presenting only

the image data needed to render the area of

the slide the pathologist is looking at (very

much like “Google Maps”). While an

entire whole slide image may be large

(0.3–10 GB), the pathologist tends to do

most of their examination at low resolution;

therefore, a relatively small percentage of

the image data (or “tiles”) is sent over the

network to be displayed

18.6.3 Digital Pathology

• There is increasing interest in the potential,

large-scale implementation of whole slide

imaging for primary diagnosis. This process,

known as digital pathology, has

predigitization, digitization, and postdigi-

tization phases, each of which impacts image

quality and each of which needs to be consid-

ered if large-scale digital pathology is to be

successful in clinical practice

18.6.3.1 Predigitization• In pathology, imaging begins as the

physiochemical process of fixing and processing

tissue, cutting tissue sections, placing them on

slides, and staining them with a variety of


technologies (e.g., histochemical staining,

immunohistochemical staining, and fluorescent

in situ hybridization [FISH] staining). These

techniques remain as the most important part

of the imaging process

• Traditionally, these techniques have been

highly manual, with a high variance from

slide to slide that is detrimental to the down-

stream digitization process. Increasingly,

however, automation has been developed for

each step of the process (processing, embed-

ding, staining, coverslipping – there is even

work on automated tissue sectioning)

18.6.3.2 Digitization• Over the past 10 years, automated devices have

been developed to digitize (or “scan”) whole

slides rapidly, automatically, and at high fidel-

ity. Current high-end devices can automatically

scan a slide in approximately 1 min at a spatial

sample period of approximately 1.5 mm(similar to the resolution of a microscope with

a 40x lens). Image quality and system through-

put (the number of slides successfully scanned

per hour) are dependent on the quality of

the prediagnostic image phase (vide supra)

18.6.3.3 Postdigitization• After image capture, the images are stored on

a server and prepared for viewing and inter-

pretation as discussed in the telepathology

section above. Parameters that affect image

quality include the amount of compression,

the quality of the pathologist’s monitor dis-

play, and the viewing environment

18.6.4 Current Status, Challenges, andPotential of Digital Pathology

• Digital pathology is in the early phases of

development and implementation. There are

still significant challenges as well as large,

potential rewards

• Imaging consumes precious time and disrupts

histology workflow

– Current high-end scanners can scan a slide

in approximately one minute (a rate that

has been decreasing rapidly). However, if

one considers that a large lab might gener-

ate 2,500 sides per day and that the standard

histology process involves a large amount

batching, it is clear that imaging the major-

ity of the lab’s slide will require a large

number of scanners and potentially

a change to a nonbatched, continuous flow

histology operation

• Cost and profitability

– Digital pathology requires significant capi-

tal, and profitability has yet to be proven

– Scanners, servers, networks, monitors,

potential infrastructural changes to the lab,

and theworkstations in the pathologist office

when combined in to become prohibitively

expensive, and no one has yet demonstrated

a model with a clear return on investment

• Regulation and validation

– While use of WSI for second opinion con-

sultation and intraoperative consultation

seems to be established, the current opinion

of the FDA is that whole slide imaging

systems will likely be regulated as class

three devices when used for primary diag-

nosis; significantly, there is no consensus of

the testing necessary to prove the safety

and efficacy of WSI in primary diagnosis

and therefore no mechanism to get devices

cleared for this application

• The potential of digital pathology

– Despite the significant challenges, digitiz-

ing the majority of histopathology slides

automatically and at high fidelity has obvi-

ous potential. It would allow laboratories to

apply network connectivity and computa-

tional power – the driving forces of inno-

vation and efficiency in the modern

world – to anatomic pathology

18.6.5 Nontraditional ImagingTechniques

• In addition to WSI and digital pathology,

pathology labs are beginning to examine the

use of techniques developed in radiology or

endoscopy

510 R.E. Lee et al.

– Virtopsy (virtual autopsy): the use of CT

and other radiology tools as adjunct to the

autopsy

– Specimen CT: potentially to evaluate mar-

gins or large tissue volumes

– In vivo microcopy (for the epithelial/

endothelial surface of hollow organs and

vessels)

– Multitissue section, high resolution, and

three-dimensional reconstruction

18.7 Image Analysis

18.7.1 Goals

• The goal of imaging analysis is to assist the

laboratory and pathologist when making

morphology-based decisions such as ruling in

or out specific diagnosis, measuring the

quality of the slides and stains, counting

structures such as mitoses or tumor size, or

standardizing tumor grade. Image analysis

can also be used to improve the digital pathology

viewing experience of the pathology by, for

example, registering the images of two adjacent

tissue sections so that they can be viewed and

navigated in tandem (Fig. 18.4)

18.7.2 Working Examples

• While diagnostic image analysis on whole slide

images is in its infancy, the use of image anal-

ysis in automated Pap screening is a mature

technique that is used by hundreds of laborato-

ries on millions of specimens each year

18.7.3 Limitations to Image Analysison Whole Slide Images

18.7.3.1 Data Size• A typical whole slide image represents giga-

bytes of data in uncompressed form, placing a

huge data load on any computational process

Fig. 18.4 Basic image analysis techniques: (a) Once the

tissue section is stained and imaged, the digital slide can

undergo a variety of manipulations for image analysis,

such as (b) sharpening; (c) segmentation, in which an

anatomical or histological structure is separated from

the rest of the image via automated algorithms; and

(d) classification, in which the segmented regions of the

image is identified/associated with a specific anatomic or

medical entity


18.7.3.2 Histology Artifact• Standard, largely manual histology processes

result in:

– Tissue sections with variable thickness and

that are rotated, translated, folded, and

twisted

– Staining can be highly variable

18.7.4 Techniques

• Histochemistry

– Though not normally considered part of

image analysis, histochemical, immunohis-

tochemical, and FISH staining is an

extremely powerful tool for tissue segmen-

tation and structure classification (vide

infra)

18.7.4.1 Averaging and Sharpening• These are basic techniques, usually applied

across the entire image, to remove noise

(averaging) or sharpen edges. Done by

applying appropriate filters to either the spatial

or the color space

18.7.4.2 Segmentation• The separation of meaningful structures

in the image (usually anatomic or disease

structures, such as separating bone from soft

tissue); segmentation is done by applying

“morphologic” or color “operators” that look

for specific shapes, textures, and colors in

image. Operators usually begin with a basic

shape (e.g., a blue circle of a given size) and

then apply “erosion,” “dilation,” or color vari-

ation programs to find similar structures

18.7.4.3 Classification• Classification is the identification/association

of specific objects or regions (identified

through segmentation) with specific anatomic

or medical entities (such as cancer cells and

blood vessels)

18.7.4.4 Registration• An image analysis technique important in dig-

ital pathology registration allows WSI from

two adjacent tissue sections (which have

been independently rotated, translated, and

twisted in the histology process) to overlay

on the same screen

18.7.4.5 Pipelining• A typical image analysis process would

involve histology staining, imaging, averaging

and sharpening, segmentation, classification,

and, potentially, registration in a “pipeline”

and creating the completed analysis

18.8 Digital Pathology, ImageAnalysis, and the LaboratoryInformation System

• As the main workflow engine of the pathology

lab, the LIS has a major role in the future

implementation of large-scale digital pathol-

ogy and image analysis

18.8.1 Image Orders and Workflow

• LIS has the capacity to include imaging and

image analysis as part of the workflows (routes

and protocols) defined in the LIS for specific

specimen types and clinical questions. For

example, the current protocol for a breast core

biopsy might call for placing the entire core in

a single block, process with a specific protocol,

cut ten levels from the block and stain level 1, 5,

and 10 with H&E, save the remainder for

potential immunohistochemistry, and send the

case to the breast pathologist on service.

This could be extended to including imaging

level 1, 5, and 10 at high resolution on a specific

slide scanner

18.8.2 Specimen Identification andMessaging

• LIS barcodes and HL7 messages between the

scanner and the LIS will manage and allow the

scanner to identify slides and the appropriate

imaging orders on each slide

512 R.E. Lee et al.

18.8.3 Imaging at Sign Out

• Incorporation of imaging at sign out by inte-

grating images into the standard sign out

workflow

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Implementing an AP solution that integrates with

your hospital’s LIS can improve workflow and produc-

tivity. Health Manag Technol. 2008;29:18, 20.

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