View the Schedule - Pathology Informatics 2014, May 13-16

mumpsimuspreviousAI and Robotics

Oct 25, 2013 (3 years and 9 months ago)



Scientific Session

Thursday, October 6, 2011

7:30 am

8:55 am


Grand Ballroom 1

Kings Garden North

Kings Garden South/LeBateau


3D Prostate Histology Reconstruction Informed
by Quantified Tissue Cutting and Deformation

Gibson, MAsc (
Cathie Crukley, MLT
, José A. Gómez, MD FRCPC
Madeleine Moussa, MBBCh, FRCPC
, Glenn Bauman,
, Aaron Fenster, PhD
, Aaron D. Ward,

The Un
iversity of Western Ontario, Robarts Research
Institute, London, Ontario, Canada

Lawson Health Research Institute, London, Ontario,

Content :

3D reconstruction of digitized 2D histology sections
sparsely sampled from grossed tissue blocks depends

on knowledge about the position, orientation and
deformation of tissue during histological processing.
Many 3D reconstruction methods make the
assumption that histology sections are taken from
equally spaced, parallel planes at the front faces of
tissue b
locks. This work quantified aspects of
histological processing and applied the results to
inform the design of a reconstruction algorithm that
aligns histology to
ex vivo

magnetic resonance (MR)


We acquired MR images with 0.27
voxels using a 3T Discovery MR750 (GE Healthcare,
Waukesha, USA), and histology images with 30x30µm
pixels using a ScanScope GL (Aperio Technologies,
Vista, USA) bright field slide scanning system.
Statistical analysis was performed using Prism 5.04
raphpad Software, Inc., San Diego, USA). We
developed the 3D reconstruction using MATLAB 7.8.0
(The Mathworks Inc., Natick, USA).


MR images of 7 radical prostatectomy specimens
were acquired before and after gross sectioning into
4.4mm tissue blo
cks. One section taken from each
block was stained and digitized. 7
15 homologous
landmarks per midgland section (204 in total) were
identified on MR and digitized histology images.
Positions and orientations of sections within the tissue
blocks were calcu
lated using the best
fit plane to
landmarks identified in MR images, and 4 deformation

models (rigid, rigid+scale, affine, and thin
spline) were assessed by aligning homologous
fiducials using each model and subsequently
measuring misalignment
of landmarks using a leave
out cross
validation. These quantifications
informed the design of a 3D reconstruction algorithm
to place histology in the context of the MR images,
which was evaluated using homologous landmarks.


Histology sections

had a mean±std depth of
1.0±0.5mm and orientation of 1.7±1.1°. Rigid,
rigid+scale, affine and thin
plate spline deformation
models yielded mean±std misalignment of 1.4±0.7,
0.6±0.3, 0.5±0.3 and 0.4±0.3mm, respectively. The
3D reconstruction yielded a mean
±std target
registration error of 0.69±0.36mm.

Conclusions :

Variability in the position and orientation of sections
within tissue blocks could contribute substantial
(>2mm) 3D reconstruction error. The deformation
models for 3D reconstruction more
flexible than
rigid+scale yielded small improvements in accuracy
(<0.2mm). Our 3D reconstruction algorithm achieved
millimeter(0.69mm) reconstruction error.

DICOM Compliant Histopathology Software

Danoush Hosseinzadeh, B.Eng, MASc
, Anne L. Martel
1, 2,3

Imaging Research, Sunnybrook Research Institute,
Toronto, Ontario, Canada

University of Toronto, Department of Medical
Biophysics, Toronto, Ontario, Canada

PathCore Inc., Toro
nto, Ontario, Canada


Recent advancements in high resolution whole slide
scanners and the DICOM standard will spur a wave of
modernization in pathology. Just as whole slide digital
scanners are becoming available from several
vendors, the DICOM st
andard has also been amended
to include pathological imagery. The latter has the
potential to affect pathology much like it has done for
radiology. This paper discusses newly developed
software that implements DICOM for histopathology
Thursday, October 6, 2011

Session #1


Grand Ballroom 1


images and discusses
the changes in DICOM which
have allowed the realization of such software.


The DICOM standard recently defined two
supplements specifically for pathology: DICOM
supplement 122 which deals with the particularities of
pathological samples (tissue

processing, specimen
information, etc.) and DICOM supplement 145 which
standardizes storage and data access methods to
overcome the challenges of high resolution
histological images.


Adoption of DICOM in pathology can simplify the
workflow for P
athologists. Current day workflows
require Pathologists to physically sign out and handle
slides. These challenges can be overcome by DICOM
since it enables viewing and management of digital
slides from any location using computers. Tele
pathology for ins
tance could help many smaller
hospitals which do not have resident pathologists and
it would allow Pathologists to review cases away from
the lab. Automated computer algorithms could also be
used to assist Pathologists in a variety of tasks such
as tumour
margin estimation and disease grading.


Software has been developed which creates
histopathology DICOM images. The software works
with whole slide scanners and can also be operated
manually by lab technicians. It produces DICOM files
containing al
l the meta
information available about
the digitized slide (tissue processing steps, specimen
collection processes, specimen type, sampling
methods, stains, fixatives and more). Like other
DICOM images, patient, study, and imaging
parameters are also embed
ded in the file.


Digital pathology enables the conveniences of modern
technologies. Recent availability of whole slide digital
scanners along with recent supplements in DICOM
have made advances in clinical pathology possible.
We have
developed software that creates DICOM
compliant histological images to promote adoption of
digital pathology.

We acknowledge support from the Ontario Institute of
Cancer Research (OICR).

Efficacy Studies Investigating the Use of a
Tablet PC to Perform
Image Annotations on
Digitized Pathology Specimens

Evita T. Sadimin, MD (,Wenjin

Chen, PhD, David J. Foran, PhD


Robert Wood Johnson Medical School,
Department of Pathology and L
aboratory Medicine,
Center for Bioimaging and Informatics, New
Brunswick, NJ


In modern pathology imaging, the task of precisely
tracing the boundaries of cells and other objects of
interest is required for performing annotations of
specimens, est
ablishing gold
standard image archives
for educational and training purposes and for
preparing ground
truth training sets to test new
quantitative imaging algorithms in computer vision
research applications such as segmentation and
classification. Given t
he potential impact of
inaccurate renderings, our team has performed a
systematic performance study to investigate the
efficacy of using a commercial, off
shelf tablet to
perform these annotations.


The onscreen interactive capabilities of

provide a much more intuitive interface for end
when compared to conventional keyboard and mouse.
In this study we explore the feasibility of tracing
generated geometric shapes exhibiting
defined spatial characteristics and a
range of
salient biological objects by comparing tracing
accuracy and repeatability of a standard stylus and


The first experiment utilized a team of volunteers who
were asked to trace 1
wide outlines of angular
(triangle and nonagon)
and curved (circle and ellipse)
shapes. Each shape was retraced at three different
scales. A Java based program was developed to
record the tracing time and the coordinates of the
traced boundaries. Tracing accuracy is measured by
computing differences
between the generated and
traced contours as well as relative error in shape
measurements. In the reproducibility experiment,
several medical professionals were asked to precisely
outline a well
defined microscopic image region five


minary results showed that tracing the images
with stylus was not only significantly more accurate in
all measurements than using mouse (p<0.05); it was
also significantly faster (p=5e
11). The stylus also
reduced error in tracing perimeter by 12%. In
dition, tracing with stylus was more reproducible
compared to mouse (p<0.05). Our results also
indicate that it is possible to achieve optimum
combination of speed and accuracy by selecting the
optimum magnification in annotating pathology



We conclude that medical annotation using stylus is
not only feasible but also more intuitive, accurate and
reproducible than using mouse. Further work in this
area will include implementation of tablet
pathology annotation applications and
better post
processing techniques to improve shape fidelity.

Development of Multigene Expression
Signature Maps at the Protein Level from
Digitized Immunohistochemistry Slides

Stephen C. Schmechel, MD, PhD

), Gregory J. Metzger, PhD,

Stephen C. Dankbar, BS,

Jonathan Henriksen, BS,

Anthony E. Rizzardi, BS,

Nikolaus K. Rosener


Departments of
Radiology and

Laboratory Medicine
and Pathology, University of Minnesota, Minneapolis,

BioNet, University of Minnesota, Minneapolis, MN


Molecular classification of diseases based on
multigene expression signatures is increasingly used
for diagnosis, prognosis, and prediction of response
to therapy. Immunohistochemistry (IHC)

is an optimal
method for validating expression signatures obtained
using high
throughput genomics techniques since IHC
allows a pathologist to examine gene expression at
the protein level within the context of histologically
interpretable tissue sections.

Additionally, validated
IHC assays may be readily implemented as clinical
tests since IHC is performed on routinely processed
clinical tissue samples. However, methods have not
been available for automated n
gene expression
profiling at the protein level
using IHC data. We have
developed the methods to compute expression level
maps (signature maps) of multiple genes from IHC
data digitized on a commercial whole slide imaging
system. Areas of cancer for these expression level
maps are defined by a pathologi
st on adjacent, co
registered H&E slides allowing assessment of IHC
statistics and heterogeneity within the diseased
tissue. This novel way of representing multiple IHC
assays as signature maps will allow the development
of n
gene expression profiling data
bases in three
dimensions throughout virtual whole organ


A software interface, which will be referred to as
SigMap, was written in the Java programming
language, generated IHC signature maps through a
multistep image analysi
s and image registration


Unstained sections of formalin
fixed, paraffin
embedded prostate tissue containing discrete areas of
prostatic adenocarcinoma of different histologic
grades were obtained with approval from the
University of Minn
esota Institutional Review Board.
Six adjacent 4 micron sections were cut from a tissue
block. One section was stained with hematoxylin and
eosin (H&E). IHC was performed for MKI67, ENO2,
CD34 and ACPP and alignment and protein expression
with IHCMap was c


The study pathologist created annotations of prostate
cancer areas by Gleason grades present in the block,
separately annotating 3+3, 3+4 and 4+3 areas within
different virtual planes (“layers”) of the reference
slide image file. Addit
ional information used by the
software included a table of IHC stains and their
respective user
input weighting factors. In this study,
the weights for MKI67, EN02, CD34 and ACPP were
chosen as 0.473, 0.035, 0.035 and
respectively. The sign of the
weights reflects the
current understanding as to each protein’s up

regulation in aggressive prostate cancer, but
the current magnitudes of the weights are somewhat
arbitrarily chosen to provide a proof a concept.


SigMap is a unique
approach to multiplexed analysis
in IHC, and uniquely leverages whole slide imaging.
We successfully developed this method and applied it
to a prostate cancer signature. Work is ongoing to
determine utility in a larger clinical dataset.

In Silico Analys
is of Diffuse Gliomas Identifies
Microenvironmental Influence on Key
Transcription Factors and Morphological
Signatures of Glioblastoma

Lee A.D. Cooper, PhD (
), Jun
Kong, Fusheng Wang, David
A. Gutman, Sharath
Cholleti, Tahsin Kurc, Carlos S. Moreno, Daniel J. Brat,
Joel H. Saltz, MD, PhD

Emory University, Center for Comprehensive
Informatics, Atlanta, GA


Emerging multi
modal datasets that link histology to
genetic and patient endpo
ints are creating new
frontiers for pathology research. Using data from The
Cancer Genome Atlas (TCGA) and REMBRANDT
projects, we have developed
In Silico

methods and
informatics tools to investigate the role of tumor
microenvironment on transcription and
associations of histology and genetics on patient
outcome. We have identified both microenvironmental

influences on the expression of key transcription
factors and the existence of morphological subtypes
of glioblastoma.


Whole slide imaging

presents opportunities to
quantitatively study morphology at large scales. We
have developed a suite of image analysis tools to
segment and characterize millions of nuclei in
gliomas. These tools generate statistical models of
patient morphology that can
be analyzed for
comparison with patient outcome and genomics. We
have also investigated necrosis in gliomas using a
computer interface to identify necrotic tissue.
Extent of necrosis can then be compared with gene
expression arrays using Significance

Analysis of
Microarray to identify genes significantly correlated
with necrosis. All segmentation and markup data are
managed through the Pathology Analytical Imaging
Standards database.


Percentage of necrosis was analyzed in whole slide
images of

frozen TCGA GBM tissues. Percentage
necrosis was correlated with gene expression to
identify transcripts that are significantly correlated
with extent of necrosis in 177 slides from 91 patients.
The morphologies of 200 million nuclei were analyzed
in imag
es of permanent TCGA GBM tissues from 162
patients. Nuclear morphology was aggregated into
level profiles that were clustered to identify
groups of patients with similar morphology. Patient
outcome and genetic alterations were analyzed across
ers to determine cluster characteristics.


The transcription factor CEBP
B/D, known for its role
as a master regulator of the aggressive Mesenchymal
GBM phenotype, was identified as significantly
correlated with extent of necrosis.
stry analysis revealed that CEBP
B/D are hypoxia inducible, suggesting that GBM
phenotype may be a local phenomenon driven by
tumor microenvironment. Morphological analysis of
nuclei revealed several patient clusters.


We have developed a suite

of bioinformatics tools for
modal glioblastoma data analysis and
integration and identified morphological signatures of
glioblastoma and microenvironmental influence on
key transcription factors.


A Clinically Intuitive, Non
Parametric Method
Using Multidimensional Polyhedrons to
Combine the Results of Multiple Laboratory
Tests and Potential Implications
for Clinical
Laboratory Decision Support

Brian H. Shirts, MD, PhD
, Sterling T. Bennett, MD,
, Brian R. Jackson, MD, MS
1, 3

University of Utah, Department of Pathology,
Lake City, UT

Intermountain Healthcare, Salt Lake City, UH

ARUP Laboratories, Salt Lake City, UT


Realizing the potential of personalized medicine will
require statistical methods to integrate traditional
laboratory data with genetic and cl
inical information
for diagnosis and risk prediction. Many methods of
multivariate analysis have been applied to
diagnostics, but they are practically opaque and none
has been widely adopted. We evaluate the method of
counting disease and non
disease cas
es in
multidimensional polyhedral partitions of the
multivariate result space to calculate likelihood ratios
and probabilities of diagnosis. In principle, this
method is a non
parametric analog of multivariate
based likelihood ratios used for ma
serum screening.


Simple tables of clinical data were used with each
parameter defining a separate dimension in a
multidimensional clinical data space. We used R
statistical software to evaluate the distribution of
cases and controls
near specific points in this
multidimensional space defined by a specific set of
patient test values.


We generated multidimensional polyhedrons,
centered on specified test values and extending a
specified multiple of the median average deviation
rom this center for each testing dimension. Counts
of cases and controls contained in this polyhedron
defined the probability of the ‘patient’ being a case or
control. We used a sample of 2053 individuals with
celiac disease workup at Intermountain Healt
hcare to

illustrate potential utility in improving decision support
information provided to clinicians and preventing
unnecessary biopsies.


tTG IgA and age were important predictors of biopsy
positivity with sufficient data for subsequent analysis.
1652 individuals in our clinical sample had both of
these measures. Probability of a positive biopsy
ranged from 0 to 1. Accuracy of prediction
with the density of past data near the test values,
with median difference between upper and lower
95% confidence limits being 0.11.


The presented method for multivariate analysis of
clinical results is transparent, conceptually simpl
e, and
provides results that are easy to interpret. A
limitation of this method is the requirement of very
large data sets when many parameters are used. An
advantage is that a diagnostic laboratory could
continuously integrate data from local clinical
ncounters into prediction databases, enabling more
precise probability estimates that are tailored to the
local population.

Design and Implementation of Custom
Middleware Based Chemistry Lab
Autoverfication Rules

William J. Lane, MD, PhD (
) ,
Frank Kuo, MD, PhD, Neal Lindeman, MD

Brigham and Women’s Hospital, Pathology
Department, Boston, MA


The accuracy of clinical laboratory test results must
be verified before release. Verification is intended to
detect analytical errors, by comparing the results with
expected values in both health and disease. In many
laboratories, this is done manually by

technologists, at great labor cost and with varying
degrees of expertise. Alternatively, a computer may
be programmed for automated review
(autoverification) of results.

Thursday, October 6,

Session #


Decision Support

Natural Language Processing

Kings Garden North



The Chemistry Lab at Brigham and Women’s Hospital
(BWH), which

performs ~4.5 million per year,
recently implemented autoverification of results
generated on Cobas 6000 Analyzers (Roche
Diagnostics, Indianapolis, IN), using middleware
(Data Innovation, South Burlington, VT) that connects
to a legacy LIS.


each analyte, an autoverification rule decision tree
was designed based on knowledge of that analyte in
health and in disease. The rules were simulated using
real patient data accrued over one month. When
needed, rules were adjusted and re
simulated. Rules

that passed the simulation were encoded in
middleware and tested in silico with “cases” of results
designed to assess the performance of the rules.
Once all testing was complete, rules were
implemented and monitored in production for several


specific autoverification hold rules were
created that identify if a particular result should be
held. The analyte
specific approach allowed
piecemeal deployment of rules for each analyte (most
common analytes first). The rules evaluate delta
ecks (difference between two successive
measurements of the same analyte in the same
patient), instrument error flags, values >3SD beyond
the population mean, and values inconsistent with
other analytes assessing complementary states of
disease or health i
n a given patient. Currently, 13
different rule prototypes are used, for 48 analytes. In
the absence of hardware errors detected by the
instrument, these rules autoverify 95% of analyte
results and 85
90% of all chemistry tests, resulting in
a significant
savings in labor and cost. Rules for the
remaining analytes are in development.


Custom chemistry analyte autoverification rules were
developed and implemented in middleware, enabling
a significant savings in labor costs for the laboratory.
ese rules should be usable by other institutions
after adjusting the rule parameters to match their
own patient populations.

Making Malarial Diagnosis More Reliable: Using
Image Analysis for Identification of
Plasmodium Falciparum Gameotcytes

Joy J. Mam
men MD (
Maqlin P.
, Feminna Sheeba, MCA
, T. Robinson PhD

Christian Medical College, Transfusion Medicine,
Vellore, India

Madras Christian College (Autonomous), Tambaram,

Chennai, India


Malaria is a significant cause of morbidity and
mortality in tropical countries. According to WHO, in
2009, more than 50% of confirmed reported malaria
cases were from India. The gold standard for the
diagnosis of malaria continu
es to be the manual
microscopic examination of a stained thick smear or
thin smear where at least 100 fields should be
screened at 100x (oil immersion) with at least 8
minutes spent per slide. Given the high prevalence
the numbers for primary screening
and quality
assurance (10
15% repeat screening) is a mammoth
task requiring scarce resources. Therefore there is a
fear of underreporting and difficulty in quality control
of positive cases. Using technology to assist in
screening of slides by image analys
is will introduce a
paradigm shift in the current scenario.


MATLAB 2009b (MathWorks Inc, MA, USA)


In India, the common species seen are

Plasmodium vivax

Automatic segmentation techniques were applied to
iff images of peripheral blood smears

acquired using Leica DFC camera, in order to identify
gametocytes. To identify the

gametocytes, as a first step, the gray image of the
source image were inversed and converted into a

binary image with a proper
threshold value, in order
to obtain all the objects in the image (I
). The

objects other than WBCs and RBCs are eliminated to
obtain image I
. The difference between images


and I
is obtained. The application then used
morphological operations and g

analysis to segment out only the gametocytes.
number of segmented gametocytes is also

obtained from the segmented binary image.


We have a prototype application that can identify p.
falciparum gametocytes. The results of the
reliminary validation study will be discussed. The
quality of the images and the presence of artifacts
affects the analysis and these issues should be taken
in order to obtain better results.


The above data shows that the possibility to use

image analysis techniques for screening of blood
smears for malaria parasites is possible. More work is
required to refine the algorithms and the methods
used. Initially this technique may be used for quality


Extraction and Analysis of Data
Elements from
based Prostate Cancer Pathology Reports

Kavous Roumina, PhD (
), Eugene
Farber; Walter H. Henricks, MD

Cleveland Clinic, Center for Pathology Informatics,
Cleveland, OH


hology reports in laboratory information systems
are inherently textual and do not easily lend
themselves to data mining activities. The capability
to extract discrete data elements from text
pathology reports would be of great value for
research an
d analysis. We describe a heuristic
approach to categorize and compartmentalize
prostatectomy cancer reports into discrete data
elements ready for further analysis.


Data analysis component (.NET Framework 3.5,
Microsoft); relational dat
abase (Access 2003,
Microsoft); laboratory information system
(CoPathPlus, Cerner).


The system consists of two components:
extract/analysis and presentation modules. The
extract/analysis module identifies Key
Value pairs
from textual, checklist
ormatted prostatectomy
reports extracted from the laboratory information
system. Keys are checklist headers, e.g. “Gleason
Score”. Values are respective observations in the
report, e.g. “7”. The system analyzes Keys and
Values, extracts pertinent Values
, and assigns them to
Keys as discrete elements in the database. The logic
accounts for variations in the tumor report checklist
over the years analyzed. Employing object
design, Key
Value pairs are organized as reusable
programming codes (“clas
ses”). The system presents
the Key
Value pairings to a reviewer who verifies
assignments by the system and resolves potentially
inaccurate matches resulting from ambiguities in the
source report. Each Key
Value pair is assigned a
coded level of “un
certainty”. The reviewer may
access the original report within the application.
Following review, the user “commits” the case to the
permanent database.


The system has processed 3456 historical
prostatectomy reports (2003
2011) from the
laboratory information system. Use of the system has
transformed the text
based, non
discrete diagnostic
and staging data in these reports into discrete data
elements avai
lable for analysis and research. A
typical prostatectomy report contained 28 Key
pairs. An average of 6.1 Key
Value pairs per report
(<25%) required modification by the user prior to
commitment to the database.


A simple yet robust, o
oriented system has
enabled the transformation of textual diagnostic,
staging, and prognostic data in prostatectomy
pathology reports into discrete data elements to
enable clinical and translational research and other
analyses. The design paradigm s
hould be deployable
to other types of textual checklist
pathology reports.

Advantages of Structured Data Reporting Using
the CAP Electronic Cancer Checklists (eCC):
The Cancer Care Ontario Experience

Samantha Spencer, MD (
, Gemma
Lee, BSc, PMP
, Jaleh Mirza, MD, MPH
, John R.
Srigley, MD, FRCPC
, Tim Yardley, HND
, Aleem
Bhanji, BSc, PMP
, Jeffery Karp, BSc
, Gregory
Gleason, MBA
, Richard Moldwin, MD, PhD

The College of American
Pathologists, Deerfield, IL

Cancer Care Ontario, Toronto, Ontario, Canada

McMaster University, Hamilton, Ontario, Canada


A standard informatics approach for recording and
reporting cancer pathology reports has the potential
to prevent diagnosti
c errors and omissions, thereby
improving patient care and research. To this end, the
College of American Pathologists produces the
electronic Cancer Checklists (eCC) based on the CAP
Cancer Protocols, widely
recognized as a gold
standard in cancer pathol
ogy data collection. The
eCC informatics model allows for standardized data
transfer from anatomic pathology software to central
cancer registries.


Checklist questions and answers are entered into an
editing tool for storage in a SQL Server d
Each checklist is exported as a single XML file from
the eCC database. Vendors use these XML files to
create standardized data
entry forms and reports for
pathologists. The standardized eCC codes stored in
the vendor database can be sent to cen
tral registries,
using HL7 messages for mandated cancer reporting.


Cancer Care Ontario has adopted the eCC into its
cancer registry data collection system to improve
interoperability and the quality of data collection for
cancer surveillance. Err
or reduction and increased
timeliness are additional factors driving eCC uptake.
For 2011/2012, Cancer Care Ontario has mandated

implementation of 63 eCC templates, involving 110
pathology laboratories throughout the province.


As of August 2011,

90/110 hospitals (82%) have
implemented eCC
based synoptic reporting. Ten to
fifteen additional hospitals are slated to participate by
late 2011. In July 2011, nearly 75% of cancer
pathology resection reports were sent to the central
registry using the eC
C model. A survey of 970
clinicians found that pathologists, surgeons and
oncologists expressed high satisfaction with the eCC
based reports compared to traditional narrative
reports. The adoption of the eCC has led to more
complete reports, as well as th
e automated capture of
cancer staging and related data. Detailed reports are
shared with hospitals to provide feedback on
workflow and to assist with quality assurance efforts.


The Cancer Care Ontario eCC integration experience
is an
informatics success story. It demonstrates that
comprehensive implementation of eCC
standardized structured reporting improves
information system interoperability, data reporting,
quality assessment, cancer research and cancer care.

Evaluation of
A Natural Language Processing
Platform in Concept Tagging of Surgical
Pathology Reports for Information Retrieval

Radhika Srinivasan, PhD (
Albert Riedl, MS
, Estella Geraghty, MD
Hogarth, MD

UC Davis School of Medicine, Departments of
Pathology and Laboratory Medicine and
Medicine, Sacramento, CA


Diagnoses in surgical pathology reports are primarily
contained in narrative, “free text” sections that

the ability to implement concept
based searching.
This work evaluates MojoMapper, a Natural Language
Processing (NLP) framework, in the task of concept
tagging biomedically relevant concepts in surgical
pathology reports to support searching cases b


MojoMapper is a java
based, web services
NLP platform developed at UC Davis. It implements
stochastic and rule
based text processing that adjusts
behavior in response to semantic and syntactic
features of the input text. Th
e architecture is pipeline
based with annotators operating on pre
text for linguistic manipulation, parts
discrimination, negation detection and

determination of semantic type.


To have the broadest concept coverage possible, we

configured MojoMapper to use the Unified Medical
Language System. We extracted 232 diagnostic
phrases from 100 sequential pathology reports.
Phrases only containing temporal concepts (“cycle day
25”), lacking biomedical concepts (“see
comments”, “no fu
rther findings”, “histologic grade,
low grade”), or conceptual content of low retrieval
value (“negative surgical margins”) were excluded
from scoring resulting in 215 phrases used to
evaluate performance. Two physicians (M.H. and
E.G.) evaluated the perfo
rmance of the system.
Individual points were awarded for each correctly
identified disease relevant concept and negation of


MojoMapper correctly identified 82% relevant
concepts. Inter
rater reliability between the two
physicians was mod
erate to good (kappa 58%). In
analyzing the MojoMapper errors, we identified a
number of optimizations that will improve the
system’s ability to correctly concept
tag biomedical
concepts for information retrieval of surgical
pathology cases.


MojoMapper was built to concept
tag causes of death
in electronic death records and was used as is without
any surgical pathology optimizations. Given this we
find that this system is still able to correctly match a
high percentage of pathology concepts. U
MojoMapper’s architecture to integrate new
annotators, we plan to add pathology annotators to
address many of the pathology lexicon specific issues
that caused matching failures in the current analysis.
We also plan to implement improved semantic
essing so that “presence of inflammatory cells” is
conceptually equivalent to “presence of an
inflammatory process”.


Automation of Parasitized
Erythrocyte Count by
Microorganisms in Wild Animals

Denise F. P. Costa (
Leonilda Santos, MSc, Fabiana Peres, MSc

State University of West of Paraná, Engineering and
Science, Fo
z do Iguacu, Brazil


To keeping the biodiversity of wildlife is required to
check the presence of microorganisms on the surface
of erythrocytes can cause anemia if the animal is with
impaired immune systems. The wild animals in
captivity, be influ
enced by stress and due to their
behavior, many of the diseases can be diagnosed only
by laboratory tests. The quantification of
microorganisms is performed manually and this
activity is an exhaustive, time consuming and more
prone, depends on physic
ian skill. In order to
facilitate this activity, a procedure is being developed
using techniques of Digital Image Processing to
perform the quantification of microorganisms


Blood samples of wild animals are collected with
anticoagulant and examined fresh; the capture of
images is made using a microscope Olympus BX
objective 40 x and eyepiece 10 x, an Olympus DP
digital camera coupled to the biological microscope
and the camera software to transfer images to the
ter via USB 2.0 for application of the
techniques of Digital Image Processing.


After defining a protocol for capturing images of
Digital Image Processing techniques are applied to
classify the constituent objects. Through a
representation and desc
ription to put in evidence the
characteristics of the objects of interest will be held
the counting of each class: total erythrocytes and
microorganisms, being defined the percentage
between the quantitative constituent objects.



automated counting of cells by Digital Image
Processing facilitates the work of professional in the
field of hematology, to be effective, accurate and fast,
reducing costs to the laboratory. Upon completion,
the final product will be used to assess the
terference of parasitic microorganisms in
erythrocytes in relation to anemia, which interferes
with the biodiversity of local fauna.


The discovery of hemotropics microorganisms in wild
animals is recent, development manual techniques,
and the
development of innovative automated
quantification of microorganisms parasites of
erythrocytes. The monitoring of parasitic
microorganisms is important in maintaining a healthy
population of wild animals which, in turn, helps in
reducing losses to the spec
ies, avoiding the imbalance
of regional biodiversity.

Application of Tracking Technology in Anatomic

Troy Brown (
James Dobbs

Orion Biosystems, Rolling Mead
ows, IL


Misidentification errors in the anatomic pathology
laboratory, while relatively infrequent, can have
disastrous consequences. Such errors can cause
patient inconvenience or harm when additional tissue
collection is needed. Misidentific
ation of cases,
specimens, blocks and slides can delay diagnosis and
treatment or cause treatment to be administered
inappropriately. Technology solutions such as
barcode labeling and tracking are being used but
have not been fully developed. This paper
misidentification errors and possible technology


We analyzed the use of relational databases and
barcoding in pathology laboratories. We also studied
the application of Lean and Six Sigma technologies in
the pathology lab
oratory. We studied the current and
Thursday, October 6, 2011

Session #

Lab Automation

Kings Garden South/LeBateau


potential effectiveness of electronic cross
and electronic tracking systems using Standard Query
Language databases.


We conducted a review of current literature regarding
misidentification of cases, sp
ecimens, blocks and
slides in pathology laboratories. We focused on
specific vulnerabilities associated with the anatomic
pathology laboratory setting, and potential remedies
for each. We reviewed the use of barcode technology
in all types of laboratorie
s, including anatomic


Barcode technology is well
established in a number of
health care settings, including laboratories. Some
anatomic pathology laboratories use barcode
technology, but it is not fully integrated, often
requiring the

use of handwriting at the point of tissue
collection and accessioning. Many anatomic
pathology laboratories rely on an unintegrated, multi
tiered and nonsynchronous approach to maintaining
quality and integrity throughout the tissue handling
process. Pa
per requisition forms, which can be lost or
placed with the wrong tissue, are still used.


Anatomic pathology laboratories are particularly
vulnerable to misidentification errors because tissue
undergoes several processes from the time of
ection through transcription. Anatomic pathology
laboratories would benefit from a barcode system that
tracks tissue from the time of collection through
transcription. Such a system would reduce human
error and identify misplaced tissue. A paperless
uisition system would also reduce misidentification
errors by reducing the potential for misplaced
requisition forms and errors related to handwritten

Deployment of an Orders Interface Between
CoPathPlus and an Automated
Staining Platform

J. Mark Tuthill, MD (
), Michael
Czechowski, Kathleen M. Roszka, HTL, ASCP,
Mehrvash Haghighi MD

Henry Ford Hospital, Division of Pathology
Informatics, Detroit, MI


Immunoperoxidase staining of tissues has become an
important routine aspect of pathology practice
resulting in the development of automation
technology to perform these assays. As orders are
typically created in the Anatomic Pathology LIS, it is a
next step to interface such orders to the
instrument platform eliminating dual order entry and
errors, improving efficiency, and thereby increasing


Sunquest CoPathPlus (Sunquest Information Systems,
Tuscon, AZ), Dako Automatic Immu
Stainer with DakoLink interface server (Denmark)


A bidirectional HL 7 interface was implemented
between Sunquest CoPathPlus version 4.1 (SQCP) and
a Dako Automated Immunostain Platform allowing
immunohistochemistry orders place i
n CoPath to be
received in the DakoLink instrument control software
markedly simplifying run setup. Slides are required to
be labeled with vendor proprietary asset tags.


While slides still need to be manually labeled for runs,
the elimination of
dual order entry by automation of
order entry markedly decreases assay run time saving
upward of 360 hour of manual effort per year,
eliminating errors, and improving laboratory


Implementation of an interface between the AP LIS
nd automated staining platforms save times and
eliminates errors increasing laboratory capacity and
throughput as well improving patient safety.

The First Conversion of Pathology Assets
to/from an APLIS

Lessons Learned

Lyman T. Garniss, BS (
), James
Floyd, Ling

Massachusetts General Hospital, Department:
Pathology Informatics, Boston, MA


Massachusetts General Hospital (MGH) Pathology
Service recently implemented
Sunquest's CoPath Plus
version 5.0 This was not the first implementation of
Sunquest CoPath Plus v 5.0 but it was the first time
that large numbers of unique cassettes and slides
were converted from a foreign system into CoPath
Plus (or any APLIS) and coul
d be recognized and
processed in the new APLIS.

During the implementation a team of dedicated
specialists from Sunquest, Massachusetts General
Hospital and Partners Healthcare Systems Information
Systems converted over 20 years of Anatomic
Pathology data.

This included over 2.4 million cases,

1.8 million unique tissue cassette numbers and 4.2
million unique slides numbers.


The technology to accomplish this project included;
The existing PowerPath APLIS database with unique
asset identifiers fo
r specimen cassettes and slides;
programs and formatting rules supplied by Sunquest,
several programs, filters and conversion utilities
developed at Partners Healthcare Systems
Information Systems and the receiving CoPath Plus v
5.0 database.


uest's CoPath Plus version 5.0 has the ability to
accept, store and make available " foreign identifiers
". In the case of the MGH data conversion the
PowerPath native identifiers for cassettes and slides
were moved to the foreign identifier fields in the
records of CoPath.


A newly installed APLIS (CoPath Plus) was able to
open, access and process new tests and orders on
cassettes and slides from a foreign APLIS for the first
time. The process was not easy and many lessons
were learned while
converting the assets and cases.


This was the first time that a new APLIS was used
convert, store, access and order new tests on
cassettes and slides from a foreign APLIS. The
"converted " assets can be used to order new stains,
new slides, or
der whole slide imaging, and order
molecular tests years after the case has been
finalized. Slides and cassettes can also be more easily
tracked and retrieved.