PAPNET™ Cytological Screening System

NEW INSTRUMENTATION PREVIEW
PAPNET™ Cytological Screening
System
least 20 years. Automation offered the
hope of efficiently and accurately processing the voluminous and labor-intensive nature of Pap smear screening. However, all previous attempts to automate
the analysis of cervical smears have relied on classical algorithmic processing
techniques. These techniques depend
on finding the boundaries of objects and
deriving simple morphological features
(eg, area and density). While these techniques work well with simple objects in
uncomplicated scenes, they are incapable
of handling the complex and infinitely
variable combinations of overlapping
material typically found on Pap smears.
Such attempts at Pap smear automation, therefore, have required some type
of monolayer cell preparation. In order
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The literature is replete with reports of failures
of the cytology laboratory to diagnose invasive
cancer. One study reported a cumulative falsenegative error rate for invasive cancer of about
50%. In the same study, the rate of screening
errors for precancerous lesions was at least
28% . . . . Regardless of the percentages, it is
clear that the error rate of cytologic screening
for precancerous lesions and invasive cancer of
the uterine cervix is quite substantial (Koss LG:
The Papanicolaou Test for Cervical Cancer Detection: A Triumph and a Tragedy. JAMA 1989;
261:737-743).
Attempts to bring automation to the
analysis of cervical smears date back at
to make a thin, monolayer preparation, only a subpopulation of all the
cells obtained from the patient is used.
Monolayer preparations thus represent
a source of false-negative results due
to the cell loss associated with subsampling and filtration or centrifugation. The very slides that typically
cause laboratory screening false-negative results have very few abnormal
cells on them; the loss of cells from the
artificial processing and subsampling
associated with all monolayer preparations increases the potential for falsenegative screening errors. Another disadvantage of monolayers is that they
require a change in standard gynecology and pathology practice. Use of the
conventionally prepared Pap smear as-
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Fig 1. Neural networks are reminiscent of neurobiology not only in the sense that they learn from experience but also because they are characterized by highly parallel architectures composed of densely interconnected but relatively simple processing elements.
276 Laboratory Medicine Vol. 22, No. 4 April 1991
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PAPNET, a semiautomated cytological
screening system, is available for investigational use from Neuromedical Systems, Inc (NSI®), of Suffern, NY. PAPNET is a computerized imaging system
that uses neural network-emulating
software to help detect abnormal cells
on conventionally prepared and stained
cervical Pap smears. NSI is the first company to apply this advanced, neural network computer technology to cytology.
The PAPNET system has a false-negative rate of less than 3% (significantly
less than that in the average laboratory), according to the initial clinical trial.
The current manual practice of
screening cervical smears has an intrinsic and unavoidable false-negative rate.
This occurs primarily because relatively
few abnormal cells are present among
the vast amounts of normal material
viewed daily. Essentially, the cytologist
is searching for a "needle in a haystack." In any screening task, be it
proofreading or Pap smear screening,
whenever the vast majority of objects
examined are not of concern (normal),
psychological habituation takes place,
which makes the proverbial needle that
much harder to find. Sometimes it is
missed altogether:
traepithelial lesions or malignancies of
other uterine sources.
sures that the classical visual presentation of cytopathology (tumor diathesis,
infective background) is maintained
and intact and that no change to current medical practice is required.
Operation Principle
The PAPNET system utilizes both algorithmic and neural network computer
technologies. Neural networks are parallel information processors that mimic
the neurological ability to learn from
experience. They, therefore, excel at
recognizing subtle, hard-to-define patterns. This contrasts them from classical computers that require a step-bystep description (or algorithm) of how
to distinguish one object from another.
Neural networks have been used primarily in aerospace and defense to
identify ambiguous objects (are they
missiles or a flock of birds?). Because
PAPNET includes a neural network (Fig
1), it can mimic the human cytotechnologist's ability to distinguish single or
overlapping abnormal cells from the
overlapping normal cells, debris, lymphocytes, blood, and neutrophils found
on the conventionally prepared Pap
smear.
A robotic arm delivers conventionally
prepared Pap smear slides from a preloaded slide cassette holder to an automated microscope stage. A bar code
reader confirms patient identification.
Slides are first scanned using a low power objective to locate cellular material
and are then scanned using high power
objectives with automatic focusing. A
high-resolution, full-color video camera
passes the images on to the primary algorithmic classifier. The primary classifier
locates cell nuclei and other matter using morphological criteria. While most
of the normal-appearing cells are
screened out, approximately 1,000 to
10,000 potentially suspect objects
(mostly overlapping normal cells) are
passed to a neural network-based secondary classifier for evaluation. The neural network then classifies these images
by generalizing from its training and selects 64 objects from each slide. These
images are then stored on a data storage cartridge.
Following the completion of PAPNET's
run of 100 slides, the cytologist removes
the data storage cartridge from the
Scanning Station and inserts it into the
Review Station. He or she now evaluates
the 64 suspect objects from each slide
selected by the PAPNET system on a
high-definition, full-color monitor (Fig
2). In approximately 30 seconds, the cytologist can either confirm a negative diagnosis or determine that the case
needs closer scrutiny, based on the presence of cells indicative of squamous in-
An automated microscope with several components has a robotic arm that delivers slides
from a preloaded cassette, which holds up to
100 slides, to the motorized stage. A bar-code
reader confirms patient identification. A highresolution, full-color video camera obtains
electronic images from a linear array of three
objectives to provide magnification of 50x,
200x, and 400x. A slide dotter uses an ink-jet
pen to mark the suspicious cells as specified
by the cytologist during the follow-up review
process.
A central processing unit is the main controller of the Scanning system. It is a very
high-speed computer system that includes a
video display controller, a video monitor, a
keyboard, a floppy disk drive, a large hard
disk drive, and parallel and serial ports.
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Fig 2. The PAPNET ™ System Review Station.
System Description
A minimum PAPNET configuration
consists of one 4x3-ft Scanning Station and one 4x3-ft Review Station.
This basic configuration has an approximate throughput of 40,000 to 50,000
slides per year. Each additional 40,000
slides per year would require an additional 4x3-ft Scanning Station. The
scanning and review stations can be
installed in different sections of the
laboratory and are operated independently of each other. The basic power
requirements are one 220-V 15-A outlet and one 110-V 15-A outlet for
each Scanning Station and one 110-V
15-A outlet for each Review Station.
The Scanning Station automatically
scans Pap smear slides for atypical
cells. It runs continuously and virtually
unattended, storing 64 images from
each slide for later inspection by the
cytotechnologist on the Review Station. The Scanning Station consists of
the following subsystems.
The primary image processor performs several
tasks. It finds areas of interest on the slides, it
finds focus, it is used as the primary screening
process for atypical cell detection, and it is
used to compose color images for creating
the 64-cell display grid. The neurocomputer is
used as a pattern-recognition device in the
secondary screening process for atypical cells.
A data storage device with removable media
is used to store the 64-cell images from each
slide for later review. The images are stored in
a digital data format with all of the images
from 100 slides stored on a single small disk
or tape cartridge.
Uboratory Medicine Vol. 22, No. 4 April 1991 277
The Review Station is used for viewing the 64cell images selected for each slide by the Scanning Station. The Review Station is the workstation for the cytologist, and consists of the
following subsystems:
A robotic arm delivers slides from a preloaded cassette
cartridge to an automated stage.
The host CPU is the main controller of the Review system workstation. It is a very highspeed computer along with a VGA video display controller, a video monitor, a keyboard, a
floppy disk drive, a large hard disk drive, and
parallel and serial ports.
The high-resolution RGB monitor is used to
present the 64-cell images from the high-resolution display controller to the cytologist for
review. This is the primary display screen to the
operator.
A bar code reader confirms patient identification.
000
Slides are scanned using a high resolution, color video
camera with automatic focusing.
A mouse is used as a pointing and selecting
device by the cytologist.
Basic Operation
The PAPNET workflow is outlined in Fig
3. The PAPNET system is designed to
use standard Papanicolaou-stained
smears on glass slides. The smears are
made and prepared just as in current
laboratory practice. Monolayer preparation or Feulgen staining, two techniques that have been used in the past
for automated cytology systems, are
not necessary with PAPNET, although
PAPNET can read slides prepared in
these ways.
A primary, "algorithmic" classifier locates cell nuclei
and other objects using morphologic criteria.
Cell nuclei and other objects are passed to a neural
network based secondary classifier.
Scanning Station
A laboratory technician places the
loaded slide holder cassette on the microscope elevator. He or she flips a toggle switch to turn on the vacuum that
keeps the slide holder cassette in place.
The technician then inserts an empty
data cartridge into the data storage device. Then, using the system keyboard,
the scanning is started. The rest of the
operations are automatically performed
by the Scanning software.
The software aligns the stage, the
objectives, and the robotic system by
issuing commands to send each to its
home position. Then the data cartridge
is initialized. A directory is made, using
the current date as directory name,
and transferred onto the data cartridge.
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64 suspect cells from every slide are digitally recorded
for display and confirmation by a cytologist.
Confirmed abnormal cells are then separately recorded
and "dotted" on the glass slide by an automated marker.
A report is generated summarizing findings by the
PAPNET system.
Fig 3. The PAPNET workflow outline.
278
Laboratory Medicine Vol. 22, No. 4 April 1991
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A data storage device with removable media is
used to retrieve the 64-cell images from each
slide as stored by the Scanning Station and to
store the locations of any cells that are tagged
by the cytologist for dotting during the review
process.
PAPNET used:
for Rescreening
Pathologist
1 False negative
Cytotechs
98
PAPNET
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100 Slides
*False negative rate <19<
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PAPNET used:
for Prescreening
Pathologist
Examination
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PAPNET
97
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Examination
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100 Slides
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Fig 5. Hypothetical case. With a more rapid turnaround time on positive results, a false-negative result
due to lab screening error could only occur if a positive result is missed by the the manual and PAPNETassisted examinations.
The robotic system then picks up the
first slide and places it onto the microscope stage, at which point the bar
code is read. The slide is then scanned.
When the scan of the first slide is completed, the grid of 64-cell images is
stored on the data cartridge and assigned the bar code number as its file
name.
The remaining slides in the cassette
are processed in the same way. The
processing of all 100 slides in a cassette should take, on average, about
16 hours. Should a technician start a
scanning run at 4 PM, the images from
these 100 slides would be available for
cytologist review around 8 AM the next
morning. Should a laboratory require
additional throughput, NSI installs additional Scanning Stations that are run in
parallel.
After the 100 slides are processed, the
system stops running automatically, indicating on the operator's screen that the
run is finished. The technician then flips
the toggle switch, releasing and removing the slide holder cassette. He or she
ejects the data cartridge from the data
storage device and places it on the back
of the corresponding slide holder cassette. The technician may then start another run as described above.
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Fig 4. Hypothetical case. A false-negative result due to lab screening error could only occur if a positive
case is missed by both the manual and PAPNET-assisted examinations.
Review Station
The cytologist removes the data cartridge from the Scanning Station's data
storage device and inserts it into the
Review Station's data storage device.
Then the cytologist selects the appropriate menu command to start the Review function. The Review function retrieves the first 64-cell image grid from
the first slide and loads it onto the
high-resolution RGB monitor.
The cytologist can now review the
slide. The 64-cell images are presented
(at 200x) as a single 8x8 grid of
"tiles" on the screen and also as four
screens of 4x4 tiles. Each tile presents
the suspicious object in its center with
a 128x104-um contextual surround.
The cytologist uses a mouse as a
pointing and selecting device and can
zoom in the image for greater detail
(400x) and zoom it back out as required using one of the mouse buttons.
When the cytologist detects an abnormal cell, the arrow cursor is placed
in the subject tile and the other mouse
button is pressed. This places a red
border around the subject tile, facilitating later review of the case on the
video screen. In addition, depressing
this mouse button will place a dot of
ink on the glass microscope slide at
the location of the selected cell. Any
number of tiles on each slide can be
tagged.
After reviewing all 64 tiles, the cytologist will classify the case. Then, the
Review function retrieves the next 64cell image grid and loads it onto the
high-resolution monitor. The cytologist
can then classify the next case as described above.
When review of all 100 slides is completed, the slide holder cassette is
placed back into the microscope. The
data cartridge is removed from the Review Station and is inserted into the
data storage device on the Scanning
Station. The CPU reads the review log
file and determines whether any slides
have been flagged by the cytologist
for dotting during the review process.
If there are any, the robotic arm retrieves them from the appropriate slide
holder cassette position. The bar code
is read to verify that it is the correct
slide. Then the automated stage
moves the slide to the positions recorded by the cytologist during the re-
Laboratory Medicine Vol. 22, No. 4 April 1991 279
Conclusion
By optimizing the combination of machine vision and human intelligence,
PAPNET can be currently used on an
investigational basis in one of two quality assurance modes: rescreening and
prescreening. In the same amount of
time that it now takes to perform the
280 Laboratory Medicine Vol. 22, No. 4 April1991
widely practiced 10% random rescreen of negative smears, a cytologist
using PAPNET can perform a 100% rescreen or prescreen. Using PAPNET as a
rescreener, a false-negative result
caused by a laboratory screening error
could only occur in the unlikely event
that a positive case is missed by both
the manual and the PAPNET-assisted
examination. Prescreening with PAPNET would offer the additional benefit
of a quicker turnaround time on positive cases, since abnormal cases
flagged by the PAPNET system would
receive the priority attention of the
pathologist. Figures 4 and 5 are hypothetical cases that illustrate how PAPNET could be implemented. (Data are
based on initial clinical trials.) A limited
number of PAPNET systems are available for investigational use pending
FDA clearance for clinical use—Robert
P. De Cresce, MD, MBA, and Mark 5.
Lifshitz, MCU
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Quality Control
Quality Control software runs diagnostic routines to continually assess the
working status of the system. To ensure the quality of the system/user interface, the grids of 64 tiles can be reviewed no more rapidly than at a preset rate. In addition, the cytologist will
be required to use the mouse to drag
the cursor through the center of each
review tile. This actually audits the fact
that the cytologist visually attends to
each suspicious cell.
the PAPNET™ cytological screening system semiautomates the Pap smear
screening process in a commercially viable way. One important advantage of
the PAPNET system over other attempts
at automated cytology is its ability to
process conventionally prepared and
stained cervical smears. Thus, the currently used methods of sample collection and processing can be maintained
without introducing new sample collection and preparation techniques that
would deviate from standard practice,
be difficult to implement on a large
scale, and cause unnecessary loss of diagnostic cells and conventional diagnostic cues.
view process and an automatic ink dotter puts a dot on the glass.