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European Biopharmaceutical Review
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Digital pathology is revolutionising the field of bioimaging by reducing
operational costs, improving quality and enabling researchers to
fast-track the discovery of novel tissue-based biomarkers for companion
diagnostics through automated tissue imaging.
The evaluation of tissue on a glass slide by experienced diagnostic
pathologists using a microscope is central to many aspects of drug
discovery, clinical trials and the development of diagnostic tests. This
is particularly important in oncology and the evaluation of solid
tumours. In the earliest stages of target identification, understanding
cancer pathobiology, studying signalling pathways and evaluating new
sequences and proteins as potential therapeutic targets, human tissue
samples are widely used. Fresh, frozen or fixed archived tissue samples
are analysed to examine the differential expression of gene products in
normal tissues and cancer subtypes, as well as the relationship between
tissue expression and clinical outcome. With increased momentum towards
the development of companion diagnostics, tumour tissue has become a
focus for biomarker discovery, again underpinning the importance of
pathology in both biomarker discovery and clinical adoption.
Digital Pathology
Digital pathology describes the creation, viewing and analysis of a high
resolution image of the glass slide, allowing the pathologist to review
the ‘digital slide’ on a computer monitor rather than using a
microscope. It follows closely on the heels of the digital radiology
revolution, which has completely changed the face of medical imaging.
However, one of the biggest benefits of digital pathology is that the
pathologist and the physical glass slide no longer need to be in the
same room. Digital slides can be viewed remotely via the web, in their
entirety at any magnification, allowing pathologists to review tissue
samples anywhere in the world, at any time.
Digital slides are large. With a resolution of 0.24μm per pixel and 25
by 20mm in size, average scans can easily be 100,000 by 80,000 pixels in
size, resulting in compressed files in the order of 1Gb each. This
requires significant storage capacity to digitally archive slides.
However, with appropriate backup, the digital slide archive represents a
permanent record of the trial or experiment, where slides can be
immediately retrieved and viewed online at any point during or after the
trial. There is no risk of fading or slide breakage, as is common with
glass slides.
Remote review of digital slides does not require the entire image to be
downloaded to the remote site. Instead, the image is served ‘on demand’,
allowing the user to rapidly navigate the image freely with only the
relevant regions of the image being downloaded to the client-side
digital slide viewer, replicating how pathologists use standard
microscopy.
Software is essential to bring all of the benefits of digital pathology
to the drug discovery and diagnostics industry. It is the software and
the architecture on which it sits that drives the improved efficiency,
enhanced workflows and reduced operational costs that can be experienced
when using digital pathology. In addition, since different scanner
manufacturers generate own proprietary image format, it is important
that digital pathology software can read and display various formats –
particularly important in an industry where collaboration between
organisations involves scanned images from many scanner brands and in
many formats.
Improving Efficiency, Workflow and Interoperability
Digital pathology, as the name suggests, should also involve the
management, distribution and analysis of the data associated with or
derived from the images. In patient evaluation, in whatever context, the
images are just part of a more complex profile and should not be
studied in isolation. It is therefore essential that digital pathology
software facilitates the integration and visualisation of the
multivariate data associated with tissue diagnostics and biomarker
discovery and the ability to report on, or score the slide,
electronically. This can be achieved with a single user interface that
displays all of the relevant digital slide and patient or sample data,
and a reporting interface which allows pathological review and biomarker
assessment. This provides a novel means of managing pathology studies
entirely electronically, distributing digital slides to pathologists for
remote review and collecting the results of their review centrally.
This, in turn, can provide increased efficiency in managing
pathology-centric studies and provides access to a greater pool of
pathologists, potentially speeding up review.
Security and regulatory compliance is essential when digital pathology
is used to handle sensitive and proprietary images and patient related
data. Digital pathology software, including cloud-based software as a
service and storage solutions, must ensure restricted, authorised access
to data and demonstrate GLP, GCP and 21 CFR part 11 compliancy.
LIMS Integration
As digital pathology increasingly encompasses wider information
management and facilitates workflow requirements, there is also a need
to ensure interoperability with other laboratory systems that already
store and process relevant information. This is particularly important
in organisations that have existing laboratory information management
systems (LIMS) that manage sample processing and associated information.
Extending existing workflows to include the management of digital
slides should be seamless, allowing effective data exchange between
information platforms, and providing a means for digital pathology to be
layered on top of existing information systems. This provides
organisations with the enhanced advantages that digital pathology brings
to a research and development programme without the need to strip out
and completely replace existing systems.
Biobanking
Digital pathology is also playing a significant role as an integrated
capability in tissue biobanks. Biobanks are organised collections of
high quality biological samples linked with well-defined data sets, and
are a critical platform for high impact diagnostics and therapeutics
research, underpinning the development of molecular biomarkers,
companion diagnostics and personalised medicine (1). Digital pathology
provides the infrastructure to digitally store tissue histology and
biomarker images, both as part of targeted tissue collections or
clinical trials, and allowing these resources to be used for subsequent
sample selection and retrieval for research. Together with integrated
tissue microarray imaging and image analysis, this provides biobanks
with added functionality to underpin their importance to
biopharmaceutical research.
Multinational Integration
Digital pathology and its ability to virtually manage tissue samples for
pathological review is a key benefit for large multi-national,
multi-site clinical trials or biomarker studies. It reduces the cost
associated with physical distribution of slides and fast-tracks data
collection by allowing immediate real-time review and reporting of
slides by pathologists offering the most competitive rates and having
the right expertise. Digital pathology can also overcome the regulatory
requirements around moving tissue samples outside of the country.
Several CRO organisations are now facilitating access to drug and
biomarker trials in China and India by using digital pathology to access
the images, avoiding the need to relocate glass slides. Global clinical
trials have the potential to shorten drug development times, lower
operating costs and expand participant numbers. Digital pathology will
not only be an enabling technology in these situations, but will also
underpin the cost-benefits in geographically dispersed and tightly
regulated trials.
Biomarker Discovery and Companion Diagnostics
Digital pathology is emerging as an essential platform on which to
investigate, identify, validate and translate new tissue biomarkers. The
convenience of using digital images for biomarker scoring and
centralised collection of data better ensures data integrity and
provides a reliable audit trail for biomarker trials.
Tissue Microarray Analysis
Tissue microarrays (TMAs) represent a highly parallelised way of
assessing cellular biomarker expression in tissues and are widely used
in tissue biomarker discovery and validation. By having hundreds of
patient tissue samples (cores) on a single slide, with different
clinical outcomes or treatment responses, individual cores can be
evaluated to determine the relationship between the presence of a
particular protein or sequence and clinical outcome. The increasing
trend to develop companion biomarkers for new drugs and therapeutic
regimes is already seeing the expanded use of TMAs in biomarker research
and validation of companion diagnostics.
Digital pathology can add enormous value to tissue microarray (TMA)
experiments by overcoming many of the manual, labour-intensive aspects
of traditional TMA evaluation. By using a dedicated software interface
to manage entire TMA experiments, configure TMA maps, define scoring
criteria, view tissue cores, collate scores and provide experimental
biomarker reports, digital pathology can significantly reduce the manual
task involved in traditional TMA evaluation. This again can be carried
out entirely on-line allowing experienced pathologists to be scoring a
TMA from anywhere in world. Virtual TMA analysis using digital pathology
can speed up conventional TMA-based biomarker analysis by up to five
times, freeing up pathologists time, reducing costs and fast-tracking
biomarker development (see Figure 1).
Image Analysis and Companion Algorithms
Visual interpretation of biomarker expression is inherently subjective
and prone to error, even when carried out by experienced pathologists.
Computerised image analysis provides the ability to use the information
inherent in a digital image to extract quantitative data on tissue
pattern and biomarker expression. Used appropriately, image analysis can
provide important objectivity and repeatability in biomarker studies,
allowing the identification of subtle changes in biomarker expression
that might be missed by the naked eye. While the value of quantitative
pathology has been advocated for many years, the advent of whole slide
imaging has resulted in a resurgence of new methods and new applications
for image analysis in tissue pathology, the development of biomarkers
and stratified medicine.
A variety of image analysis toolboxes and target specific algorithms are
commercially available that allow the quantitative measurement of
morphological features, immunohistochemical (IHC) of specific proteins
and in situ hybridisation (ISH)
detection of nucleic acid sequences in cells. Few image analysis
algorithms work ‘off the shelf’, and there is invariably the need to
configure algorithms for the specific tissue type and biomarker that
requires measurement. However, in experienced hands, algorithms can be
developed which can reliably segment cellular compartments and extract
quantitative data on the level of biomarker expression (see Figure 2,
page 34). Due to its quantitative basis and improved objectivity and
reliability, image analysis is now being recognised as an essential
prerequisite to biomarker discovery and validation.
Image analysis should not be considered as a black box to biomarker
assessment that can entirely replace experienced pathologists, except in
well-validated and tested situations. Tissue imagery is extremely
complex and image analysis should only be validated and used by those
familiar with the underlying image content and tissue morphology.
However, image analysis can provide a means to automate biomarker
evaluation in tissues and provide numerical data which can be more
easily verified than subjective visual interpretation. This is of
particular importance in TMA biomarker studies, where hundreds of
samples have to be evaluated within a single digital image. Building
imaging software to automate the identification of tissue cores and
algorithms to score biomarkers can significantly speed up multiplex
biomarker assessment across numerous samples (2). High performance
computing can further speed up tissue analysis by parallelising image
processing and measurement algorithms (2). For diagnostics companies
wishing to validate candidate tissue biomarkers for patient
stratification, image analysis is going to become an essential tool.
As the drive for personalised medicine continues, drug development and
companion diagnostics will increasingly be carried out in tandem. Once a
companion tissue diagnostic has been identified, validated and approved
for use, image analysis will also play an important role in the test
laboratory as an objective, reliable assay for the tissue biomarker.
This is already happening. While the FDA has not yet approved digital
pathology for primary diagnosis, they have approved image analysis
algorithms for the clinical evaluation of PR, ER and Her2 IHC in breast
cancer. Her2 is a good example. Recognising that up to 20 per cent of
Her2 evaluations by pathologists could be inaccurate, the American
Society of Clinical Oncology and College of American Pathologists have
recommended the use of image analysis for Her2 assessment, provided it
is validated internally within a lab (3). The utility of Her2 image
analysis has been extensively validated by some laboratories (4). This
and other emerging examples represent a step-change in how new companion
diagnostics are going to be derived in the diagnostics laboratory, and
may become the standard, forcing the concurrent development of
algorithms as part of the biomarker discovery process.
Interestingly, in addition to overall biomarker expression in tissues,
tumour heterogeneity is emerging as an important clinical indicator of
response to treatment. As an example, Her2 heterogeneity in breast
cancer may account for the 30 per cent of patients that fail to respond
to, or acquire resistance to Herceptin therapy. Image analysis provides
the perfect tool to measure levels of Her2 expression in breast cancer
and could act as a more efficient means of stratifying and selecting
patients for herceptin therapy (5).
In addition to biomarker measurement, automated imaging and tissue
analysis have many new emerging applications that will significantly
reduce the time and cost involved in drug and biomarker development.
Pathologists are heavily involved in reviewing tissue samples for
subsequent mutational analysis, sequence evaluation and genomic
profiling, both for discovery and in established molecular diagnostics.
This and other manual tasks represent a significant bottleneck to
discovery and the translation of new molecular tests based on tissue
samples. Automation of these manual tasks using digital pathology will
radically alter how tissue and molecular diagnostic tests will be
developed and delivered in the future.
Conclusion
Digital pathology is now an essential technology for drug discovery and
the development of new tissue diagnostic tests. The cost of hardware is
falling and software is now meeting the regulatory requirements, quality
standards and security levels necessary for use in private and public
sector research. At its core is the ability to share images, data and
reports, freeing up access to skilled pathologists who can be anywhere
in the world. However, the deeper applications of digital pathology will
actually transform discovery and the delivery of tissue-centric tests
in the future.
References
- Hewitt RE, Biobanking: the foundation of personalised medicine, Curr Opin Oncol 23: pp112-119, 2011
- 2. Wang Y, Savage K, Grills C, McCavigan A, James JA and Hamilton
PW, A TMA De-Arraying Method for High Throughput Biomarker Discovery in
Tissue Research, PLoS ONE 6(10): e26007, 2011 doi:10.1371/journal.
pone.0026007
- Wolff AC, Hammond ME, Schwartz JN et al, American Society of
Clinical Oncology/College of American Pathologists guideline
recommendations for human epidermal growth factor receptor 2 testing in
breast cancer, Arch Pathol Lab Med 131: pp18-43, 2007
- Gustavson MD, Bourke-Martin B, Reilly D et al, Standardization of
HER2 immunohistochemistry in breast cancer by automated quantitative
analysis, Arch Pathol Lab Me 133: pp1,413-1,419, 2009
- Potts SJ, Krueger JS, Landid ND, Eberhard DA, Young GD, Schmechel
SC and Lange H, Evaluatinfg tumour heterogeneity in
immunohistochemistry-stained breast cancer tissue, Laboratory
Investigation 92: pp1,342-1,357, 2012
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