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Definiens Tissue Studio

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DATA SHEET<br />

Understanding Images<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> TM<br />

<strong>Definiens</strong> Oncology Suite<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> TM is the most advanced digital pathology image<br />

analysis solution for biomarker translational research.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> helps you to solve<br />

biological questions<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> is built on <strong>Definiens</strong><br />

Cognition Network Technology® and is the most advanced<br />

digital pathology image analysis application<br />

for translational biomarker research. It accurately<br />

quantifies biomarkers, revealing the precise attributes<br />

of sub-anatomical objects, cells and sub-cellular<br />

objects, helping to solve your most challenging<br />

biological questions.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> is easy to use<br />

Every aspect of <strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> has been<br />

designed to support pathologists and research<br />

scientists who seek further validation and understanding<br />

of tissue-based biomarkers. It takes just<br />

three simple steps to use.<br />

1. Train the application to identify regions of interest<br />

The application can be trained to identify regions<br />

of interest automatically. Simply import sample<br />

slides and highlight the regions of interest with the<br />

”paintbrush“ tool, comparing up to four slides at once.<br />

Then, simply click the ”Learn“ button.<br />

The application uses your images to create a robust<br />

algorithm for identifying the precise regions of interest<br />

(ROI) which you seek. You can manually review the<br />

regions of interest or they can form the basis of a fully<br />

automated batch processing routine.<br />

Figure 1 <strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> supports the<br />

simultaneous utilization of up to four images which<br />

best represent variability in a given image set for<br />

creation of a robust image analysis solution.<br />

<strong>Definiens</strong><br />

<strong>Tissue</strong> <strong>Studio</strong><br />

Accurately measures<br />

nuclear, membrane and<br />

cytoplasmic biomarkers<br />

Provides multiparametric<br />

cell-by-cell quantitation<br />

Enables simple, robust<br />

detection of regions of<br />

interest<br />

Supports all standard IHC<br />

tissue stains (blue, brown<br />

and red), H&E and IF<br />

Supports all tissue formats<br />

including slides and TMAs<br />

Scales to any size for batch<br />

processing<br />

Works out-of-the-box<br />

Uses a simple interface<br />

that requires no programming<br />

skills


2<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong><br />

Figure 2 <strong>Definiens</strong> Composer Technology TM<br />

in action: In order to classify the object as a tumor,<br />

the user simply “paints” just a few representative ROIs with the paintbrush tool (green). This<br />

process is then repeated across the other images, and for other ROIs (tissue, lymph node, etc.).<br />

Figure 3 <strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> TM control panel: The colored icons at the top are used to select<br />

diferent paintbrush colors for sampling ROIs. After using the paintbrush tool, the user simply<br />

clicks the “Learn” button to teach the system to properly identify ROIs. This entire process is<br />

simple, and takes only minutes.<br />

Figure 4 Close-up view of pancreas tissue after training the system how to recognize ROIs<br />

using <strong>Definiens</strong> Composer Technology TM . Islets (both tumor and normal) are depicted in green,<br />

tissue in blue, lymph nodes in dark blue and white space in white.


2. Create unique segmentation and classifcation for sub-cellular biomarker detection<br />

Using the intuitive interface and pre-defned tools, you can create multiparametric segmentation and<br />

classifcation with ease.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> conducts segmentation and classifcation on a cell-by-cell basis, giving you<br />

unparalleled confdence and understanding of biomarkers that are related to disease progression,<br />

toxicity, or therapeutic response.<br />

Use the new, simplifed graphic user interface to train the application how to recognize the nuclear,<br />

cytoplasmic, and membrane attributes of cells. Even with challenging images, the cell simulation<br />

function will identify nuclear objects and then“grow”the cell out to establish its proper border.<br />

Choose from a complete set of default multiparametric and morphological features you want to<br />

measure – number of positive nuclei, number of negative nuclei, mean cell size, marker area,<br />

staining intensity, and many more. Custom parameters are also available for export.<br />

The solutions you develop with <strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> will enable you to data mine your tissue<br />

images and uncover underlying correlations related to clinical endpoints of interest.<br />

Figure 5 In this example, a second <strong>Definiens</strong> Composer Technology step was used to further<br />

classify islets into tumor (red) and normal (orange). ROIs (gray boxes) are then selected within<br />

the tumor regions for subsequent cell-by-cell biomarker multiparametric quantifcation.<br />

3. Run the dataset<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> works with all standard image formats – Hamamatsu, Zeiss, Aperio, Applied<br />

Imaging, <strong>Tissue</strong>Gnostics, Bacus – as well as generic formats like .tif and .jpeg. All you need to do<br />

is import the slides and click ”run“.<br />

It is that easy.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> can batch process locally or send larger jobs to servers. There is no limit to<br />

the number of CPUs that can be added, ensuring that you can handle any project of any size.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> 3


4<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong><br />

Figure 6 Example of nucleus detection in pancreas tumor.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> is uniquely powerful<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> is built on the powerful <strong>Definiens</strong> Cognition Network Technology®<br />

which does not rely solely on traditional pixel-based, pattern recognition. Instead, it builds<br />

an understanding of images iteratively, identifying objects through their characteristics, their<br />

relationships to other objects and the context in which they occur.<br />

This fundamental diference enables <strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> to address highly heterogeneous<br />

tissues, identify individual cells and the sub-cellular objects within them, and then<br />

conduct extremely accurate cell-by-cell measurements.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> is part of <strong>Definiens</strong> Oncology Suite<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> is part <strong>Definiens</strong> Oncology Suite which encompasses applications spanning<br />

cellular assays, histopathology, and non-invasive medical imaging.<br />

Defniens <strong>Tissue</strong> <strong>Studio</strong> incorporates <strong>Definiens</strong> Composer Technology<br />

<strong>Definiens</strong> Composer Technology is a new easy to use machine learning approach that enables<br />

the user to train the application to detect regions of interest using up to four images simultaneously.<br />

The resulting solution can be applied to a complete set of images with a single click for unlimited<br />

parallel batch processing.<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> improves decision making<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> surpasses every other image analysis application for translational research of<br />

tissue-based biomarkers, delivering deeper insights, faster results and better decisions.


<strong>Definiens</strong><br />

<strong>Tissue</strong> <strong>Studio</strong><br />

delivers<br />

DEEPER INSIGHTS by<br />

Quantifing nuclear,<br />

membrane and cytoplasmic<br />

biomarkers on a cell-by-cell<br />

basis<br />

Supporting all standard<br />

IHC tissue stains (blue, brown<br />

and red), H&E and IF<br />

Analyzing all slides and<br />

TMA images from all major<br />

image acquisition devices<br />

FASTER RESULTS by<br />

Identifing regions of<br />

interest automatically<br />

Operating through a simple,<br />

intuitive user interface<br />

Ofering unlimited<br />

throughput with parallel<br />

batch processing<br />

BETTER DECISIONS by<br />

Delivering extremely accurate<br />

and reproducible results<br />

Enabling multiparametric<br />

investigations to identify<br />

underlying correlations<br />

Supporting translational<br />

research through rapid<br />

iterative investigation of<br />

biomarkers<br />

Multiparametric and morphological<br />

features measured<br />

IHC<br />

No. of positive nuclei<br />

No. of negative nuclei<br />

Positive index<br />

Cell and membrane features:<br />

– Mean cell size (μm²)<br />

– Mean IHC marker intensity (cell)<br />

– Mean IHC marker intensity (cytoplasm)<br />

– Mean IHC marker intensity (membrane)<br />

– Mean ratio IHC marker intensity membrane<br />

to cytoplasm<br />

– Marker area (μm²)<br />

No. and % of:<br />

– Nuclei of low intensity<br />

– Nuclei of medium intensity<br />

– Nuclei of high intensity<br />

No. and % of:<br />

– Nuclei with small area<br />

– Nuclei with medium area<br />

– Nuclei with large area<br />

No. and % of:<br />

– Cells of negative intensity (0)<br />

– Cells of low intensity (1+)<br />

– Cells of medium intensity (2+)<br />

– Cells of high intensity (3+)<br />

No. and % of:<br />

– Cells with small area<br />

– Cells with medium area<br />

– Cells with large area<br />

H & E and IF<br />

ROI area/marker area<br />

Custom data export is also supported<br />

<strong>Definiens</strong> <strong>Tissue</strong> <strong>Studio</strong> 5


System requirements<br />

Defniens <strong>Tissue</strong> <strong>Studio</strong> is available with either two or four analysis engines to meet your<br />

processing requirements.<br />

TWO ANALYSIS ENGINES<br />

Minimum:<br />

• Windows XP Professional 64Bit SP2,<br />

Vista-Business/Ultimate 64 Bit SP2<br />

• Intel / AMD Quad Core 64 Bit 1.83Ghz +<br />

• 8 Gb Memory<br />

• 30Gb Disk Space<br />

• 20“ 1600 x 1200 Display<br />

• 100 MB Ethernet network connection<br />

FOUR ANALYSIS ENGINES<br />

Minimum:<br />

• Windows XP Professional 64Bit SP2,<br />

Vista-Business/Ultimate 64 Bit SP2<br />

• Intel / AMD Dual CPU (Socket),<br />

Quad Core 64 Bit 1.83Ghz +<br />

• 12 Gb Memory<br />

• 30Gb Disk Space<br />

• 20“ 1600 x 1200 Display<br />

• 100 MB Ethernet network connection<br />

Recommended:<br />

• Windows XP Professional -64Bit SP2,<br />

Vista-Business/Ultimate 64 Bit SP2<br />

• Intel Xeon/ AMD Quad Core 64 Bit 2.00Ghz+<br />

• 12 Gb Memory (1.33GHz Bus)<br />

• 30Gb Disk Space<br />

• 24“ 1920 x 1200 Display +<br />

• 1Gb Ethernet Connection<br />

Recommended:<br />

• Windows XP Professional 64Bit SP2,<br />

Vista-Business/Ultimate 64 Bit SP2<br />

• Intel Xeon/ AMD Dual CPU (Socket),<br />

Quad Core 64 Bit 2.00Ghz+<br />

• 16 Gb Memory (1.33GHz Bus)<br />

• 30Gb Disk Space<br />

• 24“ 1920 x 1200 Display +<br />

• 1Gb Ethernet Connection<br />

<strong>Definiens</strong> is the number one Enterprise Image Intelligence® company for analyzing and interpreting images<br />

on every scale, from microscopic cell structures to satellite images.<br />

The patented <strong>Definiens</strong> Cognition Network Technology®, developed by Nobel Laureate Prof. Gerd Binnig<br />

and his team, emulates human cognitive processes of perception to extract intelligence from images.<br />

If you are interested in learning more about how <strong>Definiens</strong> could address the challenges you face, please visit<br />

our website.<br />

www.definiens.com<br />

Corporate Headquarters Americas Headquarters<br />

<strong>Definiens</strong> AG <strong>Definiens</strong> Inc.<br />

Trappentreustrasse 1 1719 State Route 10, Suite 118<br />

80339 Munich Parsippany, New Jersey 07054<br />

Germany USA<br />

Tel. +49 (0)89 231180-0 Tel. +1-973-457-7150 DSL-0004-02-31080<br />

Copyright © 2009 <strong>Definiens</strong> AG. <strong>Definiens</strong>, <strong>Definiens</strong> Cellenger, <strong>Definiens</strong> Cognition Network Technology, <strong>Definiens</strong> eCognition, <strong>Definiens</strong> Enterprise Image Intelligence<br />

and Understanding Images are trademarks or registered trademarks of <strong>Definiens</strong> in the United States, the European Community, or certain other jurisdictions.<br />

All registered trademarks, pending trademarks, or service marks are property of their respective owners. The information in this document is subject to change<br />

without notice and should not be construed as a commitment by <strong>Definiens</strong> AG. <strong>Definiens</strong> AG assumes no responsibility for any errors that may appear in this document.

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