Positive Pixel Count Algorithm User's Guide
Contents
1. Nsp Nwp Np Nsp E Iwavg Average Intensity excluding Strong Positive pixels IwptIp Nwp Np E Nn Number of Negative pixels Blue in mark up image E In Sum of Intensity values for all Negative pixels NTotal Number of Total pixels PositivetNegative Nwp Np Nsp Nn E Positivity Total number of positive pixels divided by total number of pixels NTotal Nn NTotal ATotal Total area in square millimeters of all pixels counted in the NTotal result If the results of the analysis are not what you expect or are otherwise unsatisfactory see the appendix Troubleshooting in the Aperio Image Analysis User s Guide for some tips on identifying problems Positive Pixel Count Algorithm User s Guide ri Chapter 2 Quick Reference Positive Pixel Count Algorithm User s Guide 3 Positive Pixel Count Analysis Although you can use several different tools to perform an algorithm analysis this section shows a simple analysis using ImageScope to analyze digital slide that resides in the Spectrum digital slide information system Note that the Color Deconvolution algorithm is our professional version of the Positive Pixel Count that allows automatic and precise training of stain colors eliminating trial and error and accurate stain separation resolving the multi stain colocalization problem Color Concepts The Positive Pixel Count algorithm detects pixels that match the input parameters set for the2. 30 0 None 0 1 05 0 04 220 175 100 0 1 6 Click Inputs and adjust the algorithm parameters in the Algorithms window as discussed earlier in this document by clicking on a number and typing a new value or using the slider if one is provided for that parameter Positive Pixel Count Algorithm User s Guide Papero Chapter 3 Positive Pixel Count Analysis 7 Click Outputs and select which results will display in Spectrum by clearing the check boxes next to the results you don t want to display m aim ee a as re L i or a ey s m soos Positive Pixel Count v9 Parameters C Nwp Number of Weak Positive C Np Number of Positive C Nsp Number of Strong Positive lwp Total Intensity of Weak Positive Ip Total Intensity of Positive lep Total Intensity of Strong Positive lava lwp lp lsp e Niwp hp hsp Mer Nepe Nwp hp h sp lwayg lwp lp Nio h py Nr Number of Negative C In Total Intensity of Negative C NTotal Total Number Positive Negative Positivity NPositivesNT otal LOT E T ian N T N 8 Ifyou want to see a visual representation of the analysis as well as a quantitative one select Generate Markup Image on the Algorithms ve Pi window 9 To analyze just the annotated areas select Selected Annotation Layer under the Region of Analysis section of the Algorithms window 10 Click Run Because we requested a mark up image the I
3. Pixel Count Algorithm User s Guide Chapter 3 Positive Pixel Count Analysis D010 Darkest The Positive Pixel Count algorithm allows you to specify three ranges of intensity Iwp Weak positive intensity A high Iwp value is the upper limit of intensity for weak positive pixels Pixels which do not meet the hue saturation limits but have an intensity less than Iwp are counted as negative pixels A low Iwp value is the lower limit of intensity for weak positive pixels and the upper limit of intensity for positive pixels Iwp Low Ip High Ip Positive intensity Ip is the lower limit of intensity for positive pixels It is the upper limit of intensity for strong positive pixels Ip Low Isp High Isp Strong positive intensity This is the lower limit of intensity for strong positive pixels Isp High Ip Low Ip High Iwp Low Brightest Isp Ip Iwp 255 Running an Analysis 1 View Images Digital Slides Angelique Unetelle 12 3 1981 S08 03003 A PR Breast PR C images i 4 h EEA p E FP mee et ww lt V oat y a Qh N a en anaiita For information opening and analyzing local digital slides that reside on your workstation or local area network see the ImageScope User s Guide For information on accessing digital slides in other ways in Spectrum see the Spectrum Spectrum Plus Operator s Guide Open a digital slide in ImageScope If you are using the Spectrum digital slide i
4. algorithm An important group of these parameters relate to color This section discusses some of the concepts behind these parameters You are probably familiar with the common artist color wheel The Rare Event Detection algorithm uses a form of it called the HSI Hue Saturation Intensity wheel that quantifies the RGB red blue green color space Red 0 Blue 0 66 Green 0 33 Positive Pixel Count User s Guide 9 D IVETIO Chapter 3 Positive Pixel Count Analysis In the example above imagine every color residing on this wheel with the color red being assigned the value zero The actual color is called the hue As you move around the rim of the circle you move from one hue to another Each hue has a numeric representation on this wheel Green is 0 33 as it is a third of the way around the circle from red which is 0 00 and Blue is 0 66 two thirds of the way around the circle Each hue on the circle has a number assigned to it Brown which is almost halfway between Red and Green has a value of 0 1 The Hue Value parameter used by this algorithm is the number associated with the hue you want to use based on its position on the wheel Saturation represents the purity of the color with the rim of the wheel representing complete saturation For example fully saturated Red is the color on the rim of the wheel a less saturated Red for example Pink resides on the red vector but closer to the center of t
5. Positive Pixel Count Algorithm User s Guide D110 Copyright 2004 2006 2008 Aperio Technologies Inc Part Number Revision MAN 0024 Revision C Date September 4 2009 This document applies to software versions Release 10 1 and later All rights reserved This document may not be copied in whole or in part or reproduced in any other media without the express written permission of Aperio Technologies Inc Please note that under copyright law copying includes translation into another language User Resources For the latest information on Aperio Technologies products and services please visit the Aperio Technologies website at http www aperio com Disclaimers Use normal care in maintaining and using the Spectrum servers Interrupting network connections or turning off the Spectrum and DSR servers while they are processing data such as when they are analyzing digital slides or generating an audit report can result in data loss This manual is not a substitute for the detailed operator training provided by Aperio Technologies Inc or for other advanced instruction Aperio Technologies Field Representatives should be contacted immediately for assistance in the event of any instrument malfunction Installation of hardware should only be performed by a certified Aperio Technologies Service Engineer ImageServer is intended for use with the SVS file format the native format for digital slides created by scanning glass sl
6. e from Aperio for a license fee Algorithms have also been developed by third parties and tools are available from Aperio for creating your own algorithms contact Aperio for details These algorithms all have control parameters for example intensity and hue settings that allow the algorithm to be tailored to your specific needs The Positive Pixel Count Algorithm The Positive Pixel Count algorithm can be used to quantify the amount of a specific stain present in a scanned slide image You will specify a color range of hues and saturation and three intensity ranges weak positive and strong For pixels which satisfy the color specification the algorithm counts the number and intensity sum in each intensity range along with three additional quantities Positive Pixel Count User s Guide Papero Chapter 1 Introduction average intensity ratio of strong total number and average intensity of weak positive pixels The algorithm has a set of default input parameters when first selected these inputs have been pre configured for Brown color quantification in the three intensity ranges 220 175 175 100 and 100 0 Pixels which are stained but do not fall into the positive color specification are considered negative stained pixels these pixels are counted as well so that the fraction of positive to total stained pixels is determined The algorithm is applied to an image by using ImageScope Spectrum or TMALab Thes
7. e programs allow you to select an image Region of Analysis set of spots in TMALab specify the input parameters run the algorithm and view save the algorithm results When using the ImageScope program a pseudo color markup image is also shown as an algorithm result The markup image allows the user to confirm that specified inputs are measuring the desired color and intensity ranges Once a set of algorithm inputs has been confirmed the settings can be saved in a macro file for subsequent repeated use To use the Positive Pixel Count algorithm you need to install ImageScope free download the Positive Pixel Count algorithm will be installed as part of the ImageScope installation Running the algorithm in TMALab is not covered in this document Prerequisites The Positive Pixel Count algorithm requires that you be using Aperio Release 10 or later Because Aperio digital slides are by design high resolution and information rich for best results you should use a high quality monitor to view them Make sure the monitor is at the proper viewing height and in a room with appropriate lighting We recommend any high quality LCD monitor meeting the following requirements Display Type CRT minimum LCD flat panel recommended Screen Resolution 1024 h x 768 v pixels minimum 1920 x 1050 or larger recommended Screen Size 15 minimum 19 or larger recommended Color Depth 24 bit Brightness 300 cd m minimum 500 or higher recomme
8. ed on the color you want to detect see Color Concepts on page 9 Hue Width This value selects the range of hues centered on the Hue Value that will satisfy the hue detection process By increasing this number you specify that a larger range of hues will be accepted for D IVETIO Chapter 2 Quick Reference specifying the Positive color band By decreasing this number you tighten the range of hues that will be acceptable The number can range between zero and 1 where zero is a narrow hue width and 1 selects the entire range of hues A value between 0 33 and 0 5 is usually reasonable E Color Saturation Threshold This is the required saturation of the Positive color RGB values are represented as gray color The value can be between 0 0 and 1 0 with 1 0 corresponding to no gray component fully saturated Pixels with saturation less than this value are not reported E Iwp High Upper limit of intensity for weak positive pixels Iwp is also used as an intensity threshold for negative stained pixels pixels which do not meet the hue saturation limits but have an intensity less than Iwp are counted as negative pixels E Iwp Low Ip High Lower limit of intensity for weak positive pixels upper limit of intensity for positive pixels E Ip Low Isp High Lower limit of intensity for positive pixels upper limit of intensity for strong positive pixels Isp Low Lower limit of intensity fo
9. gorithm Algorithm Input Parameters The following inputs are accepted by the Positive Pixel Count algorithm Positive Pixel Count User s Guide View Width Width of processing box View Height Height of processing box Overlap Size Size of the overlap region for each view The image is processed in blocks views and overlap is provided to ensure that regions are processed only once Image Zoom 1 0 recommended for processing of all pixels Can be reduced to 0 5 for faster processing however the results may not be as accurate Markup Compression Type You can select among Same as processed image JPEG or JPEG2000 for the markup image Compression Quality For the compressed markup image you can select a compression quality of 0 to 95 Higher quality takes longer and yields larger files Classifier Definition List If you are using this algorithm in conjunction with the Genie image analysis program you can select Genie classifier definition lists here See the Genie user guide for details Class List If you are using this algorithm in conjunction with the Genie image analysis program you can select Genie class lists here See the Genie user guide for details Hue Value This is hue position on the color circle for Positive color ranging from 0 to 1 It can take on values between 0 0 and 1 0 Red 0 0 Green 0 33 Blue 0 66 Brown 0 1 For more information on determining this value bas
10. he wheel Hue Width is the wedge on the wheel that represents all hues that will satisty pixel detection based on the Hue Value The smaller the Hue Width the more restrictive is the definition of the hues that are acceptable For example if you want pixels to be detected only if they are precisely Brown then you might specify a Hue Width of zero If slightly reddish brown to slightly greenish brown are all acceptable to identify a pixel then you might specify a Hue Width of 5 You might think of this as a hue threshold value Intensity Another value that can be used to detect a pixel is the Intensity Not represented on the wheel above intensity is the measure of brightness of the pixel and is the average of R G B values of the pixel Intensity ranges from zero black to 255 bright white so that a large intensity value means that the pixel is brighter Intensity is the opposite of density Intensity is proportional to the amount of light transmitted through the slide while density is proportional to the amount o f light that is blocked by the stained tissue The input parameters allow defining the positive stain color and the weak positive positive and strong positive intensity thresholds for the positive stain using the HSI color model R Red i intensity Hue Value H Hue R G iwp High S Saturation Hue Width xX Saturation Threshold G Green iwp Low Ip High B Blue 10 Positive
11. ic use Intended Use Algorithms are intended to be used by trained pathologists who have an understanding of the conditions they are testing for in running the algorithm analysis Each algorithm has input parameters that must be adjusted by an expert user who understands the goal of running the analysis and can evaluate the algorithm performance in meeting that goal You will adjust tune the parameters until the algorithm results are sufficiently accurate for the purpose for which you intend to use the algorithm You will want to test the algorithm on a variety of images so its performance can be evaluated across the full spectrum of expected imaging conditions To be successful it is usually necessary to limit the field of application to a particular tissue type and a specific histological preparation A more narrowly defined application and consistency in slide preparation generally equates to a higher probability of success in obtaining satisfactory algorithm results If you get algorithm analysis results that are not what you expected please see the appendix Troubleshooting in the Aperio Image Analysis User s Guide for assistance Positive Pixel Count Algorithm User s Guide a Chapter 1 Introduction Positive Pixel Count Algorithm User s Guide 2 Quick Reference This chapter contains a quick reference to all positive pixel count algorithm inputs and outputs See the following chapter for details on using the al
12. ides with the ScanScope scanner Educators will use Aperio software to view and modify digital slides in Composite WebSlide CWS format Aperio products are FDA cleared for specific clinical applications and are intended for research use for other applications For clearance updates visit www aperio com Trademarks and Patents ScanScope is a registered trademark and ImageServer TMALab ImageScope and Spectrum are trademarks of Aperio Technologies Inc All other trade names and trademarks are the property of their respective holders Aperio products are protected by U S Patents 6 711 283 6 917 696 7 035 478 7 116 440 7 428 324 7 457 446 7 463 761 7 502 519 7 518 652 and licensed under one or more of the following U S Patents 6 101 265 6 272 235 6 522 774 6 775 402 6 396 941 6 674 881 6 226 392 6 404 906 6 674 884 and 6 466 690 Contact Information Headquarters Europe Office Asia Office Aperio Technologies Inc Aperio UK Ltd Aperio Technologies KK 1360 Park Center Drive The Vineyard UZ Building 5F Vista CA 92081 Axbridge 3 3 17 Surugadai United States Somerset BS26 2AN UK Kanda Chiyoda ku Tokyo Japan 101 0062 United States of America Tel 866 478 4111 toll free Fax 760 539 1116 Customer Service Tel 866 478 4111 toll free Technical Support Tel 866 478 3999 toll free Email Email support aperio com Europe Tel 44 0 1934 733679 Fax 44 0 1934 733660 Customer Service amp Technical Su
13. image see Algorithm Results on page 6 16 Positive Pixel Count Algorithm User s Guide analysis results 6 16 colors 16 Aperio release requirements 2 color concepts 9 drawing annotations 12 Genie 5 hue 10 saturation 10 value 5 10 width 10 image zoom 5 input parameters 5 intended use 3 intensity 6 ranges 6 10 Ip 6 11 Positive Pixel Count User s Guide Index Isp 6 11 Iwp 6 11 macro 13 creating 13 testing 13 mark up image 15 monitor requirements 2 positive intensity 6 Positive Pixel Count 1 prerequisites 2 results See analysis results running analysis 11 saturation 6 10 strong positive intensity 6 weak positive intensity 6 I7 perio Positive Pixel Count Algorithm User s Guide MAN 0024 Revision C
14. ixel Count Algorithm User s Guide Introduction This chapter introduces you to the Aperio Positive Pixel Count Algorithm For general information on using any algorithm please see the Aperio Image Analysis User s Guide The process of analyzing digital images begins with the ScanScope which creates digital slides by scanning glass slides Using Aperio image analysis algorithms to analyze digital slides provides several benefits E Increases productivity Image analysis automates repetitive tasks E Improves healthcare Analyzing digital slides helps you to examine slide staining to find patterns that will tell you more about the slide Using an algorithm to look for these patterns provides precise quantitative data that is accurate and repeatable E Development of new computer based methods Image analysis helps you answer questions that are beyond the capabilities of manual microscopy such as What is the significance of multiple stains at the cell level and colocalization of stains E Workflow integration The Spectrum digital pathology information management software suite integrates image analysis seamlessly into your digital pathology workflow requiring no additional work by the lab or pathologist With the click of a button the algorithm is executed while you review the digital slide The Positive Pixel Count algorithm is licensed without charge with other Aperio software Other algorithms are availabl
15. mageScope main window shows the results of the analysis Positive Pixel Count Algorithm User s Guide 15 D010 Chapter 3 Positive Pixel Count Analysis 11 To see the quantitative results go to the ImageScope View menu and select Annotations The summary results are shown on the left and measurements for individual regions are shown on the right Annotations Detailed View summary to E PPC Dr Beth Edwards output Nwp Number of J Nwp Number of Weak Positive Np Number of Positive Result 83 Weak Positive Np Number of Positive Nsp Number of Strong Positive lwp Total Intensity of Weak Positive Ip Total Intensity of Positive Isp Total Intensity of Strong Positive lavg 172 132 Iwp lp lsp Nwp Nr Nest 1 24335e 003 2 Nsp Nwp Np Nsp lwava 172 236 __ Ilwp lp Nwp Np Nn Number of Negative In Total Intensity of __ Negative NTotal Total 153820 Number Ei Positive Negative ATotal TotalArea 3 8933320210199997 Ei millimeter squared Positivity 0 282349 NPositive NT otal ee Algorithm Inputs Algorithm Inputs z Algorithm Positive Pixel Count y9 i Version gil View Width 1000 p View Height 1000 fal Overlap Size 0 p Image Zoom 1 iil Pixel Area 2 531 1 007 millimeter squared jil Hue Yalue Center 0 1 Ua iiidh ne The colors shown next to the results correspond to the colors in the mark up
16. nded Contrast Ratio 500 1 minimum 1000 1 or higher recommended For More Information For a quick reference to the positive pixel count algorithm input parameters and results see Chapter 2 Quick Reference on page 5 For examples and details on using the algorithm begin with Chapter 3 Positive Pixel Count Analysis on page 9 2 Positive Pixel Count Algorithm User s Guide Chapter 1 Introduction Ci DE rh d See the Aperio Image Analysis User s Guide for information on E Installing an algorithm E Opening a digital slide to analyze E Selecting areas of a digital slide to analyze E Running the analysis E Exporting analysis results For details on using the Spectrum digital slide information management system for example for information on running batch analyses see the Spectrum Spectrum Plus Operator s Guide For details on using ImageScope to view and analyze digital slides and using annotation tools to select areas of the digital slide to analyze see the ImageScope User s Guide FDA Cleared Image Analysis Algorithms Several Aperio algorithms have been cleared by the FDA for clinical use when used on ScanScope models that are labeled as approved medical devices and are intended for research use for other applications These algorithms have their own user guides Please see the Intended Use section of the user guides for the specific cleared applications you wish to use for details on in vitro diagnost
17. nformation system one way to do this is to go to the main Spectrum page and select List All Digital Slides to see the list of digital slides and then click on a digital slide thumbnail to open it in ImageScope Open Data Analyze Delete New Move Copy Assign To Export Data Annotations View Audits Label Thumbnail Slide Barcode ID Block Image Captured File Location ID t ID ID Date ee i Angelique Unetelle 12 3 1981 S08 03003 A ER BreastER i C images amp 080215 1 3 1225387887_1339_3003ER svs 2 Angelique Unetelle 12 3 Pi 2 C images z 1981 508 03003 A H amp E Breast H amp E 080215 1 3 z 1225387890_1 a 3 Angelique Unetelle 12 3 A 3 C images 1981 508 03003 A HER2 Breast HER2 080215 1 3 1225387891_1341 3003HER2 si ah Positive Pixel Count Algorithm User s Guide 11 D010 Chapter 3 Positive Pixel Count Analysis 2 If you want to limit the analysis to specific areas on the digital slide use the ImageScope free hand pen or rectangle tool on the ImageScope toolbar to draw boundaries around those areas YOY fh he A pN ae 46 A fa i oai yh A e f 5 w r A C p e p j A AN p 7 pA N N f o Ae E an Note that you can also use the i negative free hand pen to exclude areas from analysis In the example below the dotted line shows the area drawn nby the e pen EIA W We 7 is rr la Positive Pixel Count Algorithm Use
18. pport Tel 44 0 1934 733679 Email Email europesupport aperio com Asia Tel 81 3 3259 5255 Fax 81 3 3259 5256 Customer Service Email asiainfo aperio com Technical Support Email asiasupport aperio com if Positive Pixel Count Algorithm User s Guide Contents CHAPTER 1 INTRODUCTION cccccccceceeneeceenceccencencuscuauucnucnecuusuuenesneeeeceeuseass 1 The Positive Pixel Count Algorithm e seoseossoseesoessessesseesoessessesseesossoessessessossoss 1 BES SUC asc secaic se oes ed asso terse eects oe oh pcan T A Z Pie Ore Mini OR in Os oss ences carne E aenieeeteserecceneee 2 FDA Cleared Image Analysis Algorithms ccssccsccsscsssssessssessessssessseseseeees 3 MCC Se or EEA E 3 CHAPTER 2 QUICK REFERENCE scceccescencuccuecuccuccucneeneenceusencuacuacuanueneenneneess 5 Algorithm Input Parameters css esees soca t cena csecenccacaraciaescraaceadsasanseceuaseeceasenacsiaccaastiads 5 Alporthin RESUS scxscisssassritcaassvesssccavtestoessnsscsinsstaiveananvienlemanarmaneisansuetviateiats 6 CHAPTER 3 POSITIVE PIXEL COUNT ANALYSIS c0cccecescccceeceececcescesuenueeuseaseaseas 9 Color Conce pl Sesana n eaea rarae E niaaa S aera 9 NAS VSI A E E E T E 10 FRUITS an ATIVAN Y S18 sees sctactescses ens cassacetessnanecessdacscessuaeteczssadisessnctessstaceutessisvanneezssanets 11 NEN see sersienc ateuas aaee saute E en eceaeeneaneess 17 Positive Pixel Count User s Guide iii IV Contents Positive P
19. r s Guide Chapter 3 Positive Pixel Count Analysis D110 3 Go to the ImageScope View menu and select Analysis The Server Job window appears Algorithm Server Job Server o spectrum c x Select Algorithm Macro Macro Name Rare Event Detection Algorithm IHC ER Breast Dako Aperio Positive Pixel Count Sample Macro Incremental Generate Markup Image Shalt M ee a Processing Region of Analysis Selected Annotation Entire Image Test Create Cancel If an algorithm macro does not already exist for the Positive Pixel Count algorithm you or the Spectrum administrator will need to create one see the Aperio Image Analysis User s Guide for details on doing so 4 Click Test to fine tune the algorithm input parameters if you know they are already correct for your application you can just click Analyze to run the algorithm Positive Pixel Count Algorithm User s Guide l3 Papero 14 Chapter 3 Positive Pixel Count Analysis 5 After clicking Test the Algorithm window appears Macro on server o spectrum c import Macro Positive Pixel Count 2004 08 11 View Width View Height Overlap Size Image Zoom Markup Compression Type Compression Quality Classifier Definition List Class List Hue Value Hue Width Color Saturation Threshold Iwp High hwp Low Ip High Ip Low lsp High lp Low Inp High 1000 1000 0 1 0 Same as processed image
20. r strong positive pixels Intensity R G B 3 The intensity limits establish three intensity ranges for classifying and summing pixel values The greater the intensity value the brighter the pixel For more information on intensity ranges see Intensity on page 10 _Weak Positive Intensity Iwp High lt Intensity lt Iwp Low _ Positive Intensity Ip High lt Intensity lt Ip Low Strong Positive Intensity Isp High lt Intensity lt Isp Low Algorithm Results The algorithm results appear in the ImageScope Annotations window go to the ImageScope View menu and select Annotations The algorithm calculates the following quantities for each region of analysis as well as the sum of all regions for each layer that is analyzed Results are stored in an annotation layer attached to the image and can be viewed in ImageScope E Nwp Number of Weak Positive pixels Yellow in mark up image Np Number of Positive pixels Orange in mark up image Nsp Number of Strong Positive pixels Red in mark up image Iwp Sum of Intensity values for all Weak Positive pixels Ip Sum of Intensity values for all Positive pixels 6 Positive Pixel Count Algorithm User s Guide a DETO Chapter 2 Quick Reference C E Isp Sum of Intensity values for all Strong Positive pixels E avg Average Intensity of all pixels Iavg IwptIp Isp Nwp Np Nsp E Nsr Ratio of Strong Positive pixels to total pixels Nsr
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