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Arvydas Laurinavi č ius Pathology Visions 2010

The Results of Automated Image Analysis Workshop at the 10th European Congress on Telepathology and 4th International Congress on Virtual Microscopy. Arvydas Laurinavi č ius Pathology Visions 2010. VILNIUS UNIVERSITY. NATIONAL CENTRE OF PATHOLOGY. Background and Disclaimer.

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Arvydas Laurinavi č ius Pathology Visions 2010

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  1. The Results of Automated Image Analysis Workshop at the 10th European Congress on Telepathology and 4th International Congress on Virtual Microscopy Arvydas Laurinavičius Pathology Visions 2010 VILNIUS UNIVERSITY NATIONAL CENTRE OF PATHOLOGY

  2. Background and Disclaimer • Pathologist (Renal) • Director, National Center of Pathology, LT • Professor, Vilnius University • EU COST Telepathology Network • EU LLL EUROPALS • MB, IHTSDO (SNOMED CT) • International Member, CAP • User of Aperio and TissueGnostics tools • No competing interests

  3. 2010Vilnius Lithuania 2012 Venice Italy

  4. Telepathology - Program http://www.telepathology2010.com/31 Screen clipping taken: 2010-09-27; 11:14 http://www.telepathology2010.com

  5. The Goal To provide an overview of automated image analysis tools in terms of their robustness and workflow efficiency in a structured and comparable fashion

  6. Outline • Why – A Pathologist’s Vision of the Digital • How – Workshop Design and Results • What – Ways to Go

  7. Evolution of Pathology >19th 20th 21st century Spectrum of Technologies DIGITAL MOLECULAR IMUNOHISTOCHEMISTRY MICROSCOPY MACROSCOPY

  8. Pathology Lab … transforms biological information intomedical Spectrum of Technologies Biospecimen Patient Pathology Diagnosis Clinical Decision

  9. Adding Digital Path-Way • Computer analyzes images • Computer scans slides Competition? Ignorance? Synergy?

  10. Questions asked: • Does this work? • Why is Digital better than Conventional? • Tool or Toy? Long way to go… More specifically: • Shall I scan everything? • Should scanners be certified for diagnostic use? • Is it legal to make a diagnosis on virtual slides? • Can I work faster on digital images? • Are quantification results reliable?

  11. Innovation versus Routine Involvement needs awareness

  12. Treat the Tools and Humans equally intra-observer Pathologist #1 Pathologist #1 perfect Pathologist #2 Pathologist #2 moderate moderate inter-observer Tool #1 Tool #1 perfect ??? Tool #2 Tool #2 perfect Are different tools in agreement? Are they better than we?

  13. Partitioning the Observer • Computer analyzes images • Computer scans slides Automated Image Analysis Workshop 1st European Scanner Contest • “2 in 1” • “2 in 1” • “Hardware” • “Software”

  14. Outline • Why – A Pathologist’s Vision of the Digital • How – Workshop Design and Results • What – Ways to Go Next

  15. Workshop Design • Keep simple, explore feasibility of a Contest • Estrogen Receptor and HER2 IHC • Whole slide and TMAs from the Spanish QA Program • HER2 FISH • Whole slides from the NtlCtrPathol • Available for scanning >1 month (at the 1st ESC) • Participants presented their workflow and results at the Workshop • Presentations posted at http://www.telepathology2010.com

  16. Participants • * Used for analysis the FISH slides provided

  17. Workshop Results Concordance testing of the results was out of scope, however, some output data provided by the Participants were analyzed

  18. Estrogen Receptor, % Pos Nuclei 3 outlier cases by A, variable ROI selection?

  19. Estrogen Receptor, Total Nuclei Counted B and C, different size of ROI?

  20. Estrogen Receptor, % Pos Nuclei Strong correlation; nonlinearity possible? Participant B and C Correlation 0.898 p<.0001

  21. Estrogen Receptor, % Pos Nuclei Nonlinearity: C outputs higher values (frequent 100%) than B B Nonlinear regressionp<.0001

  22. Estrogen Receptor, % Pos Nuclei B tends to output lower values than A and C Not significant

  23. HER2 IHC Score Agreement between B and C Note: different cutoff used by B and C for 3+ (10 vs 30%)

  24. Lessons learned • Plan thoroughly, involve Participants • Improve scanning logistics, especially FISH • Provide gold standard slides, preferably TMAs • Define sampling • whole slide, manual annotation, automated ROI detection • Harmonize output formats

  25. Outline • Why – A Pathologist’s Vision of the Digital • How – Workshop Design and Results • What – Ways to Go

  26. Ways to Go • Do nothing • Do the same • Do inter-observer (inter-Tool) variability study • Develop an ongoing QA program • Disseminate the results

  27. Disseminate Digital Pathology League • Scanner Contest • Image Analysis Contest

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