Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer
<p>Abstract</p> <p>Background</p> <p>The immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quan...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2011-01-01
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| Series: | Diagnostic Pathology |
| Online Access: | http://www.diagnosticpathology.org/content/6/1/6 |
| _version_ | 1818143208461303808 |
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| author | Gurzó Péter Czuni László Császár Gergely Jónás Viktor Szabó Dániel Krenács Tibor Kiszler Gábor Micsik Tamás Krecsák László Ficsor Levente Molnár Béla |
| author_facet | Gurzó Péter Czuni László Császár Gergely Jónás Viktor Szabó Dániel Krenács Tibor Kiszler Gábor Micsik Tamás Krecsák László Ficsor Levente Molnár Béla |
| author_sort | Gurzó Péter |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>The immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quantization of the image objects (e.g. cell membrane, nuclei) and an unbiased analysis of immunostaining results. Validation studies of image analysis applications for the detection of ER and PR in breast cancer specimens provided strong concordance between the pathologist's manual assessment of slides and scoring performed using different software applications.</p> <p>Methods</p> <p>The effectiveness of two connected semi-automated image analysis software (<it>NuclearQuant </it>v. 1.13 application for <it>Pannoramic</it>™ <it>Viewer </it>v. 1.14) for determination of ER and PR status in formalin-fixed paraffin embedded breast cancer specimens immunostained with the automated Leica Bond Max system was studied. First the detection algorithm was calibrated to the scores provided an independent assessors (pathologist), using selected areas from 38 small digital slides (created from 16 cases) containing a mean number of 195 cells. Each cell was manually marked and scored according to the Allred-system combining frequency and intensity scores. The performance of the calibrated algorithm was tested on 16 cases (14 invasive ductal carcinoma, 2 invasive lobular carcinoma) against the pathologist's manual scoring of digital slides.</p> <p>Results</p> <p>The detection was calibrated to 87 percent object detection agreement and almost perfect Total Score agreement (Cohen's kappa 0.859, quadratic weighted kappa 0.986) from slight or moderate agreement at the start of the study, using the un-calibrated algorithm. The performance of the application was tested against the pathologist's manual scoring of digital slides on 53 regions of interest of 16 ER and PR slides covering all positivity ranges, and the quadratic weighted kappa provided almost perfect agreement (κ = 0.981) among the two scoring schemes.</p> <p>Conclusions</p> <p><it>NuclearQuant </it>v. 1.13 application for <it>Pannoramic</it>™ <it>Viewer </it>v. 1.14 software application proved to be a reliable image analysis tool for pathologists testing ER and PR status in breast cancer.</p> |
| first_indexed | 2024-12-11T11:28:01Z |
| format | Article |
| id | doaj.art-edcbbe477f3f43da84bf98a9535976d3 |
| institution | Directory Open Access Journal |
| issn | 1746-1596 |
| language | English |
| last_indexed | 2024-12-11T11:28:01Z |
| publishDate | 2011-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Diagnostic Pathology |
| spelling | doaj.art-edcbbe477f3f43da84bf98a9535976d32022-12-22T01:08:58ZengBMCDiagnostic Pathology1746-15962011-01-0161610.1186/1746-1596-6-6Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancerGurzó PéterCzuni LászlóCsászár GergelyJónás ViktorSzabó DánielKrenács TiborKiszler GáborMicsik TamásKrecsák LászlóFicsor LeventeMolnár Béla<p>Abstract</p> <p>Background</p> <p>The immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quantization of the image objects (e.g. cell membrane, nuclei) and an unbiased analysis of immunostaining results. Validation studies of image analysis applications for the detection of ER and PR in breast cancer specimens provided strong concordance between the pathologist's manual assessment of slides and scoring performed using different software applications.</p> <p>Methods</p> <p>The effectiveness of two connected semi-automated image analysis software (<it>NuclearQuant </it>v. 1.13 application for <it>Pannoramic</it>™ <it>Viewer </it>v. 1.14) for determination of ER and PR status in formalin-fixed paraffin embedded breast cancer specimens immunostained with the automated Leica Bond Max system was studied. First the detection algorithm was calibrated to the scores provided an independent assessors (pathologist), using selected areas from 38 small digital slides (created from 16 cases) containing a mean number of 195 cells. Each cell was manually marked and scored according to the Allred-system combining frequency and intensity scores. The performance of the calibrated algorithm was tested on 16 cases (14 invasive ductal carcinoma, 2 invasive lobular carcinoma) against the pathologist's manual scoring of digital slides.</p> <p>Results</p> <p>The detection was calibrated to 87 percent object detection agreement and almost perfect Total Score agreement (Cohen's kappa 0.859, quadratic weighted kappa 0.986) from slight or moderate agreement at the start of the study, using the un-calibrated algorithm. The performance of the application was tested against the pathologist's manual scoring of digital slides on 53 regions of interest of 16 ER and PR slides covering all positivity ranges, and the quadratic weighted kappa provided almost perfect agreement (κ = 0.981) among the two scoring schemes.</p> <p>Conclusions</p> <p><it>NuclearQuant </it>v. 1.13 application for <it>Pannoramic</it>™ <it>Viewer </it>v. 1.14 software application proved to be a reliable image analysis tool for pathologists testing ER and PR status in breast cancer.</p>http://www.diagnosticpathology.org/content/6/1/6 |
| spellingShingle | Gurzó Péter Czuni László Császár Gergely Jónás Viktor Szabó Dániel Krenács Tibor Kiszler Gábor Micsik Tamás Krecsák László Ficsor Levente Molnár Béla Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer Diagnostic Pathology |
| title | Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer |
| title_full | Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer |
| title_fullStr | Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer |
| title_full_unstemmed | Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer |
| title_short | Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer |
| title_sort | technical note on the validation of a semi automated image analysis software application for estrogen and progesterone receptor detection in breast cancer |
| url | http://www.diagnosticpathology.org/content/6/1/6 |
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