Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer
Objective: Ki67 is a prognostic and predictive marker in breast cancer (BC). However, manual scoring (MS) by visual assessment suffers from high inter-observer variability which limits its clinical use. Here, we developed a new digital image analysis (DIA) workflow, named KiQuant for automated scori...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-10-01
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| Series: | Breast |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0960977620301442 |
| _version_ | 1818537601332674560 |
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| author | Garazi Serna Sara Simonetti Roberta Fasani Francesca Pagliuca Xavier Guardia Paqui Gallego Jose Jimenez Vicente Peg Cristina Saura Serenella Eppenberger-Castori Santiago Ramon y Cajal Luigi Terracciano Paolo Nuciforo |
| author_facet | Garazi Serna Sara Simonetti Roberta Fasani Francesca Pagliuca Xavier Guardia Paqui Gallego Jose Jimenez Vicente Peg Cristina Saura Serenella Eppenberger-Castori Santiago Ramon y Cajal Luigi Terracciano Paolo Nuciforo |
| author_sort | Garazi Serna |
| collection | DOAJ |
| description | Objective: Ki67 is a prognostic and predictive marker in breast cancer (BC). However, manual scoring (MS) by visual assessment suffers from high inter-observer variability which limits its clinical use. Here, we developed a new digital image analysis (DIA) workflow, named KiQuant for automated scoring of Ki67 and investigated its equivalence with standard pathologist's assessment. Methods: Sequential immunohistochemistry of Ki67 and cytokeratin, for precise tumor cell recognition, were performed in the same section of 5 tissue microarrays containing 329 tumor cores from different breast cancer subtypes. Slides were digitalized and subjected to DIA and MS for Ki67 assessment. The intraclass correlation coefficient (ICC) and Bland-Altman plot were used to evaluate inter-observer reproducibility. The Kaplan-Meier analysis was used to determine the prognostic potential. Results: KiQuant showed an excellent correlation with MS (ICC:0.905,95%CI:0.878–0.926) with satisfactory inter-run (ICC:0.917,95%CI:0.884–0.942) and inter-antibody reproducibilities (ICC:0.886,95%CI:0.820–0.929). The distance between KiQuant and MS increased with the magnitude of Ki67 measurement and positively correlated with analyzed tumor area and breast cancer subtype. Agreement rates between KiQuant and MS within the clinically relevant 14% and 30% cut-off points ranged from 33% to 44% with modest interobserver reproducibility below the 20% cut-off (0.606, 95%CI:0.467–0.727). High Ki67 by KiQuant correlated with worse outcome in all BC and in the luminal subtype (P = 0.028 and P = 0.043, respectively). For MS, the association with survival was significant only in 1 out of 3 observers. Conclusions: KiQuant represents an easy and accurate methodology for Ki67 measurement providing a step toward utilizing Ki67 in the clinical setting. |
| first_indexed | 2024-12-11T18:52:51Z |
| format | Article |
| id | doaj.art-f7f89ece0aa74d5d8ad590c45bfa270d |
| institution | Directory Open Access Journal |
| issn | 1532-3080 |
| language | English |
| last_indexed | 2024-12-11T18:52:51Z |
| publishDate | 2020-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Breast |
| spelling | doaj.art-f7f89ece0aa74d5d8ad590c45bfa270d2022-12-22T00:54:14ZengElsevierBreast1532-30802020-10-0153102110Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancerGarazi Serna0Sara Simonetti1Roberta Fasani2Francesca Pagliuca3Xavier Guardia4Paqui Gallego5Jose Jimenez6Vicente Peg7Cristina Saura8Serenella Eppenberger-Castori9Santiago Ramon y Cajal10Luigi Terracciano11Paolo Nuciforo12Molecular Oncology Group, Vall D'Hebron Institute of Oncology, Barcelona, SpainMolecular Oncology Group, Vall D'Hebron Institute of Oncology, Barcelona, SpainMolecular Oncology Group, Vall D'Hebron Institute of Oncology, Barcelona, SpainUniversity of Naples Federico II, Department of Advanced Biomedical Sciences, Pathology Section, Naples, ItalyMolecular Oncology Group, Vall D'Hebron Institute of Oncology, Barcelona, SpainMolecular Oncology Group, Vall D'Hebron Institute of Oncology, Barcelona, SpainMolecular Oncology Group, Vall D'Hebron Institute of Oncology, Barcelona, SpainDepartment of Pathology, Vall D'Hebron University Hospital, Barcelona, SpainBreast Cancer and Melanoma Group, Vall D'Hebron Institute of Oncology, Barcelona, SpainInstitute of Pathology, University Hospital Basel, Basel, SwitzerlandDepartment of Pathology, Vall D'Hebron University Hospital, Barcelona, SpainInstitute of Pathology, University Hospital Basel, Basel, SwitzerlandMolecular Oncology Group, Vall D'Hebron Institute of Oncology, Barcelona, Spain; Corresponding author. Molecular Oncology Group, Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology (VHIO) C/ Natzaret, 115-117, 08035, Barcelona, Spain.Objective: Ki67 is a prognostic and predictive marker in breast cancer (BC). However, manual scoring (MS) by visual assessment suffers from high inter-observer variability which limits its clinical use. Here, we developed a new digital image analysis (DIA) workflow, named KiQuant for automated scoring of Ki67 and investigated its equivalence with standard pathologist's assessment. Methods: Sequential immunohistochemistry of Ki67 and cytokeratin, for precise tumor cell recognition, were performed in the same section of 5 tissue microarrays containing 329 tumor cores from different breast cancer subtypes. Slides were digitalized and subjected to DIA and MS for Ki67 assessment. The intraclass correlation coefficient (ICC) and Bland-Altman plot were used to evaluate inter-observer reproducibility. The Kaplan-Meier analysis was used to determine the prognostic potential. Results: KiQuant showed an excellent correlation with MS (ICC:0.905,95%CI:0.878–0.926) with satisfactory inter-run (ICC:0.917,95%CI:0.884–0.942) and inter-antibody reproducibilities (ICC:0.886,95%CI:0.820–0.929). The distance between KiQuant and MS increased with the magnitude of Ki67 measurement and positively correlated with analyzed tumor area and breast cancer subtype. Agreement rates between KiQuant and MS within the clinically relevant 14% and 30% cut-off points ranged from 33% to 44% with modest interobserver reproducibility below the 20% cut-off (0.606, 95%CI:0.467–0.727). High Ki67 by KiQuant correlated with worse outcome in all BC and in the luminal subtype (P = 0.028 and P = 0.043, respectively). For MS, the association with survival was significant only in 1 out of 3 observers. Conclusions: KiQuant represents an easy and accurate methodology for Ki67 measurement providing a step toward utilizing Ki67 in the clinical setting.http://www.sciencedirect.com/science/article/pii/S0960977620301442Ki67 quantificationBreast cancerPrognosisSequential immunohistochemistryDigital image analysis |
| spellingShingle | Garazi Serna Sara Simonetti Roberta Fasani Francesca Pagliuca Xavier Guardia Paqui Gallego Jose Jimenez Vicente Peg Cristina Saura Serenella Eppenberger-Castori Santiago Ramon y Cajal Luigi Terracciano Paolo Nuciforo Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer Breast Ki67 quantification Breast cancer Prognosis Sequential immunohistochemistry Digital image analysis |
| title | Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer |
| title_full | Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer |
| title_fullStr | Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer |
| title_full_unstemmed | Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer |
| title_short | Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer |
| title_sort | sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative ki67 measurement in breast cancer |
| topic | Ki67 quantification Breast cancer Prognosis Sequential immunohistochemistry Digital image analysis |
| url | http://www.sciencedirect.com/science/article/pii/S0960977620301442 |
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