Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists.
* Context.--Advancements in genomic, computing, and imaging technology have spurred new opportunities to use quantitative image analysis (QIA) for diagnostic testing. Objective.--To develop evidence-based recommendations to improve accuracy, precision, and reproducibility in the interpretation of hu...
| Publicado en: | Archives of Pathology & Laboratory Medicine Vol. 143; no. 10; pp. 1180 - 1196 |
|---|---|
| Autores principales: | , , , , , , , , , , , , , |
| Formato: | pictorial practice guidelines research systematic review tables/charts Journal Article |
| Publicado: |
College of American Pathologists
Oct2019
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139005602&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139005602 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00039985 1FS jtl: Archives of Pathology & Laboratory Medicine issn: 00039985 maglogo: N pubinfo: dt: Oct2019 vid: 143 iid: 10 pid: 2550 pub: College of American Pathologists place: Northfield, Illinois artinfo: ui: 139005602 139005602 139005602 10.5858/arpa.2018-0378-CP 139005602 ppf: 1180 ppct: 16 formats: fmt: @attributes: type: P tig: atl: Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists. aug: au: Bui, Marilyn M. Riben, Michael W. Allison, Kimberly H. Chlipala, Elizabeth Colasacco, Carol Kahn, Andrea G. Lacchetti, Christina Madabhushi, Anant Pantanowitz, Liron Salama, Mohamed E. Stewart, Rachel L. Thomas, Nicole E. Tomaszewski, John E. Hammond, M. Elizabeth affil: Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida sug: subj: Breast Neoplasms Diagnosis Image Processing, Computer Assisted Methods Immunohistochemistry Receptors, Cell Surface Pathologists Sensitivity and Specificity Epidermal Growth Factor Receptors Human Quantitative Studies Precision Scientists Feedback Consensus Quality Assurance Systematic Review ab: * Context.--Advancements in genomic, computing, and imaging technology have spurred new opportunities to use quantitative image analysis (QIA) for diagnostic testing. Objective.--To develop evidence-based recommendations to improve accuracy, precision, and reproducibility in the interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) for breast cancer where QIA is used. Design.--The College of American Pathologists (CAP) convened a panel of pathologists, histotechnologists, and computer scientists with expertise in image analysis, immunohistochemistry, quality management, and breast pathology to develop recommendations for QIA of HER2 IHC in breast cancer. A systematic review of the literature was conducted to address 5 key questions. Final recommendations were derived from strength of evidence, open comment feedback, expert panel consensus, and advisory panel review. Results.--Eleven recommendations were drafted: 7 based on CAP laboratory accreditation requirements and 4 based on expert consensus opinions. A 3-week open comment period received 180 comments from more than 150 participants. Conclusions.--To improve accurate, precise, and reproducible interpretation of HER2 IHC results for breast cancer, QIA and procedures must be validated before implementation, followed by regular maintenance and ongoing evaluation of quality control and quality assurance. HER2 QIA performance, interpretation, and reporting should be supervised by pathologists with expertise in QIA. pubtype: Academic Journal doctype: pictorial practice guidelines research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|