Artificial intelligence at the intersection of pathology and radiology in prostate cancer.
Pathologic grading plays a key role in prostate cancer risk stratification and treatment selection, traditionally assessed from systemic core needle biopsies sampled throughout the prostate gland. Multiparametric magnetic resonance imaging (mpMRI) has become a well-established clinical tool for dete...
| Publicado en: | Diagnostic & Interventional Radiology Vol. 25; no. 3; pp. 183 - 189 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
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Galenos Yayinevi Tic. LTD. STI
May/Jun2019
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| 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=136654841&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136654841 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13053825 39NM jtl: Diagnostic & Interventional Radiology issn: 13053825 maglogo: N pubinfo: dt: May/Jun2019 vid: 25 iid: 3 pid: 28155 pub: Galenos Yayinevi Tic. LTD. STI artinfo: ui: 136654841 136654841 NLM31063138 10.5152/dir.2019.19125 NLM31063138 136654841 ppf: 183 ppct: 6 formats: fmt: @attributes: type: P tig: atl: Artificial intelligence at the intersection of pathology and radiology in prostate cancer. aug: au: Harmon, Stephanie A. Tuncer, Sena Sanford, Thomas Choyke, Peter L. Türkbey, Barış Harmon, Stephnie A affil: Clinical Research Directorate, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, MD, USA sug: ab: Pathologic grading plays a key role in prostate cancer risk stratification and treatment selection, traditionally assessed from systemic core needle biopsies sampled throughout the prostate gland. Multiparametric magnetic resonance imaging (mpMRI) has become a well-established clinical tool for detecting and localizing prostate cancer. However, both pathologic and radiologic assessment suffer from poor reproducibility among readers. Artificial intelligence (AI) methods show promise in aiding the detection and assessment of imaging-based tasks, dependent on the curation of high-quality training sets. This review provides an overview of recent advances in AI applied to mpMRI and digital pathology in prostate cancer which enable advanced characterization of disease through combined radiology-pathology assessment. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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