Quantitative digital image analysis of tumor-infiltrating lymphocytes in HER2-positive breast cancer.
As visual quantification of the density of tumor-infiltrating lymphocytes (TILs) lacks in precision, digital image analysis (DIA) approach has been applied in order to improve. In several studies, TIL density has been examined on hematoxylin and eosin (HE)-stained sections using DIA. The aim of the...
| Publicado en: | Virchows Archiv: European Journal of Pathology Vol. 476; no. 5; pp. 701 - 710 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
May2020
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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=143194493&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 143194493 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09456317 O1Z jtl: Virchows Archiv: European Journal of Pathology issn: 09456317 maglogo: N pubinfo: dt: May2020 vid: 476 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 143194493 143194493 NLM31873876 143194493 10.1007/s00428-019-02730-6 NLM31873876 143194493 ppf: 701 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Quantitative digital image analysis of tumor-infiltrating lymphocytes in HER2-positive breast cancer. aug: au: Abe, Norie Matsumoto, Hirofumi Takamatsu, Reika Tamaki, Kentaro Takigami, Naoko Uehara, Kano Kamada, Yoshihiko Tamaki, Nobumitsu Motonari, Tokiwa Unesoko, Mikiko Nakada, Norihiro Zaha, Hisamitsu Yoshimi, Naoki affil: Department of Breast Surgery, Nakagami Hospital, Okinawa, Japan sug: subj: Breast Neoplasms Lymphocytes Pathology Receptors, Cell Surface Adult Middle Age Biopsy, Needle Breast Neoplasms Drug Therapy Aged Female Prospective Studies Neoadjuvant Therapy Breast Neoplasms Pathology Human Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Female ab: As visual quantification of the density of tumor-infiltrating lymphocytes (TILs) lacks in precision, digital image analysis (DIA) approach has been applied in order to improve. In several studies, TIL density has been examined on hematoxylin and eosin (HE)-stained sections using DIA. The aim of the present study was to quantify TIL density on HE sections of core needle biopsies using DIA and investigate its association with clinicopathological parameters and pathological response to neoadjuvant chemotherapy in human epidermal growth factor receptor 2 (HER2)-positive breast cancer. The study cohort comprised of patients with HER2-positive breast cancer, all treated with neoadjuvant anti-HER2 therapy. DIA software applying machine learning-based classification of epithelial and stromal elements was used to count TILs. TIL density was determined as the number of TILs per square millimeter of stromal tissue. Median TIL density was 1287/mm2 (range, 123-8101/mm2). A high TIL density was associated with higher histological grade (P = 0.02), estrogen receptor negativity (P = 0.036), and pathological complete response (pCR) (P < 0.0001). In analyses using receiver operating characteristic curves, a threshold TIL density of 2420/mm2 best discriminated pCR from non-pCR. In multivariate analysis, high TIL density (> 2420/mm2) was significantly associated with pCR (P < 0.0001). Our results indicate that DIA can assess TIL density quantitatively, machine learning-based classification algorithm allowing determination of TIL density as the number of TILs per unit area, and TIL density established by this method appears to be an independent predictor of pCR in HER2-positive breast cancer. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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