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Intratumoral and Peritumoral Radiomics Based on Preoperative MRI for Evaluation of Programmed Cell Death Ligand-1 Expression in Breast Cancer.
Wu, Zengjie; Lin, Qing; Wang, Haibo; Chen, Jingjing; Wang, Guanqun; Fu, Guangming; Li, Lili; Bian, Tiantian.
Afiliação
  • Wu Z; Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Lin Q; Breast Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Wang H; Breast Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Chen J; Breast Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Wang G; Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Fu G; Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Li L; Breast Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Bian T; Breast Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
J Magn Reson Imaging ; 2023 Nov 02.
Article em En | MEDLINE | ID: mdl-37916918
ABSTRACT

BACKGROUND:

Programmed cell death ligand-1 (PD-L1) is a promising target for immune checkpoint blockade therapy in breast cancer. However, the preoperative evaluation of PD-L1 expression in breast cancer is rarely explored.

PURPOSE:

To determine the ability of radiomics signatures based on preoperative dynamic contrast-enhanced (DCE) MRI to evaluate PD-L1 expression in breast cancer. STUDY TYPE Retrospective. POPULATION 196 primary breast cancer patients with preoperative MRI and postoperative pathological evaluation of PD-L1 expression, divided into training (n = 137, 28 PD-L1-positive) and test cohorts (n = 59, 12 PD-L1-positive). FIELD STRENGTH/SEQUENCE 3.0T; volume imaging for breast assessment DCE sequence. ASSESSMENT Radiomics features were extracted from the first phase of DCE-MRI by using the minimum redundancy maximum relevance method and least absolute shrinkage and selection operator algorithm. Three radiomics signatures were constructed based on the intratumoral, peritumoral, and combined intra- and peritumoral regions. The performance of the signatures was assessed using area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, and accuracy. STATISTICAL TESTS Univariable and multivariable logistic regression analysis, t-tests, chi-square tests, Fisher exact test or Yates correction, ROC analysis, and one-way analysis of variance. P < 0.05 was considered significant.

RESULTS:

In the test cohort, the combined radiomics signature (AUC, 0.853) exhibited superior performance compared to the intratumoral (AUC, 0.816; P = 0.528) and peritumoral radiomics signatures (AUC, 0.846; P = 0.905) in PD-L1 status evaluation, although the differences did not reach statistical significance. DATA

CONCLUSION:

Intratumoral and peritumoral radiomics signatures based on preoperative breast MRI showed some potential accuracy for the non-invasive evaluation of PD-L1 status in breast cancer. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY Stage 2.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Magn Reson Imaging Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Magn Reson Imaging Ano de publicação: 2023 Tipo de documento: Article