当前位置： SCI文献检索 > JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY期刊下所有文献 > A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models.

A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models.

Abstract：

PURPOSE:To determine whether multivariate machine learning models of algorithmically assessed magnetic resonance imaging (MRI) features from breast cancer patients are associated with Oncotype DX (ODX) test recurrence scores. METHODS:A set of 261 female patients with invasive breast cancer, pre-operative dynamic contrast enhanced magnetic resonance (DCE-MR) images and available ODX score at our institution was identified. A computer algorithm extracted a comprehensive set of 529 features from the DCE-MR images of these patients. The set of patients was divided into a training set and a test set. Using the training set we developed two machine learning-based models to discriminate (1) high ODX scores from intermediate and low ODX scores, and (2) high and intermediate ODX scores from low ODX scores. The performance of these models was evaluated on the independent test set. RESULTS:High against low and intermediate ODX scores were predicted by the multivariate model with AUC 0.77 (95% CI 0.56-0.98, p < 0.003). Low against intermediate and high ODX score was predicted with AUC 0.51 (95% CI 0.41-0.61, p = 0.75). CONCLUSION:A moderate association between imaging and ODX score was identified. The evaluated models currently do not warrant replacement of ODX with imaging alone.

journal_name

J Cancer Res Clin Oncol

journal_title

Journal of cancer research and clinical oncology

authors

Saha A,Harowicz MR,Wang W,Mazurowski MA

doi

10.1007/s00432-018-2595-7

subject

Has Abstract

pub_date

2018-05-01 00:00:00

pages

799-807

issue

5

eissn

0171-5216

issn

1432-1335

pii

10.1007/s00432-018-2595-7

journal_volume

144

pub_type

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