Feasibility of contrast-enhanced MRI derived textural features to predict overall survival in locally advanced breast cancer Journal Article
| Authors: | Chronaiou, I.; Giskeødegård, G. F.; Goa, P. E.; Teruel, J.; Hedayati, R.; Lundgren, S.; Huuse, E. M.; Pickles, M. D.; Gibbs, P.; Sitter, B.; Bathen, T. F. |
| Article Title: | Feasibility of contrast-enhanced MRI derived textural features to predict overall survival in locally advanced breast cancer |
| Abstract: | Background: The prognosis for women with locally advanced breast cancer (LABC) is poor and there is a need for better treatment stratification. Gray-level co-occurrence matrix (GLCM) texture analysis of magnetic resonance (MR) images has been shown to predict pathological response and could become useful in stratifying patients to more targeted treatments. Purpose: To evaluate the ability of GLCM textural features obtained before neoadjuvant chemotherapy to predict overall survival (OS) seven years after diagnosis of patients with LABC. Material and Methods: This retrospective study includes data from 55 patients with LABC. GLCM textural features were extracted from segmented tumors in pre-treatment dynamic contrast-enhanced 3-T MR images. Prediction of OS by GLCM textural features was assessed and compared to predictions using traditional clinical variables. Results: Linear mixed-effect models showed significant differences in five GLCM features (f1, f2, f5, f10, f11) between survivors and non-survivors. Using discriminant analysis for prediction of survival, GLCM features from 2 min post-contrast images achieved a classification accuracy of 73% (P < 0.001), whereas traditional prognostic factors resulted in a classification accuracy of 67% (P = 0.005). Using a combination of both yielded the highest classification accuracy (78%, P < 0.001). Median values for features f1, f2, f10, and f11 provided significantly different survival curves in Kaplan–Meier analysis. Conclusion: This study shows a clear association between textural features from post-contrast images obtained before neoadjuvant chemotherapy and OS seven years after diagnosis. Further studies in larger cohorts should be undertaken to investigate how this prognostic information can be used to benefit treatment stratification. © The Foundation Acta Radiologica 2019. |
| Keywords: | survival; adult; controlled study; aged; aged, 80 and over; middle aged; survival rate; retrospective studies; major clinical study; overall survival; mortality; cancer patient; chemotherapy; cancer staging; nuclear magnetic resonance imaging; magnetic resonance imaging; neoplasm staging; analysis; cancer grading; sensitivity and specificity; breast cancer; image analysis; image interpretation, computer-assisted; pathology; diagnostic imaging; breast neoplasms; retrospective study; cancer survivor; feasibility study; computer assisted diagnosis; image enhancement; medical imaging; feasibility studies; discriminant analysis; contrast enhancement; breast tumor; diagnosis; predictive value of tests; forecasting; contrast medium; contrast media; kaplan meier method; cancer classification; gadolinium pentetate; gadolinium dtpa; gadodiamide; diseases; predictive value; caucasian; norway; diagnostic test accuracy study; gadolinium pentetate meglumine; texture analysis; textures; procedures; cancer prognosis; neoplasm grading; very elderly; dynamic contrast enhanced; measurement accuracy; humans; prognosis; human; female; priority journal; article; locally advanced breast cancer; classification accuracy; neoadjuvant chemotherapies; gray level co occurrence matrix(glcm) |
| Journal Title: | Acta Radiologica |
| Volume: | 61 |
| Issue: | 7 |
| ISSN: | 0284-1851 |
| Publisher: | Sage Publications Ltd. |
| Date Published: | 2020-07-01 |
| Start Page: | 875 |
| End Page: | 884 |
| Language: | English |
| DOI: | 10.1177/0284185119885116 |
| PUBMED: | 31744303 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Article -- Export Date: 3 August 2020 -- Source: Scopus |
