Texture analysis in assessment and prediction of chemotherapy response in breast cancer

To assess the efficacy of dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI)‐based textural analysis in predicting response to chemotherapy in a cohort of breast cancer patients.

[1]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[2]  Thomas Tolxdorff,et al.  Feature extraction and supervised classification of MR images to support proton radiation therapy of eye tumors , 2004, Comput. Methods Programs Biomed..

[3]  Anant Madabhushi,et al.  Textural Kinetics: A Novel Dynamic Contrast-Enhanced (DCE)-MRI Feature for Breast Lesion Classification , 2011, Journal of Digital Imaging.

[4]  H. D. de Koning,et al.  Efficacy of MRI and mammography for breast-cancer screening in women with a familial or genetic predisposition. , 2004, The New England journal of medicine.

[5]  Andrzej Materka,et al.  Texture analysis for tissue discrimination on T1‐weighted MR images of the knee joint in a multicenter study: Transferability of texture features and comparison of feature selection methods and classifiers , 2005, Journal of magnetic resonance imaging : JMRI.

[6]  F. Kelcz,et al.  Improvement in breast lesion characterization with dynamic contrast‐enhanced MRI using pharmacokinetic modeling and bookend T1 measurements , 2004, Magnetic resonance in medicine.

[7]  F. Kruggel,et al.  Three-dimensional texture analysis of MRI brain datasets , 2001, IEEE Transactions on Medical Imaging.

[8]  M. Giger,et al.  Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers. , 2010, Radiology.

[9]  D Krebs,et al.  Breast MR imaging screening in 192 women proved or suspected to be carriers of a breast cancer susceptibility gene: preliminary results. , 2000, Radiology.

[10]  R. Tibshirani,et al.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[11]  R. Tibshirani,et al.  Repeated observation of breast tumor subtypes in independent gene expression data sets , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  L. Liberman,et al.  Breast imaging reporting and data system (BI-RADS). , 2002, Radiologic clinics of North America.

[13]  Mohan M. Trivedi,et al.  Segmentation of a high-resolution urban scene using texture operators , 1984, Comput. Vis. Graph. Image Process..

[14]  A. Padhani.  Dynamic contrast‐enhanced MRI in clinical oncology: Current status and future directions , 2002, Journal of magnetic resonance imaging : JMRI.

[15]  L. Turnbull,et al.  Neoadjuvant chemotherapy in breast cancer: early response prediction with quantitative MR imaging and spectroscopy , 2006, British Journal of Cancer.

[16]  B. Clymer,et al.  Texture detection of simulated microcalcification susceptibility effects in magnetic resonance imaging of breasts , 2001, Journal of magnetic resonance imaging : JMRI.

[17]  Nick C. Fox,et al.  MR image texture analysis applied to the diagnosis and tracking of Alzheimer's disease , 1998, IEEE Transactions on Medical Imaging.

[18]  L. Turnbull,et al.  Textural analysis of contrast‐enhanced MR images of the breast , 2003, Magnetic resonance in medicine.

[19]  L. Bassett,et al.  Multifeature analysis of Gd‐enhanced MR images of breast lesions , 1997, Journal of magnetic resonance imaging : JMRI.

[20]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[21]  M. Yaffe,et al.  American Cancer Society Guidelines for Breast Screening with MRI as an Adjunct to Mammography , 2007 .

[22]  L. Esserman,et al.  MRI measurements of breast tumor volume predict response to neoadjuvant chemotherapy and recurrence-free survival. , 2005, AJR. American journal of roentgenology.

[23]  M. Giger,et al.  Volumetric texture analysis of breast lesions on contrast‐enhanced magnetic resonance images , 2007, Magnetic resonance in medicine.

[24]  P. Ring,et al.  Texture Analysis in Quantitative MR Imaging , 1995, Acta radiologica.

[25]  L. Schwartz,et al.  32 INVITED New response evaluation criteria in solid tumors: revised RECIST guideline version 1.1 , 2008 .

[26]  Grégoire Toussaint,et al.  Three dimensional texture analysis in MRI: a preliminary evaluation in gliomas. , 2003, Magnetic resonance imaging.

[27]  P. Tofts,et al.  Texture analysis of spinal cord pathology in multiple sclerosis , 1999, Magnetic resonance in medicine.

[28]  L. Schad,et al.  MR image texture analysis--an approach to tissue characterization. , 1993, Magnetic resonance imaging.