Diffusion‐weighted Imaging in Evaluating the Response to Neoadjuvant Breast Cancer Treatment

Abstract:  The aim of this study was to investigate the role of diffusion imaging in the evaluation of response to neoadjuvant breast cancer treatment by correlating apparent diffusion coefficient (ADC) value changes with pathological response. From June 2007 to June 2009, all consecutive patients with histopathologically confirmed breast cancer undergoing neoadjuvant chemotherapy were enrolled. All patients underwent magnetic resonance imaging (MRI) (including diffusion sequence) before and after neoadjuvant treatment. The ADC values obtained using two different methods of region of interest (ROI) placement before and after treatment were compared with MRI response (assessed using RECIST 1.1 criteria) and pathological response (assessed using Mandard’s classification).

[1]  L. Schwartz,et al.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). , 2009, European journal of cancer.

[2]  R. Gillies,et al.  Applications of magnetic resonance in model systems: tumor biology and physiology. , 2000, Neoplasia.

[3]  J. Galons,et al.  MRI‐measured water mobility increases in response to chemotherapy via multiple cell‐death mechanisms , 2007, NMR in biomedicine.

[4]  N. van Bruggen,et al.  Quantification of tumor tissue populations by multispectral analysis , 2004, Magnetic resonance in medicine.

[5]  J. B. Moody,et al.  Diffusion imaging for evaluation of tumor therapies in preclinical animal models , 2004, Magnetic Resonance Materials in Physics, Biology and Medicine.

[6]  R. Gillies,et al.  Changes in water mobility measured by diffusion MRI predict response of metastatic breast cancer to chemotherapy. , 2004, Neoplasia.

[7]  U. Sharma,et al.  Longitudinal study of the assessment by MRI and diffusion‐weighted imaging of tumor response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy , 2009, NMR in biomedicine.

[8]  L. Turnbull,et al.  Role of dynamic contrast enhanced MRI in monitoring early response of locally advanced breast cancer to neoadjuvant chemotherapy , 2005, Breast Cancer Research and Treatment.

[9]  Roman Rouzier,et al.  Change in tumor cellularity of breast carcinoma after neoadjuvant chemotherapy as a variable in the pathologic assessment of response , 2004, Cancer.

[10]  Mark A. Helvie,et al.  Clinical and Radiologic Assessments to Predict Breast Cancer Pathologic Complete Response to Neoadjuvant Chemotherapy , 2005, Breast Cancer Research and Treatment.

[11]  Davide Caramella,et al.  The role of mean diffusivity (MD) as a predictive index of the response to chemotherapy in locally advanced breast cancer: a preliminary study , 2010, European Radiology.

[12]  Risto A Kauppinen,et al.  Monitoring cytotoxic tumour treatment response by diffusion magnetic resonance imaging and proton spectroscopy , 2002, NMR in biomedicine.

[13]  Peter Gibbs,et al.  Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. , 2006, Magnetic resonance imaging.

[14]  J. Ahn,et al.  Accuracy of MRI for estimating residual tumor size after neoadjuvant chemotherapy in locally advanced breast cancer: Relation to response patterns on MRI , 2007, Acta oncologica.

[15]  A. Cilotti,et al.  Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion , 2007, European Radiology.

[16]  C. Balu-Maestro,et al.  Imaging in Evaluation of Response to Neoadjuvant Breast Cancer Treatment Benefits of MRI , 2002, Breast Cancer Research and Treatment.

[17]  Kenneth G A Gilhuijs,et al.  Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy: initial results. , 2008, AJR. American journal of roentgenology.

[18]  Roberto Orecchia,et al.  Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group. , 2010, European journal of cancer.

[19]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[20]  J. Petiot,et al.  Pathologic assessment of tumor regression after preoperative chemoradiotherapy of esophageal carcinoma. Clinicopathologic correlations , 1994, Cancer.

[21]  T. Nagaoka,et al.  Ultrastructural and MRI study of the substantia nigra evolving exofocal post‐ischemic neuronal death in the rat , 2002, Neuropathology : official journal of the Japanese Society of Neuropathology.

[22]  S. Roth.  Dynamic Contrast-Enhanced MRI for Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy: Initial Results , 2009 .

[23]  A. Rieber,et al.  Breast MRI for monitoring response of primary breast cancer to neo-adjuvant chemotherapy , 2002, European Radiology.

[24]  R. Gillies,et al.  Applications of magnetic resonance in model systems: cancer therapeutics. , 2000, Neoplasia.

[25]  E. Winer,et al.  Preoperative therapy in invasive breast cancer: pathologic assessment and systemic therapy issues in operable disease. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[26]  R. Gilles,et al.  Locally advanced breast cancer: contrast-enhanced subtraction MR imaging of response to preoperative chemotherapy. , 1994, Radiology.

[27]  Yael Paran,et al.  Water diffusion in the different microenvironments of breast cancer , 2004, NMR in biomedicine.

[28]  Fiona J Gilbert,et al.  Neoadjuvant chemotherapy in breast cancer: significantly enhanced response with docetaxel. , 2002, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[29]  R. Kauppinen,et al.  Quantitative 1H nuclear magnetic resonance diffusion spectroscopy of BT4C rat glioma during thymidine kinase-mediated gene therapy in vivo: identification of apoptotic response. , 1998, Cancer research.

[30]  J. Hogg.  Magnetic resonance imaging. , 1994, Journal of the Royal Naval Medical Service.

[31]  Elkan F Halpern,et al.  Invasive ductal breast carcinoma response to neoadjuvant chemotherapy: noninvasive monitoring with functional MR imaging pilot study. , 2003, Radiology.

[32]  G. Hortobagyi,et al.  Clinical course of breast cancer patients with complete pathologic primary tumor and axillary lymph node response to doxorubicin-based neoadjuvant chemotherapy. , 1999, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[33]  Steinar Lundgren,et al.  Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE‐MRI , 2009, Journal of magnetic resonance imaging : JMRI.

[34]  C. Osborne,et al.  Biologic markers as predictors of clinical outcome from systemic therapy for primary operable breast cancer. , 1999, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[35]  Shigeru Nawano,et al.  Diffusion-weighted imaging of breast cancer with the sensitivity encoding technique: analysis of the apparent diffusion coefficient value. , 2004, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[36]  Orhan Nalcioglu,et al.  MRI evaluation of pathologically complete response and residual tumors in breast cancer after neoadjuvant chemotherapy , 2008, Cancer.

[37]  S. Lipsitz,et al.  Does MRI predict pathologic tumor response in women with breast cancer undergoing preoperative chemotherapy? , 2007, Journal of surgical oncology.

[38]  C. Bortner,et al.  A necessary role for cell shrinkage in apoptosis. , 1998, Biochemical pharmacology.

[39]  S. Paik,et al.  Preoperative chemotherapy: updates of National Surgical Adjuvant Breast and Bowel Project Protocols B-18 and B-27. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[40]  C. Zuiani,et al.  Locally advanced breast cancer: comparison of mammography, sonography and MR imaging in evaluation of residual disease in women receiving neoadjuvant chemotherapy , 2004, European Radiology.

[41]  Ying Lu,et al.  Accuracy of MR imaging for revealing residual breast cancer in patients who have undergone neoadjuvant chemotherapy. , 2002, AJR. American journal of roentgenology.

[42]  Masanori Ozaki,et al.  ADC mapping of benign and malignant breast tumors. , 2005, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[43]  S. Gautam,et al.  Identification of residual breast carcinoma following neoadjuvant chemotherapy: diffusion-weighted imaging--comparison with contrast-enhanced MR imaging and pathologic findings. , 2010, Radiology.

[44]  R. Kauppinen,et al.  Water diffusion in a rat glioma during ganciclovir‐thymidine kinase gene therapy‐induced programmed cell death in vivo: Correlation with cell density , 2004, Journal of magnetic resonance imaging : JMRI.

[45]  M. Dewhirst,et al.  Accuracy of MRI in the detection of residual breast cancer after neoadjuvant chemotherapy. , 2003, AJR. American journal of roentgenology.

[46]  Ning-Yu An,et al.  Differentiation of clinically benign and malignant breast lesions using diffusion‐weighted imaging , 2002, Journal of magnetic resonance imaging : JMRI.

[47]  Thomas E Yankeelov,et al.  Integration of quantitative DCE-MRI and ADC mapping to monitor treatment response in human breast cancer: initial results. , 2007, Magnetic resonance imaging.