Enhanced full-inversion-based ultrasound elastography for evaluating tumor response to neoadjuvant chemotherapy in patients with locally advanced breast cancer.

[1]  M. Gity,et al.  A novel deep learning model for breast lesion classification using ultrasound Images: A multicenter data evaluation. , 2023, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[2]  Sergio C. H. Dempsey,et al.  A novel tissue mechanics-based method for improved motion tracking in quasi-static ultrasound elastography. , 2022, Medical physics.

[3]  K. Lehti,et al.  Chemotherapy as a regulator of extracellular matrix-cell communication: implications in therapy resistance. , 2022, Seminars in cancer biology.

[4]  Qiyu Zhao,et al.  Usefulness of new shear wave elastography in early predicting the efficacy of neoadjuvant chemotherapy for patients with breast cancer: where and when to measure is optimal? , 2022, Breast Cancer.

[5]  Joseph J O'Hagan,et al.  Measurement of the hyperelastic properties of 72 normal homogeneous and heterogeneous ex vivo breast tissue samples. , 2021, Journal of the mechanical behavior of biomedical materials.

[6]  I. Masse,et al.  Biomechanical Properties of Cancer Cells , 2021, Cells.

[7]  Z. Werb,et al.  Concepts of extracellular matrix remodelling in tumour progression and metastasis , 2020, Nature Communications.

[8]  Michael C. Kolios,et al.  Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results , 2020, PloS one.

[9]  G. Czarnota,et al.  A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning , 2020, Scientific Reports.

[10]  Abbas Samani,et al.  Analytical Estimation of Out-of-plane Strain in Ultrasound Elastography to Improve Axial and Lateral Displacement Fields* , 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

[11]  Matthew B. Applegate,et al.  Recent advances in high speed diffuse optical imaging in biomedicine , 2020 .

[12]  Sara Sofia Deville,et al.  The Extracellular, Cellular, and Nuclear Stiffness, a Trinity in the Cancer Resistome—A Review , 2019, Front. Oncol..

[13]  K. Pinker,et al.  Diffusion-Weighted Magnetic Resonance Imaging of Patients with Breast Cancer Following Neoadjuvant Chemotherapy Provides Early Prediction of Pathological Response – A Prospective Study , 2019, Scientific Reports.

[14]  Wenquan Wang,et al.  The role of collagen in cancer: from bench to bedside , 2019, Journal of Translational Medicine.

[15]  W. Tran,et al.  Breast Cancer Treatment Response Monitoring Using Quantitative Ultrasound and Texture Analysis: Comparative Analysis of Analytical Models , 2019, Translational oncology.

[16]  J. Zagzebski,et al.  A Quantitative Ultrasound-Based Multi-Parameter Classifier for Breast Masses. , 2019, Ultrasound in medicine & biology.

[17]  W. Tran,et al.  A priori prediction of breast tumour response to chemotherapy using quantitative ultrasound imaging and artificial neural networks , 2019, Oncotarget.

[18]  J. Litniewski,et al.  Breast-lesions characterization using Quantitative Ultrasound features of peritumoral tissue , 2019, Scientific Reports.

[19]  J. Litniewski,et al.  Monitoring the response to neoadjuvant chemotherapy in patients with breast cancer using ultrasound scattering coefficient: A preliminary report , 2019, Journal of ultrasonography.

[20]  A. E. del Río Hernández,et al.  Role of Extracellular Matrix in Development and Cancer Progression , 2018, International journal of molecular sciences.

[21]  Jie Li,et al.  Diffuse optical spectroscopy for monitoring the responses of patients with breast cancer to neoadjuvant chemotherapy , 2018, Medicine.

[22]  Sanjiv Sharma,et al.  DCE-MRI and parametric imaging in monitoring response to neoadjuvant chemotherapy in breast carcinoma: a preliminary report , 2018, Polish journal of radiology.

[23]  E. Farge,et al.  Mechanotransduction in tumor progression: The dark side of the force , 2018, The Journal of cell biology.

[24]  Vivek Verma,et al.  Response rates and pathologic complete response by breast cancer molecular subtype following neoadjuvant chemotherapy , 2018, Breast Cancer Research and Treatment.

[25]  M. Jena,et al.  Role of extracellular matrix in breast cancer development: a brief update , 2018, F1000Research.

[26]  Kevin Kalinsky,et al.  Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer. , 2018, Radiology.

[27]  Guangyu Liu,et al.  Predicting Treatment Response of Breast Cancer to Neoadjuvant Chemotherapy Using Ultrasound-Guided Diffuse Optical Tomography , 2017, Translational oncology.

[28]  A. Nitrosi,et al.  Contrast-enhanced spectral mammography in neoadjuvant chemotherapy monitoring: a comparison with breast magnetic resonance imaging , 2017, Breast Cancer Research.

[29]  Michael C. Kolios,et al.  Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities , 2017, Scientific Reports.

[30]  Hassan Rivaz,et al.  Breast Ultrasound Elastography Using Full Inversion-Based Elastic Modulus Reconstruction , 2017, IEEE Transactions on Computational Imaging.

[31]  A. Samani,et al.  Ultrasound Elastography of the Prostate Using an Unconstrained Modulus Reconstruction Technique: A Pilot Clinical Study , 2017, Translational oncology.

[32]  Hassan Rivaz,et al.  Global Time-Delay Estimation in Ultrasound Elastography , 2017, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[33]  Mehrdad J. Gangeh,et al.  A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound , 2017, Scientific Reports.

[34]  M. Chammas,et al.  Ultrasound Elastography: Review of Techniques and Clinical Applications , 2017, Theranostics.

[35]  Ruijiang Li,et al.  Intratumor partitioning and texture analysis of dynamic contrast‐enhanced (DCE)‐MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy , 2016, Journal of magnetic resonance imaging : JMRI.

[36]  Akihiko Osaki,et al.  Near-Infrared Diffuse Optical Imaging for Early Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy: A Comparative Study Using 18F-FDG PET/CT , 2016, The Journal of Nuclear Medicine.

[37]  Rita Rynkevic,et al.  Biomechanical properties of breast tissue, a state-of-the-art review , 2016, Biomechanics and modeling in mechanobiology.

[38]  Albert C. Chen,et al.  Matrix stiffness drives Epithelial-Mesenchymal Transition and tumour metastasis through a TWIST1-G3BP2 mechanotransduction pathway , 2015, Nature Cell Biology.

[39]  Steinar Lundgren,et al.  Dynamic contrast‐enhanced MRI texture analysis for pretreatment prediction of clinical and pathological response to neoadjuvant chemotherapy in patients with locally advanced breast cancer , 2014, NMR in biomedicine.

[40]  S. Saydam,et al.  Evaluation of Neoadjuvant Chemotherapy Response with Dynamic Contrast Enhanced Breast Magnetic Resonance Imaging in Locally Advanced Invasive Breast Cancer. , 2014, The journal of breast health.

[41]  Abbas Samani,et al.  Towards clinical prostate ultrasound elastography using full inversion approach. , 2014, Medical physics.

[42]  F. Soares,et al.  Can FDG-PET/CT predict early response to neoadjuvant chemotherapy in breast cancer? , 2013, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.

[43]  Thomas E Yankeelov,et al.  Early assessment of breast cancer response to neoadjuvant chemotherapy by semi-quantitative analysis of high-temporal resolution DCE-MRI: preliminary results. , 2013, Magnetic resonance imaging.

[44]  Michael C. Kolios,et al.  Low-frequency quantitative ultrasound imaging of cell death in vivo. , 2013, Medical Physics (Lancaster).

[45]  Michael C. Kolios,et al.  Conventional frequency ultrasonic biomarkers of cancer treatment response in vivo. , 2013, Translational oncology.

[46]  J. García-Saenz,et al.  Correlation between response to neoadjuvant chemotherapy and survival in locally advanced breast cancer patients. , 2013, Annals of oncology : official journal of the European Society for Medical Oncology.

[47]  Ali Sadeghi-Naini,et al.  Evaluation of neoadjuvant chemotherapy response in women with locally advanced breast cancer using ultrasound elastography. , 2013, Translational oncology.

[48]  M. Herranz,et al.  Optical Imaging in Breast Cancer Diagnosis: The Next Evolution , 2012, Journal of oncology.

[49]  Hany Soliman,et al.  Diffuse optical spectroscopy evaluation of treatment response in women with locally advanced breast cancer receiving neoadjuvant chemotherapy. , 2012, Translational oncology.

[50]  Martin J. Yaffe,et al.  Imaging innovations for cancer therapy response monitoring , 2012 .

[51]  Gregory D. Hager,et al.  Real-Time Regularized Ultrasound Elastography , 2011, IEEE Transactions on Medical Imaging.

[52]  Thomas R. Cox,et al.  Remodeling and homeostasis of the extracellular matrix: implications for fibrotic diseases and cancer , 2011, Disease Models & Mechanisms.

[53]  Kijoon Lee,et al.  Optical mammography: Diffuse optical imaging of breast cancer. , 2011, World journal of clinical oncology.

[54]  J. Lubiński,et al.  Pathologic complete response rates in young women with BRCA1-positive breast cancers after neoadjuvant chemotherapy. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[55]  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.

[56]  Kevin Brindle,et al.  New approaches for imaging tumour responses to treatment , 2008, Nature Reviews Cancer.

[57]  M. Oelze,et al.  11B-4 Quantitative Ultrasound Assessment of Breast Cancer Using a Multiparameter Approach , 2007, 2007 IEEE Ultrasonics Symposium Proceedings.

[58]  D. Plewes,et al.  Elastic moduli of normal and pathological human breast tissues: an inversion-technique-based investigation of 169 samples , 2007, Physics in medicine and biology.

[59]  O. Eremin,et al.  Neoadjuvant chemotherapy in women with large and locally advanced breast cancer: chemoresistance and prediction of response to drug therapy. , 2006, The surgeon : journal of the Royal Colleges of Surgeons of Edinburgh and Ireland.

[60]  Mark J. Ratain,et al.  Measuring response in a post-RECIST world: from black and white to shades of grey , 2006, Nature Reviews Cancer.

[61]  T. Powles,et al.  Good clinical response of breast cancers to neoadjuvant chemoendocrine therapy is associated with improved overall survival. , 2005, Annals of oncology : official journal of the European Society for Medical Oncology.

[62]  S. Giordano,et al.  Update on locally advanced breast cancer. , 2003, The oncologist.

[63]  A. Hutcheon,et al.  A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival. , 2003, Breast.

[64]  Henry M Kuerer,et al.  Locoregional treatment outcomes for inoperable anthracycline-resistant breast cancer. , 2002, International journal of radiation oncology, biology, physics.

[65]  J. Bishop,et al.  Visualization and quantification of breast cancer biomechanical properties with magnetic resonance elastography. , 2000, Physics in medicine and biology.

[66]  Anna L. Brown,et al.  Effect of preoperative chemotherapy on the outcome of women with operable breast cancer. , 1998, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[67]  G. Hortobagyi Multidisciplinary management of advanced primary and metastatic breast cancer , 1994, Cancer.

[68]  G. Hortobagyi,et al.  Locally advanced breast cancer. , 1973, British medical journal.

[69]  A. Stout,et al.  CARCINOMA OF THE BREAST: II. CRITERIA OF OPERABILITY. , 1943, Annals of surgery.

[70]  Ali Sadeghi-Naini,et al.  Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties. , 2014, Medical physics.

[71]  R. Sen,et al.  Histopathologic changes following neoadjuvant chemotherapy in locally advanced breast cancer. , 2013, Indian journal of cancer.

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

[73]  O. Eremin,et al.  Predicting response to neoadjuvant chemotherapy in breast cancer: molecular imaging, systemic biomarkers and the cancer metabolome (Review). , 2008, Oncology reports.

[74]  Michael E. Phelps,et al.  Usefulness of 3′-[F-18]Fluoro-3′-deoxythymidine with Positron Emission Tomography in Predicting Breast Cancer Response to Therapy , 2005, Molecular Imaging and Biology.

[75]  M. Melisko,et al.  58 – Cancer of the Breast , 2010 .