Cargando…

Predicting breast cancer response to neoadjuvant chemotherapy using pretreatment diffuse optical spectroscopic texture analysis

BACKGROUND: Diffuse optical spectroscopy (DOS) has been demonstrated capable of monitoring response to neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC) patients. In this study, we evaluate texture features of pretreatment DOS functional maps for predicting LABC response to NAC...

Descripción completa

Detalles Bibliográficos
Autores principales:	Tran, William T, Gangeh, Mehrdad J, Sannachi, Lakshmanan, Chin, Lee, Watkins, Elyse, Bruni, Silvio G, Rastegar, Rashin Fallah, Curpen, Belinda, Trudeau, Maureen, Gandhi, Sonal, Yaffe, Martin, Slodkowska, Elzbieta, Childs, Charmaine, Sadeghi-Naini, Ali, Czarnota, Gregory J
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group 2017
Materias:	Translational Therapeutics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482739/ https://www.ncbi.nlm.nih.gov/pubmed/28419079 http://dx.doi.org/10.1038/bjc.2017.97

Ejemplares similares

Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features
por: Sannachi, Lakshmanan, et al.
Publicado: (2018)

Breast Cancer Treatment Response Monitoring Using Quantitative Ultrasound and Texture Analysis: Comparative Analysis of Analytical Models
por: Sannachi, Lakshmanan, et al.
Publicado: (2019)

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps
por: Sadeghi-Naini, Ali, et al.
Publicado: (2017)

A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound
por: Tadayyon, Hadi, et al.
Publicado: (2017)

Multiparametric monitoring of chemotherapy treatment response in locally advanced breast cancer using quantitative ultrasound and diffuse optical spectroscopy
por: Tran, William T., et al.
Publicado: (2016)

Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
por: Sadeghi-Naini, Ali, et al.
Publicado: (2014)

MRI texture features from tumor core and margin in the prediction of response to neoadjuvant chemotherapy in patients with locally advanced breast cancer
por: Kolios, Christopher, et al.
Publicado: (2021)

Quantitative ultrasound assessment of breast tumor response to chemotherapy using a multi-parameter approach
por: Tadayyon, Hadi, et al.
Publicado: (2016)

Correction: Quantitative ultrasound assessment of breast tumor response to chemotherapy using a multi-parameter approach
por: Tadayyon, Hadi, et al.
Publicado: (2017)

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities
por: Sadeghi-Naini, Ali, et al.
Publicado: (2017)

Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancer
por: Dasgupta, Archya, et al.
Publicado: (2020)

Prediction of chemotherapy response in breast cancer patients at pre-treatment using second derivative texture of CT images and machine learning
por: Moghadas-Dastjerdi, Hadi, et al.
Publicado: (2021)

A priori prediction of breast tumour response to chemotherapy using quantitative ultrasound imaging and artificial neural networks
por: Tadayyon, Hadi, et al.
Publicado: (2019)

Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
por: Fernandes, Jason, et al.
Publicado: (2019)

Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results
por: Quiaoit, Karina, et al.
Publicado: (2020)

Quantitative ultrasound radiomics in predicting response to neoadjuvant chemotherapy in patients with locally advanced breast cancer: Results from multi‐institutional study
por: DiCenzo, Daniel, et al.
Publicado: (2020)

Early Changes in Quantitative Ultrasound Imaging Parameters during Neoadjuvant Chemotherapy to Predict Recurrence in Patients with Locally Advanced Breast Cancer
por: Bhardwaj, Divya, et al.
Publicado: (2022)

Radiomics in predicting recurrence for patients with locally advanced breast cancer using quantitative ultrasound
por: Dasgupta, Archya, et al.
Publicado: (2021)

Predicting head and neck cancer treatment outcomes with pre-treatment quantitative ultrasound texture features and optimising machine learning classifiers with texture-of-texture features
por: Safakish, Aryan, et al.
Publicado: (2023)

A priori prediction of response in multicentre locally advanced breast cancer (LABC) patients using quantitative ultrasound and derivative texture methods
por: Osapoetra, Laurentius O., et al.
Publicado: (2021)

Breast lesion characterization using Quantitative Ultrasound (QUS) and derivative texture methods
por: Osapoetra, Laurentius O., et al.
Publicado: (2020)

Predictive quantitative ultrasound radiomic markers associated with treatment response in head and neck cancer
por: Tran, William T, et al.
Publicado: (2019)

Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies
por: Tran, William T, et al.
Publicado: (2020)

A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning
por: Moghadas-Dastjerdi, Hadi, et al.
Publicado: (2020)

Quantification of Ultrasonic Scattering Properties of In Vivo Tumor Cell Death in Mouse Models of Breast Cancer()
por: Tadayyon, Hadi, et al.
Publicado: (2015)

Noninvasive Characterization of Locally Advanced Breast Cancer Using Textural Analysis of Quantitative Ultrasound Parametric Images
por: Tadayyon, Hadi, et al.
Publicado: (2014)

Quantitative evaluation of cell death response in vitro and in vivo using conventional-frequency ultrasound
por: Sadeghi-Naini, Ali, et al.
Publicado: (2015)

Quantitative Ultrasound Spectroscopic Imaging for Characterization of Disease Extent in Prostate Cancer Patients()
por: Sadeghi-Naini, Ali, et al.
Publicado: (2015)

Novel MRI-guided focussed ultrasound stimulated microbubble radiation enhancement treatment for breast cancer
por: Dasgupta, Archya, et al.
Publicado: (2023)

MR-guided ultrasound-stimulated microbubble therapy enhances radiation-induced tumor response
por: McNabb, Evan, et al.
Publicado: (2023)

Quantitative Ultrasound for Evaluation of Tumour Response to Ultrasound-Microbubbles and Hyperthermia
por: Sharma, Deepa, et al.
Publicado: (2023)

Microbubble and ultrasound radioenhancement of bladder cancer
por: Tran, W T, et al.
Publicado: (2012)

Focused Ultrasound Stimulation of Microbubbles in Combination With Radiotherapy for Acute Damage of Breast Cancer Xenograft Model
por: Sharma, Deepa, et al.
Publicado: (2022)

Tumour Vascular Shutdown and Cell Death Following Ultrasound-Microbubble Enhanced Radiation Therapy
por: El Kaffas, Ahmed, et al.
Publicado: (2018)

Texture analysis of (125)I-A5B7 anti-CEA antibody SPECT differentiates metastatic colorectal cancer model phenotypes and anti-vascular therapy response
por: Rajkumar, V, et al.
Publicado: (2015)

A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks
por: Lagree, Andrew, et al.
Publicado: (2021)

Quantitative ultrasound imaging of therapy response in bladder cancer in vivo
por: Tran, William T., et al.
Publicado: (2016)

Breast ductography: to do or not to do? A pictorial essay
por: Alikhassi, Afsaneh, et al.
Publicado: (2023)

Chronic GLP-1 Receptor Activation by Exendin-4 Induces Expansion of Pancreatic Duct Glands in Rats and Accelerates Formation of Dysplastic Lesions and Chronic Pancreatitis in the Kras(G12D) Mouse Model
por: Gier, Belinda, et al.
Publicado: (2012)

A Lysozyme Murein Hydrolase with Broad-Spectrum Antibacterial Activity from Enterobacter Phage myPSH1140
por: Ramesh, Nachimuthu, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_ipt63oo1131sgfc62s7ksit4rh