Cargando…

Correction: Quantitative ultrasound assessment of breast tumor response to chemotherapy using a multi-parameter approach

Detalles Bibliográficos
Autores principales:	Tadayyon, Hadi, Sannachi, Lakshmanan, Gangeh, Mehrdad, Sadeghi-Naini, Ali, Tran, William, Trudeau, Maureen E., Pritchard, Kathleen, Ghandi, Sonal, Verma, Sunil, Czarnota, Gregory J.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Impact Journals LLC 2017
Materias:	Correction
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471072/ https://www.ncbi.nlm.nih.gov/pubmed/28545221 http://dx.doi.org/10.18632/oncotarget.18068

Ejemplares similares

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

A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound
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)

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

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)

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

Predicting breast cancer response to neoadjuvant chemotherapy using pretreatment diffuse optical spectroscopic texture analysis
por: Tran, William T, 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)

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)

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

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)

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

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

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

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

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)

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)

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)

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)

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

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

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

Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment
por: Taleghamar, Hamidreza, et al.
Publicado: (2021)

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)

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)

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

Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy
por: Taleghamar, Hamidreza, et al.
Publicado: (2022)

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

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)

Quantitative Ultrasound Characterization of Tumor Cell Death: Ultrasound-Stimulated Microbubbles for Radiation Enhancement
por: Kim, Hyunjung Christina, et al.
Publicado: (2014)

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

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

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

Quantitative ultrasound radiomics in predicting recurrence for patients with node‐positive head‐neck squamous cell carcinoma treated with radical radiotherapy
por: Dasgupta, Archya, et al.
Publicado: (2020)

Assessment of clinical radiosensitivity in patients with head-neck squamous cell carcinoma from pre-treatment quantitative ultrasound radiomics
por: Osapoetra, Laurentius Oscar, et al.
Publicado: (2021)

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

Effect of chromatin structure on quantitative ultrasound parameters
por: Pasternak, Maurice, et al.
Publicado: (2017)

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

Ultrasound Elastography of the Prostate Using an Unconstrained Modulus Reconstruction Technique: A Pilot Clinical Study
por: Mousavi, Seyed Reza, et al.
Publicado: (2017)

Cannot write session to /tmp/vufind_sessions/sess_84hscck5dchbajj05k5g1qg6a9