Cargando…

Development and validation of a radiopathomic model for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer patients

BACKGROUND: Neoadjuvant chemotherapy (NAC) has become the standard therapeutic option for early high-risk and locally advanced breast cancer. However, response rates to NAC vary between patients, causing delays in treatment and affecting the prognosis for patients who do not sensitive to NAC. MATERI...

Descripción completa

Detalles Bibliográficos
Autores principales:	Zhang, Jieqiu, Wu, Qi, Yin, Wei, Yang, Lu, Xiao, Bo, Wang, Jianmei, Yao, Xiaopeng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2023
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176880/ https://www.ncbi.nlm.nih.gov/pubmed/37173635 http://dx.doi.org/10.1186/s12885-023-10817-2

Ejemplares similares

ASO Author Reflections: Radiopathomics Strategy of Combing Multi-scale Tumor Information on Pretreatment to Predict the Pathologic Response to Neoadjuvant Therapy
por: Tian, Jie, et al.
Publicado: (2020)

327 Radiopathomics: Integration of Advanced Neuroimaging and Molecular Pathology Features in Meningiomas
por: Haghdel, Arsalan, et al.
Publicado: (2023)

Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study
por: Shao, Lizhi, et al.
Publicado: (2020)

2555 Predictive cytological topography (PiCT): A radiopathomics approach to mapping prostate cancer
por: McGarry, Sean D., et al.
Publicado: (2018)

Development and External Validation of a Machine Learning Model to Predict Pathological Complete Response After Neoadjuvant Chemotherapy in Breast Cancer
por: Jung, Ji-Jung, et al.
Publicado: (2023)

High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer
por: Alba, Emilio, et al.
Publicado: (2016)

Association of higher axillary pathologic complete response rate with breast pathologic complete response after neoadjuvant chemotherapy
por: Zhu, Jiujun, et al.
Publicado: (2020)

Molecular Biomarkers Predict Pathological Complete Response of Neoadjuvant Chemotherapy in Breast Cancer Patients: Review
por: de Freitas, Ana Julia Aguiar, et al.
Publicado: (2021)

Derived Neutrophil-to-Lymphocyte Ratio Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer
por: Ocaña, Alberto, et al.
Publicado: (2022)

Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using a deep learning (DL) method
por: Qu, Yu‐Hong, et al.
Publicado: (2020)

Pathological complete response and residual DCIS following neoadjuvant chemotherapy for breast carcinoma
por: Jones, R L, et al.
Publicado: (2006)

Predictors of Pathological Complete Response to Neoadjuvant Chemotherapy in Iranian Breast Cancer Patients
por: Sasanpour, Pegah, et al.
Publicado: (2018)

Influences on pathologic complete response in breast cancer patients after neoadjuvant chemotherapy
por: Müller, Carolin, et al.
Publicado: (2021)

Early changes of platelet‑lymphocyte ratio correlate with neoadjuvant chemotherapy response and predict pathological complete response in breast cancer
por: Dan, Jiaqiang, et al.
Publicado: (2023)

Development and validation of radiomics machine learning model based on contrast-enhanced computed tomography to predict axillary lymph node metastasis in breast cancer
por: Zhang, Jieqiu, et al.
Publicado: (2023)

Platelet-to-lymphocyte ratio as a predictive factor of complete pathologic response to neoadjuvant chemotherapy in breast cancer
por: Cuello-López, Javier, et al.
Publicado: (2018)

Radiomics of contrast-enhanced spectral mammography for prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer
por: Zhang, Kun, et al.
Publicado: (2023)

Nomogram for predicting pathological complete response to neoadjuvant chemotherapy in patients with advanced gastric cancer
por: Chen, Yong-He, et al.
Publicado: (2020)

Racial/Ethnic Differences and Trends in Pathologic Complete Response Following Neoadjuvant Chemotherapy for Breast Cancer
por: Ma, Sung Jun, et al.
Publicado: (2022)

Pretreatment systemic inflammation response index is predictive of pathological complete response in patients with breast cancer receiving neoadjuvant chemotherapy
por: Dong, Jie, et al.
Publicado: (2021)

Tailoring neoadjuvant chemotherapy for patients with breast cancer who have achieved pathologic complete response
por: Li, Xianjun, et al.
Publicado: (2020)

Predictive and Prognostic Roles of Pathological Indicators for Patients with Breast Cancer on Neoadjuvant Chemotherapy
por: Li, Xinyan, et al.
Publicado: (2019)

Development and Validation of a Nomogram to Predict the Probability of Breast Cancer Pathologic Complete Response after Neoadjuvant Chemotherapy: A Retrospective Cohort Study
por: Li, Yijun, et al.
Publicado: (2022)

Markers Associated With Tumor Recurrence in Patients With Breast Cancer Achieving a Pathologic Complete Response After Neoadjuvant Chemotherapy
por: Xie, Li-Yun, et al.
Publicado: (2022)

Prognostic significance of pathological complete response following neoadjuvant chemotherapy for operable breast cancer
por: KAWAJIRI, HIDEMI, et al.
Publicado: (2014)

Triple negative breast cancer subtypes and pathologic complete response rate to neoadjuvant chemotherapy
por: Santonja, Angela, et al.
Publicado: (2018)

Clinical predictors of pathological complete response to neoadjuvant chemotherapy in triple-negative breast cancer
por: Nakashoji, Ayako, et al.
Publicado: (2017)

Prognostic assessment of breast carcinoma submitted to neoadjuvant chemotherapy with pathological non-complete response
por: Resende, Uanderson, et al.
Publicado: (2019)

Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI
por: Braman, Nathaniel M., et al.
Publicado: (2017)

Prediction of Pathologic Complete Response by Ultrasonography and Magnetic Resonance Imaging After Neoadjuvant Chemotherapy in Patients with Breast Cancer
por: Zhang, Kai, et al.
Publicado: (2020)

Individualized model for predicting pathological complete response to neoadjuvant chemotherapy in patients with breast cancer: A multicenter study
por: Qian, Bei, et al.
Publicado: (2022)

Development of a nomogram for predicting pathological complete response in luminal breast cancer patients following neoadjuvant chemotherapy
por: Garufi, Giovanna, et al.
Publicado: (2023)

A Noninvasive Tool Based on Magnetic Resonance Imaging Radiomics for the Preoperative Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer
por: Li, Chenchen, et al.
Publicado: (2022)

A nomogram based on clinicopathological features and serological indicators predicting breast pathologic complete response of neoadjuvant chemotherapy in breast cancer
por: Li, Yijun, et al.
Publicado: (2021)

Development and External Validation of (18)F-FDG PET-Based Radiomic Model for Predicting Pathologic Complete Response after Neoadjuvant Chemotherapy in Breast Cancer
por: Lim, Chae Hong, et al.
Publicado: (2023)

Neoadjuvant chemotherapy with trastuzumab in HER2-positive breast cancer: pathologic complete response rate, predictive and prognostic factors
por: Buzatto, I.P.C., et al.
Publicado: (2017)

Pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: Perfusion metrics of dynamic contrast enhanced MRI
por: Lee, Jeongmin, et al.
Publicado: (2018)

Lymphovascular invasion can be better than pathologic complete response to predict prognosis in breast cancer treated with neoadjuvant chemotherapy
por: Ryu, Young Jae, et al.
Publicado: (2018)

MRI-based response patterns during neoadjuvant chemotherapy can predict pathological (complete) response in patients with breast cancer
por: Goorts, Briete, et al.
Publicado: (2018)

Erratum to: Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI
por: Braman, Nathaniel M., et al.
Publicado: (2017)

Cannot write session to /tmp/vufind_sessions/sess_hudlcelnvk5pdpjsrb4c1oefa7