Cargando…
Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning
This study aimed to investigate the predictive efficacy of positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) for the pathological response of advanced breast cancer to neoadjuvant chemotherapy (NAC). The breast PET/MRI image deep learning model was introd...
Autores principales: | Choi, Joon Ho, Kim, Hyun-Ah, Kim, Wook, Lim, Ilhan, Lee, Inki, Byun, Byung Hyun, Noh, Woo Chul, Seong, Min-Ki, Lee, Seung-Sook, Kim, Byung Il, Choi, Chang Woon, Lim, Sang Moo, Woo, Sang-Keun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712787/ https://www.ncbi.nlm.nih.gov/pubmed/33273490 http://dx.doi.org/10.1038/s41598-020-77875-5 |
Ejemplares similares
-
The Prediction of HER2-Targeted Treatment Response Using (64)Cu-Tetra-Azacyclododecanetetra-Acetic Acid (DOTA)-Trastuzumab PET/CT in Metastatic Breast Cancer: A Case Report
por: Lee, Inki, et al.
Publicado: (2022) -
A preliminary clinical trial to evaluate (64)Cu-NOTA-Trastuzumab as a positron emission tomography imaging agent in patients with breast cancer
por: Lee, Inki, et al.
Publicado: (2021) -
Early response monitoring of neoadjuvant chemotherapy using [(18)F]FDG PET can predict the clinical outcome of extremity osteosarcoma
por: Lee, Inki, et al.
Publicado: (2020) -
Deep Learning-Based Delayed PET Image Synthesis from Corresponding Early Scanned PET for Dosimetry Uptake Estimation
por: Kim, Kangsan, et al.
Publicado: (2023) -
Prediction of Neoadjuvant Chemotherapy Response in Osteosarcoma Using Convolutional Neural Network of Tumor Center (18)F-FDG PET Images
por: Kim, Jingyu, et al.
Publicado: (2021)