AI-Enhanced PET and MR Imaging for Patients with Breast Cancer

被引:8
作者
Romeo, Valeria [1 ]
Moy, Linda [2 ]
Pinker, Katja [3 ]
机构
[1] Univ Naples Federico II, Dept Adv Biomed Sci, Via S Pansini 5, I-80138 Naples, Italy
[2] NYU, Sch Med, Dept Radiol, 160 East 34th St, New York, NY 10016 USA
[3] Mem Sloan Kettering Canc Ctr, Dept Radiol, Breast Imaging Serv, 300 East 66th St, New York, NY 10065 USA
关键词
PET/MR imaging; Breast cancer; Artificial intelligence; Radiomics; NEOADJUVANT CHEMOTHERAPY; RADIOMICS MODEL; PREDICTION; FEATURES;
D O I
10.1016/j.cpet.2023.05.002
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
[No abstract available]
引用
收藏
页码:567 / 575
页数:9
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共 50 条
[1]   From Handcrafted to Deep-Learning-Based Cancer Radiomics Challenges and opportunities [J].
Afshar, Parnian ;
Mohammadi, Arash ;
Plataniotis, Konstantinos N. ;
Oikonomou, Anastasia ;
Benali, Habib .
IEEE SIGNAL PROCESSING MAGAZINE, 2019, 36 (04) :132-160
[2]   De-Escalating the Management of In Situ and Invasive Breast Cancer [J].
Angarita, Fernando A. ;
Brumer, Robert ;
Castelo, Matthew ;
Esnaola, Nestor F. ;
Edge, Stephen B. ;
Takabe, Kazuaki .
CANCERS, 2022, 14 (19)
[3]   A Role of PET/MR in Breast Cancer? [J].
Bruckmann, Nils Martin ;
Morawitz, Janna ;
Fendler, Wolfgang P. ;
Ruckhaeberele, Eugen ;
Bittner, Ann-Kathrin ;
Giesel, Frederik L. ;
Herrmann, Ken ;
Antoch, Gerald ;
Umutlu, Lale ;
Kirchner, Julian .
SEMINARS IN NUCLEAR MEDICINE, 2022, 52 (05) :611-618
[4]   The ethical, legal and social implications of using artificial intelligence systems in breast cancer care [J].
Carter, Stacy M. ;
Rogers, Wendy ;
Win, Khin Than ;
Frazer, Helen ;
Richards, Bernadette ;
Houssami, Nehmat .
BREAST, 2020, 49 :25-32
[5]   Predictive Value of 18F-FDG PET/CT-Based Radiomics Model for Occult Axillary Lymph Node Metastasis in Clinically Node-Negative Breast Cancer [J].
Chen, Kun ;
Yin, Guotao ;
Xu, Wengui .
DIAGNOSTICS, 2022, 12 (04)
[6]   Development of High-Resolution Dedicated PET-Based Radiomics Machine Learning Model to Predict Axillary Lymph Node Status in Early-Stage Breast Cancer [J].
Cheng, Jingyi ;
Ren, Caiyue ;
Liu, Guangyu ;
Shui, Ruohong ;
Zhang, Yingjian ;
Li, Junjie ;
Shao, Zhimin .
CANCERS, 2022, 14 (04)
[7]   Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning [J].
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 .
SCIENTIFIC REPORTS, 2020, 10 (01)
[8]   Molecular profiling of breast cancer: clinical implications [J].
S Cleator ;
A Ashworth .
British Journal of Cancer, 2004, 90 (6) :1120-1124
[9]   Impact of Neoadjuvant Chemotherapy on Breast Cancer Subtype: Does Subtype Change and, if so, How?: IHC Profile and Neoadjuvant Chemotherapy [J].
De la Cruz, Lucy M. ;
Harhay, Michael O. ;
Zhang, Paul ;
Ugras, Stacy .
ANNALS OF SURGICAL ONCOLOGY, 2018, 25 (12) :3535-3540
[10]  
Fowler AM, 2022, LANCET ONCOL, V23, pE32, DOI 10.1016/S1470-2045(21)00577-5